7e3ba093c4
✅ PHASE 1 ACHIEVEMENTS: - Successfully migrated from Qdrant to self-hosted Supabase - Fixed mem0 Supabase integration collection naming issues - Resolved vector dimension mismatches (1536→768 for Ollama) - All containers connected to localai docker network - Comprehensive documentation updates completed ✅ TESTING COMPLETED: - Database storage verification: Data properly stored in PostgreSQL - Vector operations: 768-dimensional embeddings working perfectly - Memory operations: Add, search, retrieve, delete all functional - Multi-user support: User isolation verified - LLM integration: Ollama qwen2.5:7b + nomic-embed-text operational - Search functionality: Semantic search with relevance scores working ✅ INFRASTRUCTURE READY: - Supabase PostgreSQL with pgvector: ✅ OPERATIONAL - Neo4j graph database: ✅ READY (for Phase 2) - Ollama LLM + embeddings: ✅ WORKING - mem0 v0.1.115: ✅ FULLY FUNCTIONAL PHASE 2 READY: Core memory system and API development can begin 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
79 lines
2.9 KiB
Python
79 lines
2.9 KiB
Python
#!/usr/bin/env python3
|
|
"""
|
|
Debug vecs library collection naming
|
|
"""
|
|
|
|
import vecs
|
|
import traceback
|
|
|
|
def debug_vecs_naming():
|
|
"""Debug the vecs collection naming issue"""
|
|
print("=" * 60)
|
|
print("VECS COLLECTION NAMING DEBUG")
|
|
print("=" * 60)
|
|
|
|
connection_string = "postgresql://supabase_admin:CzkaYmRvc26Y@localhost:5435/postgres"
|
|
|
|
try:
|
|
print("🔌 Connecting to database...")
|
|
db = vecs.create_client(connection_string)
|
|
print("✅ Connected successfully")
|
|
|
|
print("\n📋 Listing existing collections...")
|
|
collections = db.list_collections()
|
|
print(f"Existing collections: {collections}")
|
|
|
|
# Test different collection names
|
|
test_names = [
|
|
"mem0_vectors",
|
|
"mem0_working_test",
|
|
"simple_test",
|
|
"test123",
|
|
"debugtest"
|
|
]
|
|
|
|
for name in test_names:
|
|
print(f"\n🧪 Testing collection name: '{name}'")
|
|
try:
|
|
# Try to get or create collection
|
|
collection = db.get_or_create_collection(name=name, dimension=128)
|
|
print(f" ✅ Created/Retrieved: {collection.name}")
|
|
|
|
# Check actual table name in database
|
|
print(f" 📊 Collection info: {collection.describe()}")
|
|
|
|
# Clean up test collection
|
|
db.delete_collection(name)
|
|
print(f" 🗑️ Cleaned up collection: {name}")
|
|
|
|
except Exception as e:
|
|
print(f" ❌ Failed: {str(e)}")
|
|
print(f" Error type: {type(e).__name__}")
|
|
if "DuplicateTable" in str(e):
|
|
print(f" 🔍 Table already exists, examining error...")
|
|
# Extract the actual table name from error
|
|
error_str = str(e)
|
|
if 'relation "' in error_str:
|
|
start = error_str.find('relation "') + len('relation "')
|
|
end = error_str.find('" already exists', start)
|
|
if end > start:
|
|
actual_table = error_str[start:end]
|
|
print(f" 📋 Actual table name attempted: {actual_table}")
|
|
|
|
print("\n🔍 Checking database schema for existing tables...")
|
|
# Connect directly to check tables
|
|
import psycopg2
|
|
conn = psycopg2.connect("postgresql://supabase_admin:CzkaYmRvc26Y@localhost:5435/postgres")
|
|
cur = conn.cursor()
|
|
cur.execute("SELECT table_name FROM information_schema.tables WHERE table_schema = 'vecs';")
|
|
tables = cur.fetchall()
|
|
print(f"Tables in 'vecs' schema: {[t[0] for t in tables]}")
|
|
cur.close()
|
|
conn.close()
|
|
|
|
except Exception as e:
|
|
print(f"❌ Debug failed: {str(e)}")
|
|
traceback.print_exc()
|
|
|
|
if __name__ == "__main__":
|
|
debug_vecs_naming() |