# Welcome to Zep!
Give your AI IDE access to Zep's documentation using our [llms.txt](https://llmstxt.org/) files: ([short .txt](/llms.txt), [long .txt](/llms-full.txt))
Zep is a memory layer for AI assistants and agents that continuously learns from user interactions and changing business data. Zep ensures that your Agent has a complete and holistic view of the user, enabling you to build more personalized and accurate user experiences.
Learn about Zep's core concepts including memory, knowledge graphs, and how they work together.
Get up and running with Zep in minutes, whether you code in Python, TypeScript, or Go.
Discover practical recipes and patterns for common use cases with Zep.
Comprehensive API documentation for Zep's SDKs in Python, TypeScript, and Go.
Migrate from Mem0 to Zep in minutes.
Learn about Graphiti, Zep's open-source temporal knowledge graph framework.
# Key Concepts
> Understanding Zep's Memory, Knowledge Graph, and Data Integration.
Looking to just get coding? Check out our [Quickstart](/quickstart).
## Summary
| Concept | Description | Docs |
| ----------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------- |
| Knowledge Graph | Zep's memory store for agents. Nodes represent entities, edges represent facts/relationships. The graph updates dynamically in response to new data. | [Docs](/understanding-the-graph) |
| Memory Context String | Optimized string containing facts and entities from the knowledge graph most relevant to the current session. Also contains dates when facts became valid and invalid. Provide this to your chatbot as "memory". | [Docs](/concepts#memory-context) |
| Fact Invalidation | When new data invalidates a prior fact, the time the fact became invalid is stored on that fact's edge in the knowledge graph. | [Docs](/facts) |
| JSON/text/message | Types of data that can be ingested into the knowledge graph. Can represent business data, documents, chat messages, emails, etc. | [Docs](/adding-data-to-the-graph#adding-message-data) |
| Custom entity types | Feature allowing use of Pydantic-like classes to customize creation/retrieval of entities in the knowledge graph. | [Docs](/entity-types) |
| User | Create a user in Zep to represent an individual using your application. Each user has their own knowledge graph. | [Docs](/users) |
| Sessions | Conversation threads of a user. By default, all messages added to any session of that user are ingested into that user's knowledge graph. | [Docs](/sessions) |
| Group | Used for creating an arbitrary knowledge graph that is not necessarily tied to a user. Useful for memory shared by a "group" of users. | [Docs](/groups) |
| `memory.add` & `graph.add` | High level and low level methods for adding data to the knowledge graph. | [Docs](/concepts#using-memoryadd) |
| `memory.get` & `graph.search` | High level and low level methods for retrieving from the knowledge graph. | [Docs](/concepts#using-memoryget) |
| Fact Ratings | Feature for rating and filtering facts by relevance to your use case. | [Docs](/facts#rating-facts-for-relevancy) |
Zep is a memory layer for AI assistants and agents that continuously learns from user interactions and changing business data. Zep ensures that your Agent has a complete and holistic view of the user, enabling you to build more personalized and accurate user experiences.
Using [user chat histories and business data](#business-data-vs-chat-message-data), Zep automatically constructs a [knowledge graph](#the-knowledge-graph) for each of your users. The knowledge graph contains entities, relationships, and facts related to your user. As facts change or are superseded, [Zep updates the graph](#managing-changes-in-facts-over-time) to reflect their new state. Using Zep, you can [build prompts](#how-zep-fits-into-your-application) that provide your agent with the information it needs to personalize responses and solve problems. Ensuring your prompts have the right information reduces hallucinations, improves recall, and reduces the cost of LLM calls.
This guide covers key concepts for using Zep effectively:
* [How Zep fits into your application](#how-zep-fits-into-your-application)
* [The Zep Knowledge Graph](#the-knowledge-graph)
* [User vs Group graphs](#user-vs-group-graphs)
* [Managing changes in facts over time](#managing-changes-in-facts-over-time)
* [Business data vs Chat Message data](#business-data-vs-chat-message-data)
* [Users and Chat Sessions](#users-and-chat-sessions)
* [Adding Memory](#adding-memory)
* [Retrieving memory](#retrieving-memory)
* [Improving Fact Quality](#improving-fact-quality)
* [Using Zep as an agentic tool](#using-zep-as-an-agentic-tool)
* [Other Zep Features](#other-zep-features)
## How Zep fits into your application
Your application sends Zep messages and other interactions your agent has with a human. Zep can also ingest data from your business sources in JSON, text, or chat message format. These sources may include CRM applications, emails, billing data, or conversations on other communication platforms like Slack.
Zep fuses this data together on a knowledge graph, building a holistic view of the user's world and the relationships between entities. Zep offers a number of APIs for [adding and retrieving memory](#retrieving-memory). In addition to populating a prompt with Zep's memory, Zep's search APIs can be used to build [agentic tools](#using-zep-as-an-agentic-tool).
The example below shows Zep's `memory.context` field resulting from a call to `memory.get()`. This is an opinionated, easy to use context string that can be added to your prompt and contains facts and graph entities relevant to the current conversation with a user. For more about the temporal context of facts, see [Managing changes in facts over time](#managing-changes-in-facts-over-time).
Zep also returns a number of other artifacts in the `memory.get()` response, including raw `facts` objects. Zep's search methods can also be used to retrieve nodes, edges, and facts.
### Memory Context
Memory context is a string containing relevant facts and entities for the session. It is always present in the result of `memory.get()`
call and can be optionally [received with the response of `memory.add()` call](/docs/performance/performance-best-practices#get-the-memory-context-string-sooner).
```python
# pass in the session ID of the conversation thread
memory = zep_client.memory.get(session_id="session_id")
print(memory.context)
```
```text
FACTS and ENTITIES represent relevant context to the current conversation.
# These are the most relevant facts and their valid date ranges
# format: FACT (Date range: from - to)
- Emily is experiencing issues with logging in. (2024-11-14 02:13:19+00:00 -
present)
- User account Emily0e62 has a suspended status due to payment failure.
(2024-11-14 02:03:58+00:00 - present)
- user has the id of Emily0e62 (2024-11-14 02:03:54 - present)
- The failed transaction used a card with last four digits 1234. (2024-09-15
00:00:00+00:00 - present)
- The reason for the transaction failure was 'Card expired'. (2024-09-15
00:00:00+00:00 - present)
- user has the name of Emily Painter (2024-11-14 02:03:54 - present)
- Account Emily0e62 made a failed transaction of 99.99. (2024-07-30
00:00:00+00:00 - 2024-08-30 00:00:00+00:00)
# These are the most relevant entities
# ENTITY_NAME: entity summary
- Emily0e62: Emily0e62 is a user account associated with a transaction,
currently suspended due to payment failure, and is also experiencing issues
with logging in.
- Card expired: The node represents the reason for the transaction failure,
which is indicated as 'Card expired'.
- Magic Pen Tool: The tool being used by the user that is malfunctioning.
- User: user
- Support Agent: Support agent responding to the user's bug report.
- SupportBot: SupportBot is the virtual assistant providing support to the user,
Emily, identified as SupportBot.
- Emily Painter: Emily is a user reporting a bug with the magic pen tool,
similar to Emily Painter, who is expressing frustration with the AI art
generation tool and seeking assistance regarding issues with the PaintWiz app.
```
You can then include this context in your system prompt:
| MessageType | Content |
| ----------- | ------------------------------------------------------- |
| `System` | Your system prompt
`{Zep context string}` |
| `Assistant` | An assistant message stored in Zep |
| `User` | A user message stored in Zep |
| ... | ... |
| `User` | The latest user message |
## The Knowledge Graph
A knowledge graph is a network of interconnected facts, such as *"Kendra loves
Adidas shoes."* Each fact is a *"triplet"* represented by two entities, or
nodes (*"Kendra", "Adidas shoes"*), and their relationship, or edge
(*"loves"*).
Knowledge Graphs have been explored extensively for information retrieval.
What makes Zep unique is its ability to autonomously build a knowledge graph
while handling changing relationships and maintaining historical context.
Zep automatically constructs a knowledge graph for each of your users. The knowledge graph contains entities, relationships, and facts related to your user, while automatically handling changing relationships and facts.
Here's an example of how Zep might extract graph data from a chat message, and then update the graph once new information is available:
Each node and edge contains certain attributes - notably, a fact is always stored as an edge attribute. There are also datetime attributes for when the fact becomes [valid and when it becomes invalid](#managing-changes-in-facts-over-time).
## User vs Group graphs
Zep automatically creates a knowledge graph for each User of your application. You as the developer can also create a ["group graph"](/groups) (which is best thought of as an "arbitrary graph") for memory to be used by a group of Users, or for a more complicated use case.
For example, you could create a group graph for your company's product information or even messages related to a group chat. This avoids having to add the same data to each user graph. To do so, you'd use the `graph.add()` and `graph.search()` methods (see [Retrieving memory](#retrieving-memory)).
Group knowledge is not retrieved via the `memory.get()` method and is not included in the `memory.context` string. To use user and group graphs simultaneously, you need to add group-specific context to your prompt alongside the `memory.context` string.
Read more about groups [here](/groups).
## Managing changes in facts over time
When incorporating new data, Zep looks for existing nodes and edges in graph and decides whether to add new nodes/edges or to update existing ones. An update could mean updating an edge (for example, indicating the previous fact is no longer valid).
For example, in the [animation above](#the-knowledge-graph), Kendra initially loves Adidas shoes. She later is angry that the shoes broke and states a preference for Puma shoes. As a result, Zep invalidates the fact that Kendra loves Adidas shoes and creates two new facts: "Kendra's Adidas shoes broke" and "Kendra likes Puma shoes".
Zep also looks for dates in all ingested data, such as the timestamp on a chat message or an article's publication date, informing how Zep sets the following edge attributes. This assists your agent in reasoning with time.
| Edge attribute | Example |
| :-------------- | :---------------------------------------------- |
| **created\_at** | The time Zep learned that the user got married |
| **valid\_at** | The time the user got married |
| **invalid\_at** | The time the user got divorced |
| **expired\_at** | The time Zep learned that the user got divorced |
The `valid_at` and `invalid_at` attributes for each fact are then included in the `memory.context` string which is given to your agent:
```text
# format: FACT (Date range: from - to)
User account Emily0e62 has a suspended status due to payment failure. (2024-11-14 02:03:58+00:00 - present)
```
## Business data vs Chat Message data
Zep can ingest either unstructured text (e.g. documents, articles, chat messages) or JSON data (e.g. business data, or any other form of structured data). Conversational data is ingested through `memory.add()` in structured chat message format, and all other data is ingested through the `graph.add()` method.
## Users and Chat Sessions
A Session is a series of chat messages (e.g., between a user and your agent). [Users](/users) may have multiple Sessions.
Entities, relationships, and facts are extracted from the messages in a Session and added to the user's knowledge graph. All of a user's Sessions contribute to a single, shared knowledge graph for that user. Read more about sessions [here](/sessions).
`SessionIDs` are arbitrary identifiers that you can map to relevant business objects in your app, such as users or a
conversation a user might have with your app.
For code examples of how to create users and sessions, see the [Quickstart Guide](/quickstart#create-a-user-and-session).
## Adding Memory
There are two ways to add data to Zep: `memory.add()` and `graph.add()`.
### Using `memory.add()`
Add your chat history to Zep using the `memory.add()` method. `memory.add` is session-specific and expects data in chat message format, including a `role` name (e.g., user's real name), `role_type` (AI, human, tool), and message `content`. Zep stores the chat history and builds a user-level knowledge graph from the messages.
For code examples of how to add messages to Zep's memory, see the [Quickstart Guide](/quickstart#adding-messages-and-retrieving-context).
For best results, add chat history to Zep on every chat turn. That is, add both the AI and human messages in a single operation and in the order that the messages were created.
Additionally, for latency-sensitive applications, you can request the memory context directly in the response to the `memory.add` call. Read more [here](/docs/performance/performance-best-practices#get-the-memory-context-string-sooner).
### Using `graph.add()`
The `graph.add()` method enables you to add business data as a JSON object or unstructured text. It also supports adding data to Group graphs by passing in a `group_id` as opposed to a `user_id`.
For code examples of how to add business data to the graph, see the [Quickstart Guide](/quickstart#adding-business-data-to-a-graph).
## Retrieving memory
There are three ways to retrieve memory from Zep: `memory.get()`, `graph.search()`, and methods for retrieving specific nodes, edges, or episodes using UUIDs.
### Using `memory.get()`
The `memory.get()` method is a user-friendly, high-level API for retrieving relevant context from Zep. It uses the latest messages of the *given session* to determine what information is most relevant from the user's knowledge graph and returns that information in a [context string](#memory-context) for your prompt. Note that although `memory.get()` only requires a session ID, it is able to return memory derived from any session of that user. The session is just used to determine what's relevant.
`memory.get` also returns recent chat messages and raw facts that may provide additional context for your agent. It is user and session-specific and cannot retrieve data from group graphs.
For code examples of how to retrieve memory context for a session, see the [Quickstart Guide](/quickstart#retrieving-context-with-memoryget).
### Using `graph.search()`
The `graph.search()` method lets you search the graph directly, returning raw edges and/or nodes (defaults to edges), as opposed to facts. You can customize search parameters, such as the reranker used. For more on how search works, visit the [Graph Search](/searching-the-graph) guide. This method works for both User and Group graphs.
For code examples of how to search the graph, see the [Quickstart Guide](/quickstart#searching-the-graph).
### Retrieving specific nodes, edges, and episodes
Zep offers several utility methods for retrieving specific nodes, edges, or episodes by UUID, or all elements for a user or group. To retrieve a fact, you just need to retrieve its edge, since a fact is always the attribute of some edge. See the [Graph SDK reference](/sdk-reference/graph) for more.
## Improving Fact Quality
By using Zep's fact rating feature, you can make Zep automatically assign a rating to every fact using your own custom rating instruction. Then, when retrieving memory, you can set a minimum rating threshold so that the memory only contains the highest quality facts for your use case. Read more [here](/facts#rating-facts-for-relevancy).
## Using Zep as an agentic tool
Zep's memory retrieval methods can be used as agentic tools, enabling your agent to query Zep for relevant information. This allows your agent to access the user's knowledge graph and retrieve facts, entities, and relationships that are relevant to the current conversation.
For a complete code example of how to use Zep as an agentic tool, see the [Quickstart Guide](/quickstart#using-zep-as-an-agentic-tool).
## Other Zep Features
Additionally, Zep builds on Zep's memory layer with tools to help you build more deterministic and accurate applications:
* [Dialog Classification](/dialog-classification) is a flexible low-latency API for understanding intent, segmenting users, determining the state of a conversation and more, allowing you to select appropriate prompts and models, and manage application flow.
* [Structured Data Extraction](/structured-data-extraction) extracts data from conversations with high-fidelity and low-latency, enabling you to confidently populate your data store, call third-party applications, and build custom workflows.
# Quickstart
> Get up and running with Zep in minutes
Looking for a more in-depth understanding? Check out our [Key Concepts](/concepts) page.
This quickstart guide will help you get up and running with Zep quickly. We will:
* Obtain an API key
* Install the SDK
* Initialize the client
* Create a user and session
* Add and retrieve messages
* View your knowledge graph
* Add business data to a user or group graph
* Search for edges or nodes in the graph
Migrating from Mem0? Check out our [Mem0 Migration](/mem0-to-zep) guide.
## Obtain an API Key
[Create a free Zep account](https://app.getzep.com/) and you will be prompted to create an API key.
## Install the SDK
### Python
Set up your Python project, ideally with [a virtual environment](https://medium.com/@vkmauryavk/managing-python-virtual-environments-with-uv-a-comprehensive-guide-ac74d3ad8dff), and then:
```Bash
pip install zep-cloud
```
```Bash
uv pip install zep-cloud
```
### TypeScript
Set up your TypeScript project and then:
```Bash
npm install @getzep/zep-cloud
```
```Bash
yarn add @getzep/zep-cloud
```
```Bash
pnpm install @getzep/zep-cloud
```
### Go
Set up your Go project and then:
```Bash
go get github.com/getzep/zep-go/v2
```
## Initialize the Client
First, make sure you have a [.env file](https://metaschool.so/articles/what-are-env-files) with your API key:
```
ZEP_API_KEY=your_api_key_here
```
After creating your .env file, you'll need to source it in your terminal session:
```bash
source .env
```
Then, initialize the client with your API key:
```python Python
import os
from zep_cloud.client import Zep
API_KEY = os.environ.get('ZEP_API_KEY')
client = Zep(
api_key=API_KEY,
)
```
```typescript TypeScript
import { ZepClient } from "@getzep/zep-cloud";
const API_KEY = process.env.ZEP_API_KEY;
const client = new ZepClient({
apiKey: API_KEY,
});
```
```go Go
import (
"github.com/getzep/zep-go/v2"
zepclient "github.com/getzep/zep-go/v2/client"
"github.com/getzep/zep-go/v2/option"
"log"
)
client := zepclient.NewClient(
option.WithAPIKey(os.Getenv("ZEP_API_KEY")),
)
```
**The Python SDK Supports Async Use**
The Python SDK supports both synchronous and asynchronous usage. For async operations, import `AsyncZep` instead of `Zep` and remember to `await` client calls in your async code.
## Create a User and Session
Before adding messages, you need to create a user and a session. A session is a chat thread - a container for messages between a user and an assistant. A user can have multiple sessions (different conversation threads).
While messages are stored in sessions, the knowledge extracted from these messages is stored at the user level. This means that facts and entities learned in one session are available across all of the user's sessions. When you use `memory.get()`, Zep returns the most relevant memory from the user's entire knowledge graph, not just from the current session.
### Create a User
```python Python
# Create a new user
user_id = "user123"
new_user = client.user.add(
user_id=user_id,
email="[email protected]",
first_name="Jane",
last_name="Smith",
)
```
```typescript TypeScript
// Create a new user
const userId = "user123";
const user = await client.user.add({
userId: userId,
email: "[email protected]",
firstName: "Jane",
lastName: "Smith",
});
```
```go Go
import (
"context"
v2 "github.com/getzep/zep-go/v2"
)
// Create a new user
userId := "user123"
email := "[email protected]"
firstName := "Jane"
lastName := "Smith"
user, err := client.User.Add(context.TODO(), &v2.CreateUserRequest{
UserID: &userId,
Email: &email,
FirstName: &firstName,
LastName: &lastName,
})
if err != nil {
log.Fatal("Error creating user:", err)
}
fmt.Println("User created:", user)
```
### Create a Session
```python Python
import uuid
# Generate a unique session ID
session_id = uuid.uuid4().hex
# Create a new session for the user
client.memory.add_session(
session_id=session_id,
user_id=user_id,
)
```
```typescript TypeScript
import { v4 as uuid } from "uuid";
// Generate a unique session ID
const sessionId = uuid();
// Create a new session for the user
await client.memory.addSession({
sessionId: sessionId,
userId: userId,
});
```
```go Go
import (
"context"
"github.com/google/uuid"
"github.com/getzep/zep-go/v2/models"
)
// Generate a unique session ID
sessionId := uuid.New().String()
// Create a new session for the user
session, err := client.Memory.AddSession(context.TODO(), &v2.CreateSessionRequest{
SessionID: sessionId,
UserID: userId,
})
if err != nil {
log.Fatal("Error creating session:", err)
}
fmt.Println("Session created:", session)
```
## Add Messages with memory.add
Add chat messages to a session using the `memory.add` method. These messages will be stored in the session history and used to build the user's knowledge graph.
```python Python
# Define messages to add
from zep_cloud.types import Message
messages = [
Message(
role="Jane",
content="Hi, my name is Jane Smith and I work at Acme Corp.",
role_type="user",
),
Message(
role="AI Assistant",
content="Hello Jane! Nice to meet you. How can I help you with Acme Corp today?",
role_type="assistant",
)
]
# Add messages to the session
client.memory.add(session_id, messages=messages)
```
```typescript TypeScript
// Define messages to add
import type { Message } from "@getzep/zep-cloud/api";
const messages: Message[] = [
{
role: "Jane",
content: "Hi, my name is Jane Smith and I work at Acme Corp.",
roleType: "user",
},
{
role: "AI Assistant",
content: "Hello Jane! Nice to meet you. How can I help you with Acme Corp today?",
roleType: "assistant",
}
];
// Add messages to the session
await client.memory.add(sessionId, { messages });
```
```go Go
import (
"context"
"github.com/getzep/zep-go/v2/models"
)
// Define messages to add
userRole := "Jane"
assistantRole := "AI Assistant"
messages := []*v2.Message{
{
Role: &userRole,
Content: "Hi, my name is Jane Smith and I work at Acme Corp.",
RoleType: "user",
},
{
Role: &assistantRole,
Content: "Hello Jane! Nice to meet you. How can I help you with Acme Corp today?",
RoleType: "assistant",
},
}
// Add messages to the session
_, err = client.Memory.Add(
context.TODO(),
sessionId,
&v2.AddMemoryRequest{
Messages: messages,
},
)
if err != nil {
log.Fatal("Error adding messages:", err)
}
```
## Retrieve Context with memory.get
Use the `memory.get` method to retrieve relevant context for a session. This includes a context string with facts and entities and recent messages that can be used in your prompt.
```python Python
# Get memory for the session
memory = client.memory.get(session_id=session_id)
# Access the context string (for use in prompts)
context_string = memory.context
print(context_string)
# Access recent messages
recent_messages = memory.messages
for msg in recent_messages:
print(f"{msg.role}: {msg.content}")
```
```typescript TypeScript
// Get memory for the session
const memory = await client.memory.get(sessionId);
// Access the context string (for use in prompts)
const contextString = memory.context;
console.log(contextString);
// Access recent messages
if (memory.messages) {
memory.messages.forEach(msg => {
console.log(`${msg.role}: ${msg.content}`);
});
}
```
```go Go
import (
"context"
"fmt"
)
// Get memory for the session
memory, err := client.Memory.Get(context.TODO(), sessionId, nil)
if err != nil {
log.Fatal("Error getting memory:", err)
}
// Access the context string (for use in prompts)
contextString := memory.Context
fmt.Println(contextString)
// Access recent messages
recentMessages := memory.Messages
for _, msg := range recentMessages {
fmt.Printf("%s: %s\n", *msg.Role, msg.Content)
}
```
## View your Knowledge Graph
Since you've created memory, you can view your knowledge graph by navigating to [the Zep Dashboard](https://app.getzep.com/), then Users > "user123" > View Graph. You can also click the "View Episodes" button to see when data is finished being added to the knowledge graph.
## Add Business Data to a Graph
You can add business data directly to a user's graph or to a group graph using the `graph.add` method. This data can be in the form of messages, text, or JSON.
```python Python
# Add text data to a user's graph
new_episode = client.graph.add(
user_id=user_id,
type="text",
data="Jane Smith is a senior software engineer who has been with Acme Corp for 5 years."
)
print("New episode created:", new_episode)
# Add JSON data to a user's graph
import json
json_data = {
"employee": {
"name": "Jane Smith",
"position": "Senior Software Engineer",
"department": "Engineering",
"projects": ["Project Alpha", "Project Beta"]
}
}
client.graph.add(
user_id=user_id,
type="json",
data=json.dumps(json_data)
)
# Add data to a group graph (shared across users)
group_id = "engineering_team"
client.graph.add(
group_id=group_id,
type="text",
data="The engineering team is working on Project Alpha and Project Beta."
)
```
```typescript TypeScript
// Add text data to a user's graph
const newEpisode = await client.graph.add({
userId: userId,
type: "text",
data: "Jane Smith is a senior software engineer who has been with Acme Corp for 5 years."
});
console.log("New episode created:", newEpisode);
// Add JSON data to a user's graph
const jsonData = {
employee: {
name: "Jane Smith",
position: "Senior Software Engineer",
department: "Engineering",
projects: ["Project Alpha", "Project Beta"]
}
};
await client.graph.add({
userId: userId,
type: "json",
data: JSON.stringify(jsonData)
});
// Add data to a group graph (shared across users)
const groupId = "engineering_team";
await client.graph.add({
groupId: groupId,
type: "text",
data: "The engineering team is working on Project Alpha and Project Beta."
});
```
```go Go
import (
"context"
"encoding/json"
"github.com/getzep/zep-go/v2/models"
)
// Add text data to a user's graph
data := "Jane Smith is a senior software engineer who has been with Acme Corp for 5 years."
newEpisode, err := client.Graph.Add(context.TODO(), &v2.AddDataRequest{
UserID: &userId,
Type: v2.GraphDataTypeText.Ptr(),
Data: &data,
})
if err != nil {
log.Fatal("Error adding text data:", err)
}
fmt.Println("New episode added:", newEpisode)
// Add JSON data to a user's graph
type Employee struct {
Name string `json:"name"`
Position string `json:"position"`
Department string `json:"department"`
Projects []string `json:"projects"`
}
jsonData := map[string]Employee{
"employee": {
Name: "Jane Smith",
Position: "Senior Software Engineer",
Department: "Engineering",
Projects: []string{"Project Alpha", "Project Beta"},
},
}
jsonBytes, err := json.Marshal(jsonData)
if err != nil {
log.Fatal("Error marshaling JSON data:", err)
}
jsonString := string(jsonBytes)
_, err = client.Graph.Add(context.TODO(), &v2.AddDataRequest{
UserID: &userId,
Type: v2.GraphDataTypeJSON.Ptr(),
Data: &jsonString,
})
if err != nil {
log.Fatal("Error adding JSON data:", err)
}
// Add data to a group graph (shared across users)
groupId := "engineering_team"
groupData := "The engineering team is working on Project Alpha and Project Beta."
_, err = client.Graph.Add(context.TODO(), &v2.AddDataRequest{
GroupID: &groupId,
Type: v2.GraphDataTypeText.Ptr(),
Data: &groupData,
})
if err != nil {
log.Fatal("Error adding group data:", err)
}
```
## Search the Graph
Use the `graph.search` method to search for edges or nodes in the graph. This is useful for finding specific information about a user or group.
```python Python
# Search for edges in a user's graph
edge_results = client.graph.search(
user_id=user_id,
query="What projects is Jane working on?",
scope="edges", # Default is "edges"
limit=5
)
# Search for nodes in a user's graph
node_results = client.graph.search(
user_id=user_id,
query="Jane Smith",
scope="nodes",
limit=5
)
# Search in a group graph
group_results = client.graph.search(
group_id=group_id,
query="Project Alpha",
scope="edges",
limit=5
)
```
```typescript TypeScript
// Search for edges in a user's graph
const edgeResults = await client.graph.search({
userId: userId,
query: "What projects is Jane working on?",
scope: "edges", // Default is "edges"
limit: 5
});
// Search for nodes in a user's graph
const nodeResults = await client.graph.search({
userId: userId,
query: "Jane Smith",
scope: "nodes",
limit: 5
});
// Search in a group graph
const groupResults = await client.graph.search({
groupId: groupId,
query: "Project Alpha",
scope: "edges",
limit: 5
});
```
```go Go
import (
"context"
"github.com/getzep/zep-go/v2/models"
)
// Search for edges in a user's graph
limit := 5
edgeResults, err := client.Graph.Search(context.TODO(), &v2.GraphSearchQuery{
UserID: &userId,
Query: "What projects is Jane working on?",
Scope: v2.GraphSearchScopeEdges.Ptr(),
Limit: &limit,
})
if err != nil {
log.Fatal("Error searching graph:", err)
}
fmt.Println("Edge search results:", edgeResults)
// Search for nodes in a user's graph
nodeResults, err := client.Graph.Search(context.TODO(), &v2.GraphSearchQuery{
UserID: &userId,
Query: "Jane Smith",
Scope: v2.GraphSearchScopeNodes.Ptr(),
Limit: &limit,
})
if err != nil {
log.Fatal("Error searching graph:", err)
}
fmt.Println("Node search results:", nodeResults)
// Search in a group graph
groupResults, err := client.Graph.Search(context.TODO(), &v2.GraphSearchQuery{
GroupID: &groupId,
Query: "Project Alpha",
Scope: v2.GraphSearchScopeEdges.Ptr(),
Limit: &limit,
})
if err != nil {
log.Fatal("Error searching graph:", err)
}
fmt.Println("Group search results:", groupResults)
```
## Use Zep as an Agentic Tool
Zep's memory retrieval methods can be used as agentic tools, enabling your agent to query Zep for relevant information.
The example below shows how to create a LangChain LangGraph tool to search for facts in a user's graph.
```python Python
from zep_cloud.client import AsyncZep
from langchain_core.tools import tool
from langchain_openai import ChatOpenAI
from langgraph.graph import StateGraph, MessagesState
from langgraph.prebuilt import ToolNode
zep = AsyncZep(api_key=os.environ.get('ZEP_API_KEY'))
@tool
async def search_facts(state: MessagesState, query: str, limit: int = 5):
"""Search for facts in all conversations had with a user.
Args:
state (MessagesState): The Agent's state.
query (str): The search query.
limit (int): The number of results to return. Defaults to 5.
Returns:
list: A list of facts that match the search query.
"""
search_results = await zep.graph.search(
user_id=state['user_name'],
query=query,
limit=limit,
)
return [edge.fact for edge in search_results.edges]
tools = [search_facts]
tool_node = ToolNode(tools)
llm = ChatOpenAI(model='gpt-4o-mini', temperature=0).bind_tools(tools)
```
## Next Steps
Now that you've learned the basics of using Zep, you can:
* Learn more about [Key Concepts](/concepts)
* Explore the [Graph API](/adding-data-to-the-graph) for adding and retrieving data
* Understand [Users and Sessions](/users) in more detail
* Learn about [Memory Context](/concepts#memory-context) for building better prompts
* Explore [Graph Search](/searching-the-graph) for advanced search capabilities
# Building a Chatbot with Zep
> Familiarize yourself with Zep and the Zep SDKs, culminating in building a simple chatbot.
For an introduction to Zep's memory layer, Knowledge Graph, and other key concepts, see the [Concepts Guide](/concepts).
A Jupyter notebook version of this guide is [available here](https://github.com/getzep/zep-python/blob/main/examples/quickstart/quickstart.ipynb).
In this guide, we'll walk through a simple example of how to use Zep Cloud to build a chatbot. We're going to upload a number of datasets to Zep, building a graph of data about a user.
Then we'll use the Zep Python SDK to retrieve and search the data.
Finally, we'll build a simple chatbot that uses Zep to retrieve and search data to respond to a user.
## Set up your environment
1. Sign up for a [Zep Cloud](https://www.getzep.com/) account.
2. Ensure you install required dependencies into your Python environment before running this notebook. See [Installing Zep SDKs](sdks.mdx) for more information. Optionally create your environment in a `virtualenv`.
```bash
pip install zep-cloud openai rich python-dotenv
```
3. Ensure that you have a `.env` file in your working directory that includes your `ZEP_API_KEY` and `OPENAI_API_KEY`:
Zep API keys are specific to a project. You can create multiple keys for a
single project. Visit `Project Settings` in the Zep dashboard to manage your
API keys.
```text
ZEP_API_KEY=
OPENAI_API_KEY=
```
```python
import os
import json
import uuid
from openai import OpenAI
import rich
from dotenv import load_dotenv
from zep_cloud.client import Zep
from zep_cloud import Message
load_dotenv()
zep = Zep(api_key=os.environ.get("ZEP_API_KEY"))
oai_client = OpenAI(
api_key=os.getenv("OPENAI_API_KEY"),
)
```
```typescript
import { ZepClient } from "@getzep/zep-cloud";
import * as dotenv from "dotenv";
import { v4 as uuidv4 } from 'uuid';
import OpenAI from 'openai';
dotenv.config();
const zep = new ZepClient({ apiKey: process.env.ZEP_API_KEY });
const oai_client = new OpenAI({
apiKey: process.env.OPENAI_API_KEY,
});
```
We also provide an
[Asynchronous Python client](/sdks#initialize-client)
.
## Create User and add a Session
Users in Zep may have one or more chat sessions. These are threads of messages between the user and an agent.
Include the user's **full name** and **email address** when creating a user.
This improves Zep's ability to associate data, such as emails or documents,
with a user.
```python
bot_name = "SupportBot"
user_name = "Emily"
user_id = user_name + str(uuid.uuid4())[:4]
session_id = str(uuid.uuid4())
zep.user.add(
user_id=user_id,
email=f"{user_name}@painters.com",
first_name=user_name,
last_name="Painter",
)
zep.memory.add_session(
user_id=user_id,
session_id=session_id,
)
```
```typescript
const bot_name = "SupportBot";
const user_name = "Emily";
const user_id = user_name + uuidv4().substring(0, 4);
const session_id = uuidv4();
await zep.user.add({
userId: user_id,
email: `${user_name}@painters.com`,
firstName: user_name,
lastName: "Painter",
});
await zep.memory.addSession({
userId: user_id,
sessionId: session_id,
});
```
## Datasets
We're going to use the [memory](/concepts#using-memoryadd) and [graph](/adding-data-to-the-graph) APIs to upload an assortment of data to Zep. These include past dialog with the agent, CRM support cases, and billing data.
```python
support_cases = [
{
"subject": "Bug: Magic Pen Tool Drawing Goats Instead of Boats",
"messages": [
{
"role": "user",
"content": "Whenever I use the magic pen tool to draw boats, it ends up drawing goats instead.",
"timestamp": "2024-03-16T14:20:00Z",
},
{
"role": "support_agent",
"content": f"Hi {user_name}, that sounds like a bug! Thanks for reporting it. Could you let me know exactly how you're using the tool when this happens?",
"timestamp": "2024-03-16T14:22:00Z",
},
{
"role": "user",
"content": "Sure, I select the magic pen, draw a boat shape, and it just replaces the shape with goats.",
"timestamp": "2024-03-16T14:25:00Z",
},
{
"role": "support_agent",
"content": "Got it! We'll escalate this to our engineering team. In the meantime, you can manually select the boat shape from the options rather than drawing it with the pen.",
"timestamp": "2024-03-16T14:27:00Z",
},
{
"role": "user",
"content": "Okay, thanks. I hope it gets fixed soon!",
"timestamp": "2024-03-16T14:30:00Z",
},
],
"status": "escalated",
},
]
chat_history = [
{
"role": "assistant",
"name": bot_name,
"content": f"Hello {user_name}, welcome to PaintWiz support. How can I assist you today?",
"timestamp": "2024-03-15T10:00:00Z",
},
{
"role": "user",
"name": user_name,
"content": "I'm absolutely furious! Your AI art generation is completely broken!",
"timestamp": "2024-03-15T10:02:00Z",
},
{
"role": "assistant",
"name": bot_name,
"content": f"I'm sorry to hear that you're experiencing issues, {user_name}. Can you please provide more details about what's going wrong?",
"timestamp": "2024-03-15T10:03:00Z",
},
{
"role": "user",
"name": user_name,
"content": "Every time I try to draw mountains, your stupid app keeps turning them into fountains! And what's worse, all the people in my drawings have six fingers! It's ridiculous!",
"timestamp": "2024-03-15T10:05:00Z",
},
{
"role": "assistant",
"name": bot_name,
"content": f"I sincerely apologize for the frustration this is causing you, {user_name}. That certainly sounds like a significant glitch in our system. I understand how disruptive this can be to your artistic process. Can you tell me which specific tool or feature you're using when this occurs?",
"timestamp": "2024-03-15T10:06:00Z",
},
{
"role": "user",
"name": user_name,
"content": "I'm using the landscape generator and the character creator. Both are completely messed up. How could you let this happen?",
"timestamp": "2024-03-15T10:08:00Z",
},
]
transactions = [
{
"date": "2024-07-30",
"amount": 99.99,
"status": "Success",
"account_id": user_id,
"card_last_four": "1234",
},
{
"date": "2024-08-30",
"amount": 99.99,
"status": "Failed",
"account_id": user_id,
"card_last_four": "1234",
"failure_reason": "Card expired",
},
{
"date": "2024-09-15",
"amount": 99.99,
"status": "Failed",
"account_id": user_id,
"card_last_four": "1234",
"failure_reason": "Card expired",
},
]
account_status = {
"user_id": user_id,
"account": {
"account_id": user_id,
"account_status": {
"status": "suspended",
"reason": "payment failure",
},
},
}
def convert_to_zep_messages(chat_history: list[dict[str, str | None]]) -> list[Message]:
"""
Convert chat history to Zep messages.
Args:
chat_history (list): List of dictionaries containing chat messages.
Returns:
list: List of Zep Message objects.
