https://github.com/mzazakeith/mem0chat
Mem0Chat is an application showcasing an LLM-powered chat with a model-agnostic persistent memory layer powered by mem0. It enables context-aware conversations, using mem0's memory management to retain and utilize key memories across sessions/chats for a personalized, efficient user experience.
https://github.com/mzazakeith/mem0chat
ai chat llm llm-chat mem0 mem0ai memory
Last synced: about 1 month ago
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Mem0Chat is an application showcasing an LLM-powered chat with a model-agnostic persistent memory layer powered by mem0. It enables context-aware conversations, using mem0's memory management to retain and utilize key memories across sessions/chats for a personalized, efficient user experience.
- Host: GitHub
- URL: https://github.com/mzazakeith/mem0chat
- Owner: mzazakeith
- License: mit
- Created: 2025-05-15T17:57:27.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-05-16T04:04:11.000Z (about 1 year ago)
- Last Synced: 2025-07-01T02:41:05.187Z (about 1 year ago)
- Topics: ai, chat, llm, llm-chat, mem0, mem0ai, memory
- Language: JavaScript
- Homepage:
- Size: 835 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Mem0Chat - AI Chat with Persistent Memory
This project is a Next.js application demonstrating an AI chat interface with a persistent memory layer powered by [Mem0.ai](https://mem0.ai/). It allows users to have conversations with various AI models, where the AI can recall information from previous interactions to provide more personalized and context-aware responses.
## Key Features
* **AI Chat Interface:** Chat UI built with Next.js, React, Radix UI, and Tailwind CSS.
* **Chat History Sidebar:** Displays a list of past chat sessions, allowing users to easily navigate and revisit conversations. Stored locally using Dexie.js.
* **Persistent Memory:** Utilizes [Mem0.ai](https://github.com/mem0ai/mem0) as "The Memory Layer for your AI Agents," enabling the chat application to remember user preferences or anything the user needs it to.
* **Configurable AI Models:** Supports multiple AI models from Google (Gemini series) and OpenRouter (e.g., DeepSeek, Llama, Qwen). Users can set global default models and override them per chat session.
* **Client-Side Data Persistence:** Leverages Dexie.js (IndexedDB wrapper) to store chat sessions, messages, and a local cache of memories, enabling faster load times and some offline access.
* **Dynamic Title Generation:** Automatically generates concise titles for new chat conversations based on the initial message content.
* **Real-time Streaming:** Streams AI responses for a smooth and interactive user experience using the Vercel AI SDK.
* **Theming:** Supports light and dark modes.
* **Animated UI:** Uses Framer Motion for subtle UI animations.
### Settings Overview
The application provides a "Default Settings" drawer where users can configure global preferences:
* Toggle global memory activation.
* Set the default AI model for chat.
* Set the default AI model for title generation.
## Key Features in Action
### Memory Persistence
**1. Conversation without memory:** The AI responds without prior knowledge.
**2. Conversation with memory:** After a relevant memory is added (e.g., "Prefers coffee to tea"), the AI uses this information in its response. The "My Memories" panel shows the active memories.
## Technologies Used
* **Framework:** Next.js 15
* **Memory Layer:** [Mem0.ai](https://github.com/mem0ai/mem0) (`mem0ai` SDK)
* **AI Model Providers:**
* Google (Gemini series)
* OpenRouter (DeepSeek, Llama, Qwen, etc.)
* **UI Components:** Radix UI, Shadcn/ui
* **Styling:** Tailwind CSS
* **Animations:** Framer Motion
* **Client-Side Database:** Dexie.js (IndexedDB wrapper)
* **Icons:** Lucide React
## Mem0.ai Integration
This project integrates [Mem0.ai](https://github.com/mem0ai/mem0) to provide a persistent memory layer for the AI. As described on their website, "Mem0 is a self-improving memory layer for LLM applications, enabling personalized AI experiences that save costs and delight users."
Key aspects of the Mem0.ai integration in this project:
* **Memory Storage:** User interactions and explicitly added memories are stored via the Mem0.ai service.
* **Contextual Retrieval:** Before sending a query to an AI model, the application searches Mem0.ai for relevant memories based on the current conversation context.
* **Enhanced Prompts:** Retrieved memories are injected into the system prompt, providing the AI model with historical context and user preferences.
* **Personalization:** This allows the AI to "remember" past interactions and tailor its responses accordingly.
* **Client-Side Caching:** Memories fetched from Mem0.ai are cached locally using Dexie.js to improve performance.
The application uses the `mem0ai` JavaScript SDK to interact with the Mem0 Platform (Cloud version).
## Setup and Installation
1. **Clone the repository:**
```bash
git clone https://github.com/mzazakeith/Mem0Chat.git
cd Mem0Chat
```
2. **Install dependencies:**
```bash
npm install
# or
# yarn install
# or
# pnpm install
```
3. **Set up environment variables:**
Create a `.env.local` file in the root of the project and add the following environment variables:
```env
# Mem0.ai Credentials (Required for memory functionality)
MEM0_API_KEY="your_mem0_api_key"
MEM0_PROJECT_ID="your_mem0_project_id"
# OpenRouter API Key (Required if using OpenRouter models)
OPENROUTER_API_KEY="your_openrouter_api_key"
# Google API Key
GOOGLE_GENERATIVE_AI_API_KEY="your_google_api_key"
```
* Obtain your `MEM0_API_KEY` and `MEM0_PROJECT_ID` from your [Mem0.ai dashboard](https://mem0.ai/).
* Obtain your `OPENROUTER_API_KEY` from your [OpenRouter dashboard](https://openrouter.ai/).
4. **Run the development server:**
```bash
npm run dev
```
The application should now be running on [http://localhost:3000](http://localhost:3000).
## Acknowledgements
* **[Mem0.ai](https://mem0.ai/):** For providing the intelligent memory layer.
* **Vercel AI SDK:** For simplifying AI model integration and streaming.