fa9d3d8a6b
Major Changes: - Added Ollama as alternative LLM provider to OpenAI - Implemented flexible provider switching via environment variables - Support for multiple embedding models (OpenAI and Ollama) - Created comprehensive Ollama setup guide Configuration Changes (config.py): - Added LLM_PROVIDER and EMBEDDER_PROVIDER settings - Added Ollama configuration: base URL, LLM model, embedding model - Modified get_mem0_config() to dynamically switch providers - OpenAI API key now optional when using Ollama - Added validation to ensure required keys based on provider Supported Configurations: 1. Full OpenAI (default): - LLM_PROVIDER=openai - EMBEDDER_PROVIDER=openai 2. Full Ollama (local): - LLM_PROVIDER=ollama - EMBEDDER_PROVIDER=ollama 3. Hybrid configurations: - Ollama LLM + OpenAI embeddings - OpenAI LLM + Ollama embeddings Ollama Models Supported: - LLM: llama3.1:8b, llama3.1:70b, mistral:7b, codellama:7b, phi3:3.8b - Embeddings: nomic-embed-text, mxbai-embed-large, all-minilm Documentation: - Created docs/setup/ollama.mdx - Complete Ollama setup guide - Installation methods (host and Docker) - Model selection and comparison - Docker Compose configuration - Performance tuning and GPU acceleration - Migration guide from OpenAI - Troubleshooting section - Updated README.md with Ollama features - Updated .env.example with provider selection - Marked Phase 2 as complete in roadmap Environment Variables: - LLM_PROVIDER: Select LLM provider (openai/ollama) - EMBEDDER_PROVIDER: Select embedding provider (openai/ollama) - OLLAMA_BASE_URL: Ollama API endpoint (default: http://localhost:11434) - OLLAMA_LLM_MODEL: Ollama model for text generation - OLLAMA_EMBEDDING_MODEL: Ollama model for embeddings - MEM0_EMBEDDING_DIMS: Must match embedding model dimensions Breaking Changes: - None - defaults to OpenAI for backward compatibility Migration Notes: - When switching from OpenAI to Ollama embeddings, existing embeddings must be cleared due to dimension changes (1536 → 768 for nomic-embed-text) - Update MEM0_EMBEDDING_DIMS to match chosen embedding model Benefits: ✅ Cost savings - no API costs with local models ✅ Privacy - all data stays local ✅ Offline capability - works without internet ✅ Model variety - access to many open-source models ✅ Flexibility - easy switching between providers Version: 1.1.0 Status: Phase 2 Complete - Production Ready with Ollama Support 🤖 Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
48 lines
1.0 KiB
Plaintext
48 lines
1.0 KiB
Plaintext
# LLM Provider Selection
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# Options: "openai" or "ollama"
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LLM_PROVIDER=openai
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EMBEDDER_PROVIDER=openai
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# OpenAI Configuration
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# Required when LLM_PROVIDER=openai or EMBEDDER_PROVIDER=openai
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OPENAI_API_KEY=sk-your-openai-api-key-here
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# Ollama Configuration
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# Required when LLM_PROVIDER=ollama or EMBEDDER_PROVIDER=ollama
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# Ollama must be running and models must be pulled
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OLLAMA_BASE_URL=http://localhost:11434
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OLLAMA_LLM_MODEL=llama3.1:8b
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OLLAMA_EMBEDDING_MODEL=nomic-embed-text
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# Supabase Configuration
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SUPABASE_CONNECTION_STRING=postgresql://user:password@host:5432/database
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# Neo4j Configuration
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NEO4J_URI=neo4j://neo4j:7687
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NEO4J_USER=neo4j
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NEO4J_PASSWORD=your-neo4j-password
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# API Configuration
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API_HOST=0.0.0.0
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API_PORT=8080
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API_KEY=your-secure-api-key-here
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# MCP Server Configuration
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MCP_HOST=0.0.0.0
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MCP_PORT=8765
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# Mem0 Configuration
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MEM0_COLLECTION_NAME=t6_memories
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MEM0_EMBEDDING_DIMS=1536
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MEM0_VERSION=v1.1
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# Docker Network
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DOCKER_NETWORK=localai
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# Logging
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LOG_LEVEL=INFO
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LOG_FORMAT=json
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# Environment
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ENVIRONMENT=development
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