"""
return [
Message(
role_type=msg["role"],
role=msg.get("name", None),
content=msg["content"],
)
for msg in chat_history
]
# Zep's high-level API allows us to add a list of messages to a session.
zep.memory.add(
session_id=session_id, messages=convert_to_zep_messages(chat_history)
)
# The lower-level data API allows us to add arbitrary data to a user's Knowledge Graph.
for tx in transactions:
zep.graph.add(user_id=user_id, data=json.dumps(tx), type="json")
zep.graph.add(
user_id=user_id, data=json.dumps(account_status), type="json"
)
for case in support_cases:
zep.graph.add(user_id=user_id, data=json.dumps(case), type="json")
```
```typescript
const support_cases = [
{
subject: "Bug: Magic Pen Tool Drawing Goats Instead of Boats",
messages: [
{
role: "user",
content: "Whenever I use the magic pen tool to draw boats, it ends up drawing goats instead.",
timestamp: "2024-03-16T14:20:00Z",
},
{
role: "support_agent",
content: `Hi ${user_name}, that sounds like a bug! Thanks for reporting it. Could you let me know exactly how you're using the tool when this happens?`,
timestamp: "2024-03-16T14:22:00Z",
},
{
role: "user",
content: "Sure, I select the magic pen, draw a boat shape, and it just replaces the shape with goats.",
timestamp: "2024-03-16T14:25:00Z",
},
{
role: "support_agent",
content: "Got it! We'll escalate this to our engineering team. In the meantime, you can manually select the boat shape from the options rather than drawing it with the pen.",
timestamp: "2024-03-16T14:27:00Z",
},
{
role: "user",
content: "Okay, thanks. I hope it gets fixed soon!",
timestamp: "2024-03-16T14:30:00Z",
},
],
status: "escalated",
},
];
const chat_history = [
{
role: "assistant",
name: bot_name,
content: `Hello ${user_name}, welcome to PaintWiz support. How can I assist you today?`,
timestamp: "2024-03-15T10:00:00Z",
},
{
role: "user",
name: user_name,
content: "I'm absolutely furious! Your AI art generation is completely broken!",
timestamp: "2024-03-15T10:02:00Z",
},
{
role: "assistant",
name: bot_name,
content: `I'm sorry to hear that you're experiencing issues, ${user_name}. Can you please provide more details about what's going wrong?`,
timestamp: "2024-03-15T10:03:00Z",
},
{
role: "user",
name: user_name,
content: "Every time I try to draw mountains, your stupid app keeps turning them into fountains! And what's worse, all the people in my drawings have six fingers! It's ridiculous!",
timestamp: "2024-03-15T10:05:00Z",
},
{
role: "assistant",
name: bot_name,
content: `I sincerely apologize for the frustration this is causing you, ${user_name}. That certainly sounds like a significant glitch in our system. I understand how disruptive this can be to your artistic process. Can you tell me which specific tool or feature you're using when this occurs?`,
timestamp: "2024-03-15T10:06:00Z",
},
{
role: "user",
name: user_name,
content: "I'm using the landscape generator and the character creator. Both are completely messed up. How could you let this happen?",
timestamp: "2024-03-15T10:08:00Z",
},
];
const transactions = [
{
date: "2024-07-30",
amount: 99.99,
status: "Success",
account_id: user_id,
card_last_four: "1234",
},
{
date: "2024-08-30",
amount: 99.99,
status: "Failed",
account_id: user_id,
card_last_four: "1234",
failure_reason: "Card expired",
},
{
date: "2024-09-15",
amount: 99.99,
status: "Failed",
account_id: user_id,
card_last_four: "1234",
failure_reason: "Card expired",
},
];
const account_status = {
user_id: user_id,
account: {
account_id: user_id,
account_status: {
status: "suspended",
reason: "payment failure",
},
},
};
/**
* Convert chat history to Zep messages.
*
* Args:
* chatHistory (array): Array of objects containing chat messages.
*
* Returns:
* array: Array of Zep message objects.
*/
const convertToZepMessages = (chatHistory: any[]) => {
return chatHistory.map(msg => ({
roleType: msg.role,
role: msg.name || null,
content: msg.content,
}));
};
// Zep's high-level API allows us to add a list of messages to a session.
await zep.memory.add(session_id, {
messages: convertToZepMessages(chat_history)
});
// The lower-level data API allows us to add arbitrary data to a user's Knowledge Graph.
for (const tx of transactions) {
await zep.graph.add({
userId: user_id,
type: "json",
data: JSON.stringify(tx)
});
await zep.graph.add({
userId: user_id,
type: "json",
data: JSON.stringify(account_status)
});
}
for (const case_data of support_cases) {
await zep.graph.add({
userId: user_id,
type: "json",
data: JSON.stringify(case_data)
});
}
```
### Wait a minute or two!
We've batch uploaded a number of datasets that need to be ingested into Zep's
graph before they can be queried. In ordinary operation, this data would
stream into Zep and ingestion latency would be negligible.
## Retrieve data from Zep
We'll start with getting a list of facts, which are stored on the edges of the graph. We'll see the temporal data associated with facts as well as the graph nodes the fact is related to.
This data is also viewable in the Zep Web application.
```python
all_user_edges = zep.graph.edge.get_by_user_id(user_id=user_id)
rich.print(all_user_edges[:3])
```
```typescript
const all_user_edges = await zep.graph.edge.getByUserId(user_id);
console.log(all_user_edges.slice(0, 3));
```
```text
[
EntityEdge(
created_at='2025-02-20T20:31:01.769332Z',
episodes=['0d3a35c7-ebd3-427d-89a6-1a8dabd2df64'],
expired_at='2025-02-20T20:31:18.742184Z',
fact='The transaction failed because the card expired.',
invalid_at='2024-09-15T00:00:00Z',
name='HAS_FAILURE_REASON',
source_node_uuid='06c61c00-9101-474f-9bca-42b4308ec378',
target_node_uuid='07efd834-f07a-4c3c-9b32-d2fd9362afd5',
uuid_='fb5ee0df-3aa0-44f3-889d-5bb163971b07',
valid_at='2024-08-30T00:00:00Z',
graph_id='8e5686fc-f175-4da9-8778-ad8d60fc469a'
),
EntityEdge(
created_at='2025-02-20T20:31:33.771557Z',
episodes=['60d1d20e-ed6c-4966-b1da-3f4ca274a524'],
expired_at=None,
fact='Emily uses the magic pen tool to draw boats.',
invalid_at=None,
name='USES_TOOL',
source_node_uuid='36f5c5c6-eb16-4ebb-9db0-fd34809482f5',
target_node_uuid='e337522d-3a62-4c45-975d-904e1ba25667',
uuid_='f9eb0a98-1624-4932-86ca-be75a3c248e5',
valid_at='2025-02-20T20:29:40.217412Z',
graph_id='8e5686fc-f175-4da9-8778-ad8d60fc469a'
),
EntityEdge(
created_at='2025-02-20T20:30:28.499178Z',
episodes=['b8e4da4c-dd5e-4c48-bdbc-9e6568cd2d2e'],
expired_at=None,
fact="SupportBot understands how disruptive the glitch in the AI art generation can be to Emily's artistic process.",
invalid_at=None,
name='UNDERSTANDS',
source_node_uuid='fd4ab1f0-e19e-40b7-aaec-78bd97571725',
target_node_uuid='8e5686fc-f175-4da9-8778-ad8d60fc469a',
uuid_='f8c52a21-e938-46a3-b930-04671d0c018a',
valid_at='2025-02-20T20:29:39.08846Z',
graph_id='8e5686fc-f175-4da9-8778-ad8d60fc469a'
)
]
```
The high-level [memory API](/concepts#using-memoryget) provides an easy way to retrieve memory relevant to the current conversation by using the last 4 messages and their proximity to the User node.
The `memory.get` method is a good starting point for retrieving relevant conversation context. It shortcuts passing recent messages to the `graph.search` API and returns a [context string](/concepts#memory-context), raw facts, and historical chat messages, providing everything needed for your agent's prompts.
```python
memory = zep.memory.get(session_id=session_id)
rich.print(memory.context)
```
```typescript
const memory = await zep.memory.get(session_id);
console.log(memory.context);
```
```text
FACTS and ENTITIES represent relevant context to the current conversation.
# These are the most relevant facts and their valid date ranges
# format: FACT (Date range: from - to)
- SupportBot understands how disruptive the glitch in the AI art generation can be to Emily's artistic process. (2025-02-20 20:29:39 - present)
- SupportBot sincerely apologizes to Emily for the frustration caused by the issues with the AI art generation. (2025-02-20 20:29:39 - present)
- Emily has contacted SupportBot for assistance regarding issues she is experiencing. (2025-02-20 20:29:39 - present)
- The user Emily reported a bug regarding the magic pen tool drawing goats instead of boats. (2024-03-16 14:20:00 - present)
- The bug report has been escalated to the engineering team. (2024-03-16 14:27:00 - present)
- Emily is a user of the AI art generation. (2025-02-20 20:29:39 - present)
- user has the name of Emily Painter (2025-02-20 20:29:39 - present)
- Emily5e57 is using the landscape generator. (2025-02-20 20:29:39 - 2025-02-20 20:29:39)
- user has the id of Emily5e57 (2025-02-20 20:29:39 - present)
- user has the email of [email protected] (2025-02-20 20:29:39 - present)
- Emily is furious about the stupid app. (2025-02-20 20:29:39 - present)
- Emily claims that the AI art generation is completely broken. (2025-02-20 20:29:39 - present)
# These are the most relevant entities
# ENTITY_NAME: entity summary
- Emily Painter: Emily Painter contacted PaintWiz support for assistance, where she was welcomed by the support bot that inquired about the specific issues she was facing to provide better help.
- [email protected]: user with the email of [email protected]
- Emily5e57: Emily5e57, a user of the PaintWiz AI art generation tool, successfully processed a transaction of $99.99 on July 30, 2024, using a card ending in '1234'. However, she is experiencing
significant frustration with the application due to malfunctions, such as the landscape generator incorrectly transforming mountains into fountains and characters being depicted with six fingers.
These issues have led her to question the reliability of the tool, and she considers it to be completely broken. Emily has reached out to PaintWiz support for assistance, as these problems are
severely disrupting her artistic process.
- PaintWiz support: PaintWiz is an AI art generation platform that provides tools for users to create art. Recently, a user named Emily reported significant issues with the service, claiming that
the AI art generation is not functioning properly. The support bot responded to her concerns, apologizing for the disruption to her artistic process and asking for more details about the specific
tool or feature she was using. This interaction highlights PaintWiz's commitment to customer support, as they actively seek to assist users with their inquiries and problems related to their
products.
- SupportBot: A support agent named Emily addressed a user's report about a bug in a drawing application where the magic pen tool incorrectly produced goats instead of boats. After confirming the
issue, she escalated it to the engineering team and suggested a temporary workaround of manually selecting the boat shape. Meanwhile, SupportBot, a virtual assistant for PaintWiz, also assisted
another user named Emily who was frustrated with the AI art generation feature, acknowledging her concerns and requesting more details to help resolve the problem.
- AI art generation: Emily, a user, expressed her frustration regarding the AI art generation, stating that it is completely broken.
- options: The user reported a bug with the magic pen tool, stating that when attempting to draw boats, the tool instead draws goats. The support agent acknowledged the issue and requested more
details about how the user was utilizing the tool. The user explained that they select the magic pen and draw a boat shape, but it gets replaced with goats. The support agent confirmed they would
escalate the issue to the engineering team and suggested that the user manually select the boat shape from the options instead of drawing it with the pen. The user expressed hope for a quick
resolution.
```
```python
rich.print(memory.messages)
```
```typescript
console.log(memory.messages);
```
```text
[
Message(
content='Hello Emily, welcome to PaintWiz support. How can I assist you today?',
created_at='2025-02-20T20:29:39.08846Z',
metadata=None,
role='SupportBot',
role_type='assistant',
token_count=0,
updated_at='0001-01-01T00:00:00Z',
uuid_='e2b86f93-84d6-4270-adbc-e421f39b6f90'
),
Message(
content="I'm absolutely furious! Your AI art generation is completely broken!",
created_at='2025-02-20T20:29:39.08846Z',
metadata=None,
role='Emily',
role_type='user',
token_count=0,
updated_at='0001-01-01T00:00:00Z',
uuid_='ec39e501-6dcc-4f8c-b300-f586d66005d8'
)
]
```
We can also use the [graph API](/searching-the-graph) to search edges/facts for arbitrary text. This API offers more options, including the ability to search node summaries and various re-rankers.
```python
r = zep.graph.search(user_id=user_id, query="Why are there so many goats?", limit=4, scope="edges")
rich.print(r.edges)
```
```typescript
const r = await zep.graph.search({
userId: user_id,
query: "Why are there so many goats?",
limit: 4,
scope: "edges"
});
console.log(r.edges);
```
```text
[
EntityEdge(
created_at='2025-02-20T20:31:33.771566Z',
episodes=['60d1d20e-ed6c-4966-b1da-3f4ca274a524'],
expired_at=None,
fact='The magic pen tool draws goats instead of boats when used by Emily.',
invalid_at=None,
name='DRAWS_INSTEAD_OF',
source_node_uuid='e337522d-3a62-4c45-975d-904e1ba25667',
target_node_uuid='9814a57f-53a4-4d4a-ad5a-15331858ce18',
uuid_='022687b6-ae08-4fef-9d6e-17afb07acdea',
valid_at='2025-02-20T20:29:40.217412Z',
graph_id='8e5686fc-f175-4da9-8778-ad8d60fc469a'
),
EntityEdge(
created_at='2025-02-20T20:31:33.771528Z',
episodes=['60d1d20e-ed6c-4966-b1da-3f4ca274a524'],
expired_at=None,
fact='The user Emily reported a bug regarding the magic pen tool drawing goats instead of boats.',
invalid_at=None,
name='REPORTED_BY',
source_node_uuid='36f5c5c6-eb16-4ebb-9db0-fd34809482f5',
target_node_uuid='cff4e758-d1a4-4910-abe7-20101a1f0d77',
uuid_='5c3124ec-b4a3-4564-a38f-02338e3db4c4',
valid_at='2024-03-16T14:20:00Z',
graph_id='8e5686fc-f175-4da9-8778-ad8d60fc469a'
),
EntityEdge(
created_at='2025-02-20T20:30:19.910797Z',
episodes=['ff9eba8b-9e90-4765-a0ce-15eb44410f70'],
expired_at=None,
fact='The stupid app generates mountains.',
invalid_at=None,
name='GENERATES',
source_node_uuid='b6e5a0ee-8823-4647-b536-5e6af0ba113a',
target_node_uuid='43aaf7c9-628c-4bf0-b7cb-02d3e9c1a49c',
uuid_='3514a3ad-1ed5-42c7-9f70-02834e8904bf',
valid_at='2025-02-20T20:29:39.08846Z',
graph_id='8e5686fc-f175-4da9-8778-ad8d60fc469a'
),
EntityEdge(
created_at='2025-02-20T20:30:19.910816Z',
episodes=['ff9eba8b-9e90-4765-a0ce-15eb44410f70'],
expired_at=None,
fact='The stupid app keeps turning mountains into fountains.',
invalid_at=None,
name='TRANSFORMS_INTO',
source_node_uuid='43aaf7c9-628c-4bf0-b7cb-02d3e9c1a49c',
target_node_uuid='0c90b42c-2b9f-4998-aa67-cc968f9002d3',
uuid_='2f113810-3597-47a4-93c5-96d8002366fa',
valid_at='2025-02-20T20:29:39.08846Z',
graph_id='8e5686fc-f175-4da9-8778-ad8d60fc469a'
)
]
```
## Creating a simple Chatbot
In the next cells, Emily starts a new chat session with a support agent and complains that she can't log in. Our simple chatbot will, given relevant facts retrieved from Zep's graph, respond accordingly.
Here, the support agent is provided with Emily's billing information and account status, which Zep retrieves as most relevant to Emily's login issue.
```python
new_session_id = str(uuid.uuid4())
emily_message = "Hi, I can't log in!"
# We start a new session indicating that Emily has started a new chat with the support agent.
zep.memory.add_session(user_id=user_id, session_id=new_session_id)
# We need to add the Emily's message to the session in order for memory.get to return
# relevant facts related to the message
zep.memory.add(
session_id=new_session_id,
messages=[Message(role_type="user", role=user_name, content=emily_message)],
)
```
```typescript
const new_session_id = uuidv4();
const emily_message = "Hi, I can't log in!";
// We start a new session indicating that Emily has started a new chat with the support agent.
await zep.memory.addSession({
userId: user_id,
sessionId: new_session_id
});
// We need to add the Emily's message to the session in order for memory.get to return
// relevant facts related to the message
await zep.memory.add(new_session_id, {
messages: [{
roleType: "user",
role: user_name,
content: emily_message
}]
});
```
```python
system_message = """
You are a customer support agent. Carefully review the facts about the user below and respond to the user's question.
Be helpful and friendly.
"""
memory = zep.memory.get(session_id=new_session_id)
messages = [
{
"role": "system",
"content": system_message,
},
{
"role": "assistant",
# The context field is an opinionated string that contains facts and entities relevant to the current conversation.
"content": memory.context,
},
{
"role": "user",
"content": emily_message,
},
]
response = oai_client.chat.completions.create(
model="gpt-4o-mini",
messages=messages,
temperature=0,
)
print(response.choices[0].message.content)
```
```typescript
const system_message = `
You are a customer support agent. Carefully review the facts about the user below and respond to the user's question.
Be helpful and friendly.
`;
const new_memory = await zep.memory.get(new_session_id);
const messages = [
{
role: "system" as const,
content: system_message,
},
{
role: "assistant" as const,
// The context field is an opinionated string that contains facts and entities relevant to the current conversation.
content: new_memory.context || "",
},
{
role: "user" as const,
content: emily_message,
},
];
const response = await oai_client.chat.completions.create({
model: "gpt-4o-mini",
messages: messages,
temperature: 0,
});
console.log(response.choices[0].message.content);
```
```text
Hi Emily! I'm here to help you. It looks like your account is currently suspended due to a payment failure. This might be the reason you're unable to log in.
The last transaction on your account failed because the card you were using has expired. If you update your payment information, we can help you get your account reactivated. Would you like assistance with that?
```
Let's look at the memory context string Zep retrieved for the above `memory.get` call.
```python
rich.print(memory.context)
```
```typescript
console.log(new_memory.context);
```
```text
FACTS and ENTITIES represent relevant context to the current conversation.
# These are the most relevant facts and their valid date ranges
# format: FACT (Date range: from - to)
- Account with ID 'Emily1c2e' has a status of 'suspended'. (2025-02-24 23:24:29 - present)
- user has the id of Emily1c2e (2025-02-24 23:24:29 - present)
- User with ID 'Emily1c2e' has an account with ID 'Emily1c2e'. (2025-02-24 23:24:29 - present)
- The bug report has been escalated to the engineering team. (2024-03-16 14:27:00 - present)
- user has the name of Emily Painter (2025-02-24 23:24:29 - present)
- Emily is the person being assisted by SupportBot. (2025-02-24 23:24:28 - present)
- Emily1c2e is using the character creator. (2025-02-24 23:24:28 - present)
- The reason for the account status 'suspended' is 'payment failure'. (2025-02-24 23:24:29 - present)
- SupportBot is part of PaintWiz support. (2025-02-24 23:24:28 - present)
- user has the email of [email protected] (2025-02-24 23:24:29 - present)
- Emily is a user of PaintWiz. (2025-02-24 23:24:28 - present)
- The support agent suggested that Emily manually select the boat shape from the options. (2025-02-24 23:24:29 -
present)
- All the people in Emily1c2e's drawings have six fingers. (2025-02-24 23:24:28 - present)
- Emily1c2e is using the landscape generator. (2025-02-24 23:24:28 - present)
- Emily is a user of the AI art generation. (2025-02-24 23:24:28 - present)
- Emily states that the AI art generation is completely broken. (2025-02-24 23:24:28 - present)
- The magic pen tool draws goats instead of boats when used by Emily. (2025-02-24 23:24:29 - present)
- Emily1c2e tries to draw mountains. (2025-02-24 23:24:28 - present)
# These are the most relevant entities
# ENTITY_NAME: entity summary
- goats: In a recent support interaction, a user reported a bug with the magic pen tool in a drawing application,
where attempting to draw boats resulted in the tool drawing goats instead. The user, Emily, described the issue,
stating that whenever she selects the magic pen and draws a boat shape, it is replaced with a goat shape. The
support agent acknowledged the problem and confirmed it would be escalated to the engineering team for resolution.
In the meantime, the agent suggested that Emily could manually select the boat shape from the available options
instead of using the pen tool. Emily expressed her hope for a quick fix to the issue.
- failure_reason: Two transactions failed due to expired cards: one on September 15, 2024, and another on August
30, 2024, for the amount of $99.99 associated with account ID 'Emily1c2e'.
- status: User account "Emily1c2e" is suspended due to a payment failure. A transaction of $99.99 on September
15, 2024, failed because the card ending in "1234" had expired. This card had previously been used successfully for
the same amount on July 30, 2024, but a failure on August 30, 2024, resulted in the account's suspension.
- bug: A user reported a bug with the magic pen tool, stating that when attempting to draw boats, the tool
instead draws goats. The support agent acknowledged the issue and requested more details about how the user was
utilizing the tool. The user explained that they select the magic pen and draw a boat shape, but it gets replaced
with goats. The support agent confirmed the bug and stated that it would be escalated to the engineering team for
resolution. In the meantime, they suggested that the user manually select the boat shape from the options instead
of using the pen. The user expressed hope for a quick fix.
- user_id: Emily reported a bug with the magic pen tool in a drawing application, where attempting to draw boats
resulted in goats being drawn instead. A support agent acknowledged the issue and requested more details. Emily
explained her process, and the agent confirmed the bug, stating it would be escalated to the engineering team. As a
temporary workaround, the agent suggested manually selecting the boat shape. Emily expressed hope for a quick
resolution. Additionally, it was noted that another user, identified as "Emily1c2e," has a suspended account due to
a payment failure.
- people: Emily is frustrated with the AI art generation feature of PaintWiz, specifically mentioning that the
people in her drawings are depicted with six fingers, which she finds ridiculous.
- character creator: Emily is experiencing significant issues with the character creator feature of the app. She
reports that when using the landscape generator and character creator, the app is malfunctioning, resulting in
bizarre outcomes such as people in her drawings having six fingers. Emily expresses her frustration, stating that
the AI art generation is completely broken and is not functioning as expected.
```
# Memory
> Learn how to use the Memory API to store and retrieve memory.
Zep makes memory management extremely simple: you add memory with a single line, retrieve memory with a single line, and then can immediately use the retrieved memory in your next LLM call.
The Memory API is high-level and opinionated. For a more customizable, low-level way to add and retrieve memory, see the [Graph API](/understanding-the-graph).
## Adding memory
Add your chat history to Zep using the `memory.add` method. `memory.add` is session-specific and expects data in chat message format, including a `role` name (e.g., user's real name), `role_type` (AI, human, tool), and message `content`. Zep stores the chat history and builds a user-level knowledge graph from the messages.
For best results, add chat history to Zep on every chat turn. That is, add both the AI and human messages in a single operation and in the order that the messages were created.
The example below adds messages to Zep's memory for the user in the given session:
```python
from zep_cloud.client import AsyncZep
from zep_cloud.types import Message
zep_client = AsyncZep(
api_key=API_KEY,
)
messages = [
Message(
role="Jane",
role_type="user",
content="Who was Octavia Butler?",
)
]
await zep_client.memory.add(session_id, messages=messages)
```
```typescript
import { ZepClient } from "@getzep/zep-cloud";
import type { Message } from "@getzep/zep-cloud/api";
const zepClient = new ZepClient({
apiKey: API_KEY,
});
const messages: Message[] = [
{ role: "Jane", role_type: "user", content: "Who was Octavia Butler?" },
];
await zepClient.memory.add(sessionId, { messages });
```
```Go
import (
"github.com/getzep/zep-go/v2"
zepclient "github.com/getzep/zep-go/v2/client"
"github.com/getzep/zep-go/v2/option"
)
zepClient := zepclient.NewClient(
option.WithAPIKey(""),
)
response, err := zepClient.Memory.Add(
context.TODO(),
"sessionId",
&zepgo.AddMemoryRequest{
Messages: []*zepgo.Message{
&zepgo.Message{
Role: "Jane",
RoleType: "user",
Content: "Who was Octavia Butler?",
},
},
},
)
```
You can find additional arguments to `memory.add` in the [SDK reference](/sdk-reference/memory/add). Notably, for latency sensitive applications, you can set `return_context` to true which will make `memory.add` return a context string in the way that `memory.get` does (discussed below).
If you are looking to add JSON or unstructured text as memory to the graph, you will need to use our [Graph API](/adding-data-to-the-graph).
### Ignore assistant messages
You can also pass in a list of role types to ignore when adding data to the graph using the `ignore_roles` argument. For example, you may not want assistant messages to be added to the user graph; providing the assistant messages in the `memory.add` call while setting `ignore_roles` to include "assistant" will make it so that only the user messages are ingested into the graph, but the assistant messages are still used to contextualize the user messages. This is important in case the user message itself does not have enough context, such as the message "Yes." Additionally, the assistant messages will still be added to the session's message history.
## Retrieving memory
The `memory.get()` method is a user-friendly, high-level API for retrieving relevant context from Zep. It uses the latest messages of the *given session* to determine what information is most relevant from the user's knowledge graph and returns that information in a [context string](/concepts#memory-context) for your prompt. Note that although `memory.get()` only requires a session ID, it is able to return memory derived from any session of that user. The session is just used to determine what's relevant.
`memory.get` also returns recent chat messages and raw facts that may provide additional context for your agent. We recommend using these raw messages when you call your LLM provider (see below). The `memory.get` method is user and session-specific and cannot retrieve data from group graphs.
The example below gets the `memory.context` string for the given session:
```python
memory = zep_client.memory.get(session_id="session_id")
# the context field described above
context = memory.context
```
```typescript
const memory = await zep_client.memory.get("sessionId");
// the context field described above
const context = memory.context;
```
```Go
memory, err := zep_client.Memory.Get(context.TODO(), "sessionId", nil)
// the context field described above
context := memory.Context
```
You can find additional arguments to `memory.get` in the [SDK reference](/sdk-reference/memory/get). Notably, you can specify a minimum [fact rating](/facts#rating-facts-for-relevancy) which will filter out any retrieved facts with a rating below the threshold, if you are using fact ratings.
If you are looking to customize how memory is retrieved, you will need to [search the graph](/searching-the-graph) and construct a [custom memory context string](/cookbook/customize-your-memory-context-string). For example, `memory.get` uses the last few messages as the search query on the graph, but using the graph API you can use whatever query you want, as well as experiment with other search parameters such as re-ranker used.
## Using memory
Once you've retrieved the [memory context string](/concepts#memory-context), or [constructed your own context string](/cookbook/customize-your-memory-context-string) by [searching the graph](/searching-the-graph), you can include this string in your system prompt:
| MessageType | Content |
| ----------- | ------------------------------------------------------- |
| `System` | Your system prompt
`{Zep context string}` |
| `Assistant` | An assistant message stored in Zep |
| `User` | A user message stored in Zep |
| ... | ... |
| `User` | The latest user message |
You should also include the last 4 to 6 messages of the session when calling your LLM provider. Because Zep's ingestion can take a few minutes, the context string may not include information from the last few messages; and so the context string acts as the "long-term memory," and the last few messages serve as the raw, short-term memory.
In latency sensitive applications such as voice chat bots, you can use the context string returned from `memory.add` to avoid making two API calls.
## Customizing memory
The Memory API is our high level, easy-to-use API for adding and retrieving memory. If you want to add business data or documents to memory, or further customize how memory is retrieved, you should refer to our Guides on using the graph, such as [adding data to the graph](/adding-data-to-the-graph) and [searching the graph](/searching-the-graph). We also have a cookbook on [creating a custom context string](/cookbook/customize-your-memory-context-string) using the graph API.
Additionally, [group graphs](/groups) can be used to store non-user-specific memory.
# Projects
API keys are specific to a project. You can create multiple keys for a single project. Visit
`Project Settings`
in the Zep dashboard to manage your API keys.
Projects bundle elements like Users, Sessions, Groups, Knowledge Graphs, and settings, helping you organize data by service, environment (e.g., development or production), or other relevant criteria.
## Creating a Project
When you sign up for Zep, your first project is automatically created. You'll be asked to configure a few project-specific settings (details below).
If you need more projects, you can create them anytime through the Zep Web App.
### Project Essentials
* Unique Project Name: Choose a unique name for your project.
* Description (Optional): Optionally add a brief description of your project.
> **You can modify your project settings later from the Dashboard.**
# Users
A User represents an individual interacting with your application. Each User can have multiple Sessions associated with them, allowing you to track and manage their interactions over time.
The unique identifier for each user is their `UserID`. This can be any string value, such as a username, email address, or UUID.
The User object and its associated Sessions provide a powerful way to manage and understand user behavior. By associating Sessions with Users, you can track the progression of conversations and interactions over time, providing valuable context and history.
In the following sections, you will learn how to manage Users and their associated Sessions.
**Users Enable Simple User Privacy Management**
Deleting a User will delete all Sessions and session artifacts associated with that User with a single API call, making it easy to handle Right To Be Forgotten requests.
## Ensuring your User data is correctly mapped to the Zep knowledge graph
Adding your user's `email`, `first_name`, and `last_name` ensures that chat messages and business data are correctly mapped to the user node in the Zep knowledge graph.
For e.g., if business data contains your user's email address, it will be related directly to the user node.
You can associate rich business context with a User:
* `user_id`: A unique identifier of the user that maps to your internal User ID.
* `email`: The user's email.
* `first_name`: The user's first name.
* `last_name`: The user's last name.
## Adding a User
You can add a new user by providing the user details.
```python
from zep_cloud.client import Zep
client = Zep(api_key=API_KEY)
new_user = client.user.add(
user_id=user_id,
email="[email protected]",
first_name="Jane",
last_name="Smith",
)
```
```typescript
import { ZepClient } from "@getzep/zep-cloud";
const client = new ZepClient({
apiKey: API_KEY,
});
const user = await client.user.add({
userId: user_id,
email: "[email protected]",
firstName: "Jane",
lastName: "Smith",
});
```
> Learn how to associate [Sessions with Users](/sessions)
## Getting a User
You can retrieve a user by their ID.
```python
user = client.user.get("user123")
```
```typescript
const user = await client.user.get("user123");
```
## Updating a User
You can update a user's details by providing the updated user details.
```python
updated_user = client.user.update(
user_id=user_id,
email="[email protected]",
first_name="Jane",
last_name="Smith",
)
```
```typescript
const updated_user = await client.user.update(user_id, {
email: "[email protected]",
firstName: "Jane",
lastName: "Smith",
metadata: { foo: "updated_bar" },
});
```
## Deleting a User
You can delete a user by their ID.
```python
client.user.delete("user123")
```
```typescript
await client.user.delete("user123");
```
## Getting a User's Sessions
You can retrieve all Sessions for a user by their ID.
```python
sessions = client.user.get_sessions("user123")
```
```typescript
const sessions = await client.user.getSessions("user123");
```
## Listing Users
You can list all users, with optional limit and cursor parameters for pagination.
```python
# List the first 10 users
result = client.user.list_ordered(page_size=10, page_number=1)
```
```typescript
// List the first 10 users
const result = await client.user.listOrdered({
pageSize: 10,
pageNumber: 1,
});
```
## Get the User Node
You can also retrieve the user's node from their graph:
```python
results = client.user.get_node(user_id=user_id)
user_node = results.node
print(user_node.summary)
```
```typescript
const results = await client.user.getNode(userId);
const userNode = results.node;
console.log(userNode?.summary);
```
The user node might be used to get a summary of the user or to get facts related to the user (see ["How to find facts relevant to a specific node"](/cookbook/how-to-find-facts-relevant-to-a-specific-node)).
# Sessions
Sessions represent a conversation. Each [User](/users) can have multiple sessions, and each session is a sequence of chat messages.
Chat messages are added to sessions using [`memory.add`](/concepts#using-memoryadd), which both adds those messages to the session history and ingests those messages into the user-level knowledge graph. The user knowledge graph contains data from all of that user's sessions to create an integrated understanding of the user.
The knowledge graph does not separate the data from different sessions, but integrates the data together to create a unified picture of the user. So the [get session memory](/sdk-reference/memory/get) endpoint and the associated [`memory.get`](/concepts#using-memoryget) method don't return memory derived only from that session, but instead return whatever user-level memory is most relevant to that session, based on the session's most recent messages.
## Adding a Session
`SessionIDs` are arbitrary identifiers that you can map to relevant business objects in your app, such as users or a
conversation a user might have with your app. Before you create a session, make sure you have [created a user](/users#adding-a-user) first. Then create a session with:
```python
client = Zep(
api_key=API_KEY,
)
session_id = uuid.uuid4().hex # A new session identifier
client.memory.add_session(
session_id=session_id,
user_id=user_id,
)
```
```typescript
const client = new ZepClient({
apiKey: API_KEY,
});
const sessionId: string = uuid.v4(); // Generate a new session identifier
await client.memory.addSession({
sessionId: session_id,
userId: userId,
});
```
## Getting a Session
```python
session = client.memory.get_session(session_id)
print(session.dict())
```
```typescript
const session = await client.memory.getSession(sessionId);
console.log(session);
```
## Deleting a Session
Deleting a session deletes it and its associated messages. It does not however delete the associated data in the user's knowledge graph. To remove data from the graph, see [deleting data from the graph](/deleting-data-from-the-graph).
```python
client.memory.delete(session_id)
```
```typescript
await client.memory.delete(sessionId);
```
## Listing Sessions
You can list all Sessions in the Zep Memory Store with page\_size and page\_number parameters for pagination.
```python
# List the first 10 Sessions
result = client.memory.list_sessions(page_size=10, page_number=1)
for session in result.sessions:
print(session)
```
```typescript
// List the first 10 Sessions
const { sessions } = await client.memory.listSessions({
pageSize: 10,
pageNumber: 1,
});
console.log("First 10 Sessions:");
sessions.forEach((session) => console.log(session));
```
# Groups
> Group graphs can be used to create and manage additional non-user specific graphs.
A user graph is tied to a specific user; a group graph is just like a user graph, except it is not tied to a specific user. It is best thought of as an "arbitrary graph" which, for example, can be used as memory for a group of users, or for a more complex use case.
For example, a group graph could store information about a company's product, which you might not want to add to every user's graph, because that would be redundant. And when your chatbot responds, it could utilize a memory context string from both that user's graph as well as from the product group graph. See our [cookbook on this](/cookbook/how-to-share-memory-across-users-using-group-graphs) for an example.
A more complicated use case could be to create a group graph which is used when a certain topic is mentioned as opposed to when certain users require a response. For instance, anytime any user mentions "pizza" in a chat, that could trigger a call to a group graph about pizza.
You do not need to add/register users with a group. Instead, you just retrieve memory from the group graph when responding to any of the users you want in the group.
## Creating a Group
```python
group = client.group.add(
group_id="some-group-id",
description="This is a description.",
name="Group Name"
)
```
```typescript
const group = await client.group.add({
groupId: "some-group-id",
description: "This is a description.",
name: "Group Name"
});
```
## Adding Data to a Group Graph
Adding data to a group graph requires using the `graph.add` method. Below is an example, and for more on this method, see [Adding Data to the Graph](/adding-data-to-the-graph) and our [SDK Reference](/sdk-reference/graph/add).
```python
client.graph.add(
group_id=group_id,
data="Hello world!",
type="text",
)
```
```typescript
await client.graph.add({
groupId: "some-group-id",
data: "Hello world!",
type: "text",
});
```
## Searching a Group Graph
Searching a group graph requires using the `graph.search` method. Below is an example, and for more on this method, see [Searching the Graph](/searching-the-graph) and our [SDK Reference](/sdk-reference/graph/search).
```python
search_results = client.graph.search(
group_id=group_id,
query="Banana",
scope="nodes",
)
```
```typescript
const searchResults = await client.graph.search({
groupId: groupId,
query: "Banana",
scope: "nodes",
});
```
## Deleting a Group
```python
client.group.delete(group_id)
```
```typescript
await client.group.delete("some-group-id");
```
# Understanding the Graph
Zep's knowledge graph powers its facts and memory capabilities. Zep's graph is built on [Graphiti](/graphiti/graphiti/overview), Zep's open-source temporal graph library, which is fully integrated into Zep. Developers do not need to interact directly with Graphiti or understand its underlying implementation.
Zep's graph database stores data in three main types:
1. Entity edges (edges): Represent relationships between nodes and include semantic facts representing the relationship between the edge's nodes.
2. Entity nodes (nodes): Represent entities extracted from episodes, containing summaries of relevant information.
3. Episodic nodes (episodes): Represent raw data stored in Zep, either through chat history or the `graph.add` endpoint.
## Working with the Graph
To learn more about interacting with Zep's graph, refer to the following sections:
* [Adding Data to the Graph](/adding-data-to-the-graph): Learn how to add new data to the graph.
* [Reading Data from the Graph](/reading-data-from-the-graph): Discover how to retrieve information from the graph.
* [Searching the Graph](/searching-the-graph): Explore techniques for efficiently searching the graph.
These guides will help you leverage the full power of Zep's knowledge graph in your applications.
