title	app_file	sdk	sdk_version
Langchain_with_Mongodb	Chatbot.py	gradio	5.12.0

Chatbot with Memory

Welcome to the Chatbot with Memory project! This AI-powered chatbot leverages state-of-the-art frameworks and tools to deliver a coherent and contextual conversational experience. With multi-language support and persistent memory, this chatbot is designed to engage users effectively across sessions.

Key Features

1. LangChain: A robust framework for building applications powered by language models, allowing seamless integration of prompts, memory, and custom workflows.
2. LangGraph: Enhances LangChain by enabling graph-based stateful workflows, ensuring systematic management of conversation states.
3. Memory Integration: Provides the chatbot with the ability to recall previous interactions, offering a consistent and context-aware experience.
4. MongoDB: A NoSQL database for storing chat history persistently, enabling long-term memory even across multiple sessions.
5. Multi-language Support: Allows users to interact with the chatbot in various languages.
6. Gradio Interface: Provides an intuitive and user-friendly interface for seamless interaction.

How It Works

1. User Input: The chatbot captures and processes user queries from multiple users.
2. Chat History: Retrieves and updates conversation logs stored in MongoDB.
3. AI Interaction: Leverages Gemini AI to process queries and provide meaningful responses.
4. Memory Management: Ensures conversational continuity by recalling past interactions.

Resources

For a detailed explanation of how to build a chatbot with memory capabilities, check out this comprehensive tutorial.

Live Demo

Experience the chatbot live on Hugging Face Spaces: Chatbot With Memory

Installation and Setup

1. Clone the Repository

   git clone https://github.com/Tharindu1527/Chatbot_With_Memory.git
   cd Chatbot_With_Memory

2. Install Dependencies Ensure you have Python 3.8 or later installed, then run:

   pip install -r requirements.txt

3. Set Up MongoDB

   • Install and configure MongoDB.
   • Create a database and collection to store chat history.
   • Update the MongoDB connection details in the configuration file.

4. Run the Application

   python Chatbot.py

5. Access the Gradio Interface Open your browser and navigate to http://localhost:7860 to interact with the chatbot.

Usage

• Enter your query in the Gradio interface.
• Choose your preferred language for interaction.
• View responses that consider the chat context and memory.
• Switch between languages as needed for multi-lingual support.

Contributing

Contributions are welcome! Feel free to submit issues or pull requests to improve this project.

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Acknowledgments

Special thanks to the authors of the following resources and tools:

• LangChain
• LangGraph
• Gemini AI
• Gradio
• MongoDB

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We hope you enjoy exploring and using the Chatbot with Memory! If you have any feedback or feature requests, please let us know.