Fix timezone configuration and Ollama dependencies
- Fix mem0 library hardcoded US/Pacific timezone in Docker build - Add TZ=Europe/Prague environment variable to containers - Add missing ollama Python library to requirements.txt - Add Ollama environment variables to MCP container - Include test scripts for Ollama configuration validation This resolves timestamp issues where memories were created with incorrect Pacific timezone (-07:00) instead of local time (+02:00). 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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Claude Code
@@ -37,6 +37,7 @@ services:
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ports:
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- "${API_PORT:-8080}:8080"
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environment:
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- TZ=Europe/Prague
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- OPENAI_API_KEY=${OPENAI_API_KEY}
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- SUPABASE_CONNECTION_STRING=${SUPABASE_CONNECTION_STRING}
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- NEO4J_URI=neo4j://neo4j:7687
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@@ -71,17 +72,31 @@ services:
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ports:
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- "${MCP_PORT:-8765}:8765"
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environment:
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# System
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- TZ=Europe/Prague
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# LLM Provider Selection
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- LLM_PROVIDER=${LLM_PROVIDER:-openai}
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- EMBEDDER_PROVIDER=${EMBEDDER_PROVIDER:-openai}
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# OpenAI (optional if using Ollama)
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- OPENAI_API_KEY=${OPENAI_API_KEY}
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# Ollama Configuration
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- OLLAMA_BASE_URL=${OLLAMA_BASE_URL:-http://localhost:11434}
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- OLLAMA_LLM_MODEL=${OLLAMA_LLM_MODEL:-llama3.1:8b}
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- OLLAMA_EMBEDDING_MODEL=${OLLAMA_EMBEDDING_MODEL:-nomic-embed-text}
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# Database
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- SUPABASE_CONNECTION_STRING=${SUPABASE_CONNECTION_STRING}
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- NEO4J_URI=neo4j://neo4j:7687
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- NEO4J_USER=${NEO4J_USER:-neo4j}
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- NEO4J_PASSWORD=${NEO4J_PASSWORD}
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# API
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- API_KEY=${API_KEY}
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- MCP_HOST=0.0.0.0
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- MCP_PORT=8765
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# Mem0 Configuration
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- MEM0_COLLECTION_NAME=${MEM0_COLLECTION_NAME:-t6_memories}
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- MEM0_EMBEDDING_DIMS=${MEM0_EMBEDDING_DIMS:-1536}
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- MEM0_VERSION=${MEM0_VERSION:-v1.1}
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# Logging
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- LOG_LEVEL=${LOG_LEVEL:-INFO}
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- ENVIRONMENT=${ENVIRONMENT:-production}
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depends_on:
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@@ -17,6 +17,9 @@ COPY requirements.txt .
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# Install Python dependencies
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RUN pip install --no-cache-dir -r requirements.txt
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# Fix mem0 hardcoded US/Pacific timezone to use system timezone
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RUN sed -i 's/datetime\.now(pytz\.timezone("US\/Pacific"))/datetime.now().astimezone()/g' /usr/local/lib/python3.11/site-packages/mem0/memory/main.py
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# Copy application code
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COPY config.py .
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COPY memory_cleanup.py .
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@@ -20,6 +20,9 @@ vecs==0.4.*
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# mem0ai 0.1.118 requires openai<1.110.0,>=1.90.0
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openai>=1.90.0,<1.110.0
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# Ollama
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ollama>=0.4.0
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# Utilities
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python-dotenv==1.0.*
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httpx==0.28.*
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97
test-ollama-config.py
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97
test-ollama-config.py
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@@ -0,0 +1,97 @@
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#!/usr/bin/env python3
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"""
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Test Ollama configuration
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"""
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import os
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import sys
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from config import get_settings, get_mem0_config
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def test_config():
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"""Test configuration loading with Ollama"""
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print("=" * 60)
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print("Testing Ollama Configuration")
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print("=" * 60)
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# Load settings
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print("\n1. Loading settings from .env...")
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try:
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settings = get_settings()
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print(f" ✓ Settings loaded successfully")
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except Exception as e:
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print(f" ✗ Failed to load settings: {e}")
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return False
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# Display provider configuration
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print(f"\n2. Provider Configuration:")
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print(f" LLM Provider: {settings.llm_provider}")
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print(f" Embedder Provider: {settings.embedder_provider}")
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if settings.llm_provider.lower() == "ollama":
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print(f"\n3. Ollama LLM Settings:")
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print(f" Base URL: {settings.ollama_base_url}")
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print(f" LLM Model: {settings.ollama_llm_model}")
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if settings.embedder_provider.lower() == "ollama":
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print(f"\n4. Ollama Embedder Settings:")
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print(f" Base URL: {settings.ollama_base_url}")
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print(f" Embedding Model: {settings.ollama_embedding_model}")
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print(f" Embedding Dims: {settings.mem0_embedding_dims}")
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# Generate mem0 config
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print(f"\n5. Generating mem0 configuration...")
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try:
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mem0_config = get_mem0_config(settings)
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print(f" ✓ Mem0 config generated successfully")
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except Exception as e:
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print(f" ✗ Failed to generate mem0 config: {e}")
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return False
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# Display mem0 config
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print(f"\n6. Mem0 Configuration:")
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print(f" Vector Store: {mem0_config['vector_store']['provider']}")
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print(f" Graph Store: {mem0_config['graph_store']['provider']}")
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print(f" LLM Provider: {mem0_config['llm']['provider']}")
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print(f" LLM Model: {mem0_config['llm']['config'].get('model', 'N/A')}")
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print(f" Embedder Provider: {mem0_config['embedder']['provider']}")
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print(f" Embedder Model: {mem0_config['embedder']['config'].get('model', 'N/A')}")
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# Test Ollama connectivity
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if settings.llm_provider.lower() == "ollama" or settings.embedder_provider.lower() == "ollama":
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print(f"\n7. Testing Ollama connectivity...")