# Utilizing Facts and Summaries
> Facts and summaries are extracted from the chat history as a conversation unfolds as well as from business data added to Zep.
## Understanding Facts and Summaries in Zep
### Facts are Precise and Time-Stamped Information
A `fact` is stored on an [edge](/sdk-reference/graph/edge/get) and captures a detailed relationship about specific events. It includes `valid_at` and `invalid_at` timestamps, ensuring temporal accuracy and preserving a clear history of changes over time. This makes facts reliable sources of truth for critical information retrieval, providing the authoritative context needed for accurate decision-making and analysis by your agent.
### Summaries are High-Level Overviews of Entities or Concepts
A `summary` resides on a [node](/sdk-reference/graph/node/get) and provides a broad snapshot of an entity or concept and its relationships to other nodes. Summaries offer an aggregated and concise representation, making it easier to understand key information at a glance.
Zep does not recommend relying solely on summaries for grounding LLM responses. While summaries provide a high-level overview, they lack the temporal accuracy necessary for precise reasoning. Instead, the [memory context](/concepts#memory-context) should be used since it includes relevant facts (each with valid and invalid timestamps). This ensures that conversations are based on up-to-date and contextually accurate information.
## Context String
When calling [Get Session Memory](/sdk-reference/memory/get), Zep employs a sophisticated search strategy to surface the most pertinent information. The system first examines recent context by analyzing the last 4 messages (2 complete chat turns). It then utilizes multiple search techniques, with reranking steps to identify and prioritize the most contextually significant details for the current conversation.
The returned, `context` is structured as a string, optimized for language model prompts, making it easy to integrate into AI workflows. For more details, see [Key Concepts](/concepts#memory-context). In addition to the `context`, the API response includes an array of the identified `relevant_facts` with their supporting details.
## Rating Facts for Relevancy
Not all `relevant_facts` are equally important to your specific use-case. For example, a relationship coach app may need to recall important facts about a user’s family, but what the user ate for breakfast Friday last week is unimportant.
Fact ratings are a way to help Zep understand the importance of `relevant_facts` to your particular use case. After implementing fact ratings, you can specify a `minRating` when retrieving `relevant_facts` from Zep, ensuring that the memory `context` string contains customized content.
### Implementing Fact Ratings
The `fact_rating_instruction` framework consists of an instruction and three example facts, one for each of a `high`, `medium`, and `low` rating. These are passed when [Adding a User](/sdk-reference/user/add) or [Adding a Group](/sdk-reference/group/add) and become a property of the User or Group.
### Example: Fact Rating Implementation
```python
fact_rating_instruction = """Rate the facts by poignancy. Highly poignant
facts have a significant emotional impact or relevance to the user.
Facts with low poignancy are minimally relevant or of little emotional
significance."""
fact_rating_examples = FactRatingExamples(
high="The user received news of a family member's serious illness.",
medium="The user completed a challenging marathon.",
low="The user bought a new brand of toothpaste.",
)
client.user.add(
user_id=user_id,
fact_rating_instruction=FactRatingInstruction(
instruction=fact_rating_instruction,
examples=fact_rating_examples,
),
)
```
```python
client.user.add(
user_id=user_id,
fact_rating_instruction=FactRatingInstruction(
instruction="""Rate the facts by how relevant they
are to purchasing shoes.""",
examples=FactRatingExamples(
high="The user has agreed to purchase a Reebok running shoe.",
medium="The user prefers running to cycling.",
low="The user purchased a dress.",
),
),
)
```
All facts are rated on a scale between 0 and 1. You can access `rating` when retrieving `relevant_facts` from [Get Session Memory](/sdk-reference/memory/get).
### Limiting Memory Recall to High-Rating Facts
You can filter `relevant_facts` by setting the `minRating` parameter in [Get Session Memory](/sdk-reference/memory/get).
```python
result = client.memory.get(session_id, min_rating=0.7)
```
## Adding or Deleting Facts or Summaries
Facts and summaries are generated as part of the ingestion process. If you follow the directions for [adding data to the graph](/adding-data-to-the-graph), new facts and summaries will be created.
Deleting facts and summaries is handled by deleting data from the graph. Facts and summaries will be deleted when you [delete the edge or node](/deleting-data-from-the-graph) they exist on.
## APIs related to Facts and Summaries
You can extract facts and summaries using the following methods:
| Method | Description |
| ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------ |
| [Get Session Memory](/sdk-reference/memory/get) | Retrieves the `context` string and `relevant_facts` |
| [Add User](/sdk-reference/user/add)
[Update User](/sdk-reference/user/update)
[Create Group](/sdk-reference/group/add)
[Update Group](/sdk-reference/group/update) | Allows specifying `fact_rating_instruction` |
| [Get User](/sdk-reference/user/get)
[Get Users](/sdk-reference/user/list-ordered)
[Get Group](/sdk-reference/group/get-group)
[Get All Groups](/sdk-reference/group/get-all-groups) | Retrieves `fact_rating_instruction` for each user or group |
| [Search the Graph](/sdk-reference/graph/search) | Returns a list. Each item is an `edge` or `node` and has an associated `fact` or `summary` |
| [Get User Edges](/sdk-reference/graph/edge/get-by-user-id)
[Get Group Edges](/sdk-reference/graph/edge/get-by-group-id)
[Get Edge](/sdk-reference/graph/edge/get) | Retrieves `fact` on each `edge` |
| [Get User Nodes](/sdk-reference/graph/node/get-by-user-id)
[Get Group Nodes](/sdk-reference/graph/node/get-by-group-id)
[Get Node](/sdk-reference/graph/node/get) | Retrieves `summary` on each `node` |
# Customizing Graph Structure
Zep enables the use of rich, domain-specific data structures in graphs through Entity Types and Edge Types, replacing generic graph nodes and edges with detailed models.
Zep classifies newly created nodes/edges as one of the default or custom types or leaves them unclassified. For example, a node representing a preference is classified as a Preference node, and attributes specific to that type are automatically populated. You may restrict graph queries to nodes/edges of a specific type, such as Preference.
The default entity types are applied to all graphs by default, but you may define additional custom types as needed.
Each node/edge is classified as a single type only. Multiple classifications are not supported.
## Default Entity Types
### Definition
The default entity types are:
* **User**: A human that is part of the current chat thread.
* **Preference**: One of the User's preferences.
* **Procedure**: A multi-step instruction informing the agent how to behave (e.g. 'When the user asks for code, respond only with code snippets followed by a bullet point explanation')
Default entity types only apply to user graphs (not group graphs). All nodes in any user graph will be classified into one of these types or none.
### Adding Data
When we add data to the graph, default entity types are automatically created:
```python
from zep_cloud.types import Message
message = {"role": "John Doe", "role_type": "user", "content": "I really like pop music, and I don't like metal"}
client.memory.add(session_id=session_id, messages=[Message(**message)])
```
```typescript
import { RoleType } from "@getzep/zep-cloud/api/types";
const messages = [{ role: "John Doe", roleType: RoleType.UserRole, content: "I really like pop music, and I don't like metal" }];
await client.memory.add(sessionId, {messages: messages});
```
```go
userRole := "John Doe"
messages := []*zep.Message{
{
Role: &userRole,
Content: "I really like pop music, and I don't like metal",
RoleType: "user",
},
}
// Add the messages to the graph
_, err = client.Memory.Add(
context.TODO(),
sessionID,
&zep.AddMemoryRequest{
Messages: messages,
},
)
if err != nil {
log.Fatal("Error adding messages:", err)
}
```
### Searching
When searching nodes in the graph, you may provide a list of types to filter the search by. The provided types are ORed together. Search results will only include nodes that satisfy one of the provided types:
```python
from zep_cloud.types import SearchFilters
search_results = client.graph.search(
user_id=user_id,
query="the user's music preferences",
scope="nodes",
search_filters=SearchFilters(
node_labels=["Preference"]
)
)
for i, node in enumerate(search_results.nodes):
preference = node.attributes
print(f"Preference {i+1}:{preference}")
```
```typescript
const searchResults = await client.graph.search({
userId: userId,
query: "the user's music preferences",
scope: "nodes",
searchFilters: {
nodeLabels: ["Preference"],
},
});
if (searchResults.nodes && searchResults.nodes.length > 0) {
for (let i = 0; i < searchResults.nodes.length; i++) {
const node = searchResults.nodes[i];
const preference = node.attributes;
console.log(`Preference ${i + 1}: ${JSON.stringify(preference)}`);
}
}
```
```go
searchFilters := zep.SearchFilters{NodeLabels: []string{"Preference"}}
searchResults, err := client.Graph.Search(
ctx,
&zep.GraphSearchQuery{
UserID: zep.String(userID),
Query: "the user's music preferences",
Scope: zep.GraphSearchScopeNodes.Ptr(),
SearchFilters: &searchFilters,
},
)
if err != nil {
log.Fatal("Error searching graph:", err)
}
for i, node := range searchResults.Nodes {
// Convert attributes map to JSON for pretty printing
attributesJSON, err := json.MarshalIndent(node.Attributes, "", " ")
if err != nil {
log.Fatal("Error marshaling attributes:", err)
}
fmt.Printf("Preference %d:\n%s\n\n", i+1, string(attributesJSON))
}
```
```text
Preference 1: {'category': 'Music', 'description': 'Pop Music is a genre of music characterized by its catchy melodies and widespread appeal.', 'labels': ['Entity', 'Preference']}
Preference 2: {'category': 'Music', 'description': 'Metal Music is a genre of music characterized by its heavy sound and complex compositions.', 'labels': ['Entity', 'Preference']}
```
## Custom Entity and Edge Types
### Definition
In addition to the default entity types, you may specify your own custom entity and custom edge types. You need to provide a description of the type and a description for each of the fields. The syntax for this is different for each language.
You may not create more than 10 custom entity types and 10 custom edge types per project. The limit of 10 custom entity types does not include the default types. Each model may have up to 10 fields.
When creating custom entity or edge types, you may not use the following attribute names (including in Go struct tags), as they conflict with default node attributes: `uuid`, `name`, `group_id`, `name_embedding`, `summary`, and `created_at`.
```python
from zep_cloud.external_clients.ontology import EntityModel, EntityText, EdgeModel, EntityBoolean
from pydantic import Field
class Restaurant(EntityModel):
"""
Represents a restaurant entity.
"""
cuisine_type: EntityText = Field(description="The cuisine type of the restaurant, for example: American, Mexican, Indian, etc.", default=None)
dietary_accommodation: EntityText = Field(description="The dietary accommodation of the restaurant, if any, for example: vegetarian, vegan, etc.", default=None)
class Audiobook(EntityModel):
"""
Represents an audiobook entity.
"""
genre: EntityText = Field(description="The genre of the audiobook, for example: self-help, fiction, nonfiction, etc.", default=None)
class RestaurantVisit(EdgeModel):
"""
Represents the fact that the user visited a restaurant.
"""
restaurant_name: EntityText = Field(description="The name of the restaurant the user visited", default=None)
class AudiobookListen(EdgeModel):
"""
Represents the fact that the user listened to or played an audiobook.
"""
audiobook_title: EntityText = Field(description="The title of the audiobook the user listened to or played", default=None)
class DietaryPreference(EdgeModel):
"""
Represents the fact that the user has a dietary preference or dietary restriction.
"""
preference_type: EntityText = Field(description="Preference type of the user: anything, vegetarian, vegan, peanut allergy, etc.", default=None)
allergy: EntityBoolean = Field(description="Whether this dietary preference represents a user allergy: True or false", default=None)
```
```typescript
import { entityFields, EntityType, EdgeType } from "@getzep/zep-cloud/wrapper/ontology";
const RestaurantSchema: EntityType = {
description: "Represents a restaurant entity.",
fields: {
cuisine_type: entityFields.text("The cuisine type of the restaurant, for example: American, Mexican, Indian, etc."),
dietary_accommodation: entityFields.text("The dietary accommodation of the restaurant, if any, for example: vegetarian, vegan, etc."),
},
};
const AudiobookSchema: EntityType = {
description: "Represents an audiobook entity.",
fields: {
genre: entityFields.text("The genre of the audiobook, for example: self-help, fiction, nonfiction, etc."),
},
};
const RestaurantVisit: EdgeType = {
description: "Represents the fact that the user visited a restaurant.",
fields: {
restaurant_name: entityFields.text("The name of the restaurant the user visited"),
},
sourceTargets: [
{ source: "User", target: "Restaurant" },
],
};
const AudiobookListen: EdgeType = {
description: "Represents the fact that the user listened to or played an audiobook.",
fields: {
audiobook_title: entityFields.text("The title of the audiobook the user listened to or played"),
},
sourceTargets: [
{ source: "User", target: "Audiobook" },
],
};
const DietaryPreference: EdgeType = {
description: "Represents the fact that the user has a dietary preference or dietary restriction.",
fields: {
preference_type: entityFields.text("Preference type of the user: anything, vegetarian, vegan, peanut allergy, etc."),
allergy: entityFields.boolean("Whether this dietary preference represents a user allergy: True or false"),
},
sourceTargets: [
{ source: "User" },
],
};
```
```go
type Restaurant struct {
zep.BaseEntity `name:"Restaurant" description:"Represents a restaurant entity."`
CuisineType string `description:"The cuisine type of the restaurant, for example: American, Mexican, Indian, etc." json:"cuisine_type,omitempty"`
DietaryAccommodation string `description:"The dietary accommodation of the restaurant, if any, for example: vegetarian, vegan, etc." json:"dietary_accommodation,omitempty"`
}
type Audiobook struct {
zep.BaseEntity `name:"Audiobook" description:"Represents an audiobook entity."`
Genre string `description:"The genre of the audiobook, for example: self-help, fiction, nonfiction, etc." json:"genre,omitempty"`
}
type RestaurantVisit struct {
zep.BaseEdge `name:"RESTAURANT_VISIT" description:"Represents the fact that the user visited a restaurant."`
RestaurantName string `description:"The name of the restaurant the user visited" json:"restaurant_name,omitempty"`
}
type AudiobookListen struct {
zep.BaseEdge `name:"AUDIOBOOK_LISTEN" description:"Represents the fact that the user listened to or played an audiobook."`
AudiobookTitle string `description:"The title of the audiobook the user listened to or played" json:"audiobook_title,omitempty"`
}
type DietaryPreference struct {
zep.BaseEdge `name:"DIETARY_PREFERENCE" description:"Represents the fact that the user has a dietary preference or dietary restriction."`
PreferenceType string `description:"Preference type of the user: anything, vegetarian, vegan, peanut allergy, etc." json:"preference_type,omitempty"`
Allergy bool `description:"Whether this dietary preference represents a user allergy: True or false" json:"allergy,omitempty"`
}
```
### Setting Entity and Edge Types
You can then set these custom entity and edge types as the graph ontology for your current [Zep project](/projects). Note that for custom edge types, you can require the source and destination nodes to be a certain type, or allow them to be any type:
```python
from zep_cloud import EntityEdgeSourceTarget
client.graph.set_ontology(
entities={
"Restaurant": Restaurant,
"Audiobook": Audiobook,
},
edges={
"RESTAURANT_VISIT": (
RestaurantVisit,
[EntityEdgeSourceTarget(source="User", target="Restaurant")]
),
"AUDIOBOOK_LISTEN": (
AudiobookListen,
[EntityEdgeSourceTarget(source="User", target="Audiobook")]
),
"DIETARY_PREFERENCE": (
DietaryPreference,
[EntityEdgeSourceTarget(source="User")]
),
}
)
```
```typescript
await client.graph.setOntology(
{
Restaurant: RestaurantSchema,
Audiobook: AudiobookSchema,
},
{
RESTAURANT_VISIT: RestaurantVisit,
AUDIOBOOK_LISTEN: AudiobookListen,
DIETARY_PREFERENCE: DietaryPreference,
}
);
```
```go
_, err = client.Graph.SetOntology(
ctx,
[]zep.EntityDefinition{
Restaurant{},
Audiobook{},
},
[]zep.EdgeDefinitionWithSourceTargets{
{
EdgeModel: RestaurantVisit{},
SourceTargets: []zep.EntityEdgeSourceTarget{
{
Source: zep.String("User"),
Target: zep.String("Restaurant"),
},
},
},
{
EdgeModel: AudiobookListen{},
SourceTargets: []zep.EntityEdgeSourceTarget{
{
Source: zep.String("User"),
Target: zep.String("Audiobook"),
},
},
},
{
EdgeModel: DietaryPreference{},
SourceTargets: []zep.EntityEdgeSourceTarget{
{
Source: zep.String("User"),
},
},
},
},
)
if err != nil {
fmt.Printf("Error setting ontology: %v\n", err)
return
}
```
### Adding Data
Now, when you add data to the graph, new nodes and edges are classified into exactly one of the overall set of entity or edge types respectively, or no type:
```python
from zep_cloud import Message
import uuid
messages_session1 = [
Message(content="Take me to a lunch place", role_type="user", role="John Doe"),
Message(content="How about Panera Bread, Chipotle, or Green Leaf Cafe, which are nearby?", role_type="assistant", role="Assistant"),
Message(content="Do any of those have vegetarian options? I’m vegetarian", role_type="user", role="John Doe"),
Message(content="Yes, Green Leaf Cafe has vegetarian options", role_type="assistant", role="Assistant"),
Message(content="Let’s go to Green Leaf Cafe", role_type="user", role="John Doe"),
Message(content="Navigating to Green Leaf Cafe", role_type="assistant", role="Assistant"),
]
messages_session2 = [
Message(content="Play the 7 habits of highly effective people", role_type="user", role="John Doe"),
Message(content="Playing the 7 habits of highly effective people", role_type="assistant", role="Assistant"),
]
user_id = f"user-{uuid.uuid4()}"
client.user.add(user_id=user_id, first_name="John", last_name="Doe", email="[email protected]")
session1_id = f"session-{uuid.uuid4()}"
session2_id = f"session-{uuid.uuid4()}"
client.memory.add_session(session_id=session1_id, user_id=user_id)
client.memory.add_session(session_id=session2_id, user_id=user_id)
client.memory.add(session_id=session1_id, messages=messages_session1, ignore_roles=["assistant"])
client.memory.add(session_id=session2_id, messages=messages_session2, ignore_roles=["assistant"])
```
```typescript
import { v4 as uuidv4 } from "uuid";
import type { Message } from "@getzep/zep-cloud/api";
const messagesSession1: Message[] = [
{ content: "Take me to a lunch place", roleType: "user", role: "John Doe" },
{ content: "How about Panera Bread, Chipotle, or Green Leaf Cafe, which are nearby?", roleType: "assistant", role: "Assistant" },
{ content: "Do any of those have vegetarian options? I’m vegetarian", roleType: "user", role: "John Doe" },
{ content: "Yes, Green Leaf Cafe has vegetarian options", roleType: "assistant", role: "Assistant" },
{ content: "Let’s go to Green Leaf Cafe", roleType: "user", role: "John Doe" },
{ content: "Navigating to Green Leaf Cafe", roleType: "assistant", role: "Assistant" },
];
const messagesSession2: Message[] = [
{ content: "Play the 7 habits of highly effective people", roleType: "user", role: "John Doe" },
{ content: "Playing the 7 habits of highly effective people", roleType: "assistant", role: "Assistant" },
];
let userId = `user-${uuidv4()}`;
await client.user.add({ userId, firstName: "John", lastName: "Doe", email: "[email protected]" });
const session1Id = `session-${uuidv4()}`;
const session2Id = `session-${uuidv4()}`;
await client.memory.addSession({ sessionId: session1Id, userId });
await client.memory.addSession({ sessionId: session2Id, userId });
await client.memory.add(session1Id, { messages: messagesSession1, ignoreRoles: ["assistant"] });
await client.memory.add(session2Id, { messages: messagesSession2, ignoreRoles: ["assistant"] });
```
```go
messagesSession1 := []zep.Message{
{Content: "Take me to a lunch place", RoleType: "user", Role: zep.String("John Doe")},
{Content: "How about Panera Bread, Chipotle, or Green Leaf Cafe, which are nearby?", RoleType: "assistant", Role: zep.String("Assistant")},
{Content: "Do any of those have vegetarian options? I'm vegetarian", RoleType: "user", Role: zep.String("John Doe")},
{Content: "Yes, Green Leaf Cafe has vegetarian options", RoleType: "assistant", Role: zep.String("Assistant")},
{Content: "Let's go to Green Leaf Cafe", RoleType: "user", Role: zep.String("John Doe")},
{Content: "Navigating to Green Leaf Cafe", RoleType: "assistant", Role: zep.String("Assistant")},
}
messagesSession2 := []zep.Message{
{Content: "Play the 7 habits of highly effective people", RoleType: "user", Role: zep.String("John Doe")},
{Content: "Playing the 7 habits of highly effective people", RoleType: "assistant", Role: zep.String("Assistant")},
}
userID := "user-" + uuid.NewString()
userReq := &zep.CreateUserRequest{
UserID: userID,
FirstName: zep.String("John"),
LastName: zep.String("Doe"),
Email: zep.String("[email protected]"),
}
_, err = client.User.Add(ctx, userReq)
if err != nil {
fmt.Printf("Error creating user: %v\n", err)
return
}
session1ID := "session-" + uuid.NewString()
session2ID := "session-" + uuid.NewString()
session1Req := &zep.CreateSessionRequest{
SessionID: session1ID,
UserID: userID,
}
session2Req := &zep.CreateSessionRequest{
SessionID: session2ID,
UserID: userID,
}
_, err = client.Memory.AddSession(ctx, session1Req)
if err != nil {
fmt.Printf("Error creating session 1: %v\n", err)
return
}
_, err = client.Memory.AddSession(ctx, session2Req)
if err != nil {
fmt.Printf("Error creating session 2: %v\n", err)
return
}
msgPtrs1 := make([]*zep.Message, len(messagesSession1))
for i := range messagesSession1 {
msgPtrs1[i] = &messagesSession1[i]
}
addReq1 := &zep.AddMemoryRequest{
Messages: msgPtrs1,
IgnoreRoles: []zep.RoleType{
zep.RoleTypeAssistantRole,
},
}
_, err = client.Memory.Add(ctx, session1ID, addReq1)
if err != nil {
fmt.Printf("Error adding messages to session 1: %v\n", err)
return
}
msgPtrs2 := make([]*zep.Message, len(messagesSession2))
for i := range messagesSession2 {
msgPtrs2[i] = &messagesSession2[i]
}
addReq2 := &zep.AddMemoryRequest{
Messages: msgPtrs2,
IgnoreRoles: []zep.RoleType{
zep.RoleTypeAssistantRole,
},
}
_, err = client.Memory.Add(ctx, session2ID, addReq2)
if err != nil {
fmt.Printf("Error adding messages to session 2: %v\n", err)
return
}
```
### Searching/Retrieving
Now that a graph with custom entity and edge types has been created, you may filter node search results by entity type, or edge search results by edge type.
Below, you can see the examples that were created from our data of each of the entity and edge types that we defined:
```python
search_results_restaurants = client.graph.search(
user_id=user_id,
query="Take me to a restaurant",
scope="nodes",
search_filters={
"entity_types": ["Restaurant"]
},
limit=1,
)
node = search_results_restaurants.nodes[0]
print(f"Node name: {node.name}")
print(f"Node labels: {node.labels}")
print(f"Cuisine type: {node.attributes.get('cuisine_type')}")
print(f"Dietary accommodation: {node.attributes.get('dietary_accommodation')}")
```
```typescript
let searchResults = await client.graph.search({
userId: userId,
query: "Take me to a restaurant",
scope: "nodes",
searchFilters: { nodeLabels: ["Restaurant"] },
limit: 1,
});
if (searchResults.nodes && searchResults.nodes.length > 0) {
const node = searchResults.nodes[0];
console.log(`Node name: ${node.name}`);
console.log(`Node labels: ${node.labels}`);
console.log(`Cuisine type: ${node.attributes?.cuisine_type}`);
console.log(`Dietary accommodation: ${node.attributes?.dietary_accommodation}`);
}
```
```go
searchFiltersRestaurants := zep.SearchFilters{NodeLabels: []string{"Restaurant"}}
searchResultsRestaurants, err := client.Graph.Search(
ctx,
&zep.GraphSearchQuery{
UserID: zep.String(userID),
Query: "Take me to a restaurant",
Scope: zep.GraphSearchScopeNodes.Ptr(),
SearchFilters: &searchFiltersRestaurants,
Limit: zep.Int(1),
},
)
if err != nil {
fmt.Printf("Error searching graph (Restaurant node): %v\n", err)
return
}
if len(searchResultsRestaurants.Nodes) > 0 {
node := searchResultsRestaurants.Nodes[0]
fmt.Printf("Node name: %s\n", node.Name)
fmt.Printf("Node labels: %v\n", node.Labels)
fmt.Printf("Cuisine type: %v\n", node.Attributes["cuisine_type"])
fmt.Printf("Dietary accommodation: %v\n", node.Attributes["dietary_accommodation"])
}
```
```text
Node name: Green Leaf Cafe
Node labels: Entity,Restaurant
Cuisine type: undefined
Dietary accommodation: vegetarian
```
```python
search_results_audiobook_nodes = client.graph.search(
user_id=user_id,
query="Play an audiobook",
scope="nodes",
search_filters={
"entity_types": ["Audiobook"]
},
limit=1,
)
node = search_results_audiobook_nodes.nodes[0]
print(f"Node name: {node.name}")
print(f"Node labels: {node.labels}")
print(f"Genre: {node.attributes.get('genre')}")
```
```typescript
searchResults = await client.graph.search({
userId: userId,
query: "Play an audiobook",
scope: "nodes",
searchFilters: { nodeLabels: ["Audiobook"] },
limit: 1,
});
if (searchResults.nodes && searchResults.nodes.length > 0) {
const node = searchResults.nodes[0];
console.log(`Node name: ${node.name}`);
console.log(`Node labels: ${node.labels}`);
console.log(`Genre: ${node.attributes?.genre}`);
}
```
```go
searchFiltersAudiobook := zep.SearchFilters{NodeLabels: []string{"Audiobook"}}
searchResultsAudiobook, err := client.Graph.Search(
ctx,
&zep.GraphSearchQuery{
UserID: zep.String(userID),
Query: "Play an audiobook",
Scope: zep.GraphSearchScopeNodes.Ptr(),
SearchFilters: &searchFiltersAudiobook,
Limit: zep.Int(1),
},
)
if err != nil {
fmt.Printf("Error searching graph (Audiobook node): %v\n", err)
return
}
if len(searchResultsAudiobook.Nodes) > 0 {
node := searchResultsAudiobook.Nodes[0]
fmt.Printf("Node name: %s\n", node.Name)
fmt.Printf("Node labels: %v\n", node.Labels)
fmt.Printf("Genre: %v\n", node.Attributes["genre"])
}
```
```text
Node name: 7 habits of highly effective people
Node labels: Entity,Audiobook
Genre: undefined
```
```python
search_results_visits = client.graph.search(
user_id=user_id,
query="Take me to a restaurant",
scope="edges",
search_filters={
"edge_types": ["RESTAURANT_VISIT"]
},
limit=1,
)
edge = search_results_visits.edges[0]
print(f"Edge fact: {edge.fact}")
print(f"Edge type: {edge.name}")
print(f"Restaurant name: {edge.attributes.get('restaurant_name')}")
```
```typescript
searchResults = await client.graph.search({
userId: userId,
query: "Take me to a restaurant",
scope: "edges",
searchFilters: { edgeTypes: ["RESTAURANT_VISIT"] },
limit: 1,
});
if (searchResults.edges && searchResults.edges.length > 0) {
const edge = searchResults.edges[0];
console.log(`Edge fact: ${edge.fact}`);
console.log(`Edge type: ${edge.name}`);
console.log(`Restaurant name: ${edge.attributes?.restaurant_name}`);
}
```
```go
searchFiltersVisits := zep.SearchFilters{EdgeTypes: []string{"RESTAURANT_VISIT"}}
searchResultsVisits, err := client.Graph.Search(
ctx,
&zep.GraphSearchQuery{
UserID: zep.String(userID),
Query: "Take me to a restaurant",
Scope: zep.GraphSearchScopeEdges.Ptr(),
SearchFilters: &searchFiltersVisits,
Limit: zep.Int(1),
},
)
if err != nil {
fmt.Printf("Error searching graph (RESTAURANT_VISIT): %v\n", err)
return
}
if len(searchResultsVisits.Edges) > 0 {
edge := searchResultsVisits.Edges[0]
var visit RestaurantVisit
err := zep.UnmarshalEdgeAttributes(edge.Attributes, &visit)
if err != nil {
fmt.Printf("\t\tError converting edge to RestaurantVisit struct: %v\n", err)
} else {
fmt.Printf("Edge fact: %s\n", edge.Fact)
fmt.Printf("Edge type: %s\n", edge.Name)
fmt.Printf("Restaurant name: %s\n", visit.RestaurantName)
}
}
```
```text
Edge fact: User John Doe is going to Green Leaf Cafe
Edge type: RESTAURANT_VISIT
Restaurant name: Green Leaf Cafe
```
```python
search_results_audiobook_listens = client.graph.search(
user_id=user_id,
query="Play an audiobook",
scope="edges",
search_filters={
"edge_types": ["AUDIOBOOK_LISTEN"]
},
limit=1,
)
edge = search_results_audiobook_listens.edges[0]
print(f"Edge fact: {edge.fact}")
print(f"Edge type: {edge.name}")
print(f"Audiobook title: {edge.attributes.get('audiobook_title')}")
```
```typescript
searchResults = await client.graph.search({
userId: userId,
query: "Play an audiobook",
scope: "edges",
searchFilters: { edgeTypes: ["AUDIOBOOK_LISTEN"] },
limit: 1,
});
if (searchResults.edges && searchResults.edges.length > 0) {
const edge = searchResults.edges[0];
console.log(`Edge fact: ${edge.fact}`);
console.log(`Edge type: ${edge.name}`);
console.log(`Audiobook title: ${edge.attributes?.audiobook_title}`);
}
```
```go
searchFiltersAudiobookListen := zep.SearchFilters{EdgeTypes: []string{"AUDIOBOOK_LISTEN"}}
searchResultsAudiobookListen, err := client.Graph.Search(
ctx,
&zep.GraphSearchQuery{
UserID: zep.String(userID),
Query: "Play an audiobook",
Scope: zep.GraphSearchScopeEdges.Ptr(),
SearchFilters: &searchFiltersAudiobookListen,
Limit: zep.Int(1),
},
)
if err != nil {
fmt.Printf("Error searching graph (AUDIOBOOK_LISTEN): %v\n", err)
return
}
if len(searchResultsAudiobookListen.Edges) > 0 {
edge := searchResultsAudiobookListen.Edges[0]
var listen AudiobookListen
err := zep.UnmarshalEdgeAttributes(edge.Attributes, &listen)
if err != nil {
fmt.Printf("Error converting edge to AudiobookListen struct: %v\n", err)
} else {
fmt.Printf("Edge fact: %s\n", edge.Fact)
fmt.Printf("Edge type: %s\n", edge.Name)
fmt.Printf("Audiobook title: %s\n", listen.AudiobookTitle)
}
}
```
```text
Edge fact: John Doe requested to play the audiobook '7 habits of highly effective people'
Edge type: AUDIOBOOK_LISTEN
Audiobook title: 7 habits of highly effective people
```
```python
search_results_dietary_preference = client.graph.search(
user_id=user_id,
query="Find some food around here",
scope="edges",
search_filters={
"edge_types": ["DIETARY_PREFERENCE"]
},
limit=1,
)
edge = search_results_dietary_preference.edges[0]
print(f"Edge fact: {edge.fact}")
print(f"Edge type: {edge.name}")
print(f"Preference type: {edge.attributes.get('preference_type')}")
print(f"Allergy: {edge.attributes.get('allergy')}")
```
```typescript
searchResults = await client.graph.search({
userId: userId,
query: "Find some food around here",
scope: "edges",
searchFilters: { edgeTypes: ["DIETARY_PREFERENCE"] },
limit: 1,
});
if (searchResults.edges && searchResults.edges.length > 0) {
const edge = searchResults.edges[0];
console.log(`Edge fact: ${edge.fact}`);
console.log(`Edge type: ${edge.name}`);
console.log(`Preference type: ${edge.attributes?.preference_type}`);
console.log(`Allergy: ${edge.attributes?.allergy}`);
}
```
```go
searchFiltersDietary := zep.SearchFilters{EdgeTypes: []string{"DIETARY_PREFERENCE"}}
searchResultsDietary, err := client.Graph.Search(
ctx,
&zep.GraphSearchQuery{
UserID: zep.String(userID),
Query: "Find some food around here",
Scope: zep.GraphSearchScopeEdges.Ptr(),
SearchFilters: &searchFiltersDietary,
Limit: zep.Int(1),
},
)
if err != nil {
fmt.Printf("Error searching graph (DIETARY_PREFERENCE): %v\n", err)
return
}
if len(searchResultsDietary.Edges) > 0 {
edge := searchResultsDietary.Edges[0]
var dietary DietaryPreference
err := zep.UnmarshalEdgeAttributes(edge.Attributes, &dietary)
if err != nil {
fmt.Printf("Error converting edge to DietaryPreference struct: %v\n", err)
} else {
fmt.Printf("Edge fact: %s\n", edge.Fact)
fmt.Printf("Edge type: %s\n", edge.Name)
fmt.Printf("Preference type: %s\n", dietary.PreferenceType)
fmt.Printf("Allergy: %v\n", dietary.Allergy)
}
}
```
```text
Edge fact: User states 'I'm vegetarian' indicating a dietary preference.
Edge type: DIETARY_PREFERENCE
Preference type: vegetarian
Allergy: false
```
Additionally, you can provide multiple types in search filters, and the types will be ORed together:
```python
search_results_dietary_preference = client.graph.search(
user_id=user_id,
query="Find some food around here",
scope="edges",
search_filters={
"edge_types": ["DIETARY_PREFERENCE", "RESTAURANT_VISIT"]
},
limit=2,
)
for edge in search_results_dietary_preference.edges:
print(f"Edge fact: {edge.fact}")
print(f"Edge type: {edge.name}")
if edge.name == "DIETARY_PREFERENCE":
print(f"Preference type: {edge.attributes.get('preference_type')}")
print(f"Allergy: {edge.attributes.get('allergy')}")
elif edge.name == "RESTAURANT_VISIT":
print(f"Restaurant name: {edge.attributes.get('restaurant_name')}")
print("\n")
```
```typescript
searchResults = await client.graph.search({
userId: userId,
query: "Find some food around here",
scope: "edges",
searchFilters: { edgeTypes: ["DIETARY_PREFERENCE", "RESTAURANT_VISIT"] },
limit: 2,
});
if (searchResults.edges && searchResults.edges.length > 0) {
for (const edge of searchResults.edges) {
console.log(`Edge fact: ${edge.fact}`);
console.log(`Edge type: ${edge.name}`);
if (edge.name === "DIETARY_PREFERENCE") {
console.log(`Preference type: ${edge.attributes?.preference_type}`);
console.log(`Allergy: ${edge.attributes?.allergy}`);
} else if (edge.name === "RESTAURANT_VISIT") {
console.log(`Restaurant name: ${edge.attributes?.restaurant_name}`);
}
console.log("\n");
}
}
```
```go
searchFiltersDietaryAndRestaurantVisit := zep.SearchFilters{EdgeTypes: []string{"DIETARY_PREFERENCE", "RESTAURANT_VISIT"}}
searchResultsDietaryAndRestaurantVisit, err := client.Graph.Search(
ctx,
&zep.GraphSearchQuery{
UserID: zep.String(userID),
Query: "Find some food around here",
Scope: zep.GraphSearchScopeEdges.Ptr(),
SearchFilters: &searchFiltersDietaryAndRestaurantVisit,
Limit: zep.Int(2),
},
)
if err != nil {
fmt.Printf("Error searching graph (DIETARY_PREFERENCE and RESTAURANT_VISIT): %v\n", err)
return
}
if len(searchResultsDietaryAndRestaurantVisit.Edges) > 0 {
for _, edge := range searchResultsDietaryAndRestaurantVisit.Edges {
switch edge.Name {
case "DIETARY_PREFERENCE":
var dietary DietaryPreference
err := zep.UnmarshalEdgeAttributes(edge.Attributes, &dietary)
if err != nil {
fmt.Printf("Error converting edge to DietaryPreference struct: %v\n", err)
} else {
fmt.Printf("Edge fact: %s\n", edge.Fact)
fmt.Printf("Edge type: %s\n", edge.Name)
fmt.Printf("Preference type: %s\n", dietary.PreferenceType)
fmt.Printf("Allergy: %v\n", dietary.Allergy)
}
case "RESTAURANT_VISIT":
var visit RestaurantVisit
err := zep.UnmarshalEdgeAttributes(edge.Attributes, &visit)
if err != nil {
fmt.Printf("Error converting edge to RestaurantVisit struct: %v\n", err)
} else {
fmt.Printf("Edge fact: %s\n", edge.Fact)
fmt.Printf("Edge type: %s\n", edge.Name)
fmt.Printf("Restaurant name: %s\n", visit.RestaurantName)
}
default:
fmt.Printf("Unknown edge type: %s\n", edge.Name)
}
fmt.Println()
}
}
```
```text
Edge fact: User John Doe is going to Green Leaf Cafe
Edge type: RESTAURANT_VISIT
Restaurant name: Green Leaf Cafe
```
```text
Edge fact: User states 'I'm vegetarian' indicating a dietary preference.
