41cd78207a
- Configure mem0 to use self-hosted Supabase instead of Qdrant for vector storage - Update docker-compose to connect containers to localai network - Install vecs library for Supabase pgvector integration - Create comprehensive test suite for Supabase + mem0 integration - Update documentation to reflect Supabase configuration - All containers now connected to shared localai network - Successful vector storage and retrieval tests completed 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
77 lines
2.6 KiB
Python
77 lines
2.6 KiB
Python
#!/usr/bin/env python3
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"""
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Test OpenAI integration with mem0
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"""
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import os
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from dotenv import load_dotenv
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from mem0 import Memory
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from config import load_config, get_mem0_config
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# Load environment variables from .env file if it exists
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load_dotenv()
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def test_openai_integration():
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"""Test mem0 with OpenAI integration"""
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# Load configuration
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config = load_config()
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if not config.llm.openai_api_key:
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print("❌ OPENAI_API_KEY not found in environment variables")
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print("Please set your OpenAI API key in .env file or environment")
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return False
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try:
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print("Testing mem0 with OpenAI integration...")
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# Get mem0 configuration for OpenAI
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mem0_config = get_mem0_config(config, "openai")
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print(f"✅ Configuration loaded: {list(mem0_config.keys())}")
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# Initialize Memory with OpenAI
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print("Initializing mem0 Memory with OpenAI...")
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memory = Memory.from_config(config_dict=mem0_config)
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print("✅ Memory initialized successfully")
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# Test basic memory operations
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print("\nTesting basic memory operations...")
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# Add a memory
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print("Adding test memory...")
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messages = [
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{"role": "user", "content": "I love machine learning and AI. My favorite framework is PyTorch."},
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{"role": "assistant", "content": "That's great! PyTorch is indeed a powerful framework for AI development."}
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]
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result = memory.add(messages, user_id="test_user")
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print(f"✅ Memory added: {result}")
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# Search memories
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print("\nSearching memories...")
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search_results = memory.search(query="AI framework", user_id="test_user")
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print(f"✅ Search results: {len(search_results)} memories found")
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for i, result in enumerate(search_results):
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print(f" {i+1}. {result['memory'][:100]}...")
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# Get all memories
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print("\nRetrieving all memories...")
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all_memories = memory.get_all(user_id="test_user")
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print(f"✅ Total memories: {len(all_memories)}")
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return True
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except Exception as e:
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print(f"❌ Error during OpenAI integration test: {e}")
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return False
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if __name__ == "__main__":
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success = test_openai_integration()
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if success:
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print("\n🎉 OpenAI integration test passed!")
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else:
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print("\n💥 OpenAI integration test failed!")
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print("\nTo run this test:")
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print("1. Copy .env.example to .env")
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print("2. Add your OpenAI API key to .env")
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print("3. Run: python test_openai.py") |