t6_mem0/config.py

#!/usr/bin/env python3
"""
Configuration management for mem0 system
"""

import os
from typing import Dict, Any, Optional
from dataclasses import dataclass

@dataclass
class DatabaseConfig:
    """Database configuration"""
    supabase_url: Optional[str] = None
    supabase_key: Optional[str] = None
    neo4j_uri: Optional[str] = None
    neo4j_username: Optional[str] = None
    neo4j_password: Optional[str] = None

@dataclass
class LLMConfig:
    """LLM configuration"""
    openai_api_key: Optional[str] = None
    ollama_base_url: Optional[str] = None

@dataclass
class SystemConfig:
    """Complete system configuration"""
    database: DatabaseConfig
    llm: LLMConfig

def load_config() -> SystemConfig:
    """Load configuration from environment variables"""
    database_config = DatabaseConfig(
        supabase_url=os.getenv("SUPABASE_URL"),
        supabase_key=os.getenv("SUPABASE_ANON_KEY"),
        neo4j_uri=os.getenv("NEO4J_URI", "bolt://localhost:7687"),
        neo4j_username=os.getenv("NEO4J_USERNAME", "neo4j"),
        neo4j_password=os.getenv("NEO4J_PASSWORD")
    )
    
    llm_config = LLMConfig(
        openai_api_key=os.getenv("OPENAI_API_KEY"),
        ollama_base_url=os.getenv("OLLAMA_BASE_URL", "http://localhost:11434")
    )
    
    return SystemConfig(database=database_config, llm=llm_config)

def get_mem0_config(config: SystemConfig, provider: str = "openai") -> Dict[str, Any]:
    """Get mem0 configuration dictionary"""
    base_config = {}
    
    # Use Supabase for vector storage if configured
    if config.database.supabase_url and config.database.supabase_key:
        base_config["vector_store"] = {
            "provider": "supabase",
            "config": {
                "connection_string": "postgresql://supabase_admin:CzkaYmRvc26Y@localhost:5435/postgres",
                "collection_name": "mem0_vectors",
                "embedding_model_dims": 1536  # OpenAI text-embedding-3-small dimension
            }
        }
    else:
        # Fallback to Qdrant if Supabase not configured
        base_config["vector_store"] = {
            "provider": "qdrant",
            "config": {
                "host": "localhost",
                "port": 6333,
            }
        }
    
    if provider == "openai" and config.llm.openai_api_key:
        base_config["llm"] = {
            "provider": "openai",
            "config": {
                "api_key": config.llm.openai_api_key,
                "model": "gpt-4o-mini",
                "temperature": 0.2,
                "max_tokens": 1500
            }
        }
        base_config["embedder"] = {
            "provider": "openai",
            "config": {
                "api_key": config.llm.openai_api_key,
                "model": "text-embedding-3-small"
            }
        }
    elif provider == "ollama":
        base_config["llm"] = {
            "provider": "ollama",
            "config": {
                "model": "llama2",
                "base_url": config.llm.ollama_base_url
            }
        }
        base_config["embedder"] = {
            "provider": "ollama",
            "config": {
                "model": "llama2",
                "base_url": config.llm.ollama_base_url
            }
        }
    
    # Add Neo4j graph store if configured  
    if config.database.neo4j_uri and config.database.neo4j_password:
        base_config["graph_store"] = {
            "provider": "neo4j",
            "config": {
                "url": config.database.neo4j_uri,
                "username": config.database.neo4j_username,
                "password": config.database.neo4j_password
            }
        }
        base_config["version"] = "v1.1"  # Required for graph memory
        
    return base_config

if __name__ == "__main__":
    # Test configuration loading
    config = load_config()
    print("Configuration loaded:")
    print(f"  OpenAI API Key: {'Set' if config.llm.openai_api_key else 'Not set'}")
    print(f"  Supabase URL: {'Set' if config.database.supabase_url else 'Not set'}")
    print(f"  Neo4j URI: {config.database.neo4j_uri}")
    print(f"  Ollama URL: {config.llm.ollama_base_url}")
    
    # Test mem0 config generation
    print("\nMem0 OpenAI Config:")
    mem0_config = get_mem0_config(config, "openai")
    for key, value in mem0_config.items():
        print(f"  {key}: {value}")