aljaz/scale-gke-qdrant-llama
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Benito Martin
2024-06-30 14:41:57 +02:00
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@@ -10,13 +10,13 @@ For detailed project descriptions, refer to this [Medium article](XXX).
Main Steps Main Steps
- **Data Ingestion**: Load data from GitHub repositories. - **Data Ingestion**: Load data from GitHub repositories
- **Indexing**: Use SentenceSplitter for indexing in nodes. - **Indexing**: Use SentenceSplitter for indexing in nodes
- **Embedding and Model**: OpenAI. - **Embedding and Model**: OpenAI
- **Vector Store**: Use Qdrant for inserting metadata. - **Vector Store**: Use Qdrant for inserting metadata
- **Query Retrieval**: Implement RetrieverQueryEngine. - **Query Retrieval**: Implement RetrieverQueryEngine
- **FastAPI and GKE**: Handle requests via the FastAPI app deployed on GKE. - **FastAPI and GKE**: Handle requests via the FastAPI app deployed on GKE
- **Streamlit**: UI component. - **Streamlit**: UI
Feel free to ⭐ and clone this repo 😉 Feel free to ⭐ and clone this repo 😉