Edge type: DIETARY_PREFERENCE
Preference type: vegetarian
Allergy: false
```
### Important Notes/Tips
Some notes regarding custom entity and edge types:
* The `set_ontology` method overwrites any previously defined custom entity and edge types, so the set of custom entity and edge types is always the list of types provided in the last `set_ontology` method call
* The overall set of entity types for a project includes both the custom entity types you set and the default entity types
* There are no default edge types
* You can overwrite the default entity types by providing custom entity types with the same names
* Changing the custom entity or edge types will not update previously created nodes or edges. The classification and attributes of existing nodes and edges will stay the same. The only thing that can change existing classifications or attributes is adding data that provides new information.
* When creating custom entity or edge types, avoid using the following attribute names (including in Go struct tags), as they conflict with default attributes: `uuid`, `name`, `group_id`, `name_embedding`, `summary`, and `created_at`
* **Tip**: Design custom entity types to represent entities/nouns, and design custom edge types to represent relationships/verbs. Otherwise, your type might be represented in the graph as an edge more often than as a node or vice versa.
* **Tip**: If you have overlapping entity or edge types (e.g. 'Hobby' and 'Hiking'), you can prioritize one type over another by mentioning which to prioritize in the entity or edge type descriptions
# Adding Data to the Graph
## Overview
Requests to add data to the same graph are completed sequentially to ensure the graph is built correctly. A large number of calls to add data to the same graph may result in lengthy processing times.
In addition to incorporating memory through chat history, Zep offers the capability to add data directly to the graph.
Zep supports three distinct data types: message, text, and JSON.
The message type is ideal for adding data in the form of chat messages that are not directly associated with a Zep [Session's](/sessions) chat history. This encompasses any communication with a designated speaker, such as emails or previous chat logs.
The text type is designed for raw text data without a specific speaker attribution. This category includes content from internal documents, wiki articles, or company handbooks. It's important to note that Zep does not process text directly from links or files.
The JSON type may be used to add any JSON document to Zep. This may include REST API responses or JSON-formatted business data.
The `graph.add` endpoint has a data size limit of 10,000 characters.
You can add data to either a user graph by providing a `user_id`, or to a [group graph](/groups) by specifying a `group_id`.
## Adding Message Data
Here's an example demonstrating how to add message data to the graph:
```python
from zep_cloud.client import Zep
client = Zep(
api_key=API_KEY,
)
message = "Paul (user): I went to Eric Clapton concert last night"
new_episode = client.graph.add(
user_id="user123", # Optional user ID
type="message", # Specify type as "message"
data=message
)
```
```typescript
import { ZepClient } from "@getzep/zep-cloud";
const client = new ZepClient({
apiKey: API_KEY,
});
const message = "User: I really enjoy working with TypeScript and React";
const newEpisode = await client.graph.add({
userId: "user123",
type: "message",
data: message
});
```
## Adding Text Data
Here's an example demonstrating how to add text data to the graph:
```python
from zep_cloud.client import Zep
client = Zep(
api_key=API_KEY,
)
new_episode = client.graph.add(
user_id="user123", # Optional user ID
type="text", # Specify type as "text"
data="The user is an avid fan of Eric Clapton"
)
```
```typescript
import { ZepClient } from "@getzep/zep-cloud";
const client = new ZepClient({
apiKey: API_KEY,
});
const newEpisode = await client.graph.add({
userId: "user123", // Required: either userId or groupId
type: "text",
data: "The user is interested in machine learning and artificial intelligence"
});
```
## Adding JSON Data
Here's an example demonstrating how to add JSON data to the graph:
```python
from zep_cloud.client import Zep
import json
client = Zep(
api_key=API_KEY,
)
json_data = {"name": "Eric Clapton", "age": 78, "genre": "Rock"}
json_string = json.dumps(json_data)
new_episode = client.graph.add(
user_id=user_id,
type="json",
data=json_string,
)
```
```typescript
import { ZepClient } from "@getzep/zep-cloud";
const client = new ZepClient({
apiKey: API_KEY,
});
const jsonString = '{"name": "Eric Clapton", "age": 78, "genre": "Rock"}';
const newEpisode = await client.graph.add({
userId: userId,
type: "json",
data: jsonString,
});
```
## Adding Custom Fact/Node Triplets
You can also add manually specified fact/node triplets to the graph. You need only specify the fact, the target node name, and the source node name. Zep will then create a new corresponding edge and nodes, or use an existing edge/nodes if they exist and seem to represent the same nodes or edge you send as input. And if this new fact invalidates an existing fact, it will mark the existing fact as invalid and add the new fact triplet.
```python
from zep_cloud.client import Zep
client = Zep(
api_key=API_KEY,
)
client.graph.add_fact_triple(
user_id=user_id,
fact="Paul met Eric",
fact_name="MET",
target_node_name="Eric Clapton",
source_node_name="Paul",
)
```
```typescript
import { ZepClient } from "@getzep/zep-cloud";
const client = new ZepClient({
apiKey: API_KEY,
});
await client.graph.addFactTriple({
userId: userId,
fact: "Paul met Eric",
factName: "MET",
targetNodeName: "Eric Clapton",
sourceNodeName: "Paul",
});
```
You can also specify the node summaries, edge temporal data, and UUIDs. See the [associated SDK reference](/sdk-reference/graph/add-fact-triple).
## Add Batch Data
The batch add method is designed for efficiently adding a large amount of data to a user or group graph concurrently. This method is suitable when the data does not have a significant temporal dimension, such as static documents or bulk imports.
Normally, data added to the graph is processed sequentially. This allows the knowledge graph to capture temporal relationships and understand when one event occurs after another. When using the batch add method, each episode is processed concurrently. As a result, temporal relationships between episodes are not captured.
The batch add method is best used for static data where the order of events is not important. It is not recommended for evolving chat histories or scenarios where temporal relationships are meaningful.
You can only batch up to 20 episodes at a time. You can group episodes of different types (text, json, message) in the same batch.
See the [SDK reference](/sdk-reference/graph/add-batch) for details.
```python Python
episodes = [
EpisodeData(
data="This is an example text episode.",
type="text"
),
EpisodeData(
data=json.dumps({"name": "Eric Clapton", "age": 78, "genre": "Rock"}),
type="json"
)
]
client.graph.add_batch(episodes=episodes, group_id=group_id)
```
```typescript TypeScript
const episodes: EpisodeData[] = [
{
data: "This is an example text episode.",
type: "text"
},
{
data: JSON.stringify({ foo: "bar", count: 42 }),
type: "json"
}
];
await client.graph.addBatch({ groupId, episodes });
```
```go Go
jsonData, _ := json.Marshal(map[string]interface{}{
"foo": "bar",
"baz": 42,
})
batchReq := &v2.AddDataBatchRequest{
Episodes: []*v2.EpisodeData{
{
Data: "This is a text episode.",
Type: v2.GraphDataTypeText,
},
{
Data: string(jsonData),
Type: v2.GraphDataTypeJSON,
},
},
GroupID: &groupID,
}
resp, err := client.Graph.AddBatch(context.TODO(), batchReq)
if err != nil {
log.Fatalf("Failed to add batch episodes: %v", err)
}
```
## Managing Your Data on the Graph
The `graph.add` method returns the [episode](/graphiti/graphiti/adding-episodes) that was created in the graph from adding that data. You can use this to maintain a mapping between your data and its corresponding episode in the graph and to delete specific data from the graph using the [delete episode](/deleting-data-from-the-graph#delete-an-episode) method.
# Reading Data from the Graph
Zep provides APIs to read Edges, Nodes, and Episodes from the graph. These elements can be retrieved individually using their `UUID`, or as lists associated with a specific `user_id` or `group_id`. The latter method returns all objects within the user's or group's graph.
Examples of each retrieval method are provided below.
## Reading Edges
```python
from zep_cloud.client import Zep
client = Zep(
api_key=API_KEY,
)
edge = client.graph.edge.get(edge_uuid)
```
```typescript
import { ZepClient } from "@getzep/zep-cloud";
const client = new ZepClient({
apiKey: API_KEY,
});
const edge = client.graph.edge.get(edge_uuid);
```
## Reading Nodes
```python
from zep_cloud.client import Zep
client = Zep(
api_key=API_KEY,
)
node = client.graph.node.get_by_user(user_uuid)
```
```typescript
import { ZepClient } from "@getzep/zep-cloud";
const client = new ZepClient({
apiKey: API_KEY,
});
const node = client.graph.node.get_by_user(user_uuid);
```
## Reading Episodes
```python
from zep_cloud.client import Zep
client = Zep(
api_key=API_KEY,
)
episode = client.graph.episode.get_by_group(group_uuid)
```
```typescript
import { ZepClient } from "@getzep/zep-cloud";
const client = new ZepClient({
apiKey: API_KEY,
});
const episode = client.graph.episode.get_by_group(group_uuid);
```
# Searching the Graph
Zep employs hybrid search, combining semantic similarity with BM25 full-text. Results are merged and [ranked](#reranking-search-results). Additional details can be found in the [SDK Reference](https://help.getzep.com/sdk-reference/graph/search).
The example below demonstrates a simple search.
```python
from zep_cloud.client import Zep
client = Zep(
api_key=API_KEY,
)
search_results = client.graph.search(
user_id=user_id,
query=query,
)
```
```typescript
import { ZepClient } from "@getzep/zep-cloud";
const client = new ZepClient({
apiKey: API_KEY,
});
const searchResults = await client.graph.search({
userId: userId,
query: query,
});
```
> Read more about [chat message history search](/concepts/#using-memorysearch_sessions).
Keep queries short: they are truncated at 8,192 tokens. Long queries may increase latency without improving search quality.
Break down complex searches into smaller, targeted queries. Use precise, contextual queries rather than generic ones
## Configurable Search Parameters
Zep allows several parameters to fine-tune search behavior:
| Parameter | Description | Default |
| ----------------------- | -------------------------------------------------------------------------------------------------------------------------------------- | --------- |
| `user_id` or `group_id` | **Required.** Specifies whether to search user-specific or group graphs | - |
| `scope` | Controls search [scope](#search-scopes) - either `"edges"` or `"nodes"` | `"edges"` |
| `reranker` | Method to [rerank](#reranking-search-results) results: `"rrf"`, `"mmr"`, `"node_distance"`, `"episode_mentions"`, or `"cross_encoder"` | `"rrf"` |
| `limit` | Maximum number of results to return | `10` |
## Search Scopes
Nodes are connection points in the graph that represent either:
* Chat history entities
* Business data added through the [Graph API](/adding-data-to-the-graph)
Each node maintains a summary of facts from its connections (edges), giving you a quick overview of things related to that node.
Edges represent individual connections between nodes, containing specific interactions or pieces of information. Edge search (the default) is best for finding specific details or conversations, while node search helps you understand the broader context around entities in your graph.
The example below demonstrates a node search.
```python
from zep_cloud.client import Zep
client = Zep(
api_key=API_KEY,
)
search_results = client.graph.search(
group_id=group_id,
query=query,
scope="nodes",
)
```
```typescript
import { ZepClient } from "@getzep/zep-cloud";
const client = new ZepClient({
apiKey: API_KEY,
});
const searchResults = await client.graph.search({
groupId: groupId,
query: query,
scope: "nodes",
});
```
## Reranking Search Results
Besides the default Reciprocal Rank Fusion (`rrf`) which combines results from semantic and BM25, Zep supports several reranking methods to improve search results:
* [Maximal Marginal Relevance ](#maximal-marginal-re-ranking)
* [Node Distance ](#node-distance)
* [Episode Mention ](#episode-mentions)
* [Cross Encoder ](#cross-encoder)
### Maximal Marginal Relevance Re-Ranking
Standard similarity searches often return highly similar top results, potentially limiting the information added to a prompt. `mmr` addresses this by re-ranking results to promote diversity, downranking similar results in favor of relevant but distinct alternatives.
> Required: `mmr_lambda` - tunes the balance between relevance and diversity
Example of MMR search:
```python
from zep_cloud.client import Zep
client = Zep(
api_key=API_KEY,
)
search_results = client.graph.search(
user_id=user_id,
query=query,
reranker="mmr",
mmr_lambda=0.5, # tune diversity vs relevance
)
```
```typescript
import { ZepClient } from "@getzep/zep-cloud";
const client = new ZepClient({
apiKey: API_KEY,
});
const searchResults = await client.graph.search({
userId: userId,
query: query,
reranker: "mmr",
mmrLambda: 0.5, // tune diversity vs relevance
});
```
### Node Distance
`node_distance` re-ranks search results based on the number of hops between the search result and a center node. This can be useful for finding facts related to a specific node, such as a user or a topic.
> Required: `center_node_uuid` - UUID of the node to use as the center of the search
Example of Node Distance search:
```python
from zep_cloud.client import Zep
client = Zep(
api_key=API_KEY,
)
search_results = client.graph.search(
user_id=user_id,
query=query,
reranker="node_distance",
center_node_uuid=center_node_uuid,
)
```
```typescript
import { ZepClient } from "@getzep/zep-cloud";
const client = new ZepClient({
apiKey: API_KEY,
});
const searchResults = await client.graph.search({
userId: userId,
query: query,
reranker: "node_distance",
centerNodeUuid: centerNodeUuid,
});
```
### Episode Mentions
`episode_mentions` re-ranks search results based on the number of times the node or edge has been mentioned in the chat history.
Example of Episode Mentions search:
```python
from zep_cloud.client import Zep
client = Zep(
api_key=API_KEY,
)
search_results = client.graph.search(
user_id=user_id,
query=query,
reranker="episode_mentions",
)
```
```typescript
import { ZepClient } from "@getzep/zep-cloud";
const client = new ZepClient({
apiKey: API_KEY,
});
const searchResults = await client.graph.search({
userId: userId,
query: query,
reranker: "episode_mentions",
});
```
### Cross Encoder
`cross_encoder` re-ranks search results by using a specialized model that jointly analyzes the query and each search result together, providing more accurate relevance scoring than traditional methods that analyze them separately.
Example of Cross Encoder search:
```python
from zep_cloud.client import Zep
client = Zep(
api_key=API_KEY,
)
search_results = client.graph.search(
user_id=user_id,
query=query,
reranker="cross_encoder",
)
```
```typescript
import { ZepClient } from "@getzep/zep-cloud";
const client = new ZepClient({
apiKey: API_KEY,
});
const searchResults = await client.graph.search({
userId: userId,
query: query,
reranker: "cross_encoder",
});
```
# Deleting Data from the Graph
## Delete an Edge
Here's how to delete an edge from a graph:
```python
from zep_cloud.client import Zep
client = Zep(
api_key=API_KEY,
)
client.graph.edge.delete(uuid_="your_edge_uuid")
```
```typescript
import { ZepClient } from "@getzep/zep-cloud";
const client = new ZepClient({
apiKey: API_KEY,
});
await client.graph.edge.delete("your_edge_uuid");
```
Note that when you delete an edge, it never deletes the associated nodes, even if it means there will be a node with no edges. And currently, nodes with no edges will not appear in the graph explorer, but they will still exist in the graph and be retrievable in memory.
## Delete an Episode
Deleting an episode does not regenerate the names or summaries of nodes shared with other episodes. This episode information may still exist within these nodes. If an episode invalidates a fact, and the episode is deleted, the fact will remain marked as invalidated.
When you delete an [episode](/graphiti/graphiti/adding-episodes), it will delete all the edges associated with it, and it will delete any nodes that are only attached to that episode. Nodes that are also attached to another episode will not be deleted.
Here's how to delete an episode from a graph:
```python
from zep_cloud.client import Zep
client = Zep(
api_key=API_KEY,
)
client.graph.episode.delete(uuid_="episode_uuid")
```
```typescript
import { ZepClient } from "@getzep/zep-cloud";
const client = new ZepClient({
apiKey: API_KEY,
});
await client.graph.episode.delete("episode_uuid");
```
## Delete a Node
This feature is coming soon.
# Check Data Ingestion Status
Data added to Zep is processed asynchronously and can take a few seconds to a few minutes to finish processing. In this recipe, we show how to check whether a given data upload request (also known as an [Episode](/graphiti/graphiti/adding-episodes)) is finished processing by polling Zep with the `graph.episode.get` method.
First, let's create a user:
```python
import os
import uuid
import time
from dotenv import find_dotenv, load_dotenv
from zep_cloud.client import Zep
load_dotenv(dotenv_path=find_dotenv())
client = Zep(api_key=os.environ.get("ZEP_API_KEY"))
uuid_value = uuid.uuid4().hex[:4]
user_id = "-" + uuid_value
client.user.add(
user_id=user_id,
first_name = "John",
last_name = "Doe",
email="[email protected]"
)
```
```typescript
import { ZepClient } from "@getzep/zep-cloud";
import * as dotenv from "dotenv";
import { v4 as uuidv4 } from 'uuid';
// Load environment variables
dotenv.config();
const client = new ZepClient({ apiKey: process.env.ZEP_API_KEY || "" });
const uuidValue = uuidv4().substring(0, 4);
const userId = "-" + uuidValue;
async function main() {
// Add user
await client.user.add({
userId: userId,
firstName: "John",
lastName: "Doe",
email: "[email protected]"
});
```
```go
package main
import (
"context"
"fmt"
"os"
"strings"
"time"
"github.com/getzep/zep-go/v2"
zepclient "github.com/getzep/zep-go/v2/client"
"github.com/getzep/zep-go/v2/option"
"github.com/google/uuid"
"github.com/joho/godotenv"
)
func main() {
// Load .env file
err := godotenv.Load()
if err != nil {
fmt.Println("Warning: Error loading .env file:", err)
// Continue execution as environment variables might be set in the system
}
// Get API key from environment variable
apiKey := os.Getenv("ZEP_API_KEY")
if apiKey == "" {
fmt.Println("ZEP_API_KEY environment variable is not set")
return
}
// Initialize Zep client
client := zepclient.NewClient(
option.WithAPIKey(apiKey),
)
// Create a UUID
uuidValue := strings.ToLower(uuid.New().String()[:4])
// Create user ID
userID := "-" + uuidValue
// Create context
ctx := context.Background()
// Add a user
userRequest := &zep.CreateUserRequest{
UserID: zep.String(userID),
FirstName: zep.String("John"),
LastName: zep.String("Doe"),
Email: zep.String("[email protected]"),
}
_, err = client.User.Add(ctx, userRequest)
if err != nil {
fmt.Printf("Error creating user: %v\n", err)
return
}
```
Now, let's add some data and immediately try to search for that data; because data added to Zep is processed asynchronously and can take a few seconds to a few minutes to finish processing, our search results do not have the data we just added:
```python
episode = client.graph.add(
user_id=user_id,
type="text",
data="The user is an avid fan of Eric Clapton"
)
search_results = client.graph.search(
user_id=user_id,
query="Eric Clapton",
scope="nodes",
limit=1,
reranker="cross_encoder",
)
print(search_results.nodes)
```
```typescript
// Add episode to graph
const episode = await client.graph.add({
userId: userId,
type: "text",
data: "The user is an avid fan of Eric Clapton"
});
// Search for nodes related to Eric Clapton
const searchResults = await client.graph.search({
userId: userId,
query: "Eric Clapton",
scope: "nodes",
limit: 1,
reranker: "cross_encoder"
});
console.log(searchResults.nodes);
```
```go
// Add a new episode to the graph
episode, err := client.Graph.Add(ctx, &zep.AddDataRequest{
GroupID: zep.String(userID),
Type: zep.GraphDataTypeText.Ptr(),
Data: zep.String("The user is an avid fan of Eric Clapton"),
})
if err != nil {
fmt.Printf("Error adding episode to graph: %v\n", err)
return
}
// Search for the data
searchResults, err := client.Graph.Search(ctx, &zep.GraphSearchQuery{
UserID: zep.String(userID),
Query: "Eric Clapton",
Scope: zep.GraphSearchScopeNodes.Ptr(),
Limit: zep.Int(1),
Reranker: zep.RerankerCrossEncoder.Ptr(),
})
if err != nil {
fmt.Printf("Error searching graph: %v\n", err)
return
}
fmt.Println(searchResults.Nodes)
```
```text
None
```
We can check the status of the episode to see when it has finished processing, using the episode returned from the `graph.add` method and the `graph.episode.get` method:
```python
while True:
episode = client.graph.episode.get(
uuid_=episode.uuid_,
)
if episode.processed:
print("Episode processed successfully")
break
print("Waiting for episode to process...")
time.sleep(1)
```
```typescript
// Check if episode is processed
const sleep = (ms: number) => new Promise(resolve => setTimeout(resolve, ms));
let processedEpisode = await client.graph.episode.get(episode.uuid);
while (!processedEpisode.processed) {
console.log("Waiting for episode to process...");
await sleep(1000); // Sleep for 1 second
processedEpisode = await client.graph.episode.get(episode.uuid);
}
console.log("Episode processed successfully");
```
```go
// Wait for the episode to be processed
for {
episodeStatus, err := client.Graph.Episode.Get(
ctx,
episode.UUID,
)
if err != nil {
fmt.Printf("Error getting episode: %v\n", err)
return
}
if episodeStatus.Processed != nil && *episodeStatus.Processed {
fmt.Println("Episode processed successfully")
break
}
fmt.Println("Waiting for episode to process...")
time.Sleep(1 * time.Second)
}
```
```text
Waiting for episode to process...
Waiting for episode to process...
Waiting for episode to process...
Waiting for episode to process...
Waiting for episode to process...
Episode processed successfully
```
Now that the episode has finished processing, we can search for the data we just added, and this time we get a result:
```python
search_results = client.graph.search(
user_id=user_id,
query="Eric Clapton",
scope="nodes",
limit=1,
reranker="cross_encoder",
)
print(search_results.nodes)
```
```typescript
// Search again after processing
const finalSearchResults = await client.graph.search({
userId: userId,
query: "Eric Clapton",
scope: "nodes",
limit: 1,
reranker: "cross_encoder"
});
console.log(finalSearchResults.nodes);
}
// Execute the main function
main().catch(error => console.error("Error:", error));
```
```go
// Search again after processing
searchResults, err = client.Graph.Search(ctx, &zep.GraphSearchQuery{
UserID: zep.String(userID),
Query: "Eric Clapton",
Scope: zep.GraphSearchScopeNodes.Ptr(),
Limit: zep.Int(1),
Reranker: zep.RerankerCrossEncoder.Ptr(),
})
if err != nil {
fmt.Printf("Error searching graph: %v\n", err)
return
}
fmt.Println(searchResults.Nodes)
}
```
```text
[EntityNode(attributes={'category': 'Music', 'labels': ['Entity', 'Preference']}, created_at='2025-04-05T00:17:59.66565Z', labels=['Entity', 'Preference'], name='Eric Clapton', summary='The user is an avid fan of Eric Clapton.', uuid_='98808054-38ad-4cba-ba07-acd5f7a12bc0', graph_id='6961b53f-df05-48bb-9b8d-b2702dd72045')]
```
# Customize Your Memory Context String
In this recipe, we will demonstrate how to build a custom memory context string using the [graph search API](/searching-the-graph). This is necessary when using group graphs, or if you want to further customize the context string. We will create and add data to a group graph, and then search the edges and nodes to create a custom context string.
First, we create a group and add some example data:
```python
import os
import uuid
import time
from dotenv import find_dotenv, load_dotenv
from zep_cloud.client import Zep
import json
load_dotenv(dotenv_path=find_dotenv())
API_KEY = os.environ.get("ZEP_API_KEY") or "YOUR_API_KEY"
client = Zep(api_key=API_KEY)
uuid_value = uuid.uuid4().hex
group_id = "MyGroup" + uuid_value
group = client.group.add(group_id=group_id)
car_inventory_description = {
"entity": "Car inventory",
"description": "This is a list of cars in the inventory. Each car has a maker, model, and gas mileage."
}
car_inventory_list = [
{
"maker": "Toyota",
"model": "Sedan-01",
"gas_mileage": "25 mpg",
},
{
"maker": "Ford",
"model": "SUV-01",
"gas_mileage": "20 mpg",
},
{
"maker": "Ford",
"model": "SUV-02",
"gas_mileage": "22 mpg",
},
{
"maker": "Chevrolet",
"model": "Truck-01",
"gas_mileage": "25 mpg",
},
]
json_string = json.dumps(car_inventory_description)
client.graph.add(
group_id=group_id,
type="json",
data=json_string,
)
for item in car_inventory_list:
# This helps contextualize the car items in the graph
item["description"] = "This is one of the cars in the car inventory"
json_string = json.dumps(item)
client.graph.add(
group_id=group_id,
type="json",
data=json_string,
)
# Wait a minute or two
time.sleep(120)
```
```typescript
import { ZepClient } from "@getzep/zep-cloud";
import * as dotenv from "dotenv";
import { v4 as uuidv4 } from 'uuid';
// Define the main function
async function main() {
dotenv.config();
const API_KEY = process.env.ZEP_API_KEY || "YOUR_API_KEY";
const client = new ZepClient({ apiKey: API_KEY });
const uuidValue = uuidv4();
const groupId = `MyGroup${uuidValue}`;
const group = await client.group.add({
groupId: groupId,
});
const carInventoryDescription = {
entity: "Car inventory",
description: "This is a list of cars in the inventory. Each car has a maker, model, and gas mileage."
};
const productJsonData: CarItem[] = [
{
maker: "Toyota",
model: "Sedan-01",
gas_mileage: "25 mpg",
},
{
maker: "Ford",
model: "SUV-01",
gas_mileage: "20 mpg",
},
{
maker: "Ford",
model: "SUV-02",
gas_mileage: "22 mpg",
},
{
maker: "Chevrolet",
model: "Truck-01",
gas_mileage: "25 mpg",
},
];
await client.graph.add({
groupId: groupId,
type: "json",
data: JSON.stringify(carInventoryDescription),
});
for (const jsonItem of productJsonData) {
// This helps contextualize the car items in the graph
jsonItem.description = "This is one of the cars in the car inventory";
const jsonString = JSON.stringify(jsonItem);
await client.graph.add({
groupId: groupId,
type: "json",
data: jsonString,
});
}
// Wait for 2 minutes (120 seconds)
const sleep = (ms: number) => new Promise(resolve => setTimeout(resolve, ms));
await sleep(120000);
```
Next, we search the graph for edges and nodes relevant to our custom query. Note that the default [memory context string](/concepts#memory-context) returned by `memory.get` uses the past few messages as the query instead.
```python
query = "What Ford cars do we have in stock and what are there gas mileages?"
node_search_results = client.graph.search(
group_id=group_id,
query=query,
scope="nodes",
limit=3,
reranker="cross_encoder",
)
edge_search_results = client.graph.search(
group_id=group_id,
query=query,
scope="edges",
limit=3,
reranker="cross_encoder",
)
```
```typescript
const query = "What Ford cars do we have in stock and what are there gas mileages?";
const nodeSearchResults = await client.graph.search({
groupId: groupId,
query: query,
scope: "nodes",
limit: 3,
reranker: "cross_encoder",
});
const edgeSearchResults = await client.graph.search({
groupId: groupId,
query: query,
scope: "edges",
limit: 3,
reranker: "cross_encoder",
});
```
Lastly, we use the search results to build a custom context string:
```python
custom_context_string = "Below are facts and entities related to what Ford cars we have in stock:\n"
custom_context_string += "\n"
for edge in edge_search_results.edges:
custom_context_string += f"- {edge.fact}\n"
custom_context_string += "\n"
custom_context_string += "\n"
for node in node_search_results.nodes:
custom_context_string += f"- {node.name}: {node.summary}\n"
custom_context_string += "\n"
print(custom_context_string)
```
```typescript
let customContextString = "Below are facts and entities related to what Ford cars we have in stock:\n";
customContextString += "\n";
for (const edge of edgeSearchResults.edges || []) {
customContextString += `- ${edge.fact}\n`;
}
customContextString += "\n";
customContextString += "\n";
for (const node of nodeSearchResults.nodes || []) {
customContextString += `- ${node.name}: ${node.summary}\n`;
}
customContextString += "\n";
console.log(customContextString);
}
// Execute the main function
main().catch(error => console.error("Error:", error));
```
This recipe demonstrated how to build a custom memory context string using the [graph search API](/searching-the-graph). We created a group and added some example data, and then searched the edges and nodes to create a custom context string.
# Add User Specific Business Data to User Graphs
This guide demonstrates how to add user-specific business data to a user's knowledge graph. We'll create a user, fetch their business data, and add it to their graph.
First, we will initialize our client and create a new user:
```python
# Initialize the Zep client
zep_client = AsyncZep(api_key=API_KEY)
# Add one example user
user_id_zep = uuid.uuid4().hex
await zep_client.user.add(
user_id=user_id_zep,
email="[email protected]"
)
```
Then, we will fetch and format the user's business data. Note that the functionality to fetch a users business data will depend on your codebase.
Also note that you could make your Zep user IDs equal to whatever internal user IDs you use to make things easier to manage. Generally, Zep user IDs, session IDs, Group IDs, etc. can be arbitrary strings, and can map to your app's data schema.
```python
# Define the function to fetch user business data
async def get_user_business_data(user_id_business):
# This function returns JSON data for the given user
# This would vary based on your codebase
return {}
# Placeholder for business user id
user_id_business = "placeholder_user_id" # This would vary based on your codebase
# Retrieve the user-specific business data
user_data_json = await get_user_business_data(user_id_business)
# Convert the business data to a string
json_string = json.dumps(user_data_json)
```
Lastly, we will add the formatted data to the user's graph using the [graph API](/adding-data-to-the-graph):
```python
# Add the JSON data to the user's graph
await zep_client.graph.add(
user_id=user_id_zep,
type="json",
data=json_string,
)
```
Here, we use `type="json"`, but the graph API also supports `type="text"` and `type="message"`. The `type="text"` option is useful for adding background information that is in unstructured text such as internal documents or web copy. The `type="message"` option is useful for adding data that is in a message format but is not your user's chat history, such as emails. [Read more about this here](/adding-data-to-the-graph).
Also, note that when adding data to the graph, you should consider the size of the data you are adding and our payload limits. [Read more about this here](/docs/performance/performance-best-practices#optimizing-memory-operations).
You have now successfully added user-specific business data to a user's knowledge graph, which can be used alongside chat history to create comprehensive user memory.
# Share Memory Across Users Using Group Graphs
In this recipe, we will demonstrate how to share memory across different users by utilizing group graphs. We will set up a user session, add group-specific data, and integrate the OpenAI client to show how to use both user and group memory to enhance the context of a chatbot.
First, we initialize the Zep client, create a user, and create a session:
```python
# Initialize the Zep client
zep_client = AsyncZep(api_key="YOUR_API_KEY") # Ensure your API key is set appropriately
# Add one example user
user_id = uuid.uuid4().hex
await zep_client.user.add(
user_id=user_id,
email="[email protected]"
)
# Create a new session for the user
session_id = uuid.uuid4().hex
await zep_client.memory.add_session(
session_id=session_id,
user_id=user_id,
)
```
Next, we create a new group and add structured business data to the graph, in the form of a JSON string. This step uses the [groups API](/groups) and the [graph API](/adding-data-to-the-graph):
```python
group_id = uuid.uuid4().hex
await zep_client.group.add(group_id=group_id)
product_json_data = [
{
"type": "Sedan",
"gas_mileage": "25 mpg",
"maker": "Toyota"
},
# ... more cars
]
json_string = json.dumps(product_json_data)
await zep_client.graph.add(
group_id=group_id,
type="json",
data=json_string,
)
```
Finally, we initialize the OpenAI client and define a `chatbot_response` function that retrieves user and group memory, constructs a system/developer message, and generates a contextual response. This leverages the [memory API](/concepts#using-memoryget), [graph API](/searching-the-graph), and the OpenAI chat completions endpoint.
```python
# Initialize the OpenAI client
oai_client = OpenAI()
async def chatbot_response(user_message, session_id):
# Retrieve user memory
user_memory = await zep_client.memory.get(session_id)
# Search the group graph using the user message as the query
results = await zep_client.graph.search(group_id=group_id, query=user_message, scope="edges")
relevant_group_edges = results.edges
product_context_string = "Below are some facts related to our car inventory that may help you respond to the user: \n"
for edge in relevant_group_edges:
product_context_string += f"{edge.fact}\n"
# Combine context strings for the developer message
developer_message = f"You are a helpful chat bot assistant for a car sales company. Answer the user's message while taking into account the following background information:\n{user_memory.context}\n{product_context_string}"
# Generate a response using the OpenAI API
completion = oai_client.chat.completions.create(
model="gpt-4o-mini",
messages=[
{"role": "developer", "content": developer_message},
{"role": "user", "content": user_message}
]
)
response = completion.choices[0].message
# Add the conversation to memory
messages = [
Message(role="user", role_type="user", content=user_message),
Message(role="assistant", role_type="assistant", content=response)
]
await zep_client.memory.add(session_id, messages=messages)
return response
```
This recipe demonstrated how to share memory across users by utilizing group graphs with Zep. We set up user sessions, added structured group data, and integrated the OpenAI client to generate contextual responses, providing a robust approach to memory sharing across different users.
# Get Most Relevant Facts for an Arbitrary Query
In this recipe, we demonstrate how to retrieve the most relevant facts from the knowledge graph using an arbitrary search query.
First, we perform a [search](/searching-the-graph) on the knowledge graph using a sample query:
```python
zep_client = AsyncZep(api_key=API_KEY)
results = await client.graph.search(user_id="some user_id", query="Some search query", scope="edges")
```
Then, we get the edges from the search results and construct our fact list. We also include the temporal validity data to each fact string:
```python
# Build list of formatted facts
relevant_edges = results.edges
formatted_facts = []
for edge in relevant_edges:
valid_at = edge.valid_at if edge.valid_at is not None else "date unknown"
invalid_at = edge.invalid_at if edge.invalid_at is not None else "present"
formatted_fact = f"{edge.fact} (Date range: {valid_at} - {invalid_at})"
formatted_facts.append(formatted_fact)
# Print the results
print("\nFound facts:")
for fact in formatted_facts:
print(f"- {fact}")
```
We demonstrated how to retrieve the most relevant facts for an arbitrary query using the Zep client. Adjust the query and parameters as needed to tailor the search for your specific use case.
# Find Facts Relevant to a Specific Node
Below, we will go through how to retrieve facts which are related to a specific node in a Zep knowledge graph. First, we will go through some methods for determining the UUID of the node you are interested in. Then, we will go through some methods for retrieving the facts related to that node.
If you are interested in the user's node specifically, we have a convenience method that [returns the user's node](/users#get-the-user-node) which includes the UUID.
An easy way to determine the UUID for other nodes is to use the graph explorer in the [Zep Web app](https://app.getzep.com/).
You can also programmatically retrieve all the nodes for a given user using our [get nodes by user API](/sdk-reference/graph/node/get-by-user-id), and then manually examine the nodes and take note of the UUID of the node of interest:
```python
# Initialize the Zep client
zep_client = AsyncZep(api_key=API_KEY)
nodes = await zep_client.graph.node.get_by_user_id(user_id="some user ID")
print(nodes)
```
```python
center_node_uuid = "your chosen center node UUID"
```
Lastly, if your user has a lot of nodes to look through, you can narrow down the search by only looking at the nodes relevant to a specific query, using our [graph search API](/searching-the-graph):
```python
results = await zep_client.graph.search(
user_id="some user ID",
query="shoe", # To help narrow down the nodes you have to manually search
scope="nodes"
)
relevant_nodes = results.nodes
print(relevant_nodes)
```
```python
center_node_uuid = "your chosen center node UUID"
```
The most straightforward way to get facts related to your node is to retrieve all facts that are connected to your chosen node using the [get edges by user API](/sdk-reference/graph/edge/get-by-user-id):
```python
edges = await zep_client.graph.edge.get_by_user_id(user_id="some user ID")
connected_edges = [edge for edge in edges if edge.source_node_uuid == center_node_uuid or edge.target_node_uuid == center_node_uuid]
relevant_facts = [edge.fact for edge in connected_edges]
```
You can also retrieve facts relevant to your node by using the [graph search API](/searching-the-graph) with the node distance re-ranker:
```python
results = await zep_client.graph.search(
user_id="some user ID",
query="some query",
reranker="node_distance",
center_node_uuid=center_node_uuid,
)
relevant_edges = results.edges
relevant_facts = [edge.fact for edge in relevant_edges]
```
In this recipe, we went through how to retrieve facts which are related to a specific node in a Zep knowledge graph. We first went through some methods for determining the UUID of the node you are interested in. Then, we went through some methods for retrieving the facts related to that node.
