.env.example

@@ -5,9 +5,11 @@ OPENAI_BASE_URL=https://your-openai-compatible-endpoint.com/v1
 EMBEDDER_API_KEY=AIzaSy-your-google-gemini-api-key-here
 
 # Database Configuration
-QDRANT_HOST=qdrant
+POSTGRES_DB=mem0_db
-QDRANT_PORT=6333
+POSTGRES_USER=mem0_user
-QDRANT_COLLECTION_NAME=mem0
+POSTGRES_PASSWORD=mem0_password
+POSTGRES_HOST=postgres
+POSTGRES_PORT=5432
 
 # Neo4j Configuration
 NEO4J_AUTH=neo4j/mem0_neo4j_password
@@ -34,5 +36,4 @@ EXPERT_MODEL=o3                      # Expert-level comprehensive analysis
 # - Ensure all models are available on your OpenAI-compatible endpoint
 # - Verify model availability: curl -H "Authorization: Bearer $API_KEY" $BASE_URL/v1/models
 # - Neo4j must be version 5.18+ for vector.similarity.cosine() function
-# - Qdrant vector database for embeddings storage (replaces PostgreSQL+pgvector)
+# - Ollama must be running locally with nomic-embed-text:latest model
-# - Ollama must be running locally with nomic-embed-text:latest model

README.md

@@ -1,12 +1,12 @@
 # Mem0 Interface - Production Ready
 
-A fully operational Mem0 interface with Qdrant and Neo4j integration, featuring intelligent model routing, comprehensive memory management, and production-grade monitoring.
+A fully operational Mem0 interface with PostgreSQL and Neo4j integration, featuring intelligent model routing, comprehensive memory management, and production-grade monitoring.
 
 ## Features
 
 ### Core Memory System
 - ✅ **Mem0 OSS Integration**: Complete hybrid datastore (Vector + Graph + KV storage)
-- ✅ **Qdrant**: Purpose-built vector database for high-performance embeddings storage
+- ✅ **PostgreSQL + pgvector**: High-performance vector embeddings storage
 - ✅ **Neo4j 5.18**: Graph relationships with native vector similarity functions
 - ✅ **Google Gemini Embeddings**: Enterprise-grade embedding generation
 - ✅ **Memory Operations**: Store, search, update, delete memories with semantic search
@@ -62,7 +62,7 @@ curl http://localhost:8000/health
 ### Core Components
 - **FastAPI Backend**: Production-ready API with comprehensive monitoring
 - **Mem0 OSS**: Hybrid memory management (vector + graph + key-value)
-- **Qdrant**: Purpose-built vector database for embeddings storage and similarity search
+- **PostgreSQL + pgvector**: Vector embeddings storage and similarity search
 - **Neo4j 5.18**: Graph relationships with native vector functions
 - **Google Gemini**: Enterprise-grade embedding generation
 
@@ -203,13 +203,13 @@ curl http://localhost:8000/graph/relationships/alice
 
 ### Service Dependencies
 - **Neo4j**: Must start before backend for vector functions
-- **Qdrant**: Required for vector storage initialization
+- **PostgreSQL**: Required for vector storage initialization
 - **Ollama**: Must be running locally on port 11434
 - **API Endpoint**: Must have valid models available
 
 ## Production Notes
 
-- **Memory Usage**: Neo4j and Qdrant require adequate RAM for vector operations
+- **Memory Usage**: Neo4j and PostgreSQL require adequate RAM for vector operations
 - **API Rate Limits**: Monitor usage on custom endpoint
 - **Data Persistence**: All data stored in Docker volumes
 - **Scaling**: Individual services can be scaled independently
@@ -217,4 +217,4 @@ curl http://localhost:8000/graph/relationships/alice
 
 ## Development
 
-See individual README files in `backend/` and `frontend/` directories for development setup.
+See individual README files in `backend/` and `frontend/` directories for development setup.

