sajad-dev
2c42ebe01c
- Removed deprecated user_info files and paths from configuration. - Added user soil data integration in chat context to improve response accuracy. - Updated build_rag_context and chat_rag_stream functions to include sensor_uuid for user-specific data retrieval. - Enhanced load_sources function to load user data from the database. - Implemented filtering in search_with_query and QdrantVectorStore to isolate user data based on sensor_uuid. - Introduced Celery Beat schedule for periodic user data ingestion.
29 lines
773 B
YAML
29 lines
773 B
YAML
# تنظیمات RAG برای پایگاه دانش CropLogic
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embedding:
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provider: "avalai" # Avalai API (OpenAI-compatible)
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model: "text-embedding-3-small"
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base_url: "https://api.avalai.ir/v1"
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api_key_env: "AVALAI_API_KEY"
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batch_size: 32
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# فاز یک: Qdrant بهعنوان vector store
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qdrant:
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host: "localhost" # یا qdrant در Docker
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port: 6333
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collection_name: "croplogic_kb"
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vector_size: 1536 # متناسب با text-embedding-3-small
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chunking:
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max_chunk_tokens: 500
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overlap_tokens: 50
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# تنظیمات مدل چت (LLM) — Avalai
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llm:
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model: "gpt-4o"
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base_url: "https://api.avalai.ir/v1"
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api_key_env: "AVALAI_API_KEY"
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tone_file: "config/tone.txt"
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knowledge_base_path: "config/knowledge_base"
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