PHASE 1 COMPLETE: mem0 + Supabase integration tested and working
✅ 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>
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Docker Config Backup
133
inspect_supabase_data.py
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133
inspect_supabase_data.py
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#!/usr/bin/env python3
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"""
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Inspect current data in Supabase database
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"""
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import psycopg2
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import json
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def inspect_supabase_data():
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"""Inspect all data currently stored in Supabase"""
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print("=" * 70)
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print("SUPABASE DATABASE INSPECTION")
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print("=" * 70)
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connection_string = "postgresql://supabase_admin:CzkaYmRvc26Y@localhost:5435/postgres"
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try:
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conn = psycopg2.connect(connection_string)
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cursor = conn.cursor()
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# Get all tables in vecs schema
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print("📊 All tables in vecs schema:")
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cursor.execute("SELECT table_name FROM information_schema.tables WHERE table_schema = 'vecs';")
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tables = cursor.fetchall()
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table_names = [t[0] for t in tables]
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print(f" Tables: {table_names}")
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for table_name in table_names:
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print(f"\n🔍 Inspecting table: {table_name}")
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try:
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# Get table structure
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cursor.execute(f"""
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SELECT column_name, data_type, is_nullable
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FROM information_schema.columns
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WHERE table_schema = 'vecs' AND table_name = %s
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ORDER BY ordinal_position;
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""", (table_name,))
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columns = cursor.fetchall()
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print(" Table structure:")
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for col in columns:
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print(f" - {col[0]}: {col[1]} (nullable: {col[2]})")
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# Get record count
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cursor.execute(f'SELECT COUNT(*) FROM vecs."{table_name}";')
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count = cursor.fetchone()[0]
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print(f" Record count: {count}")
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if count > 0:
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# Get sample records
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cursor.execute(f"""
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SELECT id, metadata,
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CASE WHEN vec IS NOT NULL THEN 'Vector present' ELSE 'No vector' END as vec_status
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FROM vecs."{table_name}"
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LIMIT 5;
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""")
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records = cursor.fetchall()
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print(" Sample records:")
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for i, record in enumerate(records):
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record_id = record[0]
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metadata = record[1] if record[1] else {}
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vec_status = record[2]
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print(f" Record {i+1}:")
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print(f" ID: {record_id}")
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print(f" Vector: {vec_status}")
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if isinstance(metadata, dict):
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print(f" Metadata keys: {list(metadata.keys())}")
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if 'user_id' in metadata:
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print(f" User ID: {metadata['user_id']}")
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if 'content' in metadata:
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content = metadata['content'][:100] + "..." if len(str(metadata['content'])) > 100 else metadata['content']
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print(f" Content: {content}")
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if 'created_at' in metadata:
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print(f" Created: {metadata['created_at']}")
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else:
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print(f" Metadata: {metadata}")
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print()
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except Exception as e:
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print(f" ❌ Error inspecting {table_name}: {e}")
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# Summary statistics
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print("\n📊 SUMMARY:")
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total_records = 0
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for table_name in table_names:
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try:
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cursor.execute(f'SELECT COUNT(*) FROM vecs."{table_name}";')
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count = cursor.fetchone()[0]
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total_records += count
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print(f" {table_name}: {count} records")
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except:
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print(f" {table_name}: Error getting count")
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print(f" Total records across all tables: {total_records}")
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# Check for different users
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print("\n👥 USER ANALYSIS:")
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for table_name in table_names:
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try:
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cursor.execute(f"""
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SELECT metadata->>'user_id' as user_id, COUNT(*) as count
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FROM vecs."{table_name}"
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WHERE metadata->>'user_id' IS NOT NULL
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GROUP BY metadata->>'user_id'
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ORDER BY count DESC;
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""")
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users = cursor.fetchall()
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if users:
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print(f" {table_name} users:")
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for user, count in users:
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print(f" - {user}: {count} memories")
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else:
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print(f" {table_name}: No user data found")
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except Exception as e:
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print(f" Error analyzing users in {table_name}: {e}")
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cursor.close()
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conn.close()
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print("\n" + "=" * 70)
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print("🎉 DATABASE INSPECTION COMPLETE")
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print("=" * 70)
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except Exception as e:
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print(f"❌ Inspection failed: {str(e)}")
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import traceback
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traceback.print_exc()
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if __name__ == "__main__":
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inspect_supabase_data()
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