61a4050a8e
Implementation Summary:
- REST API with FastAPI (complete CRUD operations)
- MCP Server with Python MCP SDK (7 tools)
- Supabase migrations (pgvector setup)
- Docker Compose orchestration
- Mintlify documentation site
- Environment configuration
- Shared config module
REST API Features:
- POST /v1/memories/ - Add memory
- GET /v1/memories/search - Semantic search
- GET /v1/memories/{id} - Get memory
- GET /v1/memories/user/{user_id} - User memories
- PATCH /v1/memories/{id} - Update memory
- DELETE /v1/memories/{id} - Delete memory
- GET /v1/health - Health check
- GET /v1/stats - Statistics
- Bearer token authentication
- OpenAPI documentation
MCP Server Tools:
- add_memory - Add from messages
- search_memories - Semantic search
- get_memory - Retrieve by ID
- get_all_memories - List all
- update_memory - Update content
- delete_memory - Delete by ID
- delete_all_memories - Bulk delete
Infrastructure:
- Neo4j 5.26 with APOC/GDS
- Supabase pgvector integration
- Docker network: localai
- Health checks and monitoring
- Structured logging
Documentation:
- Introduction page
- Quickstart guide
- Architecture deep dive
- Mintlify configuration
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
122 lines
3.4 KiB
Python
122 lines
3.4 KiB
Python
"""
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Shared configuration for T6 Mem0 v2
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Loads environment variables and creates Mem0 configuration
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"""
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import os
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from typing import Dict, Any
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from pydantic_settings import BaseSettings
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from pydantic import Field
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class Settings(BaseSettings):
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"""Application settings loaded from environment variables"""
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# OpenAI
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openai_api_key: str = Field(..., env="OPENAI_API_KEY")
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# Supabase
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supabase_connection_string: str = Field(..., env="SUPABASE_CONNECTION_STRING")
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# Neo4j
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neo4j_uri: str = Field(..., env="NEO4J_URI")
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neo4j_user: str = Field(default="neo4j", env="NEO4J_USER")
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neo4j_password: str = Field(..., env="NEO4J_PASSWORD")
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# API
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api_host: str = Field(default="0.0.0.0", env="API_HOST")
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api_port: int = Field(default=8080, env="API_PORT")
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api_key: str = Field(..., env="API_KEY")
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# MCP Server
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mcp_host: str = Field(default="0.0.0.0", env="MCP_HOST")
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mcp_port: int = Field(default=8765, env="MCP_PORT")
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# Mem0
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mem0_collection_name: str = Field(default="t6_memories", env="MEM0_COLLECTION_NAME")
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mem0_embedding_dims: int = Field(default=1536, env="MEM0_EMBEDDING_DIMS")
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mem0_version: str = Field(default="v1.1", env="MEM0_VERSION")
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# Logging
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log_level: str = Field(default="INFO", env="LOG_LEVEL")
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log_format: str = Field(default="json", env="LOG_FORMAT")
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# Environment
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environment: str = Field(default="development", env="ENVIRONMENT")
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class Config:
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env_file = ".env"
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env_file_encoding = "utf-8"
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case_sensitive = False
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def get_settings() -> Settings:
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"""Get application settings"""
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return Settings()
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def get_mem0_config(settings: Settings) -> Dict[str, Any]:
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"""
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Generate Mem0 configuration from settings
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Args:
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settings: Application settings
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Returns:
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Dict containing Mem0 configuration
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"""
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return {
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# Vector Store - Supabase
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"vector_store": {
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"provider": "supabase",
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"config": {
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"connection_string": settings.supabase_connection_string,
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"collection_name": settings.mem0_collection_name,
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"embedding_model_dims": settings.mem0_embedding_dims,
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"index_method": "hnsw", # Fastest search
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"index_measure": "cosine_distance" # Best for embeddings
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}
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},
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# Graph Store - Neo4j
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"graph_store": {
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"provider": "neo4j",
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"config": {
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"url": settings.neo4j_uri,
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"username": settings.neo4j_user,
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"password": settings.neo4j_password
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}
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},
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# LLM Provider - OpenAI
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"llm": {
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"provider": "openai",
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"config": {
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"model": "gpt-4o-mini",
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"temperature": 0.1,
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"max_tokens": 2000,
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"api_key": settings.openai_api_key
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}
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},
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# Embedder - OpenAI
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"embedder": {
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"provider": "openai",
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"config": {
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"model": "text-embedding-3-small",
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"embedding_dims": settings.mem0_embedding_dims,
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"api_key": settings.openai_api_key
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}
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},
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# Version
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"version": settings.mem0_version
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}
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# Global settings instance
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settings = get_settings()
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# Global mem0 config
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mem0_config = get_mem0_config(settings)
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