feat(memory): integrate Mem0 for enhanced conversational memory

memory_module/README.md

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+# Memory Module Integration
+
+This module provides memory integration for the chat service using Mem0, allowing the system to remember user preferences and past conversations.
+
+## Features
+
+- **Persistent Memory**: Stores user interactions and preferences
+- **Contextual Responses**: Uses stored memories to provide personalized responses
+- **Memory Search**: Search through stored memories
+- **Memory Management**: View and clear user memories
+
+## Usage
+
+### Basic Chat with Memory
+
+```python
+from api.chat_service import ChatService
+
+# Initialize chat service
+chat_service = ChatService("user_id")
+chat_service.initialize()
+
+# Send a message
+result = chat_service.chat("My name is Alice and I love sci-fi movies")
+print(result["response"])
+```
+
+### Memory Operations
+
+```python
+# Get all memories for a user
+memories = chat_service.get_user_memories()
+
+# Search memories
+search_results = chat_service.search_memories("movies")
+
+# Clear all memories
+chat_service.clear_user_memories()
+```
+
+## Configuration
+
+The Mem0 configuration is defined in `config/config.py`:
+
+```python
+MEM0_CONFIG = {
+    "vector_store": {
+        "provider": "milvus",
+        "config": {
+            "embedding_model_dims": 2048,
+        }
+    },
+    "llm": {
+        "provider": "openai",
+        "config": {
+            "api_key": OPENAI_API_KEY_FROM_CONFIG,
+            "model": "doubao-seed-1-6-250615",
+            "openai_base_url": OPENAI_API_BASE_URL_CONFIG
+        }
+    },
+    "embedder": {
+        "provider": "openai",
+        "config": {
+            "api_key": OPENAI_EMBEDDING_KEY,
+            "model": "doubao-embedding-large-text-250515",
+            "openai_base_url": OPENAI_EMBEDDING_BASE
+        }
+    },
+}
+```
+
+## How It Works
+
+1. **Memory Retrieval**: When a user sends a message, the system searches for relevant memories about the user
+2. **Enhanced Prompt**: The retrieved memories are formatted and included in the prompt to the LLM
+3. **Response Generation**: The LLM generates a response considering the user's memories
+4. **Memory Storage**: The conversation is automatically stored as new memories
+
+## API Endpoints
+
+The main API endpoints remain the same:
+
+- `POST /chat` - Send a message and get a response
+- `GET /health` - Health check
+
+Additional memory management endpoints can be added to the main API if needed.