t6_mem0_v2/config.py

"""
Shared configuration for T6 Mem0 v2
Loads environment variables and creates Mem0 configuration
"""

import os
from typing import Dict, Any
from pydantic_settings import BaseSettings
from pydantic import Field


class Settings(BaseSettings):
    """Application settings loaded from environment variables"""

    # LLM Provider Selection
    llm_provider: str = Field(default="openai", env="LLM_PROVIDER")  # openai or ollama
    embedder_provider: str = Field(default="openai", env="EMBEDDER_PROVIDER")  # openai or ollama

    # OpenAI
    openai_api_key: str = Field(default="", env="OPENAI_API_KEY")  # Optional if using Ollama

    # Ollama
    ollama_base_url: str = Field(default="http://localhost:11434", env="OLLAMA_BASE_URL")
    ollama_llm_model: str = Field(default="llama3.1:8b", env="OLLAMA_LLM_MODEL")
    ollama_embedding_model: str = Field(default="nomic-embed-text", env="OLLAMA_EMBEDDING_MODEL")

    # Supabase
    supabase_connection_string: str = Field(..., env="SUPABASE_CONNECTION_STRING")

    # Neo4j
    neo4j_uri: str = Field(..., env="NEO4J_URI")
    neo4j_user: str = Field(default="neo4j", env="NEO4J_USER")
    neo4j_password: str = Field(..., env="NEO4J_PASSWORD")

    # API
    api_host: str = Field(default="0.0.0.0", env="API_HOST")
    api_port: int = Field(default=8080, env="API_PORT")
    api_key: str = Field(..., env="API_KEY")

    # MCP Server
    mcp_host: str = Field(default="0.0.0.0", env="MCP_HOST")
    mcp_port: int = Field(default=8765, env="MCP_PORT")

    # Mem0
    mem0_collection_name: str = Field(default="t6_memories", env="MEM0_COLLECTION_NAME")
    mem0_embedding_dims: int = Field(default=1536, env="MEM0_EMBEDDING_DIMS")
    mem0_version: str = Field(default="v1.1", env="MEM0_VERSION")

    # Logging
    log_level: str = Field(default="INFO", env="LOG_LEVEL")
    log_format: str = Field(default="json", env="LOG_FORMAT")

    # Environment
    environment: str = Field(default="development", env="ENVIRONMENT")

    # Docker (optional, for container deployments)
    docker_network: str = Field(default="bridge", env="DOCKER_NETWORK")

    class Config:
        env_file = ".env"
        env_file_encoding = "utf-8"
        case_sensitive = False


def get_settings() -> Settings:
    """Get application settings"""
    return Settings()


def get_mem0_config(settings: Settings) -> Dict[str, Any]:
    """
    Generate Mem0 configuration from settings with support for OpenAI and Ollama

    Args:
        settings: Application settings

    Returns:
        Dict containing Mem0 configuration
    """
    # LLM Configuration - Switch between OpenAI and Ollama
    if settings.llm_provider.lower() == "ollama":
        llm_config = {
            "provider": "ollama",
            "config": {
                "model": settings.ollama_llm_model,
                "temperature": 0.1,
                "max_tokens": 2000,
                "ollama_base_url": settings.ollama_base_url
            }
        }
    else:  # Default to OpenAI
        if not settings.openai_api_key:
            raise ValueError("OPENAI_API_KEY is required when LLM_PROVIDER=openai")
        llm_config = {
            "provider": "openai",
            "config": {
                "model": "gpt-4o-mini",
                "temperature": 0.1,
                "max_tokens": 2000,
                "api_key": settings.openai_api_key
            }
        }

    # Embedder Configuration - Switch between OpenAI and Ollama
    if settings.embedder_provider.lower() == "ollama":
        embedder_config = {
            "provider": "ollama",
            "config": {
                "model": settings.ollama_embedding_model,
                "ollama_base_url": settings.ollama_base_url
            }
        }
    else:  # Default to OpenAI
        if not settings.openai_api_key:
            raise ValueError("OPENAI_API_KEY is required when EMBEDDER_PROVIDER=openai")
        embedder_config = {
            "provider": "openai",
            "config": {
                "model": "text-embedding-3-small",
                "embedding_dims": settings.mem0_embedding_dims,
                "api_key": settings.openai_api_key
            }
        }

    return {
        # Vector Store - Supabase
        "vector_store": {
            "provider": "supabase",
            "config": {
                "connection_string": settings.supabase_connection_string,
                "collection_name": settings.mem0_collection_name,
                "embedding_model_dims": settings.mem0_embedding_dims,
                "index_method": "hnsw",  # Fastest search
                "index_measure": "cosine_distance"  # Best for embeddings
            }
        },

        # Graph Store - Neo4j
        "graph_store": {
            "provider": "neo4j",
            "config": {
                "url": settings.neo4j_uri,
                "username": settings.neo4j_user,
                "password": settings.neo4j_password
            }
        },

        # LLM Provider - Dynamic (OpenAI or Ollama)
        "llm": llm_config,

        # Embedder - Dynamic (OpenAI or Ollama)
        "embedder": embedder_config,

        # Version
        "version": settings.mem0_version
    }


# Global settings instance
settings = get_settings()

# Global mem0 config
mem0_config = get_mem0_config(settings)