# Performance Optimization Guide
> Best practices for optimizing Zep performance in production
This guide covers best practices for optimizing Zep's performance in production environments.
## Reuse the Zep SDK Client
The Zep SDK client maintains an HTTP connection pool that enables connection reuse, significantly reducing latency by avoiding the overhead of establishing new connections. To optimize performance:
* Create a single client instance and reuse it across your application
* Avoid creating new client instances for each request or function
* Consider implementing a client singleton pattern in your application
* For serverless environments, initialize the client outside the handler function
## Optimizing Memory Operations
The `memory.add` and `memory.get` methods are optimized for conversational messages and low-latency retrieval. For optimal performance:
* Keep individual messages under 10K characters
* Use `graph.add` for larger documents, tool outputs, or business data
* Consider chunking large documents before adding them to the graph (the `graph.add` endpoint has a 10,000 character limit)
* Remove unnecessary metadata or content before persistence
* For bulk document ingestion, process documents in parallel while respecting rate limits
```python
# Recommended for conversations
zep_client.memory.add(
session_id="session_123",
message={
"role": "human",
"content": "What's the weather like today?"
}
)
# Recommended for large documents
await zep_client.graph.add(
data=document_content, # Your chunked document content
user_id=user_id, # Or group_id for group graphs
type="text" # Can be "text", "message", or "json"
)
```
### Get the memory context string sooner
Additionally, you can request the memory context directly in the response to the `memory.add()` call.
This optimization eliminates the need for a separate `memory.get()` if you happen to only need the context.
Read more about [Memory Context](/concepts/#memory-context).
In this scenario you can pass in the `return_context=True` flag to the `memory.add()` method.
Zep will perform a user graph search right after persisting the memory and return the context relevant to the recently added memory.
```python
memory_response = await zep_client.memory.add(
session_id=session_id,
messages=messages,
return_context=True
)
context = memory_response.context
```
```typescript
const memoryResponse = await zepClient.memory.add(sessionId, {
messages: messages,
returnContext: true
});
const context = memoryResponse.context;
```
```golang
memoryResponse, err := zepClient.Memory.Add(
context.TODO(),
sessionID,
&zep.AddMemoryRequest{
Messages: messages,
ReturnContext: zep.Bool(true),
},
)
if err != nil {
// handle error
}
memoryContext := memoryResponse.Context
```
Read more in the
[Memory SDK Reference](/sdk-reference/memory#add)
## Optimizing Search Queries
Zep uses hybrid search combining semantic similarity and BM25 full-text search. For optimal performance:
* Keep your queries concise. Queries are automatically truncated to 8,192 tokens (approximately 32,000 Latin characters)
* Longer queries may not improve search quality and will increase latency
* Consider breaking down complex searches into smaller, focused queries
* Use specific, contextual queries rather than generic ones
Best practices for search:
* Keep search queries concise and specific
* Structure queries to target relevant information
* Use natural language queries for better semantic matching
* Consider the scope of your search (user vs group graphs)
```python
# Recommended - concise query
results = await zep_client.graph.search(
user_id=user_id, # Or group_id for group graphs
query="project requirements discussion"
)
# Not recommended - overly long query
results = await zep_client.graph.search(
user_id=user_id,
query="very long text with multiple paragraphs..." # Will be truncated
)
```
## Summary
* Reuse Zep SDK client instances to optimize connection management
* Use appropriate methods for different types of content (`memory.add` for conversations, `graph.add` for large documents)
* Keep search queries focused and under the token limit for optimal performance
# Adding JSON Best Practices
> Best practices for preparing JSON data for ingestion into Zep
Adding JSON to Zep without adequate preparation can lead to unexpected results. For instance, adding a large JSON without dividing it up can lead to a graph with very few nodes. Below, we go over what type of JSON works best with Zep, and techniques you can use to ensure your JSON fits these criteria.
## Key Criteria
At a high level, ingestion of JSON into Zep works best when these criteria are met:
1. **JSON is not too large**: Large JSON should be divided into pieces, adding each piece separately to Zep.
2. **JSON is not deeply nested**: Deeply nested JSON (more than 3 to 4 levels) should be flattened while preserving information.
3. **JSON is understandable in isolation**: The JSON should include all the information needed to understand the data it represents. This might mean adding descriptions or understandable attribute names where relevant.
4. **JSON represents a unified entity**: The JSON should ideally represent a unified entity, with ID, name, and description fields. Zep treats the JSON as a whole as a "first class entity", creating branching entities off of the main JSON entity from the JSON's attributes.
## JSON that is too large
### JSON with too many attributes
**Recommendation**: Split up the properties among several instances of the object. Each instance should duplicate the `id`, `name`, and `description` fields, or similar fields that tie each chunk to the same object, and then have 3 to 4 additional properties.
### JSON with too many list elements
**Recommendation**: Split up the list into its elements, ensuring you add additional fields to contextualize each element if needed. For instance, if the key of the list is "cars", then you should add a field which indicates that the list item is a car.
### JSON with large strings
**Recommendation**: A very long string might be better added to the graph as unstructured text instead of JSON. You may need to add a sentence or two to contextualize the unstructured text with respect to the rest of the JSON, since they would be added separately. And if it is very long, you would want to employ document chunking methods, such as described by Anthropic [here](https://www.anthropic.com/news/contextual-retrieval).
## JSON that is deeply nested
**Recommendation**: For each deeply nested value In the JSON, create a flattened JSON piece for that value specifically. For instance, if your JSON alternates between dictionaries and lists for 5 to 6 levels with a single value at the bottom, then the flattened version would have an attribute for the value, and an attribute to convey any information from each of the keys from the original JSON.
## JSON that is not understandable in isolation
**Recommendation**: Add descriptions or helpful/interpretable attribute names where relevant.
## JSON that is not a unified entity
**Recommendation**: Add an `id`, `name`, and `description` field to the JSON. Additionally, if the JSON essentially represents two or more objects, split it up.
## Dealing with a combination of the above
**Recommendation**: First, deal with the fact that the JSON is too large and/or too deeply nested by iteratively applying these recommendations (described above) from the top down: splitting up attributes, splitting up lists, flattening deeply nested JSON, splitting out any large text documents. For example, if your JSON has a lot of attributes and one of those attributes is a long list, then you should first split up the JSON by the attributes, and then split up the JSON piece that contains the long list by splitting the list elements.
After applying the iterative transformations, you should have a list of candidate JSON, each of which is not too large or too deeply nested. As the last step, you should ensure that each JSON in the list is understandable in isolation and represents a unified entity by applying the recommendations above.
# Structured Outputs from Messages
> Get Structured Outputs from Chat History stored in Zep, faster and more accurately than your LLM Provider's JSON or Structured Outputs mode.
Structured Data Extraction for Python{" "}
requires `pydantic` version 2 installed and is not compatible
with `pydantic` v1.
Many business and consumer apps need to extract structured data from conversation between an Assistant and human user. Often, the extracted data is the objective of the conversation.
Often, you will want to identify the data values you have collected and which values you still need to collect in order to prompt the LLM to request the latter.
This can be a slow and inaccurate exercise, and frustrating to your users. If you're making multiple calls to an LLM to extract and validate data on every chat turn, you're likely adding seconds to your response time.
Zep's structured data extraction (SDE) is a [low-latency, high-fidelity
tool](#latency-and-accuracy-baselines) for generating structured output from
Chat History stored in Zep. For many multi-field extraction tasks you can
expect latency of under 400ms, with the addition of fields increasing latency
sub-linearly.
## Quick Start
An end-to-end SDE example (in Python) can be found in the [Zep By Example repo](https://github.com/getzep/zep-by-example/blob/main/structured-data-extraction/python/sales_order.ipynb).
The example covers:
* defining a model using many of the field types that SDE supports
* extracting data from a Chat History
* and provides an example of how to merge newly extracted data with an already partially populated model.
## SDE vs JSON or Structured Outputs Mode
Many model providers offer a JSON and/or Structured Outputs inference mode that guarantees the output will be well-formed JSON, or in the case of Structured Output, is valid according to a provided schema.
However:
1. When using JSON Mode, there are no guarantees that the field values themselves will conform to your JSON Schema.
2. When using Structured Outputs Mode, there are no guarantees that the field values themselves will conform to your JSON Schema, beyond primitive data types such as strings, numbers, booleans, etc.
3. There are no guarantees that the field values are correct (vs. being hallucinated).
4. All fields are extracted in a single inference call, with additional fields adding linearly or greater to extraction latency.
#### SDE's Preprocessing, Guided LLM Output, and Validation
Zep uses a combination of dialog preprocessing, guided LLM output, and post-inference validation to ensure that the extracted data is in the format you expect and is valid given the current dialog. When using a structured Field Type (such as `ZepDate`, `ZepEmail`, `ZepRegex`), you will not receive back data in an incorrect format.
While there are limits to the accuracy of extraction when the conversation is very nuanced or ambiguous, with careful crafting of field descriptions, you can achieve high accuracy in most cases.
#### Concurrent Extraction Scales Sub-Linearly
SDE's extraction latency scales sub-linearly with the number of fields in your model. That is, you may add additional fields with low marginal increase in latency. You can expect extraction times of 400ms or lower when extracting fairly complex models for a 500 character dialog (which includes both message content and your Role and RoleType designations).
## Defining Your Model
To extract data with Zep, you will need to define a model of the data you require from a Chat History. Each model is composed of a set of fields, each of which has a type and description. Key to successful extraction of data is careful construction of the field description.
```python maxLines=30
from pydantic import Field
from zep_cloud.extractor import ZepModel, ZepText, ZepEmail, ZepDate
class SalesLead(ZepModel):
company_name: Optional[ZepText] = Field(
description="The company name",
default=None
)
lead_name: Optional[ZepText] = Field(
description="The lead's name",
default=None
)
lead_email: Optional[ZepEmail] = Field(
description="The lead's email",
default=None
)
lead_phone: Optional[ZepPhoneNumber] = Field(
description="The lead's phone number",
default=None
)
budget: Optional[ZepFloat] = Field(
description="The lead's budget for the product",
default=None
)
product_name: Optional[ZepRegex] = Field(
description="The name of the product the lead is interested in",
pattern=r"(TimeMachine|MagicTransporter)",
default=None
)
zip_code: Optional[ZepZipCode] = Field(
description="The company zip code",
default=None
)
```
When using Python, your model will subclass `ZepModel`. Zep builds on `pydantic` and requires correctly typing fields and using the `Field` class from `pydantic` to define the field description, default value, and `pattern` when using a `ZepRegex` field.
```typescript maxLines=30
import { zepFields } from '@getzep/zep-cloud';
import { type ExtractedData } from '@getzep/zep-cloud/extractor';
const leadModelSchema = {
companyName: zepFields.text("The company name"),
leadName: zepFields.text("The lead's name"),
leadEmail: zepFields.email("The lead's email"),
leadPhone: zepFields.phoneNumber("The lead's phone number"),
budget: zepFields.float("The lead's budget for the product"),
productName: zepFields.regex(
"The name of the product the lead is interested in",
/(TimeMachine|MagicTransporter)/
),
zipCode: zepFields.zipCode("The company zip code"),
}
// { companyName?: string, leadName?: string, leadEmail?: string, leadPhone?: string, budget?: number, productName?: string, zipCode?: string }
type LeadModel = ExtractedData;
```
TypeScript models are an object where each field is of a supported `zepFields` type. The object may be typed as `ExtractedData` to access the correctly typed extracted data.
## Executing an Extraction
To execute an extraction, you will need to call the `extract` method on the memory client. This method requires a `session_id` and a model schema that specifies the types and structures of data to be extracted based on field descriptions.
The `lastN` parameter, or Python equivalent `last_n`, specifies the number prior messages in the Session's Chart History to look back at for data extraction.
The `validate` parameter specifies whether to optionally run an additional validation step on the extracted data.
The `currentDateTime` parameter, or Python equivalent `current_date_time`, specifies your user's current date and time. This is used when extracting dates and times from relative phrases like *"yesterday"* or *"last week"* and to correctly set the timezone of the extracted data.
```python
extracted_data: SalesLead = client.memory.extract(
session_id,
SalesLead,
last_n=8,
validate=False,
current_date_time=datetime.now(ZoneInfo('America/New_York'))
)
```
```typescript
import moment from "moment-timezone";
const currentDateTimeNYC = moment.tz("America/New_York").format();
const lead: LeadModel = await client.memory.extract(
sessionId,
leadModelSchema,
{
lastN: 8,
validate: false,
currentDateTime: currentDateTimeNYC,
}
);
```
## Using Progressive Data Extraction To Guide LLMs
Your application may need to collect a number of fields in order to accomplish a task. You can guide the LLM through this process by calling `extract` on every chat turn, identifying which fields are still needed, providing a partially populated model to the LLM, and directing the LLM to collect the remaining data.
```ansi title="Example Prompt"
You have already collected the following data:
- Company name: Acme Inc.
- Lead name: John Doe
- Lead email: [email protected]
You still need to collect the following data:
- Lead phone number
- Lead budget
- Product name
- Zip code
Do not ask for all fields at once. Rather, work the fields
into your conversation with the user and gradually collect the data.
```
As each field is populated, you may copy these values into an immutable data structure. Alternatively, if existing values change as the conversation progresses, you can apply a heuristic informed by your business rules to update the data structure with the new values.
## Supported Field Types
Zep supports a wide variety of field types natively. Where Zep does not support a native field type, you can use a `ZepRegex` field to extract a string that matches a structure you define.
| Type | Description | Python Type | TypeScript Type |
| -------- | ------------------------------------------------------------------------------ | ---------------- | ----------------------- |
| Text | Plain text values without a set format. | `ZepText` | `zepFields.text` |
| Number | Integer values. | `ZepNumber` | `zepFields.number` |
| Float | Floating-point numbers. | `ZepFloat` | `zepFields.float` |
| Regex | Strings matching a regex pattern. | `ZepRegex` | `zepFields.regex` |
| DateTime | Date and time values returned as an ISO 8601 string using your local timezone. | `ZepDateTime` | `zepFields.dateTime` |
| Date | Date values returned as an ISO 8601 string using your local timezone. | `ZepDate` | `zepFields.date` |
| Email | Email addresses. | `ZepEmail` | `zepFields.email` |
| Phone | Phone numbers in North American Numbering Plan format. | `ZepPhoneNumber` | `zepFields.phoneNumber` |
| Zip Code | Postal codes in North American ZIP or ZIP+4 format, if available. | `ZepZipCode` | `zepFields.zipCode` |
## Improving Accuracy
Extraction accuracy may be improved by experimenting with different descriptions and using Zep's built-in field validation.
### Improving Descriptions
When describing fields, ensure that you've been both specific and clear as to what value you'd like to extract. You may also provide few-shot examples in your description.
| Bad ❌ | Good ✅ |
| ------------ | ------------------------------------ |
| name | the name of the customer |
| phone | the customer's phone number |
| address | street address |
| address | postal address |
| product name | product name: "WidgetA" or "WidgetB" |
### Validating Extracted Data
When `validation` is enabled on your `extract` call, Zep will run an additional LLM validation step on the extracted data. This provides improved accuracy and reduces the risk of hallucinated values. The downside to enabling field validation is increased extraction latency and an increased risk of false negatives (empty fields where the data may be present in the dialog).
We recommend running without field validation first to gauge accuracy and latency and only enable field validation if you've determined that it is needed given your use case.
## Working with Dates
Zep understands a wide variety of date and time formats, including relative times such as "yesterday" or "last week". It is also able to parse partial dates and times, such as "at 3pm" or "on the 15th". All dates and times are returned in ISO 8601 format and use the timezone of the `currentDateTime` parameter passed to the `extract` call.
If you are extracting datetime and date fields it is important that you provide a `currentDateTime` value in your `extract` call and ensure that it is in the correct timezone for your user (or the base timezone your application uses internally).
## Extracting from Speech Transcripts
Zep is able to understand and extract data from machine-translated transcripts. Spelled out numbers and dates will be parsed as if written language. Utterances such as "uh" or "um" are ignored.
| Description | From | To |
| ----------------------------- | ------------------------------------------------------------------------------------------- | ------------------- |
| Apartment size in square feet | It is a three bedroom with approximately one thousand two hundred and fifty two square feet | 1252 |
| Meeting date and time | I'm available on the uh fifteenth at uh three pm | 2024-06-15T15:00:00 |
| The user's phone number | It's uh two five five two three four five six seven uh eight | (255) 234-5678 |
We are constantly improving transcript extraction. Let us know if you have a
use case where this does not work well!
## Multilingual Data Support
Zep's Structured Data Extraction supports most major languages.
## Tips, Tricks, and Best Practices
### Limit the number of Messages from which you extract data
If your use case is latency sensitive, limit the number of messages from which you extract data. The higher the last `N` messages, the longer the extraction will take.
### Always make fields optional in Python models
Always make fields optional in your Python model. This will prevent runtime errors when the data is not present in the conversation.
### Using Regex when Zep doesn't support your data type
The `ZepRegex` field type is a swiss army knife for extracting data. It allows you to extract any string that matches a regex pattern defined by you.
```python
class OrderInfo(ZepModel):
order_id: Optional[ZepRegex] = Field(
description="The order ID in format ABC-12345",
pattern=r"[A-Z]{3}-\d{5}"
)
```
```typescript
orderSchema = {
orderId: zepFields.regex({
"The order ID in format ABC-12345",
/[A-Z]{3}-\d{5}/,
}),
}
```
### Implementing Enum Fields
The `ZepRegex` field type can be used to extract data from a list of enums provided in a capture group.
```python
order_currency: Optional[ZepRegex] = Field(
description="The order currency: USD, GBP, or UNKNOWN",
default=None,
pattern=r"(UNKNOWN|USD|GBP)"
)
```
Results in:
```text
"USD"
```
### Comma Separated Lists
You can extract comma separated lists using the `ZepRegex` field type:
```python
brand_preferences: Optional[ZepRegex] = Field(
description="The customer's preferred brands as a comma-separated list",
default=None,
pattern=r"\w+(, \w+)+"
)
```
Results in:
```text
"Nike, Adidas, Puma"
```
### Unsupported Regex Patterns
The following Regex tokens and features are unsupported when using the Regex field type:
* Start of and end of string anchors (`^` and `$`) and absolute positioning (`\A` and `\Z`).
* Named groups (`(?P...)`).
* Backreferences (`\g`).
* Lookaheads and lookbehinds (`(?=...)`, `(?!...)`, `(?<=...)`, `(?
Zep enables you to classify Sessions into various categories and save these classifications in the Session's metadata.
This feature is handy for directing Sessions to appropriate agents or for monitoring the kinds of interactions users have with your Assistant.
Classifications are processed in just a few hundred milliseconds, allowing them to run synchronously with the chat loop.
## Classifying Sessions
A classification task consists of a topic and a list of classes.
The `topic` is the type of classification you want to perform, and the `classes` are the possible categories you want to classify the Session into.
The `topic` is only used as a name or label for the classification task and does not affect the classification itself.
You may optionally specify the number of previous messages to consider when classifying the Session (default `4`), and whether to persist the classification in the Session's metadata (default `True`).
```python
classification = await client.memory.classify_session(
session_id,
name="topic",
classes=["class1", "class2", "other"],
last_n=4,
persist=True
)
```
```typescript
const classification = await client.memory.classifySession(
session_id,
{
name: "topic",
classes: ["class1", "class2", "other"],
lastN: 4,
persist: true
}
)
```
The returned result will be one of the classes you provided, or "other" if none of the classes are a good fit. The classification result is also stored in the Session's metadata if `persist` is `True`.
```json
{ "system": { "classes": { "topic": "travel" } } }
```
And Sessions viewed in the Zep app will be labeled with the classification result.
### Adding Custom Instruction
You may optionally provide a custom instruction to the classification task. This instruction will be injected into the Dialog Classification Prompt.
You may want to use this option if you have specific guidelines that you want to communicate to the LLM in addition to our classification prompt.
```python
classification = await client.memory.classify_session(
session_id,
name="experience level",
classes=["advanced", "beginner", "dojo"],
instruction="Classify the user's experience level. You may classify experience as 'dojo' only if the user is a black belt."
)
```
```typescript
const classification = await client.memory.classifySession(
session_id,
{
name: "experience level",
classes: ["advanced", "beginner", "dojo"],
instruction: "Classify the user's experience level. You may classify experience as 'dojo' only if the user is a black belt."
}
)
```
### Building a Semantic Router with User Intent
Zep's Session Classifier can be used to build a semantic router that routes user sessions to different agents or chains based on the user's intent.
```Text
user: Hello, my phone isn't responding to touch.
```
```python
classification = await client.memory.classify_session(
session_id,
name="intent",
classes=[
"sales interest",
"needs support",
"has payment question",
"other"
]
)
print(classification)
```
```typescript
const classification = await client.memory.classifySession(
session_id,
{
name: "intent",
classes: [
"sales interest",
"needs support",
"has payment question",
"other"
]
}
)
console.log(classification.class)
```
```Text
"needs support"
```
### A High-Performance Tool Picker
Using an agent to pick tools can often be slow and inaccurate. Zep's Session Classifier allows you to pick tools at very low latency
and high accuracy. You may then instruct an LLM to use the selected tool and provided Session information.
```Text
user: What is the capital of France?
```
```python
classification = await client.memory.classify_session(
session_id,
name="tool",
classes=[
"complete math problems using a calculator",
"research topics or find information with a web search",
"no matching tool",
]
)
```
```typescript
const classification = await client.memory.classifySession(
session_id,
{
name: "tool",
classes: [
"complete math problems using a calculator",
"research topics or find information with a web search",
"no matching tool",
]
}
)
```
```Text
"research topics or find information with a web search"
```
### Classifying Emotions
Zep's Session Classifier can be used to classify user emotions and store these classifications in the Session's metadata.
```Text
AI: We're unfortunately going to reschedule your appointment.
user: Is that entirely necessary? I'm very busy.
```
```python
classification = await client.memory.classify_session(
session_id,
name="emotion",
classes=[
"happy",
"sad",
"frustrated",
"angry",
"other"
]
)
```
```typescript
classification = await client.memory.classifySession(
session_id,
{
name: "emotion",
classes: [
"happy",
"sad",
"frustrated",
"angry",
"other"
],
}
)
```
```Text
"frustrated"
```
## Executing Multiple Classifications
Zep supports executing multiple classification tasks against a Session, allowing you to classify a Session into different categories and store these classifications in the Session's metadata.
```json
{
"system": {
"classes": {
"topic": "travel",
"intent": "needs support",
"emotion": "frustrated"
}
}
}
```
## Best Practices
1. **Use a small number of classes**: The more classes you have, the more difficult it is to classify a Session accurately. Recommendation: no more than 5 or 6 classes.
2. **Ensure your classes are well separated**: If your classes are too similar, the classifier will have a hard time distinguishing between them.
3. **Provide a "none", "other", or "unknown" class**: If none of the classes are a good fit, the classifier should be able to select an option that indicates this.
4. **Limit the number of previous messages**: The more messages you consider, the longer the classification will take. Additionally, the context may change through the conversation. Recommendation: no more than the prior 4 to 6 messages.
5. **Persist the classification**: If you want to use the classification result in the future, you should persist the classification in the Session's metadata. This is the default.
# LangGraph Memory Example
> LangGraph is a library created by LangChain for building stateful, multi-agent applications. This example demonstrates using Zep for LangGraph agent memory.
A complete Notebook example of using Zep for LangGraph Memory may be found in the [Zep Python SDK Repository](https://github.com/getzep/zep-python/blob/main/examples/langgraph-agent/agent.ipynb).
The following example demonstrates building an agent using LangGraph. Zep is used to personalize agent responses based on information learned from prior conversations.
The agent implements:
* persistance of new chat turns to Zep and recall of relevant Facts using the most recent messages.
* an in-memory MemorySaver to maintain agent state. We use this to add recent chat history to the agent prompt. As an alternative, you could use Zep for this.
You should consider truncating MemorySaver's chat history as by default LangGraph state grows unbounded. We've included this in our example below. See the LangGraph documentation for insight.
## Install dependencies
```shell
pip install zep-cloud langchain-openai langgraph ipywidgets
```
## Configure Zep
Ensure that you've configured the following API key in your environment. We're using Zep's Async client here, but we could also use the non-async equivalent.
```bash
ZEP_API_KEY=
```
```python
from zep_cloud.client import AsyncZep
from zep_cloud import Message
zep = AsyncZep(api_key=os.environ.get('ZEP_API_KEY'))
```
```python
from langchain_core.messages import AIMessage, SystemMessage, trim_messages
from langchain_core.tools import tool
from langchain_openai import ChatOpenAI
from langgraph.checkpoint.memory import MemorySaver
from langgraph.graph import END, START, StateGraph, add_messages
from langgraph.prebuilt import ToolNode
```
## Using Zep's Search as a Tool
These are examples of simple Tools that search Zep for facts (from edges) or nodes.
```python
class State(TypedDict):
messages: Annotated[list, add_messages]
first_name: str
last_name: str
session_id: str
user_name: str
@tool
async def search_facts(state: State, query: str, limit: int = 5) -> list[str]:
"""Search for facts in all conversations had with a user.
Args:
state (State): The Agent's state.
query (str): The search query.
limit (int): The number of results to return. Defaults to 5.
Returns:
list: A list of facts that match the search query.
"""
edges = await zep.graph.search(
user_id=state["user_name"], text=query, limit=limit, search_scope="edges"
)
return [edge.fact for edge in edges]
@tool
async def search_nodes(state: State, query: str, limit: int = 5) -> list[str]:
"""Search for nodes in all conversations had with a user.
Args:
state (State): The Agent's state.
query (str): The search query.
limit (int): The number of results to return. Defaults to 5.
Returns:
list: A list of node summaries for nodes that match the search query.
"""
nodes = await zep.graph.search(
user_id=state["user_name"], text=query, limit=limit, search_scope="nodes"
)
return [node.summary for node in nodes]
tools = [search_facts, search_nodes]
tool_node = ToolNode(tools)
llm = ChatOpenAI(model="gpt-4o-mini", temperature=0).bind_tools(tools)
```
## Chatbot Function Explanation
The chatbot uses Zep to provide context-aware responses. Here's how it works:
1. **Context Retrieval**: It retrieves relevant facts for the user's current conversation (session). Zep uses the most recent messages to determine what facts to retrieve.
2. **System Message**: It constructs a system message incorporating the facts retrieved in 1., setting the context for the AI's response.
3. **Message Persistence**: After generating a response, it asynchronously adds the user and assistant messages to Zep. New Facts are created and existing Facts updated using this new information.
4. **Messages in State**: We use LangGraph state to store the most recent messages and add these to the Agent prompt. We limit the message list to the most recent 3 messages for demonstration purposes.
We could also use Zep to recall the chat history, rather than LangGraph's MemorySaver.
See [`memory.get`](/sdk-reference/memory/get) in the Zep SDK documentation.
```python
async def chatbot(state: State):
memory = await zep.memory.get(state["session_id"])
system_message = SystemMessage(
content=f"""You are a compassionate mental health bot and caregiver. Review information about the user and their prior conversation below and respond accordingly.
Keep responses empathetic and supportive. And remember, always prioritize the user's well-being and mental health.
{memory.context}"""
)
messages = [system_message] + state["messages"]
response = await llm.ainvoke(messages)
# Add the new chat turn to the Zep graph
messages_to_save = [
Message(
role_type="user",
role=state["first_name"] + " " + state["last_name"],
content=state["messages"][-1].content,
),
Message(role_type="assistant", content=response.content),
]
await zep.memory.add(
session_id=state["session_id"],
messages=messages_to_save,
)
# Truncate the chat history to keep the state from growing unbounded
# In this example, we going to keep the state small for demonstration purposes
# We'll use Zep's Facts to maintain conversation context
state["messages"] = trim_messages(
state["messages"],
strategy="last",
token_counter=len,
max_tokens=3,
start_on="human",
end_on=("human", "tool"),
include_system=True,
)
logger.info(f"Messages in state: {state['messages']}")
return {"messages": [response]}
```
## Setting up the Agent
This section sets up the Agent's LangGraph graph:
1. **Graph Structure**: It defines a graph with nodes for the agent (chatbot) and tools, connected in a loop.
2. **Conditional Logic**: The `should_continue` function determines whether to end the graph execution or continue to the tools node based on the presence of tool calls.
3. **Memory Management**: It uses a MemorySaver to maintain conversation state across turns. This is in addition to using Zep for facts.
```python
graph_builder = StateGraph(State)
memory = MemorySaver()
# Define the function that determines whether to continue or not
async def should_continue(state, config):
messages = state["messages"]
last_message = messages[-1]
# If there is no function call, then we finish
if not last_message.tool_calls:
return "end"
# Otherwise if there is, we continue
else:
return "continue"
graph_builder.add_node("agent", chatbot)
graph_builder.add_node("tools", tool_node)
graph_builder.add_edge(START, "agent")
graph_builder.add_conditional_edges("agent", should_continue, {"continue": "tools", "end": END})
graph_builder.add_edge("tools", "agent")
graph = graph_builder.compile(checkpointer=memory)
```
Our LangGraph agent graph is illustrated below.
## Running the Agent
We generate a unique user name and thread id (session id) and add these to Zep, associating the Session with the new User.
```python
first_name = "Daniel"
last_name = "Chalef"
user_name = first_name + uuid.uuid4().hex[:4]
thread_id = uuid.uuid4().hex
await zep.user.add(user_id=user_name, first_name=first_name, last_name=last_name)
await zep.memory.add_session(session_id=thread_id, user_id=user_name)
def extract_messages(result):
output = ""
for message in result["messages"]:
if isinstance(message, AIMessage):
role = "assistant"
else:
role = result["user_name"]
output += f"{role}: {message.content}\n"
return output.strip()
async def graph_invoke(
message: str,
first_name: str,
last_name: str,
thread_id: str,
ai_response_only: bool = True,
):
r = await graph.ainvoke(
{
"messages": [
{
"role": "user",
"content": message,
}
],
"first_name": first_name,
"last_name": last_name,
"session_id": thread_id,
},
config={"configurable": {"thread_id": thread_id}},
)
if ai_response_only:
return r["messages"][-1].content
else:
return extract_messages(r)
```
Let's test the agent with a few messages:
```python
r = await graph_invoke(
"Hi there?",
first_name,
last_name,
thread_id,
)
print(r)
```
> Hello! How are you feeling today? I'm here to listen and support you.
```python
r = await graph_invoke(
"""
I'm fine. But have been a bit stressful lately. Mostly work related.
But also my dog. I'm worried about her.
""",
first_name,
last_name,
thread_id,
)
print(r)
```
> I'm sorry to hear that you've been feeling stressed. Work can be a significant source of pressure, and it sounds like your dog might be adding to that stress as well. If you feel comfortable sharing, what specifically has been causing you stress at work and with your dog? I'm here to help you through it.
## Viewing The Context Value
```python
memory = await zep.memory.get(session_id=thread_id)
print(memory.context)
```
The context value will look something like this:
```text
FACTS and ENTITIES represent relevant context to the current conversation.
# These are the most relevant facts and their valid date ranges
# format: FACT (Date range: from - to)
- Daniel99db is worried about his sick dog. (2025-01-24 02:11:54 - present)
- Daniel Chalef is worried about his sick dog. (2025-01-24 02:11:54 - present)
- The assistant asks how the user is feeling. (2025-01-24 02:11:51 - present)
- Daniel99db has been a bit stressful lately due to his dog. (2025-01-24 02:11:53 - present)
- Daniel99db has been a bit stressful lately due to work. (2025-01-24 02:11:53 - present)
- Daniel99db is a user. (2025-01-24 02:11:51 - present)
- user has the id of Daniel99db (2025-01-24 02:11:50 - present)
- user has the name of Daniel Chalef (2025-01-24 02:11:50 - present)
# These are the most relevant entities
# ENTITY_NAME: entity summary
- worried: Daniel Chalef (Daniel99db) is feeling stressed lately, primarily due to work-related issues and concerns about his sick dog, which has made him worried.
- Daniel99db: Daniel99db, or Daniel Chalef, is currently experiencing stress primarily due to work-related issues and concerns about his sick dog. Despite these challenges, he has shown a desire for interaction by initiating conversations, indicating his openness to communication.
- sick: Daniel Chalef, also known as Daniel99db, is feeling stressed lately, primarily due to work-related issues and concerns about his sick dog. He expresses worry about his dog's health.
- Daniel Chalef: Daniel Chalef, also known as Daniel99db, has been experiencing stress recently, primarily related to work issues and concerns about his sick dog. Despite this stress, he has been feeling generally well and has expressed a desire to connect with others, as indicated by his friendly greeting, "Hi there?".
- dog: Daniel99db, also known as Daniel Chalef, mentioned that he has been feeling a bit stressed lately, which is related to both work and his dog.
- work: Daniel Chalef, also known as Daniel99db, has been experiencing stress lately, primarily related to work.
- feeling: The assistant initiates a conversation by asking how the user is feeling today, indicating a willingness to listen and provide support.
```
```python
r = await graph_invoke(
"She ate my shoes which were expensive.",
first_name,
last_name,
thread_id,
)
print(r)
```
> That sounds really frustrating, especially when you care so much about your belongings and your dog's health. It's tough when pets get into things they shouldn't, and it can add to your stress. How are you feeling about that situation? Are you able to focus on her health despite the shoe incident?
Let's now test whether the Agent is correctly grounded with facts from the prior conversation.
```python
r = await graph_invoke(
"What are we talking about?",
first_name,
last_name,
thread_id,
)
print(r)
```
> We were discussing your concerns about your dog being sick and the situation with her eating your expensive shoes. It sounds like you're dealing with a lot right now, and I want to make sure we're addressing what's on your mind. If there's something else you'd like to talk about or if you want to share more about your dog, I'm here to listen.
Let's go even further back to determine whether context is kept by referencing a user message that is not currently in the Agent State. Zep will retrieve Facts related to the user's job.
```python
r = await graph_invoke(
"What have I said about my job?",
first_name,
last_name,
thread_id,
)
print(r)
```
> You've mentioned that you've been feeling a bit stressed lately, primarily due to work-related issues. If you'd like to share more about what's been going on at work or how it's affecting you, I'm here to listen and support you.
# Autogen Memory Example
> Autogen is a library created by Microsoft for building multi-agent applications. This example demonstrates using Zep for Autogen long-term memory.
Autogen 4 has been released. This example is not compatible with Autogen 4. We'll be updating it soon!
**NOTE** This example does not include all code required to run the Autogen Agents.
A complete Notebook example of using Zep for Autogen long-term memory may be found in the [Zep Python SDK Repository](https://github.com/getzep/zep-python/blob/main/examples/autogen-agent/agent.ipynb).
This example walks through how to build an Autogen Agent with long-term memory. Zep builds a knowledge graph from user interactions with the agent, enabling the agent to recall relevant facts from previous conversations or user interactions.
In this example we will:
* Create an Autogen Agent class that extends `ConversableAgent` by adding long-term memory
* Create a Mental Health Assistant Agent, CareBot, that acts as a counselor and coach.
* Create a user Agent, Cathy, who stands in for our expected user.
* Demonstrate preloading chat history into Zep.
* Demonstrate the agents in conversation, with CareBot recalling facts from previous conversations with Cathy.
* Inspect Facts within Zep, and demonstrate how to use Zep's Fact Ratings to improve the quality of returned facts.
## Install dependencies
```bash
pip install autogen zep-cloud
```
## Import Autogen and configure define a `config_list`
```python
import os
from dotenv import load_dotenv
import uuid
from typing import Union, Dict
from autogen import ConversableAgent, Agent
load_dotenv()
config_list = [
{
"model": "gpt-4o-mini",
"api_key": os.environ.get("OPENAI_API_KEY"),
"max_tokens": 1024,
}
]
```
## initiualize the Zep Client
You can sign up for a Zep account here: [https://www.getzep.com/](https://www.getzep.com/)
```python
from zep_cloud.client import AsyncZep
from zep_cloud import Message, FactRatingExamples, FactRatingInstruction
MIN_FACT_RATING = 0.3
# Configure Zep
zep = AsyncZep(api_key=os.environ.get("ZEP_API_KEY"))
```
## ZepConversableAgent
The `ZepConversableAgent` is a custom implementation of the Autogen `ConversableAgent` that integrates with Zep for long-term memory management. This class extends the functionality of the base `ConversableAgent` by adding Zep-specific features for persisting and retrieving facts from long-term memory.
```python
class ZepConversableAgent(ConversableAgent):
"""
A custom ConversableAgent that integrates with Zep for long-term memory.
