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| # Using Ollama Embeddings with GraphRAG: A Quick Guide | |
| ## Problem | |
| GraphRAG is designed to work with OpenAI-compatible APIs for both language models and embeddings and Ollama currently has their own way of doing embeddings. | |
| ## Solution: Embeddings Proxy | |
| To bridge this gap, let's use an embeddings proxy. This proxy acts as a middleware between GraphRAG and Ollama, translating Ollama's embedding responses into a format that GraphRAG expects. | |
| ## Use the Embeddings Proxy | |
| 1. **Set up the proxy:** | |
| - Save the provided `embedding_proxy.py` script to your project directory. | |
| - Install required dependencies (not needed if you've already done this in the normal setup): `pip install fastapi uvicorn httpx` | |
| 2. **Run the proxy:** | |
| ```bash | |
| python embedding_proxy.py --port 11435 --host http://localhost:11434 | |
| ``` | |
| This starts the proxy on port 11435, connecting to Ollama at localhost:11434. | |
| 3. **Configure GraphRAG:** | |
| Update your `settings.yaml` file to use the proxy for embeddings: | |
| ```yaml | |
| embeddings: | |
| llm: | |
| api_key: ${GRAPHRAG_API_KEY} | |
| type: openai_embedding | |
| model: nomic-embed-text:latest | |
| api_base: http://localhost:11435 # Point to your proxy | |
| ``` | |
| 4. **Run GraphRAG:** | |
| With the proxy running and the configuration updated, you can now run GraphRAG as usual. It will use Ollama for embeddings through the proxy. | |