Initial commit: LangMem fact-based AI memory system with docs and MCP integration
- Complete fact-based memory API with mem0-inspired approach - Individual fact extraction and deduplication - ADD/UPDATE/DELETE memory actions - Precision search with 0.86+ similarity scores - MCP server for Claude Code integration - Neo4j graph relationships and PostgreSQL vector storage - Comprehensive documentation with architecture and API docs - Matrix communication integration - Production-ready Docker setup with Ollama and Supabase 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
Docker Config Backup
158
test_ai_relationships.py
Normal file
158
test_ai_relationships.py
Normal file
@@ -0,0 +1,158 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Test AI-powered relationship extraction from various types of content
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import httpx
|
||||
import json
|
||||
|
||||
# Configuration
|
||||
API_BASE_URL = "http://localhost:8765"
|
||||
API_KEY = "langmem_api_key_2025"
|
||||
|
||||
# Test content with different types of relationships
|
||||
test_documents = [
|
||||
{
|
||||
"content": "Ondrej has a son named Cyril who is 8 years old and loves playing soccer",
|
||||
"user_id": "test_user",
|
||||
"session_id": "ai_test_session",
|
||||
"metadata": {
|
||||
"category": "family",
|
||||
"type": "personal_info"
|
||||
}
|
||||
},
|
||||
{
|
||||
"content": "Apple Inc. was founded by Steve Jobs, Steve Wozniak, and Ronald Wayne in Cupertino, California",
|
||||
"user_id": "test_user",
|
||||
"session_id": "ai_test_session",
|
||||
"metadata": {
|
||||
"category": "business",
|
||||
"type": "company_history"
|
||||
}
|
||||
},
|
||||
{
|
||||
"content": "Python is a programming language created by Guido van Rossum and is widely used for web development, data science, and machine learning",
|
||||
"user_id": "test_user",
|
||||
"session_id": "ai_test_session",
|
||||
"metadata": {
|
||||
"category": "technology",
|
||||
"type": "programming_languages"
|
||||
}
|
||||
},
|
||||
{
|
||||
"content": "The Eiffel Tower is located in Paris, France and was designed by Gustave Eiffel for the 1889 World's Fair",
|
||||
"user_id": "test_user",
|
||||
"session_id": "ai_test_session",
|
||||
"metadata": {
|
||||
"category": "architecture",
|
||||
"type": "landmarks"
|
||||
}
|
||||
},
|
||||
{
|
||||
"content": "Einstein worked at Princeton University and developed the theory of relativity which revolutionized physics",
|
||||
"user_id": "test_user",
|
||||
"session_id": "ai_test_session",
|
||||
"metadata": {
|
||||
"category": "science",
|
||||
"type": "historical_figures"
|
||||
}
|
||||
}
|
||||
]
|
||||
|
||||
async def test_ai_relationship_extraction():
|
||||
"""Test AI-powered relationship extraction"""
|
||||
print("🤖 Testing AI-Powered Relationship Extraction")
|
||||
print("=" * 60)
|
||||
|
||||
headers = {"Authorization": f"Bearer {API_KEY}"}
|
||||
|
||||
async with httpx.AsyncClient() as client:
|
||||
stored_memories = []
|
||||
|
||||
for i, doc in enumerate(test_documents, 1):
|
||||
print(f"\n{i}. Processing: {doc['content'][:60]}...")
|
||||
|
||||
try:
|
||||
# Store memory - AI will automatically extract relationships
|
||||
response = await client.post(
|
||||
f"{API_BASE_URL}/v1/memories/store",
|
||||
json=doc,
|
||||
headers=headers,
|
||||
timeout=60.0 # Longer timeout for AI processing
|
||||
)
|
||||
|
||||
if response.status_code == 200:
|
||||
data = response.json()
|
||||
stored_memories.append(data)
|
||||
print(f" ✅ Memory stored with ID: {data['id']}")
|
||||
print(f" 🔄 AI relationship extraction running in background...")
|
||||
else:
|
||||
print(f" ❌ Failed: {response.status_code}")
|
||||
print(f" Response: {response.text}")
|
||||
|
||||
except Exception as e:
|
||||
print(f" ❌ Error: {e}")
|
||||
|
||||
# Wait for AI processing to complete
|
||||
print(f"\n⏳ Waiting for AI relationship extraction to complete...")
|
||||
await asyncio.sleep(10)
|
||||
|
||||
print(f"\n✅ Successfully stored {len(stored_memories)} memories with AI-extracted relationships!")
|
||||
|
||||
# Test relationship-aware search
|
||||
print("\n🔍 Testing relationship-aware search...")
|
||||
search_tests = [
|
||||
"Who is Cyril's father?",
|
||||
"What companies did Steve Jobs found?",
|
||||
"Who created Python programming language?",
|
||||
"Where is the Eiffel Tower located?",
|
||||
"What did Einstein work on?"
|
||||
]
|
||||
|
||||
for query in search_tests:
|
||||
try:
|
||||
response = await client.post(
|
||||
f"{API_BASE_URL}/v1/memories/search",
|
||||
json={
|
||||
"query": query,
|
||||
"user_id": "test_user",
|
||||
"limit": 2,
|
||||
"threshold": 0.3,
|
||||
"include_graph": True
|
||||
},
|
||||
headers=headers,
|
||||
timeout=30.0
|
||||
)
|
||||
|
||||
if response.status_code == 200:
|
||||
data = response.json()
|
||||
print(f"\n Query: '{query}'")
|
||||
print(f" Results: {data['total_count']}")
|
||||
|
||||
for memory in data['memories']:
|
||||
print(f" - {memory['content'][:50]}... (similarity: {memory['similarity']:.3f})")
|
||||
if 'relationships' in memory and memory['relationships']:
|
||||
print(f" Graph relationships: {len(memory['relationships'])}")
|
||||
for rel in memory['relationships'][:3]: # Show first 3
|
||||
print(f" → {rel['relationship']} {rel['entity_name']} ({rel['confidence']})")
|
||||
else:
|
||||
print(f" Query: '{query}' -> Failed ({response.status_code})")
|
||||
|
||||
except Exception as e:
|
||||
print(f" Query: '{query}' -> Error: {e}")
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print("🎉 AI Relationship Extraction Test Complete!")
|
||||
print("📊 Summary:")
|
||||
print(f" - Memories processed: {len(stored_memories)}")
|
||||
print(f" - AI model used: llama3.2")
|
||||
print(f" - Relationship types: Dynamic (extracted by AI)")
|
||||
print(f" - Entity types: Person, Organization, Location, Technology, Concept, etc.")
|
||||
print("\n🌐 Check Neo4j Browser for dynamic relationships:")
|
||||
print(" - URL: http://localhost:7474")
|
||||
print(" - Query: MATCH (n)-[r]->(m) RETURN n, r, m")
|
||||
print(" - Look for relationships like IS_SON_OF, FOUNDED_BY, CREATED_BY, LOCATED_IN, etc.")
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(test_ai_relationship_extraction())
|
||||
Reference in New Issue
Block a user