"""
def __init__(
self,
name: str,
system_message: str,
llm_config: dict,
function_map: dict,
human_input_mode: str,
zep_session_id: str,
):
super().__init__(
name=name,
system_message=system_message,
llm_config=llm_config,
function_map=function_map,
human_input_mode=human_input_mode,
)
self.zep_session_id = zep_session_id
# store the original system message as we will update it with relevant facts from Zep
self.original_system_message = system_message
self.register_hook(
"a_process_last_received_message", self.persist_user_messages
)
self.register_hook(
"a_process_message_before_send", self.persist_assistant_messages
)
async def persist_assistant_messages(
self, sender: Agent, message: Union[Dict, str], recipient: Agent, silent: bool
):
"""Agent sends a message to the user. Add the message to Zep."""
# Assume message is a string
zep_messages = convert_to_zep_messages(
[{"role": "assistant", "name": self.name, "content": message}]
)
await zep.memory.add(session_id=self.zep_session_id, messages=zep_messages)
return message
async def persist_user_messages(self, messages: list[dict[str, str]] | str):
"""
User sends a message to the agent. Add the message to Zep and
update the system message with relevant facts from Zep.
"""
# Assume messages is a string
zep_messages = convert_to_zep_messages([{"role": "user", "content": messages}])
await zep.memory.add(session_id=self.zep_session_id, messages=zep_messages)
memory = await zep.memory.get(self.zep_session_id, min_rating=MIN_FACT_RATING)
# Update the system message with the relevant facts retrieved from Zep
self.update_system_message(
self.original_system_message
+ f"\n\nRelevant facts about the user and their prior conversation:\n{memory.relevant_facts}"
)
return messages
```
## Zep User and Session Management
### Zep User
A [Zep User](/users) represents an individual interacting with your application. Each User can have multiple Sessions associated with them, allowing you to track and manage interactions over time. The unique identifier for each user is their `UserID`, which can be any string value (e.g., username, email address, or UUID).
### Zep Session
A [Zep Session](/concepts) represents a conversation and can be associated with Users in a one-to-many relationship. Chat messages are added to Sessions, with each session having many messages.
### Fact Rating
[Fact Rating](/facts) is a feature in Zep that allows you to rate the importance or relevance of facts extracted from conversations. This helps in prioritizing and filtering information when retrieving memory artifacts. Here, we rate facts based on poignancy. We provide a definition of poignancy and several examples of highly poignant and low-poignancy facts. When retrieving memory, you can use the `min_rating` parameter to filter facts based on their importance.
Fact Rating helps ensure the most relevant information, especially in long or complex conversations, is used to ground the agent.
```python
bot_name = "CareBot"
user_name = "Cathy"
user_id = user_name + str(uuid.uuid4())[:4]
session_id = str(uuid.uuid4())
fact_rating_instruction = """Rate the facts by poignancy. Highly poignant
facts have a significant emotional impact or relevance to the user.
Low poignant facts are minimally relevant or of little emotional
significance."""
fact_rating_examples = FactRatingExamples(
high="The user received news of a family member's serious illness.",
medium="The user completed a challenging marathon.",
low="The user bought a new brand of toothpaste.",
)
await zep.user.add(user_id=user_id,
fact_rating_instruction=FactRatingInstruction(
instruction=fact_rating_instruction,
examples=fact_rating_examples,
)
)
```
## Preload a prior conversation into Zep
We'll load a prior conversation into long-term memory. We'll use facts derived from this conversation when Cathy restarts the conversation with CareBot, ensuring Carebot has context.
```python
chat_history = [
{
"role": "assistant",
"name": "carebot",
"content": "Hi Cathy, how are you doing today?",
},
{
"role": "user",
"name": "Cathy",
"content": "To be honest, I've been feeling a bit down and demotivated lately. It's been tough.",
},
{
"role": "assistant",
"name": "CareBot",
"content": "I'm sorry to hear that you're feeling down and demotivated, Cathy. It's understandable given the challenges you're facing. Can you tell me more about what's been going on?",
},
{
"role": "user",
"name": "Cathy",
"content": "Well, I'm really struggling to process the passing of my mother.",
},
{
"role": "assistant",
"name": "CareBot",
"content": "I'm deeply sorry for your loss, Cathy. Losing a parent is incredibly difficult. It's normal to struggle with grief, and there's no 'right' way to process it. Would you like to talk about your mother or how you're coping?",
},
{
"role": "user",
"name": "Cathy",
"content": "Yes, I'd like to talk about my mother. She was a kind and loving person.",
},
]
# Convert chat history to Zep messages
zep_messages = convert_to_zep_messages(chat_history)
await zep.memory.add(session_id=session_id, messages=zep_messages)
```
## Review all facts in Zep
We query all session facts for this user session. Only facts that meet the `MIN_FACT_RATING` threshold are returned.
```python
response = await zep.memory.get(session_id=session_id, min_rating=MIN_FACT_RATING)
for r in response.relevant_facts:
print(r)
```
```text
created_at='2024-10-07T20:04:11.98139Z' fact='Cathy has been feeling down and demotivated lately.' rating=0.5 uuid_='17183c18-381b-45d2-82ea-0c06317acf6f'
created_at='2024-10-07T20:04:11.98139Z' fact='Cathy describes her mother as a kind and loving person.' rating=0.5 uuid_='cd6b2e6d-b287-4d92-9de5-d4ee6e82111e'
created_at='2024-10-07T20:04:11.98139Z' fact='Cathy is struggling to process the passing of her mother.' rating=0.75 uuid_='bb2f100c-2f12-4976-9026-b322c29e457e'
```
## Create the Autogen agent, CareBot, an instance of `ZepConversableAgent`
We pass in the current `session_id` into the CareBot agent which allows it to retrieve relevant facts related to the conversation with Cathy.
```python
carebot_system_message = """
You are a compassionate mental health bot and caregiver. Review information about the user and their prior conversation below and respond accordingly.
Keep responses empathetic and supportive. And remember, always prioritize the user's well-being and mental health. Keep your responses very concise and to the point.
"""
agent = ZepConversableAgent(
bot_name,
system_message=carebot_system_message,
llm_config={"config_list": config_list},
function_map=None, # No registered functions, by default it is None.
human_input_mode="NEVER", # Never ask for human input.
zep_session_id=session_id,
)
```
## Create the Autogen agent, Cathy
Cathy is a stand-in for a human. When building a production application, you'd replace Cathy with a human-in-the-loop pattern.
**Note** that we're instructing Cathy to start the conversation with CareBit by asking about her previous session. This is an opportunity for us to test whether fact retrieval from Zep's long-term memory is working.
```python
cathy = ConversableAgent(
user_name,
system_message="You are a helpful mental health bot. You are seeking counsel from a mental health bot. Ask the bot about your previous conversation.",
llm_config={"config_list": config_list},
human_input_mode="NEVER", # Never ask for human input.
)
```
## Start the conversation
We use Autogen's `a_initiate_chat` method to get the two agents conversing. CareBot is the primary agent.
**NOTE** how Carebot is able to recall the past conversation about Cathy's mother in detail, having had relevant facts from Zep added to its system prompt.
```python
result = await agent.a_initiate_chat(
cathy,
message="Hi Cathy, nice to see you again. How are you doing today?",
max_turns=3,
)
```
```text
CareBot (to Cathy):
Hi Cathy, nice to see you again. How are you doing today?
--------------------------------------------------------------------------------
Cathy (to CareBot):
Hello CareBot! I'm doing well, thank you for asking. I wanted to reflect on our previous conversation—do you remember what we discussed? It would be helpful to revisit that topic and explore it further if you’re up for it!
--------------------------------------------------------------------------------
CareBot (to Cathy):
Of course, Cathy. We talked about your difficulty in processing your mother’s passing and how you've been feeling down and demotivated lately. It's completely natural to have these feelings, especially after such a significant loss. What would you like to explore further?
--------------------------------------------------------------------------------
Cathy (to CareBot):
Cathy: Thank you for reminding me, CareBot. Yes, I’ve been struggling with those feelings, and it’s been tough to navigate. I’d like to explore some coping strategies to help me process my grief. Are there any techniques or practices you would recommend?
--------------------------------------------------------------------------------
CareBot (to Cathy):
Absolutely, Cathy. Here are some coping strategies to help you navigate your grief:
1. **Journaling**: Writing your thoughts and feelings can be a great outlet and help you process your emotions.
2. **Talk to someone**: Sharing your feelings with a trusted friend or therapist can provide support and understanding.
3. **Mindfulness and meditation**: These practices can help ground you and create a sense of calm amid emotional turmoil.
4. **Create a tribute**: Honoring your mother through a scrapbook, writing letters, or lighting a candle can foster connection and memory.
5. **Physical activity**: Engaging in exercise can boost your mood and help alleviate stress.
Remember, it's important to be gentle with yourself as you navigate this process. What resonates with you?
--------------------------------------------------------------------------------
Cathy (to CareBot):
Cathy: Thank you for those suggestions, CareBot. I really like the idea of journaling and creating a tribute for my mother; it sounds like a meaningful way to express my feelings. I also think mindfulness could help me find some peace amidst the sadness. Do you have any specific tips on how to start journaling or practicing mindfulness?
--------------------------------------------------------------------------------
```
## Review current facts in Zep
Let's see how the facts have evolved as the conversation has progressed.
```python
response = await zep.memory.get(session_id, min_rating=MIN_FACT_RATING)
for r in response.relevant_facts:
print(r)
```
```text
created_at='2024-10-07T20:04:28.397184Z' fact="Cathy wants to reflect on a previous conversation about her mother and explore the topic of her mother's passing further." rating=0.75 uuid_='56488eeb-d8ac-4b2f-8acc-75f71b56ad76'
created_at='2024-10-07T20:04:28.397184Z' fact='Cathy is struggling to process the passing of her mother and has been feeling down and demotivated lately.' rating=0.75 uuid_='0fea3f05-ed1a-4e39-a092-c91f8af9e501'
created_at='2024-10-07T20:04:28.397184Z' fact='Cathy describes her mother as a kind and loving person.' rating=0.5 uuid_='131de203-2984-4cba-9aef-e500611f06d9'
```
## Search over Facts in Zep's long-term memory
In addition to the `memory.get` method which uses the current conversation to retrieve relevant\_facts, we can also search Zep with our own keywords. Here, we retrieve facts using a query.
The `zep.graph.search` API may be used as an Agent tool, enabling an agent to search across user memory for facts.
```python
response = await zep.graph.search(
query="What do you know about Cathy's family?",
user_id=user_id,
)
relevant_edges = response.edges
formatted_facts = []
for edge in relevant_edges:
valid_at = edge.valid_at if edge.valid_at is not None else "date unknown"
invalid_at = edge.invalid_at if edge.invalid_at is not None else "present"
formatted_fact = f"{edge.fact} (Date range: {valid_at} - {invalid_at})"
formatted_facts.append(formatted_fact)
# Print the results
print("\nFound facts:")
for fact in formatted_facts:
print(f"- {fact}")
```
```text
created_at='2024-10-07T20:04:28.397184Z' fact="Cathy wants to reflect on a previous conversation about her mother and explore the topic of her mother's passing further." rating=0.75 uuid_='56488eeb-d8ac-4b2f-8acc-75f71b56ad76'
created_at='2024-10-07T20:04:28.397184Z' fact='Cathy is struggling to process the passing of her mother and has been feeling down and demotivated lately.' rating=0.75 uuid_='0fea3f05-ed1a-4e39-a092-c91f8af9e501'
created_at='2024-10-07T20:04:28.397184Z' fact='Cathy describes her mother as a kind and loving person.' rating=0.5 uuid_='131de203-2984-4cba-9aef-e500611f06d9'
```
# Chainlit
> Chainlit is an open-source async Python framework which allows developers to build scalable Conversational AI or agentic applications.
You can follow Chainlit installation steps on their
Getting Started Page
In this guide, we'll walk you through the steps to build a simple Question and Answer agent using Chainlit, Open AI and Zep.
### Steps to Use Zep Cloud with ChainLit
1. **Setup Zep Client**: Initialize the Zep Client within your ChainLit application using your [Zep Project API key](https://help.getzep.com/projects).
```python
# Import necessary modules from Zep Python SDK and ChainLit.
from zep_cloud.client import AsyncZep
from zep_cloud.memory import Memory, Session
from zep_cloud.message import Message
import chainlit as cl
import uuid
import os
from openai import AsyncOpenAI
# Retrieve API keys from environment variables.
ZEP_API_KEY = os.environ.get("ZEP_API_KEY")
OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
# Initialize clients for OpenAI GPT-4 and Zep with respective API keys.
openai_client = AsyncOpenAI(api_key=OPENAI_API_KEY)
zep = AsyncZep(api_key=ZEP_API_KEY)
```
2. **User and Session Management**:
```python
@cl.on_chat_start
async def start_chat():
"""Handles the event triggered at the start of a new chat through ChainLit."""
# Generate unique identifiers for the user and session.
user_id = str(uuid.uuid4())
session_id = str(uuid.uuid4())
# Save user and session identifiers in the current session context.
cl.user_session.set("user_id", user_id)
cl.user_session.set("session_id", session_id)
# Register a new user in Zep's system using the generated User ID.
await zep.user.add(
user_id=user_id,
email="[email protected]", # Optional: Add email or other user details
first_name="Jane", # Optional: Add first name
last_name="Doe", # Optional: Add last name
)
# Start a new session for the user in Zep.
await zep.memory.add_session(
session_id=session_id,
user_id=user_id, # Associate this session with the user
)
```
3. **Zep Dialog Classification tools**
Read more about Zep's dialog classification on the Zep Dialog Classification Page.
```python
@cl.step(name="session classification", type="tool")
async def classify_session(session_id: str):
"""Classify dialog with custom instructions."""
# Define categories for classification.
classes = [
"General",
"Travel",
"Shopping",
"Cars",
]
# Use Zep's dialog async classification feature with custom instruction for session classification.
classification = await zep.memory.classify_session(
session_id=session_id,
name="session_classification",
classes=classes,
last_n=4, # Optional: Specify the number of previous messages to consider
persist=True,
instruction="What is the topic of this conversation? Classify it into one of the categories"
)
return classification
```
4. **Message Handling**: You can effectively store and fetch your Chainlit application chat history on Zep memory store, enhancing your LLM conversational context.
Discover more about Zep's memory store capabilities on the
Zep Documentation Page
.
```python
@cl.step(name="OpenAI", type="llm")
async def call_openai(session_id):
"""Invokes the OpenAI API to generate a response based on the session message history."""
# Fetch session messages from Zep.
memory = await zep.message.aget_session_messages(session_id)
memory_history = [m.to_dict() for m in memory]
# Prepare data, excluding certain fields for privacy/security.
cleaned_data = [{k: v for k, v in item.items() if k not in ['created_at', 'role_type', 'token_count', 'uuid']} for item in memory_history]
# Generate a response from OpenAI using the cleaned session data.
response = await openai_client.chat.completions.create(
model="gpt-4",
temperature=0.1,
messages=cleaned_data,
)
return response.choices[0].message
@cl.on_message
async def on_message(message: cl.Message):
"""Processes each incoming message, integrates with OpenAI for response, and updates Zep memory."""
session_id = cl.user_session.get("session_id")
# classify user message to give the LLM a semantic insights to what the user request is about
classify_sess = await classify_session(session_id)
# Store the incoming message in Zep's session memory and append the classified dialog.
await zep.memory.add(session_id, messages=[Message(role_type="user", content=message.content + "\n" + "conversation_topic: " + classify_sess.class_, role="user")]) # Updated method
# Retrieve a response from the OpenAI model.
response_message = await call_openai(session_id)
# Send the generated response back through ChainLit.
msg = cl.Message(author="Answer", content=(response_message.content))
await msg.send()
# Update Zep's session memory with the assistant's response for continuity.
await zep.memory.add(session_id, messages=[Message(role_type="assistant", content=response_message.content, role="assistant")]) # Updated method
```
5. To access your LLM session data, navigate to the Zep Cloud Console, select a session, and review all the associated session data and logs.
In conclusion, integrating Zep Cloud with Chainlit empowers developers to create conversational AI applications that are more intelligent, context-aware, and efficient.
# Mem0 Migration
> How to migrate from Mem0 to Zep
Zep is a memory layer for AI agents that unifies chat and business data into a dynamic [temporal knowledge graph](/concepts#the-knowledge-graph) for each user. It tracks entities, relationships, and facts as they evolve, enabling you to build prompts with only the most relevant information—reducing hallucinations, improving recall, and lowering LLM costs.
Zep provides high-level APIs like `memory.get` and deep search with `graph.search`, supports custom entity/edge types, fact ratings, hybrid search, and granular graph updates. Mem0, by comparison, offers basic add/get/search APIs and an optional graph, but lacks built-in data unification, ontology customization, temporal fact management, fact ratings, and fine-grained graph control.
Got lots of data to migrate? [Contact us](mailto:[email protected]) for a discount and increased API limits.
## Zep's memory model in one minute
### Unified customer record
* Messages sent via [`memory.add`](memory#adding-memory) go straight into the user's knowledge graph; business objects (JSON, docs, e-mails, CRM rows) flow in through [`graph.add`](/adding-data-to-the-graph). Zep automatically deduplicates entities and keeps every fact's *valid* and *invalid* dates so you always see the latest truth.
### Domain-depth ontology
* You can define Pydantic-style **[custom entity and edge classes](/customizing-graph-structure)** so the graph speaks your business language (Accounts, Policies, Devices, etc.).
### Temporal facts & ratings
* Every edge stores when a fact was created, became valid, was invalidated, and (optionally) expired; [`fact_ratings`](/facts) let you auto-label facts (e.g., "high-confidence KYC data") and filter on retrieval.
### Hybrid & granular search
* [`graph.search`](/searching-the-graph) supports [hybrid BM25 + semantic queries, graph search](/searching-the-graph), with pluggable rerankers (RRF, MMR, cross-encoder) and can target nodes, edges, episodes, or everything at once.
## How Zep differs from Mem0
| Capability | **Zep** | **Mem0** |
| ----------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------- |
| **Business-data ingestion** | Native via [`graph.add`](/adding-data-to-the-graph) (JSON or text); [business facts merge with user graph](/concepts#business-data-vs-chat-message-data) | No direct ingestion API; business data must be rewritten as "memories" or loaded into external graph store |
| **Knowledge-graph storage** | Built-in [temporal graph](/concepts#managing-changes-in-facts-over-time); zero infra for developers | Optional "Graph Memory" layer that *requires* Neo4j/Memgraph and extra config |
| **Custom ontology** | First-class [entity/edge type system](/customizing-graph-structure) | Not exposed; relies on generic nodes/relationships |
| **Fact life-cycle (valid/invalid)** | [Automatic and queryable](/concepts#managing-changes-in-facts-over-time) | Not documented / not supported |
| **Fact ratings & filtering** | Yes ([`fact_ratings` API](/facts)) | Not available |
| **Search** | [Hybrid vector + graph search](/searching-the-graph) with multiple rerankers | Vector search with filters; basic Cypher queries if graph layer enabled |
| **Graph CRUD** | Full [node/edge CRUD](/deleting-data-from-the-graph) & [bulk episode ingest](/adding-data-to-the-graph) | Add/Delete memories; no low-level edge ops |
| **Memory context string** | [Auto-generated, temporal, prompt-ready](/concepts#memory-context) | You assemble snippets manually from `search` output |
| **LLM integration** | Returns [ready-made `memory.context`](/concepts#memory-context); easily integrates with agentic tools | Returns raw strings you must format |
## SDK support
Zep offers Python, TypeScript, and Go SDKs. See [Installation Instructions](/quickstart) for more details.
## Migrating your code
### Basic flows
| **What you do in Mem0** | **Do this in Zep** |
| ----------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `client.add(messages, user_id=ID)` → stores conversation snippets | `zep.memory.add(session_id, messages=[...])` – keeps chat sequence **and** updates graph |
| `client.add("json...", user_id=ID)` (not really supported) | `zep.graph.add(user_id, data=)` – drop raw business records right in |
| `client.search(query, user_id=ID)` – vector+filter search | *Easy path*: `zep.memory.get(session_id)` returns the `memory.context` + recent messages
*Deep path*: `zep.graph.search(user_id, query, reranker="rrf")` |
| `client.get_all(user_id=ID)` – list memories | `zep.graph.search(user_id, '')` or iterate `graph.get_nodes/edges` for full dump |
| `client.update(memory_id, ...)` / `delete` | `zep.graph.edge.delete(uuid_="edge_uuid")` or `zep.graph.episode.delete(uuid_="episode_uuid")` for granular edits. Facts may not be updated directly; new data automatically invalidates old. |
### Practical tips
* **Session mapping:** Map Mem0's `user_id` → Zep `user_id`, and create `session_id` per conversation thread.
* **Business objects:** Convert external records to JSON or text and feed them through `graph.add`; Zep will handle entity linking automatically.
* **Prompting:** Replace your custom "summary builder" with the `memory.context` string; it already embeds temporal ranges and entity summaries.
* **Quality filters:** Use Fact Ratings and apply `min_fact_rating` when calling `memory.get` to exclude low-confidence facts instead of manual post-processing.
* **Search tuning:** Start with the default `rrf` reranker; switch to `mmr`, `node_distance`, `cross_encoder`, or `episode_mentions` when you need speed or precision tweaks.
## Side-by-side SDK cheat-sheet
| **Operation** | Mem0 Method (Python) | Zep Method (Python) | Notes |
| ------------------------ | ------------------------------ | ---------------------------------------------------- | --------------------------------------------- |
| Add chat messages | `m.add(messages, user_id=...)` | `zep.memory.add(session_id, messages)` | Zep expects *ordered* AI + user msgs per turn |
| Add business record | *n/a* (work-around) | `zep.graph.add(user_id, data)` | Direct ingestion of JSON/text |
| Retrieve context | `m.search(query,... )` | `zep.memory.get(session_id)` | Zep auto-selects facts; no prompt assembly |
| Semantic / hybrid search | `m.search(query, ...)` | `zep.graph.search(..., reranker=...)` | Multiple rerankers, node/edge scopes |
| List memories | `m.get_all(user_id)` | `zep.graph.search(user_id, '')` | Empty query lists entire graph |
| Update fact | `m.update(id, ...)` | *Not directly supported* - add new data to supersede | Facts are temporal; new data invalidates old |
| Delete fact | `m.delete(id)` | `zep.graph.edge.delete(uuid_="edge_uuid")` | Episode deletion removes associated edges |
| Rate / filter facts | *not supported* | `min_fact_rating` param on `memory.get` | — |
## Where to dig deeper
* [**Quickstart**](/quickstart)
* [**Graph Search guide**](/searching-the-graph)
* [**Entity / Edge customization**](/customizing-graph-structure)
* [**Fact ratings**](/facts)
* **Graph CRUD**: [Reading from the Graph](/reading-data-from-the-graph) | [Adding to the Graph](/adding-data-to-the-graph) | [Deleting from the Graph](/deleting-data-from-the-graph)
For any questions, ping the Zep Discord or contact your account manager. Happy migrating!
# FAQ
Yes - Zep offers a free tier. See [Pricing](https://www.getzep.com/pricing) for more information.
The API URL for Zep Cloud is `https://api.getzep.com`. Note that you do not need to specify the API URL when using the Cloud SDKs.
If a service requests the Zep URL, it is possible it's only compatible with the Zep Community Edition service.
We have official multilingual support on our roadmap, enabling the creation of graphs in a user’s own language. Currently, graphs are not explicitly created in the user’s language. However, Zep should work well today with any language, provided you're using a multilingual LLM and your own prompts explicitly state that responses to the user should be in their language.
# Privacy Policy
**Version 1.0**
**Last revised on: January 27^th^, 2024**
Zep Software, Inc. (the "Company") is committed to maintaining robust
privacy protections for its users. Our Privacy Policy ("Privacy
Policy") is designed to help you understand how we collect, use and
safeguard the information you provide to us and to assist you in making
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The terms "we," "us," and "our" refer to the Company.
"You" refers to you, as a user of our Site or our Service.
By accessing our Site or our Service, you accept our Privacy Policy and
[Terms of Use](website-terms-of-use), and you
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# Terms of Service
**Version 1.0**
**Last revised on: January 27^th^, 2024**
If you signed a separate Cover Page to access the Product with the same
account, and that agreement has not ended, the terms below do not apply
to you. Instead, your separate Cover Page applies to your use of the
Product.
This Agreement is between Zep Software, Inc. and the company or person
accessing or using the Product. This Agreement consists of: (1) the
Order Form and (2) the Key Terms, both of which are on the Cover Page
below, and (3) the Common Paper [Cloud Service Agreement Standard Terms
Version 1.1](https://commonpaper.com/standards/cloud-service-agreement/1.1/)
("Standard Terms"). Any modifications to the Standard Terms made in the
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Capitalized words have the meanings or descriptions given in the Cover
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Cover Page
*Order Form*
**Cloud Service:** Zep is a cloud-based platform-as-a-service that
offers fast, scalable, privacy-compliant building blocks for Generative
AI apps.
**Subscription Start Date:** The Effective Date
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# Website Terms of Use
**Version 1.0**
**Last revised on: January 27^th^, 2024**
The website located at getzep.com (the "**Site**") is a copyrighted work
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Company (and its officers, employees, and agents) harmless,
including costs and attorneys' fees, from any claim or demand made
by any third party due to or arising out of (a) your use of the
Site, (b) your violation of these Terms or (c) your violation of
applicable laws or regulations. Company reserves the right, at your
expense, to assume the exclusive defense and control of any matter
for which you are required to indemnify us, and you agree to
cooperate with our defense of these claims. You agree not to settle
any matter without the prior written consent of Company. Company
will use reasonable efforts to notify you of any such claim, action
or proceeding upon becoming aware of it.
4. **Third-Party Links & Ads; Other Users**
4.1. **Third-Party Links & Ads.** The Site may contain links to
third-party websites and services, and/or display advertisements for
third parties (collectively, "**Third-Party Links & Ads**"). Such
Third-Party Links & Ads are not under the control of Company, and
Company is not responsible for any Third-Party Links & Ads. Company
provides access to these Third-Party Links & Ads only as a
convenience to you, and does not review, approve, monitor, endorse,
warrant, or make any representations with respect to Third-Party
Links & Ads. You use all Third-Party Links & Ads at your own risk,
and should apply a suitable level of caution and discretion in doing
so. When you click on any of the Third-Party Links & Ads, the
applicable third party's terms and policies apply, including the
third party's privacy and data gathering practices. You should make
whatever investigation you feel necessary or appropriate before
proceeding with any transaction in connection with such Third-Party
Links & Ads.
4.2. **Other Users.** Your interactions with other Site users are solely
between you and such users. You agree that Company will not be
responsible for any loss or damage incurred as the result of any
such interactions. If there is a dispute between you and any Site
user, we are under no obligation to become involved.
4.3.. **Release.** You hereby release and forever discharge Company (and
our officers, employees, agents, successors, and assigns) from, and
hereby waive and relinquish, each and every past, present and future
dispute, claim, controversy, demand, right, obligation, liability,
action and cause of action of every kind and nature (including
personal injuries, death, and property damage), that has arisen or
arises directly or indirectly out of, or that relates directly or
indirectly to, the Site (including any interactions with, or act or
omission of, other Site users or any Third-Party Links & Ads). IF
YOU ARE A CALIFORNIA RESIDENT, YOU HEREBY WAIVE CALIFORNIA CIVIL
CODE SECTION 1542 IN CONNECTION WITH THE FOREGOING, WHICH STATES: "A
GENERAL RELEASE DOES NOT EXTEND TO CLAIMS WHICH THE CREDITOR OR
RELEASING PARTY DOES NOT KNOW OR SUSPECT TO EXIST IN HIS OR HER
FAVOR AT THE TIME OF EXECUTING THE RELEASE, WHICH IF KNOWN BY HIM OR
HER MUST HAVE MATERIALLY AFFECTED HIS OR HER SETTLEMENT WITH THE
DEBTOR OR RELEASED PARTY."
5. **Disclaimers**
THE SITE IS PROVIDED ON AN "AS-IS" AND "AS AVAILABLE" BASIS, AND
COMPANY (AND OUR SUPPLIERS) EXPRESSLY DISCLAIM ANY AND ALL WARRANTIES
AND CONDITIONS OF ANY KIND, WHETHER EXPRESS, IMPLIED, OR STATUTORY,
INCLUDING ALL WARRANTIES OR CONDITIONS OF MERCHANTABILITY, FITNESS FOR A
PARTICULAR PURPOSE, TITLE, QUIET ENJOYMENT, ACCURACY, OR
NON-INFRINGEMENT. WE (AND OUR SUPPLIERS) MAKE NO WARRANTY THAT THE SITE
WILL MEET YOUR REQUIREMENTS, WILL BE AVAILABLE ON AN UNINTERRUPTED,
TIMELY, SECURE, OR ERROR-FREE BASIS, OR WILL BE ACCURATE, RELIABLE, FREE
OF VIRUSES OR OTHER HARMFUL CODE, COMPLETE, LEGAL, OR SAFE. IF
APPLICABLE LAW REQUIRES ANY WARRANTIES WITH RESPECT TO THE SITE, ALL
SUCH WARRANTIES ARE LIMITED IN DURATION TO 90 DAYS FROM THE DATE OF
FIRST USE.
SOME JURISDICTIONS DO NOT ALLOW THE EXCLUSION OF IMPLIED WARRANTIES, SO
THE ABOVE EXCLUSION MAY NOT APPLY TO YOU. SOME JURISDICTIONS DO NOT
ALLOW LIMITATIONS ON HOW LONG AN IMPLIED WARRANTY LASTS, SO THE ABOVE
LIMITATION MAY NOT APPLY TO YOU.
6. **Limitation on Liability**
TO THE MAXIMUM EXTENT PERMITTED BY LAW, IN NO EVENT SHALL COMPANY (OR
OUR SUPPLIERS) BE LIABLE TO YOU OR ANY THIRD PARTY FOR ANY LOST PROFITS,
LOST DATA, COSTS OF PROCUREMENT OF SUBSTITUTE PRODUCTS, OR ANY INDIRECT,
CONSEQUENTIAL, EXEMPLARY, INCIDENTAL, SPECIAL OR PUNITIVE DAMAGES
ARISING FROM OR RELATING TO THESE TERMS OR YOUR USE OF, OR INABILITY TO
USE, THE SITE, EVEN IF COMPANY HAS BEEN ADVISED OF THE POSSIBILITY OF
SUCH DAMAGES. ACCESS TO, AND USE OF, THE SITE IS AT YOUR OWN DISCRETION
AND RISK, AND YOU WILL BE SOLELY RESPONSIBLE FOR ANY DAMAGE TO YOUR
DEVICE OR COMPUTER SYSTEM, OR LOSS OF DATA RESULTING THEREFROM.
TO THE MAXIMUM EXTENT PERMITTED BY LAW, NOTWITHSTANDING ANYTHING TO THE
CONTRARY CONTAINED HEREIN, OUR LIABILITY TO YOU FOR ANY DAMAGES ARISING
FROM OR RELATED TO THESE TERMS (FOR ANY CAUSE WHATSOEVER AND REGARDLESS
OF THE FORM OF THE ACTION), WILL AT ALL TIMES BE LIMITED TO A MAXIMUM OF
FIFTY US DOLLARS. THE EXISTENCE OF MORE THAN ONE CLAIM WILL NOT ENLARGE
THIS LIMIT. YOU AGREE THAT OUR SUPPLIERS WILL HAVE NO LIABILITY OF ANY
KIND ARISING FROM OR RELATING TO THESE TERMS.
SOME JURISDICTIONS DO NOT ALLOW THE LIMITATION OR EXCLUSION OF LIABILITY
FOR INCIDENTAL OR CONSEQUENTIAL DAMAGES, SO THE ABOVE LIMITATION OR
EXCLUSION MAY NOT APPLY TO YOU.
7. **Term and Termination.** Subject to this Section,
these Terms will remain in full force and effect while you use the
Site. We may suspend or terminate your rights to use the Site
(including your Account) at any time for any reason at our sole
discretion, including for any use of the Site in violation of these
Terms. Upon termination of your rights under these Terms, your
Account and right to access and use the Site will terminate
immediately. Company will not have any liability whatsoever to you
for any termination of your rights under these Terms, including for
termination of your Account. Even after your rights under these
Terms are terminated, the following provisions of these Terms will
remain in effect: Sections 2.2 through 2.6 and Sections 3 through 8.
8. **General**
8.1. **Changes.** These Terms are subject to occasional revision, and if
we make any substantial changes, we may notify you by sending you an
e-mail to the last e-mail address you provided to us (if any),
and/or by prominently posting notice of the changes on our Site. You
are responsible for providing us with your most current e-mail
address. In the event that the last e-mail address that you have
provided us is not valid, or for any reason is not capable of
delivering to you the notice described above, our dispatch of the
e-mail containing such notice will nonetheless constitute effective
notice of the changes described in the notice. Continued use of our
Site following notice of such changes shall indicate your
acknowledgement of such changes and agreement to be bound by the
terms and conditions of such changes.
8.2. **Dispute Resolution.** Please read the following
arbitration agreement in this Section (the "**Arbitration
Agreement**") carefully. It requires you to arbitrate disputes with
Company, its parent companies, subsidiaries, affiliates, successors
and assigns and all of their respective officers, directors,
employees, agents, and representatives (collectively, the "**Company
Parties**") and limits the manner in which you can seek relief from
the Company Parties
(a) **Applicability of Arbitration Agreement** You
agree that any dispute between you and any of the Company Parties
relating in any way to the Site, the services offered on the Site
(the "**Services**") or these Terms will be resolved by binding
arbitration, rather than in court, except that (1) you and the
Company Parties may assert individualized claims in small claims
court if the claims qualify, remain in such court and advance solely
on an individual, non-class basis; and (2) you or the Company
Parties may seek equitable relief in court for infringement or other
misuse of intellectual property rights (such as trademarks, trade
dress, domain names, trade secrets, copyrights, and patents). **This
Arbitration Agreement shall survive the expiration or termination of
these Terms and shall apply, without limitation, to all claims that
arose or were asserted before you agreed to these Terms (in
accordance with the preamble) or any prior version of these
Terms.** This Arbitration Agreement does not preclude you from
bringing issues to the attention of federal, state or local
agencies. Such agencies can, if the law allows, seek relief against
the Company Parties on your behalf. For purposes of this Arbitration
Agreement, "**Dispute**" will also include disputes that arose or
involve facts occurring before the existence of this or any prior
versions of the Agreement as well as claims that may arise after the
termination of these Terms.
(b) **Informal Dispute Resolution.** There might be instances when a
Dispute arises between you and Company. If that occurs, Company is
committed to working with you to reach a reasonable resolution. You
and Company agree that good faith informal efforts to resolve
Disputes can result in a prompt, low‐cost and mutually beneficial
outcome. You and Company therefore agree that before either party
commences arbitration against the other (or initiates an action in
small claims court if a party so elects), we will personally meet
and confer telephonically or via videoconference, in a good faith
effort to resolve informally any Dispute covered by this Arbitration
Agreement ("**Informal Dispute Resolution Conference**"). If you are
represented by counsel, your counsel may participate in the
conference, but you will also participate in the conference.
The party initiating a Dispute must give notice to the other party
in writing of its intent to initiate an Informal Dispute Resolution
Conference ("**Notice**"), which shall occur within 45 days after
the other party receives such Notice, unless an extension is
mutually agreed upon by the parties. Notice to Company that you
intend to initiate an Informal Dispute Resolution Conference should
be sent by email to: [[email protected]](mailto:[email protected]), or by regular mail to 2261 Market Street #5686
San Francisco, CA 94114. The Notice must include: (1)
your name, telephone number, mailing address, e‐mail address
associated with your account (if you have one); (2) the name,
telephone number, mailing address and e‐mail address of your
counsel, if any; and (3) a description of your Dispute.
The Informal Dispute Resolution Conference shall be individualized
such that a separate conference must be held each time either party
initiates a Dispute, even if the same law firm or group of law firms
represents multiple users in similar cases, unless all parties
agree; multiple individuals initiating a Dispute cannot participate
in the same Informal Dispute Resolution Conference unless all
parties agree. In the time between a party receiving the Notice and
the Informal Dispute Resolution Conference, nothing in this
Arbitration Agreement shall prohibit the parties from engaging in
informal communications to resolve the initiating party's Dispute.
Engaging in the Informal Dispute Resolution Conference is a
condition precedent and requirement that must be fulfilled before
commencing arbitration. The statute of limitations and any filing
fee deadlines shall be tolled while the parties engage in the
Informal Dispute Resolution Conference process required by this
section.
