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https://github.com/tushar2704/llm_chatbot_streamlit
Streamlit application called T-BOT, using HugChat
https://github.com/tushar2704/llm_chatbot_streamlit
artificial-intelligence chatbot data-science hugchat huggingface llama llm
Last synced: 19 days ago
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Streamlit application called T-BOT, using HugChat
- Host: GitHub
- URL: https://github.com/tushar2704/llm_chatbot_streamlit
- Owner: tushar2704
- Created: 2023-05-14T23:22:37.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-05-31T04:22:57.000Z (over 1 year ago)
- Last Synced: 2024-10-29T09:00:31.421Z (3 months ago)
- Topics: artificial-intelligence, chatbot, data-science, hugchat, huggingface, llama, llm
- Language: Python
- Homepage: https://tushar2704-llm-chatbot-streamlit-chatbot-dssay9.streamlit.app/
- Size: 16.6 KB
- Stars: 2
- Watchers: 1
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# LLM_ChatBot_streamlit
LLM_ChatBot_streamlit- T-BOT, is an amazing chatbot application powered by the latest natural language processing technology. It is designed to provide a seamless conversational experience and assist users in various tasks. This repository contains the code and resources required to deploy the chatbot using Streamlit.
- Using HugChat, an innovative and versatile Python package designed to simplify the development of chatbot applications. With HugChat, developers can quickly and effortlessly create intelligent conversational agents that interact with users in a natural and engaging manner.
## Features
- Natural language processing capabilities
- Contextual understanding of user queries
- Rich and engaging conversation flow
- Seamless integration with Streamlit
- Easy-to-use and interactive user interface
- Front-end: The user submits an input prompt (by providing a string of text to the text box via st.text_input()), and the app generates a response.
- Back-end: Input prompt is sent to hugchat (the unofficial port to the HuggingChat API) via streamlit-chat for generating a response.
- Front-end: Generated responses are displayed in the app via's message() command.
## Installation
To run the LLM_ChatBot_streamlit locally, you need to follow these steps:
1. Clone the repository:
```bash
git clone https://github.com/tushar2704/LLM_ChatBot_streamlit.git
cd LLM_ChatBot_streamlit
```
2. Install the dependencies:
```bash
pip install -r requirements.txt
```
3. Run the Streamlit app:
```bash
streamlit run chatbot.py
```
This command will start the Streamlit app and you can access it in your web browser.
## Usage
Once the application is running, you can interact with the chatbot through the user interface. The chatbot will respond to your queries and engage in a conversation with you. Feel free to explore its features and capabilities.
## Deployment
The LLM_ChatBot_streamlit app is deployed using Streamlit Sharing, allowing you to access it directly from your web browser. Here are the deployment links:
[](https://tushar2704-llm-chatbot-streamlit-chatbot-dssay9.streamlit.app/)
## Demo
You can find a live demo of the LLM_ChatBot_streamlit app in action at the following link:
- [Demo](https://tushar2704-llm-chatbot-streamlit-chatbot-dssay9.streamlit.app/)
## Author
- ©2023 Tushar Aggarwal. All rights reserved
- [LinkedIn](https://www.linkedin.com/in/tusharaggarwalinseec/)
- [Medium](https://medium.com/@tushar_aggarwal)
- [Tushar-Aggarwal.com](https://www.tushar-aggarwal.com/)
- [Kaggle](https://www.kaggle.com/tusharaggarwal27)
## Contributing
Contributions are welcome! If you find any issues or have suggestions for improvements, please feel free to open an issue or submit a pull request.
## License
LLM_ChatBot_streamlit is licensed under the [MIT License](https://github.com/tushar2704/LLM_ChatBot_streamlit/blob/main/LICENSE).
## Acknowledgements
We would like to express our gratitude to the open-source community for their invaluable contributions and support.