backend/README.md

@@ -9,7 +9,7 @@ A production-ready FastAPI backend that provides intelligent memory integration
 1. **Mem0Manager** (`mem0_manager.py`)
    - Central orchestration of memory operations
    - Integration with custom OpenAI-compatible endpoint
-   - Memory persistence across Qdrant and Neo4j
+   - Memory persistence across PostgreSQL and Neo4j
    - Performance timing and operation tracking
 
 2. **Configuration System** (`config.py`)
@@ -39,8 +39,8 @@ A production-ready FastAPI backend that provides intelligent memory integration
 
 ```
 ┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
-│     Qdrant      │    │     Neo4j       │    │  Custom LLM     │
+│   PostgreSQL    │    │     Neo4j       │    │  Custom LLM     │
-│  (Vector DB)    │    │   (APOC)        │    │   Endpoint      │
+│   (pgvector)    │    │   (APOC)        │    │   Endpoint      │
 ├─────────────────┤    ├─────────────────┤    ├─────────────────┤
 │ • Vector Store  │    │ • Graph Store   │    │ • claude-sonnet-4│
 │ • Embeddings    │    │ • Relationships │    │ • Gemini Embed │
@@ -134,9 +134,11 @@ backend/
 | `OPENAI_COMPAT_API_KEY` | Your custom endpoint API key | - | ✅ |
 | `OPENAI_BASE_URL` | Custom endpoint URL | - | ✅ |
 | `EMBEDDER_API_KEY` | Google Gemini API key for embeddings | - | ✅ |
-| `QDRANT_HOST` | Qdrant vector database host | qdrant | ✅ |
+| `POSTGRES_HOST` | PostgreSQL host | postgres | ✅ |
-| `QDRANT_PORT` | Qdrant vector database port | 6333 | ✅ |
+| `POSTGRES_PORT` | PostgreSQL port | 5432 | ✅ |
-| `QDRANT_COLLECTION_NAME` | Qdrant collection name | mem0 | ✅ |
+| `POSTGRES_DB` | Database name | mem0_db | ✅ |
+| `POSTGRES_USER` | Database user | mem0_user | ✅ |
+| `POSTGRES_PASSWORD` | Database password | - | ✅ |
 | `NEO4J_URI` | Neo4j connection URI | bolt://neo4j:7687 | ✅ |
 | `NEO4J_USERNAME` | Neo4j username | neo4j | ✅ |
 | `NEO4J_PASSWORD` | Neo4j password | - | ✅ |
@@ -281,7 +283,7 @@ docker exec mem0-neo4j cypher-shell -u neo4j -p mem0_neo4j_password \
 
 ### Key Integration Points Verified
 - ✅ **Ollama Embeddings**: nomic-embed-text:latest working for vector generation
-- ✅ **Qdrant**: Vector storage and similarity search operational  
+- ✅ **PostgreSQL + pgvector**: Vector storage and similarity search operational  
 - ✅ **Neo4j 5.18**: Graph relationships and native vector functions working
 - ✅ **Custom LLM Endpoint**: All 4 models accessible and routing correctly
 - ✅ **Memory Persistence**: Data survives container restarts via Docker volumes
@@ -388,7 +390,7 @@ backend:
 #### Dependency Requirements
 - Neo4j 5.18+ (for vector.similarity.cosine function)
 - Ollama running locally with nomic-embed-text:latest
-- Qdrant vector database
+- PostgreSQL with pgvector extension
 - Valid API keys for custom LLM endpoint
 
 ### Debugging Commands
@@ -445,4 +447,4 @@ docker logs mem0-backend --tail 20 -f
 
 ## 📄 License
 
-This POC is designed for demonstration and evaluation purposes.
+This POC is designed for demonstration and evaluation purposes.

backend/config.py

@@ -10,16 +10,18 @@ class Settings(BaseSettings):
     """Application settings loaded from environment variables."""
     
     # API Configuration
-    openai_api_key: str = Field(..., env="OPENAI_COMPAT_API_KEY")
+    openai_api_key: str = Field(..., env="OPENAI_API_KEY")
-    openai_base_url: str = Field(..., env="OPENAI_COMPAT_BASE_URL")
