45 lines
1.9 KiB
Text
45 lines
1.9 KiB
Text
# API Configuration - UPDATE THESE WITH YOUR VALUES
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OPENAI_API_KEY=sk-your-openai-api-key-here
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OPENAI_COMPAT_API_KEY=sk-your-openai-compatible-api-key-here
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OPENAI_BASE_URL=https://your-openai-compatible-endpoint.com/v1
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EMBEDDER_API_KEY=AIzaSy-your-google-gemini-api-key-here
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COHERE_API_KEY=your-cohere-api-key-here
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# Database Configuration
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QDRANT_HOST=qdrant
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QDRANT_PORT=6333
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QDRANT_COLLECTION_NAME=mem0
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# Neo4j Configuration
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NEO4J_AUTH=neo4j/mem0_neo4j_password
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NEO4J_URI=bolt://neo4j:7687
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NEO4J_USERNAME=neo4j
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NEO4J_PASSWORD=mem0_neo4j_password
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# Application Configuration
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BACKEND_PORT=8000
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FRONTEND_PORT=3000
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LOG_LEVEL=INFO
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CORS_ORIGINS=http://localhost:3000
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# Model Configuration - Intelligent Routing
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# These models are automatically selected based on task complexity
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DEFAULT_MODEL=claude-sonnet-4 # General purpose model
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EXTRACTION_MODEL=claude-sonnet-4 # Memory extraction and processing
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FAST_MODEL=o4-mini # Simple/quick responses
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ANALYTICAL_MODEL=gemini-2.5-pro # Analysis and comparison tasks
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REASONING_MODEL=claude-sonnet-4 # Complex reasoning tasks
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EXPERT_MODEL=o3 # Expert-level comprehensive analysis
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# Authentication - API Keys mapped to User IDs
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# Format: JSON string mapping API keys to user IDs
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# Example: {"api_key_123": "alice", "api_key_456": "bob"}
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# IMPORTANT: Generate secure random keys for production (e.g., using `openssl rand -hex 32`)
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API_KEYS={"sk-user1-key-replace-with-random": "user1", "sk-user2-key-replace-with-random": "user2"}
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# IMPORTANT NOTES:
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# - Ensure all models are available on your OpenAI-compatible endpoint
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# - Verify model availability: curl -H "Authorization: Bearer $API_KEY" $BASE_URL/v1/models
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# - Neo4j must be version 5.18+ for vector.similarity.cosine() function
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# - Qdrant vector database for embeddings storage (replaces PostgreSQL+pgvector)
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# - Ollama must be running locally with nomic-embed-text:latest model
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