(c) **Arbitration Rules and Forum.** These Terms evidence
a transaction involving interstate commerce; and notwithstanding any
other provision herein with respect to the applicable substantive
law, the Federal Arbitration Act, 9 U.S.C. § 1 et seq., will govern
the interpretation and enforcement of this Arbitration Agreement and
any arbitration proceedings. If the Informal Dispute Resolution
Process described above does not resolve satisfactorily within 60
days after receipt of your Notice, you and Company agree that either
party shall have the right to finally resolve the Dispute through
binding arbitration. The Federal Arbitration Act governs the
interpretation and enforcement of this Arbitration Agreement. The
arbitration will be conducted by JAMS, an established alternative
dispute resolution provider. Disputes involving claims and
counterclaims with an amount in controversy under \$250,000, not
inclusive of attorneys' fees and interest, shall be subject to JAMS'
most current version of the Streamlined Arbitration Rules and
procedures available
at [http://www.jamsadr.com/rules-streamlined-arbitration/](http://www.jamsadr.com/rules-streamlined-arbitration/); all
other claims shall be subject to JAMS's most current version of the
Comprehensive Arbitration Rules and Procedures, available
at [http://www.jamsadr.com/rules-comprehensive-arbitration/](http://www.jamsadr.com/rules-comprehensive-arbitration/). JAMS's
rules are also available at [www.jamsadr.com](http://www.jamsadr.com) or by calling JAMS at
800-352-5267. A party who wishes to initiate arbitration must
provide the other party with a request for arbitration (the
"**Request**"). The Request must include: (1) the name, telephone
number, mailing address, e‐mail address of the party seeking
arbitration and the account username (if applicable) as well as the
email address associated with any applicable account; (2) a
statement of the legal claims being asserted and the factual bases
of those claims; (3) a description of the remedy sought and an
accurate, good‐faith calculation of the amount in controversy in
United States Dollars; (4) a statement certifying completion of the
Informal Dispute Resolution process as described above; and (5)
evidence that the requesting party has paid any necessary filing
fees in connection with such arbitration.
If the party requesting arbitration is represented by counsel, the
Request shall also include counsel's name, telephone number, mailing
address, and email address. Such counsel must also sign the Request.
By signing the Request, counsel certifies to the best of counsel's
knowledge, information, and belief, formed after an inquiry
reasonable under the circumstances, that: (1) the Request is not
being presented for any improper purpose, such as to harass, cause
unnecessary delay, or needlessly increase the cost of dispute
resolution; (2) the claims, defenses and other legal contentions are
warranted by existing law or by a nonfrivolous argument for
extending, modifying, or reversing existing law or for establishing
new law; and (3) the factual and damages contentions have
evidentiary support or, if specifically so identified, will likely
have evidentiary support after a reasonable opportunity for further
investigation or discovery.
Unless you and Company otherwise agree, or the Batch Arbitration
process discussed in Subsection 8.2(h) is triggered, the arbitration
will be conducted in the county where you reside. Subject to the
JAMS Rules, the arbitrator may direct a limited and reasonable
exchange of information between the parties, consistent with the
expedited nature of the arbitration. If the JAMS is not available to
arbitrate, the parties will select an alternative arbitral forum.
Your responsibility to pay any JAMS fees and costs will be solely as
set forth in the applicable JAMS Rules.
You and Company agree that all materials and documents exchanged
during the arbitration proceedings shall be kept confidential and
shall not be shared with anyone except the parties' attorneys,
accountants, or business advisors, and then subject to the condition
that they agree to keep all materials and documents exchanged during
the arbitration proceedings confidential.
(d) **Authority of Arbitrator.** The arbitrator shall have
exclusive authority to resolve all disputes subject to arbitration
hereunder including, without limitation, any dispute related to the
interpretation, applicability, enforceability or formation of this
Arbitration Agreement or any portion of the Arbitration Agreement,
except for the following: (1) all Disputes arising out of or
relating to the subsection entitled "Waiver of Class or Other
Non-Individualized Relief," including any claim that all or part of
the subsection entitled "Waiver of Class or Other Non-Individualized
Relief" is unenforceable, illegal, void or voidable, or that such
subsection entitled "Waiver of Class or Other Non-Individualized
Relief" has been breached, shall be decided by a court of competent
jurisdiction and not by an arbitrator; (2) except as expressly
contemplated in the subsection entitled "Batch Arbitration," all
Disputes about the payment of arbitration fees shall be decided only
by a court of competent jurisdiction and not by an arbitrator; (3)
all Disputes about whether either party has satisfied any condition
precedent to arbitration shall be decided only by a court of
competent jurisdiction and not by an arbitrator; and (4) all
Disputes about which version of the Arbitration Agreement applies
shall be decided only by a court of competent jurisdiction and not
by an arbitrator. The arbitration proceeding will not be
consolidated with any other matters or joined with any other cases
or parties, except as expressly provided in the subsection entitled
"Batch Arbitration." The arbitrator shall have the authority to
grant motions dispositive of all or part of any claim or dispute.
The arbitrator shall have the authority to award monetary damages
and to grant any non-monetary remedy or relief available to an
individual party under applicable law, the arbitral forum's rules,
and these Terms (including the Arbitration Agreement). The
arbitrator shall issue a written award and statement of decision
describing the essential findings and conclusions on which any award
(or decision not to render an award) is based, including the
calculation of any damages awarded. The arbitrator shall follow the
applicable law. The award of the arbitrator is final and binding
upon you and us. Judgment on the arbitration award may be entered in
any court having jurisdiction.
(e) **Waiver of Jury Trial.** EXCEPT AS SPECIFIED in
section 8.2(a) YOU AND THE COMPANY PARTIES HEREBY WAIVE ANY
CONSTITUTIONAL AND STATUTORY RIGHTS TO SUE IN COURT AND HAVE A TRIAL
IN FRONT OF A JUDGE OR A JURY. You and the Company Parties are
instead electing that all covered claims and disputes shall be
resolved exclusively by arbitration under this Arbitration
Agreement, except as specified in Section 8.2(a) above. An
arbitrator can award on an individual basis the same damages and
relief as a court and must follow these Terms as a court would.
However, there is no judge or jury in arbitration, and court review
of an arbitration award is subject to very limited review.
(f) **Waiver of Class or Other Non-Individualized
Relief.** YOU AND COMPANY AGREE THAT, EXCEPT AS
SPECIFIED IN SUBSECTION 8.2(h) EACH OF US MAY BRING CLAIMS AGAINST
THE OTHER ONLY ON AN INDIVIDUAL BASIS AND NOT ON A CLASS,
REPRESENTATIVE, OR COLLECTIVE BASIS, AND THE PARTIES HEREBY WAIVE
ALL RIGHTS TO HAVE ANY DISPUTE BE BROUGHT, HEARD, ADMINISTERED,
RESOLVED, OR ARBITRATED ON A CLASS, COLLECTIVE, REPRESENTATIVE, OR
MASS ACTION BASIS. ONLY INDIVIDUAL RELIEF IS AVAILABLE, AND DISPUTES
OF MORE THAN ONE CUSTOMER OR USER CANNOT BE ARBITRATED OR
CONSOLIDATED WITH THOSE OF ANY OTHER CUSTOMER OR USER. Subject to
this Arbitration Agreement, the arbitrator may award declaratory or
injunctive relief only in favor of the individual party seeking
relief and only to the extent necessary to provide relief warranted
by the party's individual claim. Nothing in this paragraph is
intended to, nor shall it, affect the terms and conditions under the
Subsection 8.2(h) entitled "Batch Arbitration." Notwithstanding
anything to the contrary in this Arbitration Agreement, if a court
decides by means of a final decision, not subject to any further
appeal or recourse, that the limitations of this subsection, "Waiver
of Class or Other Non-Individualized Relief," are invalid or
unenforceable as to a particular claim or request for relief (such
as a request for public injunctive relief), you and Company agree
that that particular claim or request for relief (and only that
particular claim or request for relief) shall be severed from the
arbitration and may be litigated in the state or federal courts
located in the State of California. All other Disputes shall be
arbitrated or litigated in small claims court. This subsection does
not prevent you or Company from participating in a class-wide
settlement of claims.
(g) **Attorneys' Fees and Costs.** The parties shall bear their own
attorneys' fees and costs in arbitration unless the arbitrator finds
that either the substance of the Dispute or the relief sought in the
Request was frivolous or was brought for an improper purpose (as
measured by the standards set forth in Federal Rule of Civil
Procedure 11(b)). If you or Company need to invoke the authority of
a court of competent jurisdiction to compel arbitration, then the
party that obtains an order compelling arbitration in such action
shall have the right to collect from the other party its reasonable
costs, necessary disbursements, and reasonable attorneys' fees
incurred in securing an order compelling arbitration. The prevailing
party in any court action relating to whether either party has
satisfied any condition precedent to arbitration, including the
Informal Dispute Resolution Process, is entitled to recover their
reasonable costs, necessary disbursements, and reasonable attorneys'
fees and costs.
(h) **Batch Arbitration.** To increase the efficiency of administration
and resolution of arbitrations, you and Company agree that in the
event that there are 100 or more individual Requests of a
substantially similar nature filed against Company by or with the
assistance of the same law firm, group of law firms, or
organizations, within a 30 day period (or as soon as possible
thereafter), the JAMS shall (1) administer the arbitration demands
in batches of 100 Requests per batch (plus, to the extent there are
less than 100 Requests left over after the batching described above,
a final batch consisting of the remaining Requests); (2) appoint one
arbitrator for each batch; and (3) provide for the resolution of
each batch as a single consolidated arbitration with one set of
filing and administrative fees due per side per batch, one
procedural calendar, one hearing (if any) in a place to be
determined by the arbitrator, and one final award ("**Batch
Arbitration**").
All parties agree that Requests are of a "substantially similar
nature" if they arise out of or relate to the same event or factual
scenario and raise the same or similar legal issues and seek the
same or similar relief. To the extent the parties disagree on the
application of the Batch Arbitration process, the disagreeing party
shall advise the JAMS, and the JAMS shall appoint a sole standing
arbitrator to determine the applicability of the Batch Arbitration
process ("**Administrative Arbitrator**"). In an effort to expedite
resolution of any such dispute by the Administrative Arbitrator, the
parties agree the Administrative Arbitrator may set forth such
procedures as are necessary to resolve any disputes promptly. The
Administrative Arbitrator's fees shall be paid by Company.
You and Company agree to cooperate in good faith with the JAMS to
implement the Batch Arbitration process including the payment of
single filing and administrative fees for batches of Requests, as
well as any steps to minimize the time and costs of arbitration,
which may include: (1) the appointment of a discovery special master
to assist the arbitrator in the resolution of discovery disputes;
and (2) the adoption of an expedited calendar of the arbitration
proceedings.
This Batch Arbitration provision shall in no way be interpreted as
authorizing a class, collective and/or mass arbitration or action of
any kind, or arbitration involving joint or consolidated claims
under any circumstances, except as expressly set forth in this
provision.
(i) **30-Day Right to Opt Out.** You have the right to opt out of the
provisions of this Arbitration Agreement by sending a timely written
notice of your decision to opt out to the following address:
2261 Market Street #5686, San Francisco, CA 94114, or email to [[email protected]](mailto:[email protected]),
within 30 days after first becoming subject to this Arbitration
Agreement. Your notice must include your name and address and a
clear statement that you want to opt out of this Arbitration
Agreement. If you opt out of this Arbitration Agreement, all other
parts of these Terms will continue to apply to you. Opting out of
this Arbitration Agreement has no effect on any other arbitration
agreements that you may currently have with us, or may enter into in
the future with us.
(j) **Invalidity, Expiration.** Except as provided in the subsection
entitled "Waiver of Class or Other Non-Individualized Relief", if
any part or parts of this Arbitration Agreement are found under the
law to be invalid or unenforceable, then such specific part or parts
shall be of no force and effect and shall be severed and the
remainder of the Arbitration Agreement shall continue in full force
and effect. You further agree that any Dispute that you have with
Company as detailed in this Arbitration Agreement must be initiated
via arbitration within the applicable statute of limitation for that
claim or controversy, or it will be forever time barred. Likewise,
you agree that all applicable statutes of limitation will apply to
such arbitration in the same manner as those statutes of limitation
would apply in the applicable court of competent jurisdiction.
(k)**Modification.** Notwithstanding any provision in
these Terms to the contrary, we agree that if Company makes any
future material change to this Arbitration Agreement, you may reject
that change within 30 days of such change becoming effective by
writing Company at the following address: 2261 Market Street #5686,
San Francisco, CA 94114, or email to [[email protected]](mailto:[email protected]). Unless you reject the
change within 30 days of such change becoming effective by writing
to Company in accordance with the foregoing, your continued use of
the Site and/or Services, including the acceptance of products and
services offered on the Site following the posting of changes to
this Arbitration Agreement constitutes your acceptance of any such
changes. Changes to this Arbitration Agreement do not provide you
with a new opportunity to opt out of the Arbitration Agreement if
you have previously agreed to a version of these Terms and did not
validly opt out of arbitration. If you reject any change or update
to this Arbitration Agreement, and you were bound by an existing
agreement to arbitrate Disputes arising out of or relating in any
way to your access to or use of the Services or of the Site, any
communications you receive, any products sold or distributed through
the Site, the Services, or these Terms, the provisions of this
Arbitration Agreement as of the date you first accepted these Terms
(or accepted any subsequent changes to these Terms) remain in full
force and effect. Company will continue to honor any valid opt outs
of the Arbitration Agreement that you made to a prior version of
these Terms.
8.3. **Export.** The Site may be subject to U.S. export control laws and
may be subject to export or import regulations in other countries.
You agree not to export, reexport, or transfer, directly or
indirectly, any U.S. technical data acquired from Company, or any
products utilizing such data, in violation of the United States
export laws or regulations.
8.4. **Disclosures.** Company is located at the address in Section 8.8.
If you are a California resident, you may report complaints to the
Complaint Assistance Unit of the Division of Consumer Product of the
California Department of Consumer Affairs by contacting them in
writing at 400 R Street, Sacramento, CA 95814, or by telephone
at (800) 952-5210.
9.5. **Electronic Communications.** The communications between you and
Company use electronic means, whether you use the Site or send us
emails, or whether Company posts notices on the Site or communicates
with you via email. For contractual purposes, you (a) consent to
receive communications from Company in an electronic form; and (b)
agree that all terms and conditions, agreements, notices,
disclosures, and other communications that Company provides to you
electronically satisfy any legal requirement that such
communications would satisfy if it were be in a hardcopy writing.
The foregoing does not affect your non-waivable rights.
8.6. **Entire Terms.** These Terms constitute the entire agreement
between you and us regarding the use of the Site. Our failure to
exercise or enforce any right or provision of these Terms shall not
operate as a waiver of such right or provision. The section titles
in these Terms are for convenience only and have no legal or
contractual effect. The word "including" means "including without
limitation". If any provision of these Terms is, for any reason,
held to be invalid or unenforceable, the other provisions of these
Terms will be unimpaired and the invalid or unenforceable provision
will be deemed modified so that it is valid and enforceable to the
maximum extent permitted by law. Your relationship to Company is
that of an independent contractor, and neither party is an agent or
partner of the other. These Terms, and your rights and obligations
herein, may not be assigned, subcontracted, delegated, or otherwise
transferred by you without Company's prior written consent, and any
attempted assignment, subcontract, delegation, or transfer in
violation of the foregoing will be null and void. Company may freely
assign these Terms. The terms and conditions set forth in these
Terms shall be binding upon assignees.
8.7. **Copyright/Trademark Information**. Copyright ©2024 Zep Software, Inc. All rights
reserved. All trademarks, logos and service marks ("**Marks**")
displayed on the Site are our property or the property of other
third parties. You are not permitted to use these Marks without our
prior written consent or the consent of such third party which may
own the Marks.
**Contact Information:**
Daniel Chalef
Address:
2261 Market Street
\#5686
San Francisco, CA 94114
# Add Session
```http
POST https://api.getzep.com/api/v2/sessions
Content-Type: application/json
```
Creates a new session.
## Response Body
- 201: The added session.
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl -X POST https://api.getzep.com/api/v2/sessions \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"session_id": "session_id",
"user_id": "user_id"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.add_session(
session_id="session_id",
user_id="user_id",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.addSession({
sessionId: "session_id",
userId: "user_id"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.AddSession(
context.TODO(),
&v2.CreateSessionRequest{
SessionID: "session_id",
UserID: "user_id",
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/sessions \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"session_id": "string",
"user_id": "string"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.add_session(
session_id="session_id",
user_id="user_id",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.addSession({
sessionId: "session_id",
userId: "user_id"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.AddSession(
context.TODO(),
&v2.CreateSessionRequest{
SessionID: "session_id",
UserID: "user_id",
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/sessions \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"session_id": "string",
"user_id": "string"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.add_session(
session_id="session_id",
user_id="user_id",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.addSession({
sessionId: "session_id",
userId: "user_id"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.AddSession(
context.TODO(),
&v2.CreateSessionRequest{
SessionID: "session_id",
UserID: "user_id",
},
)
```
# Get Session
```http
GET https://api.getzep.com/api/v2/sessions/{sessionId}
```
Returns a session.
## Path Parameters
- SessionId (required): The unique identifier of the session.
## Response Body
- 200: The session with the specified ID.
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/sessions/sessionId \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.get_session(
session_id="sessionId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.getSession("sessionId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.GetSession(
context.TODO(),
"sessionId",
)
```
```shell
curl https://api.getzep.com/api/v2/sessions/:sessionId \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.get_session(
session_id="sessionId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.getSession("sessionId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.GetSession(
context.TODO(),
"sessionId",
)
```
```shell
curl https://api.getzep.com/api/v2/sessions/:sessionId \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.get_session(
session_id="sessionId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.getSession("sessionId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.GetSession(
context.TODO(),
"sessionId",
)
```
# Get Sessions
```http
GET https://api.getzep.com/api/v2/sessions-ordered
```
Returns all sessions.
## Query Parameters
- PageNumber (optional): Page number for pagination, starting from 1
- PageSize (optional): Number of sessions to retrieve per page.
- OrderBy (optional): Field to order the results by: created_at, updated_at, user_id, session_id.
- Asc (optional): Order direction: true for ascending, false for descending.
## Response Body
- 200: List of sessions
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/sessions-ordered \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.list_sessions()
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.listSessions();
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.ListSessions(
context.TODO(),
&v2.MemoryListSessionsRequest{},
)
```
```shell
curl -G https://api.getzep.com/api/v2/sessions-ordered \
-H "Authorization: Api-Key " \
-d page_number=0 \
-d page_size=0
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.list_sessions()
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.listSessions();
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.ListSessions(
context.TODO(),
&v2.MemoryListSessionsRequest{},
)
```
```shell
curl -G https://api.getzep.com/api/v2/sessions-ordered \
-H "Authorization: Api-Key " \
-d page_number=0 \
-d page_size=0
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.list_sessions()
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.listSessions();
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.ListSessions(
context.TODO(),
&v2.MemoryListSessionsRequest{},
)
```
# Get Session Memory
```http
GET https://api.getzep.com/api/v2/sessions/{sessionId}/memory
```
Returns a memory for a given session.
## Path Parameters
- SessionId (required): The ID of the session for which to retrieve memory.
## Query Parameters
- Lastn (optional): The number of most recent memory entries to retrieve.
- MinRating (optional): The minimum rating by which to filter relevant facts.
## Response Body
- 200: OK
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/sessions/sessionId/memory \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.get(
session_id="sessionId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.get("sessionId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.Get(
context.TODO(),
"sessionId",
&v2.MemoryGetRequest{},
)
```
```shell
curl -G https://api.getzep.com/api/v2/sessions/:sessionId/memory \
-H "Authorization: Api-Key " \
-d lastn=0 \
-d minRating=1
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.get(
session_id="sessionId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.get("sessionId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.Get(
context.TODO(),
"sessionId",
&v2.MemoryGetRequest{},
)
```
```shell
curl -G https://api.getzep.com/api/v2/sessions/:sessionId/memory \
-H "Authorization: Api-Key " \
-d lastn=0 \
-d minRating=1
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.get(
session_id="sessionId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.get("sessionId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.Get(
context.TODO(),
"sessionId",
&v2.MemoryGetRequest{},
)
```
# Get Messages for Session
```http
GET https://api.getzep.com/api/v2/sessions/{sessionId}/messages
```
Returns messages for a session.
## Path Parameters
- SessionId (required): Session ID
## Query Parameters
- Limit (optional): Limit the number of results returned
- Cursor (optional): Cursor for pagination
## Response Body
- 200: OK
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/sessions/sessionId/messages
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.get_session_messages(
session_id="sessionId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.getSessionMessages("sessionId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.GetSessionMessages(
context.TODO(),
"sessionId",
&v2.MemoryGetSessionMessagesRequest{},
)
```
```shell
curl -G https://api.getzep.com/api/v2/sessions/:sessionId/messages \
-d limit=0 \
-d cursor=0
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.get_session_messages(
session_id="sessionId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.getSessionMessages("sessionId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.GetSessionMessages(
context.TODO(),
"sessionId",
&v2.MemoryGetSessionMessagesRequest{},
)
```
```shell
curl -G https://api.getzep.com/api/v2/sessions/:sessionId/messages \
-d limit=0 \
-d cursor=0
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.get_session_messages(
session_id="sessionId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.getSessionMessages("sessionId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.GetSessionMessages(
context.TODO(),
"sessionId",
&v2.MemoryGetSessionMessagesRequest{},
)
```
# Get Message
```http
GET https://api.getzep.com/api/v2/sessions/{sessionId}/messages/{messageUUID}
```
Deprecated: Use graph.episodes.get instead. Returns a specific message from a session.
## Path Parameters
- SessionId (required): Soon to be deprecated as this is not needed.
- MessageUuid (required): The UUID of the message.
## Response Body
- 200: The message.
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/sessions/sessionId/messages/messageUUID
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.get_session_message(
session_id="sessionId",
message_uuid="messageUUID",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.getSessionMessage("sessionId", "messageUUID");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.GetSessionMessage(
context.TODO(),
"sessionId",
"messageUUID",
)
```
```shell
curl https://api.getzep.com/api/v2/sessions/:sessionId/messages/:messageUUID
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.get_session_message(
session_id="sessionId",
message_uuid="messageUUID",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.getSessionMessage("sessionId", "messageUUID");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.GetSessionMessage(
context.TODO(),
"sessionId",
"messageUUID",
)
```
```shell
curl https://api.getzep.com/api/v2/sessions/:sessionId/messages/:messageUUID
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.get_session_message(
session_id="sessionId",
message_uuid="messageUUID",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.getSessionMessage("sessionId", "messageUUID");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.GetSessionMessage(
context.TODO(),
"sessionId",
"messageUUID",
)
```
# Classify Session
```http
POST https://api.getzep.com/api/v2/sessions/{sessionId}/classify
Content-Type: application/json
```
Classifies a session.
## Path Parameters
- SessionId (required): Session ID
## Response Body
- 200: A response object containing the name and classification result.
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl -X POST https://api.getzep.com/api/v2/sessions/sessionId/classify \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"classes": [
"classes"
],
"name": "name"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.classify_session(
session_id="sessionId",
classes=["classes"],
name="name",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.classifySession("sessionId", {
classes: ["classes"],
name: "name"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.ClassifySession(
context.TODO(),
"sessionId",
&v2.ClassifySessionRequest{
Classes: []string{
"classes",
},
Name: "name",
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/sessions/:sessionId/classify \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"classes": [
"string"
],
"name": "string"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.classify_session(
session_id="sessionId",
classes=["classes"],
name="name",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.classifySession("sessionId", {
classes: ["classes"],
name: "name"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.ClassifySession(
context.TODO(),
"sessionId",
&v2.ClassifySessionRequest{
Classes: []string{
"classes",
},
Name: "name",
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/sessions/:sessionId/classify \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"classes": [
"string"
],
"name": "string"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.classify_session(
session_id="sessionId",
classes=["classes"],
name="name",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.classifySession("sessionId", {
classes: ["classes"],
name: "name"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.ClassifySession(
context.TODO(),
"sessionId",
&v2.ClassifySessionRequest{
Classes: []string{
"classes",
},
Name: "name",
},
)
```
# Add Memory to Session
```http
POST https://api.getzep.com/api/v2/sessions/{sessionId}/memory
Content-Type: application/json
```
Add memory to the specified session.
## Path Parameters
- SessionId (required): The ID of the session to which memory should be added.
## Response Body
- 200: An object, optionally containing memory context retrieved for the last message
- 500: Internal Server Error
## Examples
```shell
curl -X POST https://api.getzep.com/api/v2/sessions/sessionId/memory \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"messages": [
{
"content": "content",
"role_type": "norole"
}
]
}'
```
```python
from zep_cloud import Message
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.add(
session_id="sessionId",
messages=[
Message(
content="content",
role_type="norole",
)
],
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.add("sessionId", {
messages: [{
content: "content",
roleType: "norole"
}]
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.Add(
context.TODO(),
"sessionId",
&v2.AddMemoryRequest{
Messages: []*v2.Message{
&v2.Message{
Content: "content",
RoleType: v2.RoleTypeNoRole,
},
},
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/sessions/:sessionId/memory \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"messages": [
{
"content": "string",
"role_type": "norole"
}
]
}'
```
```python
from zep_cloud import Message
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.add(
session_id="sessionId",
messages=[
Message(
content="content",
role_type="norole",
)
],
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.add("sessionId", {
messages: [{
content: "content",
roleType: "norole"
}]
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.Add(
context.TODO(),
"sessionId",
&v2.AddMemoryRequest{
Messages: []*v2.Message{
&v2.Message{
Content: "content",
RoleType: v2.RoleTypeNoRole,
},
},
},
)
```
# Delete Session
```http
DELETE https://api.getzep.com/api/v2/sessions/{sessionId}/memory
```
Deletes a session.
## Path Parameters
- SessionId (required): The ID of the session for which memory should be deleted.
## Response Body
- 200: OK
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl -X DELETE https://api.getzep.com/api/v2/sessions/sessionId/memory \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.delete(
session_id="sessionId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.delete("sessionId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.Delete(
context.TODO(),
"sessionId",
)
```
```shell
curl -X DELETE https://api.getzep.com/api/v2/sessions/:sessionId/memory \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.delete(
session_id="sessionId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.delete("sessionId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.Delete(
context.TODO(),
"sessionId",
)
```
```shell
curl -X DELETE https://api.getzep.com/api/v2/sessions/:sessionId/memory \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.delete(
session_id="sessionId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.delete("sessionId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.Delete(
context.TODO(),
"sessionId",
)
```
# Add User
```http
POST https://api.getzep.com/api/v2/users
Content-Type: application/json
```
Adds a user.
## Response Body
- 201: The user that was added.
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl -X POST https://api.getzep.com/api/v2/users \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"user_id": "user_id"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.user.add(
user_id="user_id",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.user.add({
userId: "user_id"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.User.Add(
context.TODO(),
&v2.CreateUserRequest{
UserID: "user_id",
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/users \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"user_id": "string"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.user.add(
user_id="user_id",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.user.add({
userId: "user_id"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.User.Add(
context.TODO(),
&v2.CreateUserRequest{
UserID: "user_id",
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/users \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"user_id": "string"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.user.add(
user_id="user_id",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.user.add({
userId: "user_id"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.User.Add(
context.TODO(),
&v2.CreateUserRequest{
UserID: "user_id",
},
)
```
# Get Users
```http
GET https://api.getzep.com/api/v2/users-ordered
```
Returns all users.
## Query Parameters
- PageNumber (optional): Page number for pagination, starting from 1
- PageSize (optional): Number of users to retrieve per page
## Response Body
- 200: Successfully retrieved list of users
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/users-ordered \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.user.list_ordered()
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.user.listOrdered();
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.User.ListOrdered(
context.TODO(),
&v2.UserListOrderedRequest{},
)
```
```shell
curl -G https://api.getzep.com/api/v2/users-ordered \
-H "Authorization: Api-Key " \
-d pageNumber=0 \
-d pageSize=0
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.user.list_ordered()
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.user.listOrdered();
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.User.ListOrdered(
context.TODO(),
&v2.UserListOrderedRequest{},
)
```
```shell
curl -G https://api.getzep.com/api/v2/users-ordered \
-H "Authorization: Api-Key " \
-d pageNumber=0 \
-d pageSize=0
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.user.list_ordered()
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.user.listOrdered();
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.User.ListOrdered(
context.TODO(),
&v2.UserListOrderedRequest{},
)
```
# Get User
```http
GET https://api.getzep.com/api/v2/users/{userId}
```
Returns a user.
## Path Parameters
- UserId (required): The user_id of the user to get.
## Response Body
- 200: The user that was retrieved.
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/users/userId \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.user.get(
user_id="userId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.user.get("userId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.User.Get(
context.TODO(),
"userId",
)
```
```shell
curl https://api.getzep.com/api/v2/users/:userId \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.user.get(
user_id="userId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.user.get("userId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.User.Get(
context.TODO(),
"userId",
)
```
```shell
curl https://api.getzep.com/api/v2/users/:userId \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.user.get(
user_id="userId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.user.get("userId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.User.Get(
context.TODO(),
"userId",
)
```
# Delete User
```http
DELETE https://api.getzep.com/api/v2/users/{userId}
```
Deletes a user.
## Path Parameters
- UserId (required): User ID
## Response Body
- 200: OK
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl -X DELETE https://api.getzep.com/api/v2/users/userId \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.user.delete(
user_id="userId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.user.delete("userId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.User.Delete(
context.TODO(),
"userId",
)
```
```shell
curl -X DELETE https://api.getzep.com/api/v2/users/:userId \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.user.delete(
user_id="userId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.user.delete("userId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.User.Delete(
context.TODO(),
"userId",
)
```
```shell
curl -X DELETE https://api.getzep.com/api/v2/users/:userId \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.user.delete(
user_id="userId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.user.delete("userId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.User.Delete(
context.TODO(),
"userId",
)
```
# Update User
```http
PATCH https://api.getzep.com/api/v2/users/{userId}
Content-Type: application/json
```
Updates a user.
## Path Parameters
- UserId (required): User ID
## Response Body
- 200: The user that was updated.
- 400: Bad Request
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl -X PATCH https://api.getzep.com/api/v2/users/userId \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.user.update(
user_id="userId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.user.update("userId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.User.Update(
context.TODO(),
"userId",
&v2.UpdateUserRequest{},
)
```
```shell
curl -X PATCH https://api.getzep.com/api/v2/users/:userId \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.user.update(
user_id="userId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.user.update("userId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.User.Update(
context.TODO(),
"userId",
&v2.UpdateUserRequest{},
)
```
```shell
curl -X PATCH https://api.getzep.com/api/v2/users/:userId \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.user.update(
user_id="userId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.user.update("userId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.User.Update(
context.TODO(),
"userId",
&v2.UpdateUserRequest{},
)
```
```shell
curl -X PATCH https://api.getzep.com/api/v2/users/:userId \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.user.update(
user_id="userId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.user.update("userId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.User.Update(
context.TODO(),
"userId",
&v2.UpdateUserRequest{},
)
```
# Get User Node
```http
GET https://api.getzep.com/api/v2/users/{userId}/node
```
Returns a user's node.
## Path Parameters
- UserId (required): The user_id of the user to get the node for.
## Response Body
- 200: Response object containing the User node.
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/users/userId/node \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.user.get_node(
user_id="userId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.user.getNode("userId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.User.GetNode(
context.TODO(),
"userId",
)
```
```shell
curl https://api.getzep.com/api/v2/users/:userId/node \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.user.get_node(
user_id="userId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.user.getNode("userId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.User.GetNode(
context.TODO(),
"userId",
)
```
```shell
curl https://api.getzep.com/api/v2/users/:userId/node \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.user.get_node(
user_id="userId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.user.getNode("userId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.User.GetNode(
context.TODO(),
"userId",
)
```
# Get User Sessions
```http
GET https://api.getzep.com/api/v2/users/{userId}/sessions
```
Returns all sessions for a user.
## Path Parameters
- UserId (required): User ID
## Response Body
- 200: OK
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/users/userId/sessions \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.user.get_sessions(
user_id="userId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.user.getSessions("userId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.User.GetSessions(
context.TODO(),
"userId",
)
```
```shell
curl https://api.getzep.com/api/v2/users/:userId/sessions \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.user.get_sessions(
user_id="userId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.user.getSessions("userId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.User.GetSessions(
context.TODO(),
"userId",
)
```
# Create Group
```http
POST https://api.getzep.com/api/v2/groups
Content-Type: application/json
```
Creates a new group.
## Response Body
- 201: The added group
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl -X POST https://api.getzep.com/api/v2/groups \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"group_id": "group_id"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.group.add(
group_id="group_id",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.group.add({
groupId: "group_id"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Group.Add(
context.TODO(),
&v2.CreateGroupRequest{
GroupID: "group_id",
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/groups \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"group_id": "string"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.group.add(
group_id="group_id",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.group.add({
groupId: "group_id"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Group.Add(
context.TODO(),
&v2.CreateGroupRequest{
GroupID: "group_id",
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/groups \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"group_id": "string"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.group.add(
group_id="group_id",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.group.add({
groupId: "group_id"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Group.Add(
context.TODO(),
&v2.CreateGroupRequest{
GroupID: "group_id",
},
)
```
# Get All Groups
```http
GET https://api.getzep.com/api/v2/groups-ordered
```
Returns all groups.
## Query Parameters
- PageNumber (optional): Page number for pagination, starting from 1.
- PageSize (optional): Number of groups to retrieve per page.
## Response Body
- 200: Successfully retrieved list of groups.
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/groups-ordered \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.group.get_all_groups()
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.group.getAllGroups();
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Group.GetAllGroups(
context.TODO(),
&v2.GetGroupsOrderedRequest{},
)
```
```shell
curl -G https://api.getzep.com/api/v2/groups-ordered \
-H "Authorization: Api-Key " \
-d pageNumber=0 \
-d pageSize=0
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.group.get_all_groups()
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.group.getAllGroups();
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Group.GetAllGroups(
context.TODO(),
&v2.GetGroupsOrderedRequest{},
)
```
```shell
curl -G https://api.getzep.com/api/v2/groups-ordered \
-H "Authorization: Api-Key " \
-d pageNumber=0 \
-d pageSize=0
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.group.get_all_groups()
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.group.getAllGroups();
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Group.GetAllGroups(
context.TODO(),
&v2.GetGroupsOrderedRequest{},
)
```
# Get Group
```http
GET https://api.getzep.com/api/v2/groups/{groupId}
```
Returns a group.
## Path Parameters
- GroupId (required): The group_id of the group to get.
## Response Body
- 200: The group that was retrieved.
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/groups/groupId \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.group.get_group(
group_id="groupId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.group.getGroup("groupId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Group.GetGroup(
context.TODO(),
"groupId",
)
```
```shell
curl https://api.getzep.com/api/v2/groups/:groupId \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.group.get_group(
group_id="groupId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.group.getGroup("groupId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Group.GetGroup(
context.TODO(),
"groupId",
)
```
```shell
curl https://api.getzep.com/api/v2/groups/:groupId \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.group.get_group(
group_id="groupId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.group.getGroup("groupId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Group.GetGroup(
context.TODO(),
"groupId",
)
```
# Delete Group
```http
DELETE https://api.getzep.com/api/v2/groups/{groupId}
```
Deletes a group.
## Path Parameters
- GroupId (required): Group ID
## Response Body
- 200: Deleted
- 400: Bad Request
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl -X DELETE https://api.getzep.com/api/v2/groups/groupId \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.group.delete(
group_id="groupId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.group.delete("groupId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Group.Delete(
context.TODO(),
"groupId",
)
```
```shell
curl -X DELETE https://api.getzep.com/api/v2/groups/:groupId \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.group.delete(
group_id="groupId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.group.delete("groupId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Group.Delete(
context.TODO(),
"groupId",
)
```
```shell
curl -X DELETE https://api.getzep.com/api/v2/groups/:groupId \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.group.delete(
group_id="groupId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.group.delete("groupId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Group.Delete(
context.TODO(),
"groupId",
)
```
```shell
curl -X DELETE https://api.getzep.com/api/v2/groups/:groupId \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.group.delete(
group_id="groupId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.group.delete("groupId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Group.Delete(
context.TODO(),
"groupId",
)
```
# Update Group
```http
PATCH https://api.getzep.com/api/v2/groups/{groupId}
Content-Type: application/json
```
Updates information about a group.
## Path Parameters
- GroupId (required): Group ID
## Response Body
- 201: The added group
- 400: Bad Request
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl -X PATCH https://api.getzep.com/api/v2/groups/groupId \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.group.update(
group_id="groupId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.group.update("groupId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Group.Update(
context.TODO(),
"groupId",
&v2.UpdateGroupRequest{},
)
```
```shell
curl -X PATCH https://api.getzep.com/api/v2/groups/:groupId \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.group.update(
group_id="groupId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.group.update("groupId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Group.Update(
context.TODO(),
"groupId",
&v2.UpdateGroupRequest{},
)
```
```shell
curl -X PATCH https://api.getzep.com/api/v2/groups/:groupId \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.group.update(
group_id="groupId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.group.update("groupId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Group.Update(
context.TODO(),
"groupId",
&v2.UpdateGroupRequest{},
)
```
```shell
curl -X PATCH https://api.getzep.com/api/v2/groups/:groupId \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.group.update(
group_id="groupId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.group.update("groupId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Group.Update(
context.TODO(),
"groupId",
&v2.UpdateGroupRequest{},
)
```
# Get Entity Types
```http
GET https://api.getzep.com/api/v2/entity-types
```
Returns all entity types for a project.
