Installation

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from openai import AsyncAzureOpenAI
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from graphiti_core import Graphiti
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from graphiti_core.llm_client import OpenAIClient
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from graphiti_core.embedder.openai import OpenAIEmbedder, OpenAIEmbedderConfig
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from graphiti_core.cross_encoder.openai_reranker_client import OpenAIRerankerClient
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# Azure OpenAI configuration
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api_key = "<your-api-key>"
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api_version = "<your-api-version>"
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azure_endpoint = "<your-azure-endpoint>"
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# Create Azure OpenAI client for LLM
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azure_openai_client = AsyncAzureOpenAI(
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    api_key=api_key,
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    api_version=api_version,
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    azure_endpoint=azure_endpoint
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)
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# Initialize Graphiti with Azure OpenAI clients
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graphiti = Graphiti(
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    "bolt://localhost:7687",
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    "neo4j",
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    "password",
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    llm_client=OpenAIClient(
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        client=azure_openai_client
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    ),
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    embedder=OpenAIEmbedder(
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        config=OpenAIEmbedderConfig(
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            embedding_model="text-embedding-3-small"  # Use your Azure deployed embedding model name
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        ),
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        client=azure_openai_client
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    ),
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    # Optional: Configure the OpenAI cross encoder with Azure OpenAI
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    cross_encoder=OpenAIRerankerClient(
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        client=azure_openai_client
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    )
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)
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# Now you can use Graphiti with Azure OpenAI

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import os
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from graphiti_core import Graphiti
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from graphiti_core.llm_client.gemini_client import GeminiClient, LLMConfig
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from graphiti_core.embedder.gemini import GeminiEmbedder, GeminiEmbedderConfig
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# Google API key configuration
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api_key = os.environ.get("GOOGLE_API_KEY")
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if not api_key:
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    raise ValueError("GOOGLE_API_KEY environment variable must be set")
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# Initialize Graphiti with Gemini clients
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graphiti = Graphiti(
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    "bolt://localhost:7687",
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    "neo4j",
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    "password",
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    llm_client=GeminiClient(
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        config=LLMConfig(
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            api_key=api_key,
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            model="gemini-2.0-flash"
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        )
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    ),
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    embedder=GeminiEmbedder(
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        config=GeminiEmbedderConfig(
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            api_key=api_key,
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            embedding_model="embedding-001"
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        )
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    )
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)