+    openai_base_url: str = Field(..., env="OPENAI_BASE_URL")
     embedder_api_key: str = Field(..., env="EMBEDDER_API_KEY")
 
     # ollama_base_url: str = Field(..., env="OLLAMA_BASE_URL")
 
     # Database Configuration
-    qdrant_host: str = Field("localhost", env="QDRANT_HOST")
+    postgres_host: str = Field("localhost", env="POSTGRES_HOST")
-    qdrant_port: int = Field(6333, env="QDRANT_PORT")
+    postgres_port: int = Field(5432, env="POSTGRES_PORT")
-    qdrant_collection_name: str = Field("mem0", env="QDRANT_COLLECTION_NAME")
+    postgres_db: str = Field("mem0_db", env="POSTGRES_DB")
+    postgres_user: str = Field("mem0_user", env="POSTGRES_USER")
+    postgres_password: str = Field("mem0_password", env="POSTGRES_PASSWORD")
     
     # Neo4j Configuration
     neo4j_uri: str = Field("bolt://localhost:7687", env="NEO4J_URI")
@@ -33,6 +35,10 @@ class Settings(BaseSettings):
     # Model Configuration - Ultra-minimal (single model)
     default_model: str = Field("claude-sonnet-4", env="DEFAULT_MODEL")
     
+    @property
+    def postgres_url(self) -> str:
+        """Build PostgreSQL connection URL."""
+        return f"postgresql://{self.postgres_user}:{self.postgres_password}@{self.postgres_host}:{self.postgres_port}/{self.postgres_db}"
     
     @property
     def cors_origins_list(self) -> List[str]:
@@ -45,4 +51,4 @@ class Settings(BaseSettings):
 
 
 # Global settings instance
-settings = Settings()
+settings = Settings()

backend/mem0_manager.py

@@ -39,13 +39,14 @@ class Mem0Manager:
                 }
             },
             "vector_store": {
-                "provider": "qdrant",
+                "provider": "pgvector",
                 "config": {
-                    "collection_name": settings.qdrant_collection_name,
+                    "dbname": settings.postgres_db,
-                    "host": settings.qdrant_host,
+                    "user": settings.postgres_user,
-                    "port": settings.qdrant_port,
+                    "password": settings.postgres_password,
-                    "embedding_model_dims": 2560,
+                    "host": settings.postgres_host,
-                    "on_disk": True
+                    "port": settings.postgres_port,
+                    "embedding_model_dims": 2560
                 }
             },
             "graph_store": {

backend/requirements.txt

@@ -9,7 +9,8 @@ openai
 google-genai
 
 # Database
-qdrant-client
+psycopg2-binary
+pgvector
 neo4j
 langchain-neo4j
 rank-bm25
@@ -29,4 +30,4 @@ python-json-logger
 
 # CORS and Security
 python-jose[cryptography]
-passlib[bcrypt]
+passlib[bcrypt]

config/postgres-init.sql

@@ -0,0 +1,66 @@
+-- Initialize PostgreSQL database for Mem0 with pgvector extension
+
+-- Create the pgvector extension for vector operations
+CREATE EXTENSION IF NOT EXISTS vector;
+
+-- Create user if not exists (in case it's needed)
+DO
+$do$
+BEGIN
+   IF NOT EXISTS (
+      SELECT FROM pg_catalog.pg_roles
+      WHERE  rolname = 'mem0_user') THEN
+
+      CREATE ROLE mem0_user LOGIN PASSWORD 'mem0_password';
+   END IF;
+END
+$do$;
+
+-- Grant necessary permissions
+GRANT ALL PRIVILEGES ON DATABASE mem0_db TO mem0_user;
+GRANT ALL ON SCHEMA public TO mem0_user;
+
+-- Create table for vector embeddings (if needed by Mem0's pgvector implementation)
+CREATE TABLE IF NOT EXISTS embeddings (
+    id SERIAL PRIMARY KEY,
+    user_id VARCHAR(255),
+    content TEXT,