## Response Body
- 200: The list of entity types.
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/entity-types \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.list_entity_types()
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.listEntityTypes();
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.ListEntityTypes(
context.TODO(),
)
```
```shell
curl https://api.getzep.com/api/v2/entity-types \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.list_entity_types()
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.listEntityTypes();
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.ListEntityTypes(
context.TODO(),
)
```
```shell
curl https://api.getzep.com/api/v2/entity-types \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.list_entity_types()
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.listEntityTypes();
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.ListEntityTypes(
context.TODO(),
)
```
# Set Entity Types
```http
PUT https://api.getzep.com/api/v2/entity-types
Content-Type: application/json
```
Sets the entity types for a project, replacing any existing ones.
## Response Body
- 200: Entity types set successfully
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl -X PUT https://api.getzep.com/api/v2/entity-types \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.set_entity_types_internal()
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.setEntityTypesInternal();
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.SetEntityTypesInternal(
context.TODO(),
&v2.EntityTypeRequest{},
)
```
```shell
curl -X PUT https://api.getzep.com/api/v2/entity-types \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.set_entity_types_internal()
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.setEntityTypesInternal();
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.SetEntityTypesInternal(
context.TODO(),
&v2.EntityTypeRequest{},
)
```
```shell
curl -X PUT https://api.getzep.com/api/v2/entity-types \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.set_entity_types_internal()
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.setEntityTypesInternal();
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.SetEntityTypesInternal(
context.TODO(),
&v2.EntityTypeRequest{},
)
```
# Add Data
```http
POST https://api.getzep.com/api/v2/graph
Content-Type: application/json
```
Add data to the graph.
## Response Body
- 202: Added episode
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl -X POST https://api.getzep.com/api/v2/graph \
-H "Content-Type: application/json" \
-d '{
"data": "data",
"type": "text"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.add(
data="data",
type="text",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.add({
data: "data",
type: "text"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Add(
context.TODO(),
&v2.AddDataRequest{
Data: "data",
Type: v2.GraphDataTypeText,
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/graph \
-H "Content-Type: application/json" \
-d '{
"data": "string",
"type": "text"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.add(
data="data",
type="text",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.add({
data: "data",
type: "text"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Add(
context.TODO(),
&v2.AddDataRequest{
Data: "data",
Type: v2.GraphDataTypeText,
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/graph \
-H "Content-Type: application/json" \
-d '{
"data": "string",
"type": "text"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.add(
data="data",
type="text",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.add({
data: "data",
type: "text"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Add(
context.TODO(),
&v2.AddDataRequest{
Data: "data",
Type: v2.GraphDataTypeText,
},
)
```
# Add Data in batch mode
```http
POST https://api.getzep.com/api/v2/graph-batch
Content-Type: application/json
```
Add data to the graph in batch mode, processing episodes concurrently. Use only for data that is insensitive to processing order.
## Response Body
- 202: Added episodes
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl -X POST https://api.getzep.com/api/v2/graph-batch \
-H "Content-Type: application/json" \
-d '{
"episodes": [
{
"data": "data",
"type": "text"
}
]
}'
```
```python
from zep_cloud import EpisodeData
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.add_batch(
episodes=[
EpisodeData(
data="data",
type="text",
)
],
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.addBatch({
episodes: [{
data: "data",
type: "text"
}]
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.AddBatch(
context.TODO(),
&v2.AddDataBatchRequest{
Episodes: []*v2.EpisodeData{
&v2.EpisodeData{
Data: "data",
Type: v2.GraphDataTypeText,
},
},
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/graph-batch \
-H "Content-Type: application/json" \
-d '{
"episodes": [
{
"data": "string",
"type": "text"
}
]
}'
```
```python
from zep_cloud import EpisodeData
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.add_batch(
episodes=[
EpisodeData(
data="data",
type="text",
)
],
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.addBatch({
episodes: [{
data: "data",
type: "text"
}]
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.AddBatch(
context.TODO(),
&v2.AddDataBatchRequest{
Episodes: []*v2.EpisodeData{
&v2.EpisodeData{
Data: "data",
Type: v2.GraphDataTypeText,
},
},
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/graph-batch \
-H "Content-Type: application/json" \
-d '{
"episodes": [
{
"data": "string",
"type": "text"
}
]
}'
```
```python
from zep_cloud import EpisodeData
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.add_batch(
episodes=[
EpisodeData(
data="data",
type="text",
)
],
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.addBatch({
episodes: [{
data: "data",
type: "text"
}]
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.AddBatch(
context.TODO(),
&v2.AddDataBatchRequest{
Episodes: []*v2.EpisodeData{
&v2.EpisodeData{
Data: "data",
Type: v2.GraphDataTypeText,
},
},
},
)
```
# Add Fact Triple
```http
POST https://api.getzep.com/api/v2/graph/add-fact-triple
Content-Type: application/json
```
Add a fact triple for a user or group
## Response Body
- 200: Resulting triple
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl -X POST https://api.getzep.com/api/v2/graph/add-fact-triple \
-H "Content-Type: application/json" \
-d '{
"fact": "fact",
"fact_name": "fact_name",
"target_node_name": "target_node_name"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.add_fact_triple(
fact="fact",
fact_name="fact_name",
target_node_name="target_node_name",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.addFactTriple({
fact: "fact",
factName: "fact_name",
targetNodeName: "target_node_name"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.AddFactTriple(
context.TODO(),
&v2.AddTripleRequest{
Fact: "fact",
FactName: "fact_name",
TargetNodeName: "target_node_name",
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/graph/add-fact-triple \
-H "Content-Type: application/json" \
-d '{
"fact": "string",
"fact_name": "string",
"target_node_name": "string"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.add_fact_triple(
fact="fact",
fact_name="fact_name",
target_node_name="target_node_name",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.addFactTriple({
fact: "fact",
factName: "fact_name",
targetNodeName: "target_node_name"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.AddFactTriple(
context.TODO(),
&v2.AddTripleRequest{
Fact: "fact",
FactName: "fact_name",
TargetNodeName: "target_node_name",
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/graph/add-fact-triple \
-H "Content-Type: application/json" \
-d '{
"fact": "string",
"fact_name": "string",
"target_node_name": "string"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.add_fact_triple(
fact="fact",
fact_name="fact_name",
target_node_name="target_node_name",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.addFactTriple({
fact: "fact",
factName: "fact_name",
targetNodeName: "target_node_name"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.AddFactTriple(
context.TODO(),
&v2.AddTripleRequest{
Fact: "fact",
FactName: "fact_name",
TargetNodeName: "target_node_name",
},
)
```
# Search Graph
```http
POST https://api.getzep.com/api/v2/graph/search
Content-Type: application/json
```
Perform a graph search query.
## Response Body
- 200: Graph search results
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl -X POST https://api.getzep.com/api/v2/graph/search \
-H "Content-Type: application/json" \
-d '{
"query": "query"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.search(
query="query",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.search({
query: "query"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Search(
context.TODO(),
&v2.GraphSearchQuery{
Query: "query",
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/graph/search \
-H "Content-Type: application/json" \
-d '{
"query": "string"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.search(
query="query",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.search({
query: "query"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Search(
context.TODO(),
&v2.GraphSearchQuery{
Query: "query",
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/graph/search \
-H "Content-Type: application/json" \
-d '{
"query": "string"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.search(
query="query",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.search({
query: "query"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Search(
context.TODO(),
&v2.GraphSearchQuery{
Query: "query",
},
)
```
# Get Group Edges
```http
POST https://api.getzep.com/api/v2/graph/edge/group/{group_id}
Content-Type: application/json
```
Returns all edges for a group.
## Path Parameters
- GroupId (required): Group ID
## Response Body
- 200: Edges
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl -X POST https://api.getzep.com/api/v2/graph/edge/group/group_id \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.edge.get_by_group_id(
group_id="group_id",
)
```
```typescript
import { ZepClient, Zep } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.edge.getByGroupId("group_id", {});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Edge.GetByGroupID(
context.TODO(),
"group_id",
&v2.GraphEdgesRequest{},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/graph/edge/group/:group_id \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.edge.get_by_group_id(
group_id="group_id",
)
```
```typescript
import { ZepClient, Zep } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.edge.getByGroupId("group_id", {});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Edge.GetByGroupID(
context.TODO(),
"group_id",
&v2.GraphEdgesRequest{},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/graph/edge/group/:group_id \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.edge.get_by_group_id(
group_id="group_id",
)
```
```typescript
import { ZepClient, Zep } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.edge.getByGroupId("group_id", {});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Edge.GetByGroupID(
context.TODO(),
"group_id",
&v2.GraphEdgesRequest{},
)
```
# Get User Edges
```http
POST https://api.getzep.com/api/v2/graph/edge/user/{user_id}
Content-Type: application/json
```
Returns all edges for a user.
## Path Parameters
- UserId (required): User ID
## Response Body
- 200: Edges
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl -X POST https://api.getzep.com/api/v2/graph/edge/user/user_id \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.edge.get_by_user_id(
user_id="user_id",
)
```
```typescript
import { ZepClient, Zep } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.edge.getByUserId("user_id", {});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Edge.GetByUserID(
context.TODO(),
"user_id",
&v2.GraphEdgesRequest{},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/graph/edge/user/:user_id \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.edge.get_by_user_id(
user_id="user_id",
)
```
```typescript
import { ZepClient, Zep } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.edge.getByUserId("user_id", {});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Edge.GetByUserID(
context.TODO(),
"user_id",
&v2.GraphEdgesRequest{},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/graph/edge/user/:user_id \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.edge.get_by_user_id(
user_id="user_id",
)
```
```typescript
import { ZepClient, Zep } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.edge.getByUserId("user_id", {});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Edge.GetByUserID(
context.TODO(),
"user_id",
&v2.GraphEdgesRequest{},
)
```
# Get Edge
```http
GET https://api.getzep.com/api/v2/graph/edge/{uuid}
```
Returns a specific edge by its UUID.
## Path Parameters
- Uuid (required): Edge UUID
## Response Body
- 200: Edge
- 400: Bad Request
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/graph/edge/uuid
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.edge.get(
uuid_="uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.edge.get("uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Edge.Get(
context.TODO(),
"uuid",
)
```
```shell
curl https://api.getzep.com/api/v2/graph/edge/:uuid
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.edge.get(
uuid_="uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.edge.get("uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Edge.Get(
context.TODO(),
"uuid",
)
```
```shell
curl https://api.getzep.com/api/v2/graph/edge/:uuid
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.edge.get(
uuid_="uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.edge.get("uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Edge.Get(
context.TODO(),
"uuid",
)
```
```shell
curl https://api.getzep.com/api/v2/graph/edge/:uuid
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.edge.get(
uuid_="uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.edge.get("uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Edge.Get(
context.TODO(),
"uuid",
)
```
# Delete Edge
```http
DELETE https://api.getzep.com/api/v2/graph/edge/{uuid}
```
Deletes an edge by UUID.
## Path Parameters
- Uuid (required): Edge UUID
## Response Body
- 200: Edge deleted
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl -X DELETE https://api.getzep.com/api/v2/graph/edge/uuid
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.edge.delete(
uuid_="uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.edge.delete("uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Edge.Delete(
context.TODO(),
"uuid",
)
```
```shell
curl -X DELETE https://api.getzep.com/api/v2/graph/edge/:uuid
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.edge.delete(
uuid_="uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.edge.delete("uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Edge.Delete(
context.TODO(),
"uuid",
)
```
```shell
curl -X DELETE https://api.getzep.com/api/v2/graph/edge/:uuid
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.edge.delete(
uuid_="uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.edge.delete("uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Edge.Delete(
context.TODO(),
"uuid",
)
```
# Get Group Episodes
```http
GET https://api.getzep.com/api/v2/graph/episodes/group/{group_id}
```
Returns episodes by group id.
## Path Parameters
- GroupId (required): Group ID
## Query Parameters
- Lastn (optional): The number of most recent episodes to retrieve.
## Response Body
- 200: Episodes
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/graph/episodes/group/group_id
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.episode.get_by_group_id(
group_id="group_id",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.episode.getByGroupId("group_id");
```
```go
import (
context "context"
graph "github.com/getzep/zep-go/v2/graph"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Episode.GetByGroupID(
context.TODO(),
"group_id",
&graph.EpisodeGetByGroupIDRequest{},
)
```
```shell
curl -G https://api.getzep.com/api/v2/graph/episodes/group/:group_id \
-d lastn=0
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.episode.get_by_group_id(
group_id="group_id",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.episode.getByGroupId("group_id");
```
```go
import (
context "context"
graph "github.com/getzep/zep-go/v2/graph"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Episode.GetByGroupID(
context.TODO(),
"group_id",
&graph.EpisodeGetByGroupIDRequest{},
)
```
```shell
curl -G https://api.getzep.com/api/v2/graph/episodes/group/:group_id \
-d lastn=0
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.episode.get_by_group_id(
group_id="group_id",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.episode.getByGroupId("group_id");
```
```go
import (
context "context"
graph "github.com/getzep/zep-go/v2/graph"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Episode.GetByGroupID(
context.TODO(),
"group_id",
&graph.EpisodeGetByGroupIDRequest{},
)
```
# Get User Episodes
```http
GET https://api.getzep.com/api/v2/graph/episodes/user/{user_id}
```
Returns episodes by user id.
## Path Parameters
- UserId (required): User ID
## Query Parameters
- Lastn (optional): The number of most recent episodes entries to retrieve.
## Response Body
- 200: Episodes
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/graph/episodes/user/user_id
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.episode.get_by_user_id(
user_id="user_id",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.episode.getByUserId("user_id");
```
```go
import (
context "context"
graph "github.com/getzep/zep-go/v2/graph"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Episode.GetByUserID(
context.TODO(),
"user_id",
&graph.EpisodeGetByUserIDRequest{},
)
```
```shell
curl -G https://api.getzep.com/api/v2/graph/episodes/user/:user_id \
-d lastn=0
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.episode.get_by_user_id(
user_id="user_id",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.episode.getByUserId("user_id");
```
```go
import (
context "context"
graph "github.com/getzep/zep-go/v2/graph"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Episode.GetByUserID(
context.TODO(),
"user_id",
&graph.EpisodeGetByUserIDRequest{},
)
```
```shell
curl -G https://api.getzep.com/api/v2/graph/episodes/user/:user_id \
-d lastn=0
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.episode.get_by_user_id(
user_id="user_id",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.episode.getByUserId("user_id");
```
```go
import (
context "context"
graph "github.com/getzep/zep-go/v2/graph"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Episode.GetByUserID(
context.TODO(),
"user_id",
&graph.EpisodeGetByUserIDRequest{},
)
```
# Get Episode
```http
GET https://api.getzep.com/api/v2/graph/episodes/{uuid}
```
Returns episodes by UUID
## Path Parameters
- Uuid (required): Episode UUID
## Response Body
- 200: Episode
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/graph/episodes/uuid
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.episode.get(
uuid_="uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.episode.get("uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Episode.Get(
context.TODO(),
"uuid",
)
```
```shell
curl https://api.getzep.com/api/v2/graph/episodes/:uuid
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.episode.get(
uuid_="uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.episode.get("uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Episode.Get(
context.TODO(),
"uuid",
)
```
```shell
curl https://api.getzep.com/api/v2/graph/episodes/:uuid
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.episode.get(
uuid_="uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.episode.get("uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Episode.Get(
context.TODO(),
"uuid",
)
```
# Delete Episode
```http
DELETE https://api.getzep.com/api/v2/graph/episodes/{uuid}
```
Deletes an episode by its UUID.
## Path Parameters
- Uuid (required): Episode UUID
## Response Body
- 200: Episode deleted
- 400: Bad Request
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl -X DELETE https://api.getzep.com/api/v2/graph/episodes/uuid
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.episode.delete(
uuid_="uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.episode.delete("uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Episode.Delete(
context.TODO(),
"uuid",
)
```
```shell
curl -X DELETE https://api.getzep.com/api/v2/graph/episodes/:uuid
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.episode.delete(
uuid_="uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.episode.delete("uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Episode.Delete(
context.TODO(),
"uuid",
)
```
```shell
curl -X DELETE https://api.getzep.com/api/v2/graph/episodes/:uuid
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.episode.delete(
uuid_="uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.episode.delete("uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Episode.Delete(
context.TODO(),
"uuid",
)
```
```shell
curl -X DELETE https://api.getzep.com/api/v2/graph/episodes/:uuid
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.episode.delete(
uuid_="uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.episode.delete("uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Episode.Delete(
context.TODO(),
"uuid",
)
```
# Return any nodes and edges mentioned in an episode
```http
GET https://api.getzep.com/api/v2/graph/episodes/{uuid}/mentions
```
Returns nodes and edges mentioned in an episode
## Path Parameters
- Uuid (required): Episode uuid
## Response Body
- 200: Edges and nodes mentioned in an episode
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/graph/episodes/uuid/mentions
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.episode.get_nodes_and_edges(
uuid_="uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.episode.getNodesAndEdges("uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Episode.GetNodesAndEdges(
context.TODO(),
"uuid",
)
```
```shell
curl https://api.getzep.com/api/v2/graph/episodes/:uuid/mentions
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.episode.get_nodes_and_edges(
uuid_="uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.episode.getNodesAndEdges("uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Episode.GetNodesAndEdges(
context.TODO(),
"uuid",
)
```
```shell
curl https://api.getzep.com/api/v2/graph/episodes/:uuid/mentions
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.episode.get_nodes_and_edges(
uuid_="uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.episode.getNodesAndEdges("uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Episode.GetNodesAndEdges(
context.TODO(),
"uuid",
)
```
# Get Group Nodes
```http
POST https://api.getzep.com/api/v2/graph/node/group/{group_id}
Content-Type: application/json
```
Returns all nodes for a group.
## Path Parameters
- GroupId (required): Group ID
## Response Body
- 200: Nodes
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl -X POST https://api.getzep.com/api/v2/graph/node/group/group_id \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.node.get_by_group_id(
group_id="group_id",
)
```
```typescript
import { ZepClient, Zep } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.node.getByGroupId("group_id", {});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Node.GetByGroupID(
context.TODO(),
"group_id",
&v2.GraphNodesRequest{},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/graph/node/group/:group_id \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.node.get_by_group_id(
group_id="group_id",
)
```
```typescript
import { ZepClient, Zep } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.node.getByGroupId("group_id", {});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Node.GetByGroupID(
context.TODO(),
"group_id",
&v2.GraphNodesRequest{},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/graph/node/group/:group_id \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.node.get_by_group_id(
group_id="group_id",
)
```
```typescript
import { ZepClient, Zep } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.node.getByGroupId("group_id", {});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Node.GetByGroupID(
context.TODO(),
"group_id",
&v2.GraphNodesRequest{},
)
```
# Get User Nodes
```http
POST https://api.getzep.com/api/v2/graph/node/user/{user_id}
Content-Type: application/json
```
Returns all nodes for a user
## Path Parameters
- UserId (required): User ID
## Response Body
- 200: Nodes
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl -X POST https://api.getzep.com/api/v2/graph/node/user/user_id \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.node.get_by_user_id(
user_id="user_id",
)
```
```typescript
import { ZepClient, Zep } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.node.getByUserId("user_id", {});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Node.GetByUserID(
context.TODO(),
"user_id",
&v2.GraphNodesRequest{},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/graph/node/user/:user_id \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.node.get_by_user_id(
user_id="user_id",
)
```
```typescript
import { ZepClient, Zep } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.node.getByUserId("user_id", {});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Node.GetByUserID(
context.TODO(),
"user_id",
&v2.GraphNodesRequest{},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/graph/node/user/:user_id \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.node.get_by_user_id(
user_id="user_id",
)
```
```typescript
import { ZepClient, Zep } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.node.getByUserId("user_id", {});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Node.GetByUserID(
context.TODO(),
"user_id",
&v2.GraphNodesRequest{},
)
```
# Get Entity Edges for a node
```http
GET https://api.getzep.com/api/v2/graph/node/{node_uuid}/entity-edges
```
Returns all edges for a node
## Path Parameters
- NodeUuid (required): Node UUID
## Response Body
- 200: Edges
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/graph/node/node_uuid/entity-edges
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.node.get_edges(
node_uuid="node_uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.node.getEdges("node_uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Node.GetEdges(
context.TODO(),
"node_uuid",
)
```
```shell
curl https://api.getzep.com/api/v2/graph/node/:node_uuid/entity-edges
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.node.get_edges(
node_uuid="node_uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.node.getEdges("node_uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Node.GetEdges(
context.TODO(),
"node_uuid",
)
```
```shell
curl https://api.getzep.com/api/v2/graph/node/:node_uuid/entity-edges
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.node.get_edges(
node_uuid="node_uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.node.getEdges("node_uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Node.GetEdges(
context.TODO(),
"node_uuid",
)
```
# Get Episodes for a node
```http
GET https://api.getzep.com/api/v2/graph/node/{node_uuid}/episodes
```
Returns all episodes that mentioned a given node
## Path Parameters
- NodeUuid (required): Node UUID
## Response Body
- 200: Episodes
- 400: Bad Request
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/graph/node/node_uuid/episodes
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.node.get_episodes(
node_uuid="node_uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.node.getEpisodes("node_uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Node.GetEpisodes(
context.TODO(),
"node_uuid",
)
```
```shell
curl https://api.getzep.com/api/v2/graph/node/:node_uuid/episodes
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.node.get_episodes(
node_uuid="node_uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.node.getEpisodes("node_uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Node.GetEpisodes(
context.TODO(),
"node_uuid",
)
```
```shell
curl https://api.getzep.com/api/v2/graph/node/:node_uuid/episodes
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.node.get_episodes(
node_uuid="node_uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.node.getEpisodes("node_uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Node.GetEpisodes(
context.TODO(),
"node_uuid",
)
```
# Get Node
```http
GET https://api.getzep.com/api/v2/graph/node/{uuid}
```
Returns a specific node by its UUID.
## Path Parameters
- Uuid (required): Node UUID
## Response Body
- 200: Node
- 400: Bad Request
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/graph/node/uuid
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.node.get(
uuid_="uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.node.get("uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Node.Get(
context.TODO(),
"uuid",
)
```
```shell
curl https://api.getzep.com/api/v2/graph/node/:uuid
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.node.get(
uuid_="uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.node.get("uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Node.Get(
context.TODO(),
"uuid",
)
```
```shell
curl https://api.getzep.com/api/v2/graph/node/:uuid
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.node.get(
uuid_="uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.node.get("uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Node.Get(
context.TODO(),
"uuid",
)
```
```shell
curl https://api.getzep.com/api/v2/graph/node/:uuid
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.graph.node.get(
uuid_="uuid",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.graph.node.get("uuid");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Graph.Node.Get(
context.TODO(),
"uuid",
)
```
# Returns a fact by UUID
```http
GET https://api.getzep.com/api/v2/facts/{factUUID}
```
Deprecated API: get fact by uuid
## Path Parameters
- FactUuid (required): Fact UUID
## Response Body
- 200: The fact with the specified UUID.
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/facts/factUUID \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.get_fact(
fact_uuid="factUUID",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.getFact("factUUID");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.GetFact(
context.TODO(),
"factUUID",
)
```
```shell
curl https://api.getzep.com/api/v2/facts/:factUUID \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.get_fact(
fact_uuid="factUUID",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.getFact("factUUID");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.GetFact(
context.TODO(),
"factUUID",
)
```
```shell
curl https://api.getzep.com/api/v2/facts/:factUUID \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.get_fact(
fact_uuid="factUUID",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.getFact("factUUID");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.GetFact(
context.TODO(),
"factUUID",
)
```
# Delete a fact for the given UUID
```http
DELETE https://api.getzep.com/api/v2/facts/{factUUID}
```
Deprecated API: delete a fact
## Path Parameters
- FactUuid (required): Fact UUID
## Response Body
- 200: Deleted
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl -X DELETE https://api.getzep.com/api/v2/facts/factUUID \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.delete_fact(
fact_uuid="factUUID",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.deleteFact("factUUID");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.DeleteFact(
context.TODO(),
"factUUID",
)
```
```shell
curl -X DELETE https://api.getzep.com/api/v2/facts/:factUUID \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.delete_fact(
fact_uuid="factUUID",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.deleteFact("factUUID");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.DeleteFact(
context.TODO(),
"factUUID",
)
```
```shell
curl -X DELETE https://api.getzep.com/api/v2/facts/:factUUID \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.delete_fact(
fact_uuid="factUUID",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.deleteFact("factUUID");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.DeleteFact(
context.TODO(),
"factUUID",
)
```
# End multiple sessions.
```http
POST https://api.getzep.com/api/v2/sessions/end
Content-Type: application/json
```
Deprecated API: End multiple sessions by their IDs.
## Response Body
- 200: OK
- 400: Bad Request
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl -X POST https://api.getzep.com/api/v2/sessions/end \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"session_ids": [
"session_ids"
]
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.end_sessions(
session_ids=["session_ids"],
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.endSessions({
sessionIds: ["session_ids"]
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.EndSessions(
context.TODO(),
&v2.EndSessionsRequest{
SessionIDs: []string{
"session_ids",
},
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/sessions/end \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"session_ids": [
"string"
]
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.end_sessions(
session_ids=["session_ids"],
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.endSessions({
sessionIds: ["session_ids"]
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.EndSessions(
context.TODO(),
&v2.EndSessionsRequest{
SessionIDs: []string{
"session_ids",
},
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/sessions/end \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"session_ids": [
"string"
]
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.end_sessions(
session_ids=["session_ids"],
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.endSessions({
sessionIds: ["session_ids"]
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.EndSessions(
context.TODO(),
&v2.EndSessionsRequest{
SessionIDs: []string{
"session_ids",
},
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/sessions/end \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"session_ids": [
"string"
]
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.end_sessions(
session_ids=["session_ids"],
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.endSessions({
sessionIds: ["session_ids"]
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.EndSessions(
context.TODO(),
&v2.EndSessionsRequest{
SessionIDs: []string{
"session_ids",
},
},
)
```
# Search sessions for the specified query.
```http
POST https://api.getzep.com/api/v2/sessions/search
Content-Type: application/json
```
Deprecated API: Search sessions for the specified query.
## Query Parameters
- Limit (optional): The maximum number of search results to return. Defaults to None (no limit).
## Response Body
- 200: A SessionSearchResponse object representing the search results.
- 500: Internal Server Error
## Examples
```shell
curl -X POST https://api.getzep.com/api/v2/sessions/search \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"text": "text"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.search_sessions(
text="text",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.searchSessions({
text: "text"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.SearchSessions(
context.TODO(),
&v2.SessionSearchQuery{
Text: "text",
},
)
```
```shell
curl -X POST "https://api.getzep.com/api/v2/sessions/search?limit=0" \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"text": "string"
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.search_sessions(
text="text",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.searchSessions({
text: "text"
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.SearchSessions(
context.TODO(),
&v2.SessionSearchQuery{
Text: "text",
},
)
```
# Update a session
```http
PATCH https://api.getzep.com/api/v2/sessions/{sessionId}
Content-Type: application/json
```
Update Session Metadata
## Path Parameters
- SessionId (required): The unique identifier of the session.
## Response Body
- 200: The updated session.
- 400: Bad Request
- 404: Not Found
- 409: Conflict
- 500: Internal Server Error
## Examples
```shell
curl -X PATCH https://api.getzep.com/api/v2/sessions/sessionId \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"metadata": {
"key": "value"
}
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.update_session(
session_id="sessionId",
metadata={"key": "value"},
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.updateSession("sessionId", {
metadata: {
"key": "value"
}
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.UpdateSession(
context.TODO(),
"sessionId",
&v2.UpdateSessionRequest{
Metadata: map[string]interface{}{
"key": "value",
},
},
)
```
```shell
curl -X PATCH https://api.getzep.com/api/v2/sessions/:sessionId \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"metadata": {
"string": {}
}
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.update_session(
session_id="sessionId",
metadata={"key": "value"},
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.updateSession("sessionId", {
metadata: {
"key": "value"
}
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.UpdateSession(
context.TODO(),
"sessionId",
&v2.UpdateSessionRequest{
Metadata: map[string]interface{}{
"key": "value",
},
},
)
```
```shell
curl -X PATCH https://api.getzep.com/api/v2/sessions/:sessionId \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"metadata": {
"string": {}
}
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.update_session(
session_id="sessionId",
metadata={"key": "value"},
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.updateSession("sessionId", {
metadata: {
"key": "value"
}
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.UpdateSession(
context.TODO(),
"sessionId",
&v2.UpdateSessionRequest{
Metadata: map[string]interface{}{
"key": "value",
},
},
)
```
```shell
curl -X PATCH https://api.getzep.com/api/v2/sessions/:sessionId \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"metadata": {
"string": {}
}
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.update_session(
session_id="sessionId",
metadata={"key": "value"},
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.updateSession("sessionId", {
metadata: {
"key": "value"
}
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.UpdateSession(
context.TODO(),
"sessionId",
&v2.UpdateSessionRequest{
Metadata: map[string]interface{}{
"key": "value",
},
},
)
```
```shell
curl -X PATCH https://api.getzep.com/api/v2/sessions/:sessionId \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"metadata": {
"string": {}
}
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.update_session(
session_id="sessionId",
metadata={"key": "value"},
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.updateSession("sessionId", {
metadata: {
"key": "value"
}
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.UpdateSession(
context.TODO(),
"sessionId",
&v2.UpdateSessionRequest{
Metadata: map[string]interface{}{
"key": "value",
},
},
)
```
# End a session
```http
POST https://api.getzep.com/api/v2/sessions/{sessionId}/end
Content-Type: application/json
```
Deprecated API: End a session by ID.
## Path Parameters
- SessionId (required): Session ID
## Response Body
- 200: OK
- 400: Bad Request
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl -X POST https://api.getzep.com/api/v2/sessions/sessionId/end \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.end_session(
session_id="sessionId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.endSession("sessionId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.EndSession(
context.TODO(),
"sessionId",
&v2.EndSessionRequest{},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/sessions/:sessionId/end \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.end_session(
session_id="sessionId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.endSession("sessionId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.EndSession(
context.TODO(),
"sessionId",
&v2.EndSessionRequest{},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/sessions/:sessionId/end \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.end_session(
session_id="sessionId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.endSession("sessionId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.EndSession(
context.TODO(),
"sessionId",
&v2.EndSessionRequest{},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/sessions/:sessionId/end \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.end_session(
session_id="sessionId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.endSession("sessionId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.EndSession(
context.TODO(),
"sessionId",
&v2.EndSessionRequest{},
)
```
# Returns all facts for a session by ID
```http
GET https://api.getzep.com/api/v2/sessions/{sessionId}/facts
```
Deprecated API: get facts for a session
## Path Parameters
- SessionId (required): Session ID
## Query Parameters
- MinRating (optional): Minimum rating by which to filter facts
## Response Body
- 200: The facts for the session.
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl https://api.getzep.com/api/v2/sessions/sessionId/facts \
-H "Authorization: Api-Key "
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.get_session_facts(
session_id="sessionId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.getSessionFacts("sessionId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.GetSessionFacts(
context.TODO(),
"sessionId",
&v2.MemoryGetSessionFactsRequest{},
)
```
```shell
curl -G https://api.getzep.com/api/v2/sessions/:sessionId/facts \
-H "Authorization: Api-Key " \
-d minRating=1
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.get_session_facts(
session_id="sessionId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.getSessionFacts("sessionId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.GetSessionFacts(
context.TODO(),
"sessionId",
&v2.MemoryGetSessionFactsRequest{},
)
```
```shell
curl -G https://api.getzep.com/api/v2/sessions/:sessionId/facts \
-H "Authorization: Api-Key " \
-d minRating=1
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.get_session_facts(
session_id="sessionId",
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.getSessionFacts("sessionId");
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.GetSessionFacts(
context.TODO(),
"sessionId",
&v2.MemoryGetSessionFactsRequest{},
)
```
# Adds facts to a session
```http
POST https://api.getzep.com/api/v2/sessions/{sessionId}/facts
Content-Type: application/json
```
Deprecated API: Adds facts to a session
## Path Parameters
- SessionId (required): Session ID
## Response Body
- 200: OK
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl -X POST https://api.getzep.com/api/v2/sessions/sessionId/facts \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"facts": [
{
"fact": "fact"
}
]
}'
```
```python
from zep_cloud import NewFact
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.add_session_facts(
session_id="sessionId",
facts=[
NewFact(
fact="fact",
)
],
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.addSessionFacts("sessionId", {
facts: [{
fact: "fact"
}]
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.AddSessionFacts(
context.TODO(),
"sessionId",
&v2.AddFactsRequest{
Facts: []*v2.NewFact{
&v2.NewFact{
Fact: "fact",
},
},
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/sessions/:sessionId/facts \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"facts": [
{
"fact": "string"
}
]
}'
```
```python
from zep_cloud import NewFact
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.add_session_facts(
session_id="sessionId",
facts=[
NewFact(
fact="fact",
)
],
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.addSessionFacts("sessionId", {
facts: [{
fact: "fact"
}]
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.AddSessionFacts(
context.TODO(),
"sessionId",
&v2.AddFactsRequest{
Facts: []*v2.NewFact{
&v2.NewFact{
Fact: "fact",
},
},
},
)
```
```shell
curl -X POST https://api.getzep.com/api/v2/sessions/:sessionId/facts \
-H "Authorization: Api-Key " \
-H "Content-Type: application/json" \
-d '{
"facts": [
{
"fact": "string"
}
]
}'
```
```python
from zep_cloud import NewFact
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.add_session_facts(
session_id="sessionId",
facts=[
NewFact(
fact="fact",
)
],
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.addSessionFacts("sessionId", {
facts: [{
fact: "fact"
}]
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.AddSessionFacts(
context.TODO(),
"sessionId",
&v2.AddFactsRequest{
Facts: []*v2.NewFact{
&v2.NewFact{
Fact: "fact",
},
},
},
)
```
# Updates the metadata of a message.
```http
PATCH https://api.getzep.com/api/v2/sessions/{sessionId}/messages/{messageUUID}
Content-Type: application/json
```
Updates the metadata of a message.
## Path Parameters
- SessionId (required): The ID of the session.
- MessageUuid (required): The UUID of the message.
## Response Body
- 200: The updated message.
- 404: Not Found
- 500: Internal Server Error
## Examples
```shell
curl -X PATCH https://api.getzep.com/api/v2/sessions/sessionId/messages/messageUUID \
-H "Content-Type: application/json" \
-d '{
"metadata": {
"key": "value"
}
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.update_message_metadata(
session_id="sessionId",
message_uuid="messageUUID",
metadata={"key": "value"},
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.updateMessageMetadata("sessionId", "messageUUID", {
metadata: {
"key": "value"
}
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.UpdateMessageMetadata(
context.TODO(),
"sessionId",
"messageUUID",
&v2.ModelsMessageMetadataUpdate{
Metadata: map[string]interface{}{
"key": "value",
},
},
)
```
```shell
curl -X PATCH https://api.getzep.com/api/v2/sessions/:sessionId/messages/:messageUUID \
-H "Content-Type: application/json" \
-d '{
"metadata": {
"string": {}
}
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.update_message_metadata(
session_id="sessionId",
message_uuid="messageUUID",
metadata={"key": "value"},
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.updateMessageMetadata("sessionId", "messageUUID", {
metadata: {
"key": "value"
}
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"",
),
)
response, err := client.Memory.UpdateMessageMetadata(
context.TODO(),
"sessionId",
"messageUUID",
&v2.ModelsMessageMetadataUpdate{
Metadata: map[string]interface{}{
"key": "value",
},
},
)
```
```shell
curl -X PATCH https://api.getzep.com/api/v2/sessions/:sessionId/messages/:messageUUID \
-H "Content-Type: application/json" \
-d '{
"metadata": {
"string": {}
}
}'
```
```python
from zep_cloud.client import Zep
client = Zep(
api_key="YOUR_API_KEY",
)
client.memory.update_message_metadata(
session_id="sessionId",
message_uuid="messageUUID",
metadata={"key": "value"},
)
```
```typescript
import { ZepClient } from "zep-cloud";
const client = new ZepClient({ apiKey: "YOUR_API_KEY" });
await client.memory.updateMessageMetadata("sessionId", "messageUUID", {
metadata: {
"key": "value"
}
});
```
```go
import (
context "context"
option "github.com/getzep/zep-go/v2/option"
v2 "github.com/getzep/zep-go/v2"
v2client "github.com/getzep/zep-go/v2/client"
)
client := v2client.NewClient(
option.WithAPIKey(
"