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feat(vector-io): add OpenGauss vector database provider
Implement OpenGauss vector database integration for Llama Stack with the following features: - Add OpenGaussVectorIOAdapter for vector storage and retrieval - Support native vector similarity search operations - Provide configuration template for easy setup - Add comprehensive unit tests - Align with the latest Llama Stack provider architecture, including KVStore and OpenAI Vector Store Mixin. The implementation allows Llama Stack users to leverage OpenGauss as an enterprise-grade vector database for RAG applications.
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Llama Stack Inference API for generating completions, chat completions, and embeddings.
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This API provides the raw interface to the underlying models. Two kinds of models are supported:
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- LLM models: these models generate "raw" and "chat" (conversational) completions.
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- Embedding models: these models generate embeddings to be used for semantic search.
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This API provides the raw interface to the underlying models. Two kinds of models are supported:
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- LLM models: these models generate "raw" and "chat" (conversational) completions.
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- Embedding models: these models generate embeddings to be used for semantic search.
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This section contains documentation for all available providers for the **inference** API.
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