+    embedding VECTOR(2560),  -- OpenAI embedding dimension
+    metadata JSONB,
+    created_at TIMESTAMP DEFAULT NOW()
+);
+
+-- Create index for efficient vector similarity search
+CREATE INDEX IF NOT EXISTS embeddings_embedding_idx ON embeddings 
+USING ivfflat (embedding vector_cosine_ops) WITH (lists = 100);
+
+-- Create index for user_id lookups
+CREATE INDEX IF NOT EXISTS embeddings_user_id_idx ON embeddings (user_id);
+
+-- Create index for metadata queries
+CREATE INDEX IF NOT EXISTS embeddings_metadata_idx ON embeddings USING GIN (metadata);
+
+-- Grant permissions on the table
+GRANT ALL PRIVILEGES ON TABLE embeddings TO mem0_user;
+GRANT USAGE, SELECT ON SEQUENCE embeddings_id_seq TO mem0_user;
+
+-- Create table for memory history tracking
+CREATE TABLE IF NOT EXISTS memory_history (
+    id SERIAL PRIMARY KEY,
+    memory_id VARCHAR(255),
+    user_id VARCHAR(255),
+    action VARCHAR(50),
+    previous_value TEXT,
+    new_value TEXT,
+    metadata JSONB,
+    created_at TIMESTAMP DEFAULT NOW()
+);
+
+-- Create indexes for memory history
+CREATE INDEX IF NOT EXISTS memory_history_memory_id_idx ON memory_history (memory_id);
+CREATE INDEX IF NOT EXISTS memory_history_user_id_idx ON memory_history (user_id);
+CREATE INDEX IF NOT EXISTS memory_history_created_at_idx ON memory_history (created_at);
+
+-- Grant permissions
+GRANT ALL PRIVILEGES ON TABLE memory_history TO mem0_user;
+GRANT USAGE, SELECT ON SEQUENCE memory_history_id_seq TO mem0_user;

docker-compose.yml

@@ -1,17 +1,20 @@
 services:
-  # Qdrant vector database for vector storage
+  # PostgreSQL with pgvector extension for vector storage
-  qdrant:
+  postgres:
-    image: qdrant/qdrant:latest
+    image: pgvector/pgvector:pg17-trixie
-    container_name: mem0-qdrant
+    container_name: mem0-postgres
+    environment:
+      POSTGRES_DB: ${POSTGRES_DB:-mem0_db}
+      POSTGRES_USER: ${POSTGRES_USER:-mem0_user}
+      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-mem0_password}
     expose:
-      - "6333"
+      - "5432"
     volumes:
-      - qdrant_data:/qdrant/storage
+      - postgres_data:/var/lib/postgresql/data
-    command: >
+      - ./config/postgres-init.sql:/docker-entrypoint-initdb.d/init.sql
-      sh -c "apt-get update && apt-get install -y curl && ./entrypoint.sh"
     healthcheck:
-      test: ["CMD", "curl", "-f", "http://localhost:6333/"]
+      test: ["CMD-SHELL", "pg_isready -U ${POSTGRES_USER:-mem0_user} -d ${POSTGRES_DB:-mem0_db}"]
-      interval: 10s
+      interval: 5s
       timeout: 5s
       retries: 5
     restart: unless-stopped
@@ -54,9 +57,11 @@ services:
       OPENAI_API_KEY: ${OPENAI_COMPAT_API_KEY}
       OPENAI_BASE_URL: ${OPENAI_COMPAT_BASE_URL}
       EMBEDDER_API_KEY: ${EMBEDDER_API_KEY:-AIzaSyA_}
-      QDRANT_HOST: qdrant
+      POSTGRES_HOST: postgres
-      QDRANT_PORT: 6333
+      POSTGRES_PORT: 5432
-      QDRANT_COLLECTION_NAME: ${QDRANT_COLLECTION_NAME:-mem0}
+      POSTGRES_DB: ${POSTGRES_DB:-mem0_db}
+      POSTGRES_USER: ${POSTGRES_USER:-mem0_user}
+      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-mem0_password}
       NEO4J_URI: bolt://neo4j:7687
       NEO4J_USERNAME: ${NEO4J_USERNAME:-neo4j}
       NEO4J_PASSWORD: ${NEO4J_PASSWORD:-mem0_neo4j_password}
@@ -66,7 +71,7 @@ services:
     ports:
       - "${BACKEND_PORT:-8000}:8000"
     depends_on:
-      qdrant:
+      postgres:
         condition: service_healthy