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import httpx
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try:
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response = httpx.get(f"{settings.ollama_base_url}/api/tags", timeout=5.0)
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if response.status_code == 200:
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print(f" ✓ Ollama is reachable at {settings.ollama_base_url}")
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models = response.json()
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model_names = [m['name'] for m in models.get('models', [])]
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# Check if required models are available
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if settings.llm_provider.lower() == "ollama":
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if settings.ollama_llm_model in model_names or f"{settings.ollama_llm_model}:latest" in model_names:
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print(f" ✓ LLM model '{settings.ollama_llm_model}' is available")
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else:
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print(f" ✗ LLM model '{settings.ollama_llm_model}' not found")
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print(f" Available models: {', '.join(model_names[:5])}")
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if settings.embedder_provider.lower() == "ollama":
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if settings.ollama_embedding_model in model_names or f"{settings.ollama_embedding_model}:latest" in model_names:
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print(f" ✓ Embedding model '{settings.ollama_embedding_model}' is available")
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else:
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print(f" ✗ Embedding model '{settings.ollama_embedding_model}' not found")
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else:
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print(f" ✗ Ollama returned status code: {response.status_code}")
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except Exception as e:
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print(f" ✗ Cannot reach Ollama: {e}")
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print("\n" + "=" * 60)
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print("Configuration test completed successfully!")
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print("=" * 60)
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return True
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if __name__ == "__main__":
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success = test_config()
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sys.exit(0 if success else 1)
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118
test-ollama-memory.py
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118
test-ollama-memory.py
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@@ -0,0 +1,118 @@
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#!/usr/bin/env python3
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"""
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Test memory operations with Ollama
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"""
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import sys
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from mem0 import Memory
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from config import mem0_config
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def test_memory_operations():
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"""Test memory operations with Ollama LLM and embeddings"""
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print("=" * 60)
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print("Testing Memory Operations with Ollama")
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print("=" * 60)
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# Initialize mem0
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print("\n1. Initializing mem0 with Ollama...")
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try:
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memory = Memory.from_config(mem0_config)
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print(" ✓ Mem0 initialized successfully")
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print(f" LLM: {mem0_config['llm']['provider']} ({mem0_config['llm']['config']['model']})")
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print(f" Embedder: {mem0_config['embedder']['provider']} ({mem0_config['embedder']['config']['model']})")
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except Exception as e:
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print(f" ✗ Failed to initialize mem0: {e}")
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return False
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# Test 1: Add memory
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print("\n2. Test: Adding memory...")
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try:
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messages = [
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{"role": "user", "content": "I am testing Ollama integration with local LLM models"},
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{"role": "assistant", "content": "Great! I'll remember that you're testing Ollama."}
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]
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result = memory.add(messages, user_id="ollama_test_user")
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print(f" ✓ Memory added successfully")
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print(f" Result: {result}")
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except Exception as e:
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print(f" ✗ Failed to add memory: {e}")
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return False
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# Test 2: Search memory
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print("\n3. Test: Searching memories...")
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try:
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search_results = memory.search("What am I testing?", user_id="ollama_test_user")
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print(f" ✓ Search completed successfully")
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print(f" Found {len(search_results)} results")
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if search_results:
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for i, result in enumerate(search_results, 1):
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if isinstance(result, dict):
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print(f" Result {i}: {result.get('memory', 'N/A')}")
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else:
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print(f" Result {i}: {result}")
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except Exception as e:
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print(f" ✗ Failed to search memories: {e}")
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import traceback
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traceback.print_exc()
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return False
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# Test 3: Get all memories
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print("\n4. Test: Getting all memories...")
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try:
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all_memories = memory.get_all(user_id="ollama_test_user")
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print(f" ✓ Retrieved all memories successfully")
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print(f" Total memories: {len(all_memories)}")
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except Exception as e:
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print(f" ✗ Failed to get all memories: {e}")
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return False
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# Test 4: Add another memory
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print("\n5. Test: Adding another memory...")
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try:
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messages = [
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{"role": "user", "content": "Ollama provides privacy and cost savings compared to OpenAI"},
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{"role": "assistant", "content": "Noted! Those are great advantages of local LLMs."}
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]
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result = memory.add(messages, user_id="ollama_test_user")
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print(f" ✓ Second memory added successfully")
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except Exception as e:
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print(f" ✗ Failed to add second memory: {e}")
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return False
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# Test 5: Search again
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print("\n6. Test: Searching for Ollama advantages...")
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try:
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search_results = memory.search("What are the benefits of Ollama?", user_id="ollama_test_user")
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print(f" ✓ Search completed successfully")
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print(f" Found {len(search_results)} results")
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if search_results:
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for i, result in enumerate(search_results, 1):
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if isinstance(result, dict):
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memory_text = result.get('memory', str(result))
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score = result.get('score', 0)
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print(f" Result {i} (score: {score:.3f}): {memory_text}")
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else:
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print(f" Result {i}: {result}")
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except Exception as e:
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print(f" ✗ Failed to search memories: {e}")
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return False
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# Test 6: Cleanup
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print("\n7. Test: Cleaning up test data...")
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try:
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memory.delete_all(user_id="ollama_test_user")
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print(f" ✓ Test data cleaned up successfully")
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except Exception as e:
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print(f" ⚠ Warning: Failed to cleanup: {e}")
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print("\n" + "=" * 60)
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print("All memory operations completed successfully!")
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print("Ollama integration is working correctly.")
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print("=" * 60)
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return True
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if __name__ == "__main__":
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success = test_memory_operations()
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sys.exit(0 if success else 1)
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