t6_mem0_v2/UPGRADE_SUMMARY.md

T6 Mem0 v2 - mem0ai 0.1.118 Upgrade Summary

Date: 2025-10-15 Upgrade: mem0ai v0.1.101 → v0.1.118

Issue Discovered

While testing the MCP server, encountered a critical bug in mem0ai v0.1.101:

AttributeError: 'list' object has no attribute 'id'

This error occurred in mem0's internal _get_all_from_vector_store method at line 580, indicating a bug in the library itself.

Root Cause

In mem0ai v0.1.101, the get_all() method had a bug where it tried to access .id attribute on a list object instead of iterating over the list properly.

Solution

1. Upgraded mem0ai Library

Previous version: 0.1.101 New version: 0.1.118 (latest stable release)

The upgrade fixed the internal bug and changed the return format of both get_all() and search() methods:

Old format (v0.1.101):

• get_all() - Attempted to return list but had bugs
• search() - Returned list directly

New format (v0.1.118):

• get_all() - Returns dict: {'results': [...], 'relations': [...]}
• search() - Returns dict: {'results': [...], 'relations': [...]}

2. Code Updates

Updated both REST API and MCP server code to handle the new dict format:

REST API (api/memory_service.py)

search_memories (lines 111-120):

result = self.memory.search(...)
# In mem0 v0.1.118+, search returns dict with 'results' key
memories_list = result.get('results', []) if isinstance(result, dict) else result

get_all_memories (lines 203-210):

result = self.memory.get_all(...)
# In mem0 v0.1.118+, get_all returns dict with 'results' key
memories_list = result.get('results', []) if isinstance(result, dict) else result

MCP Server (mcp_server/tools.py)

handle_search_memories (lines 215-223):

result = self.memory.search(...)
# In mem0 v0.1.118+, search returns dict with 'results' key
memories = result.get('results', []) if isinstance(result, dict) else result

handle_get_all_memories (lines 279-285):

result = self.memory.get_all(...)
# In mem0 v0.1.118+, get_all returns dict with 'results' key
memories = result.get('results', []) if isinstance(result, dict) else result

3. Dependencies Updated

requirements.txt changes:

# Core Memory System
- mem0ai[graph]==0.1.*
+ # Requires >=0.1.118 for get_all() and search() dict return format fix
+ mem0ai[graph]>=0.1.118,<0.2.0

# Web Framework
- pydantic==2.9.*
+ pydantic>=2.7.3,<3.0

# OpenAI
- openai==1.58.*
+ # mem0ai 0.1.118 requires openai<1.110.0,>=1.90.0
+ openai>=1.90.0,<1.110.0

Testing Results

MCP Server Live Test

All 7 MCP tools tested successfully:

✅ add_memory - Working correctly ✅ search_memories - Working correctly (fixed with v0.1.118) ✅ get_memory - Working correctly ✅ get_all_memories - Working correctly (fixed with v0.1.118) ✅ update_memory - Working correctly ✅ delete_memory - Working correctly ✅ delete_all_memories - Working correctly

Sample Test Output

[4/6] Testing search_memories...
Found 3 relevant memory(ies):

1. Loves Python
   ID: 4580c26a-11e1-481d-b06f-9a2ba71c71c9
   Relevance: 61.82%

2. Is a software engineer
   ID: 7848e945-d5f1-4048-99e8-c581b8388f43
   Relevance: 64.86%

3. Loves TypeScript
   ID: 9d4a3566-5374-4d31-9dfb-30a1686641d0
   Relevance: 71.95%

[5/6] Testing get_all_memories...
Retrieved 3 memory(ies):

1. Is a software engineer
   ID: 7848e945-d5f1-4048-99e8-c581b8388f43

2. Loves Python
   ID: 4580c26a-11e1-481d-b06f-9a2ba71c71c9

3. Loves TypeScript
   ID: 9d4a3566-5374-4d31-9dfb-30a1686641d0

REST API Health Check

{
    "status": "healthy",
    "version": "0.1.0",
    "timestamp": "2025-10-15T06:26:26.341277",
    "dependencies": {
        "mem0": "healthy"
    }
}

Deployment Status

✅ Docker Containers Rebuilt: API and MCP server containers rebuilt with mem0ai 0.1.118 ✅ Containers Restarted: All containers running with updated code ✅ Health Checks Passing: API and Neo4j containers healthy

Container Status

• t6-mem0-api - Up and healthy
• t6-mem0-mcp - Up and running with stdio transport
• t6-mem0-neo4j - Up and healthy

Files Modified

1. /home/klas/mem0/api/memory_service.py - Updated search_memories and get_all_memories methods
2. /home/klas/mem0/mcp_server/tools.py - Updated handle_search_memories and handle_get_all_memories methods
3. /home/klas/mem0/requirements.txt - Updated mem0ai, pydantic, and openai version constraints
4. /home/klas/mem0/docker-compose.yml - No changes needed (uses requirements.txt)

Testing Scripts Created

1. /home/klas/mem0/test-mcp-server-live.py - Comprehensive MCP server test suite
2. /home/klas/mem0/MCP_SETUP.md - Complete MCP server documentation

Breaking Changes

The upgrade maintains backward compatibility through defensive coding:

# Handles both old list format and new dict format
memories_list = result.get('results', []) if isinstance(result, dict) else result

This ensures the code works with both:

• Older mem0 versions that might return lists
• New mem0 v0.1.118+ that returns dicts

Recommendations

1. Monitor logs for any Pydantic deprecation warnings (cosmetic, not critical)
2. Test n8n workflows using the mem0 API to verify compatibility
3. Consider updating config.py to use ConfigDict instead of class-based config (Pydantic v2 best practice)

Conclusion

✅ Successfully upgraded to mem0ai 0.1.118 ✅ Fixed critical get_all() bug ✅ Updated all code to handle new dict return format ✅ All MCP tools tested and working ✅ Docker containers rebuilt and deployed ✅ System fully operational

The upgrade resolves the core issue while maintaining backward compatibility and improving reliability of both the REST API and MCP server.