       neo4j:
         condition: service_healthy
@@ -76,7 +81,7 @@ services:
     command: ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000", "--reload"]
 
 volumes:
-  qdrant_data:
+  postgres_data:
   neo4j_data:
   neo4j_logs:
   neo4j_import:
@@ -84,4 +89,4 @@ volumes:
 
 networks:
   default:
-    name: mem0-network
+    name: mem0-network

frontend/index.html

@@ -37,14 +37,7 @@
             padding: 20px;
             background: #fafafa;
             border-bottom: 1px solid #e0e0e0;
-            display: flex;
-            justify-content: space-between;
-            align-items: center;
-        }
-
-        .chat-header-content {
             text-align: center;
-            flex: 1;
         }
 
         .chat-header h1 {
@@ -58,31 +51,6 @@
             font-size: 14px;
         }
 
-        .clear-chat-btn {
-            background: #f8f9fa;
-            color: #666;
-            border: 1px solid #e0e0e0;
-            padding: 8px 12px;
-            border-radius: 6px;
-            cursor: pointer;
-            font-size: 12px;
-            font-weight: 500;
-            display: flex;
-            align-items: center;
-            gap: 5px;
-            transition: all 0.2s ease;
-        }
-
-        .clear-chat-btn:hover {
-            background: #e9ecef;
-            border-color: #ced4da;
-            color: #495057;
-        }
-
-        .clear-chat-btn:active {
-            background: #dee2e6;
-        }
-
         .chat-messages {
             flex: 1;
             overflow-y: auto;
@@ -274,13 +242,8 @@
         <!-- Chat Section -->
         <div class="chat-section">
             <div class="chat-header">
-                <div class="chat-header-content">
+                <h1>What can I help you with?</h1>
-                    <h1>What can I help you with?</h1>
+                <p>Chat with your memories - User: pratik</p>
-                    <p>Chat with your memories - User: pratik</p>
-                </div>
-                <button class="clear-chat-btn" id="clearChatBtn" title="Clear chat history">
-                    🗑️ Clear Chat
-                </button>
             </div>
             
             <div class="chat-messages" id="chatMessages">
@@ -318,7 +281,6 @@
         const memoriesList = document.getElementById('memoriesList');
         const memoryCount = document.getElementById('memoryCount');
         const refreshButton = document.getElementById('refreshMemories');
-        const clearChatBtn = document.getElementById('clearChatBtn');
 
         // Chat history in localStorage
         let chatHistory = JSON.parse(localStorage.getItem('chatHistory') || '[]');
@@ -334,7 +296,6 @@
                 if (e.key === 'Enter') sendMessage();
             });
             refreshButton.addEventListener('click', loadMemories);
-            clearChatBtn.addEventListener('click', clearChatWithConfirmation);
         });
 
         // Load chat history from localStorage
@@ -532,13 +493,6 @@
             }, 5000);
         }
 
-        // Clear chat history with confirmation
-        function clearChatWithConfirmation() {
-            if (confirm('Are you sure you want to clear the chat history? This action cannot be undone.')) {
-                clearChatHistory();
-            }
-        }
-
         // Clear chat history (for debugging)
         function clearChatHistory() {
             chatHistory = [];