This repository provides a Streamlit web application that runs the DeepSeek-R1 model locally. The app allows users to input text prompts and receive AI-generated responses from the DeepSeek R1 model in an interactive and user-friendly interface.

• Local Execution: Runs the DeepSeek R1 model on your machine.
• Streamlit UI: A lightweight and interactive web-based interface.
• Real-time Inference: Get responses from the DeepSeek R1 model instantly.
• Easy Setup: Simple installation and execution steps.

Ensure you have the following installed:

• Python 3.8+
• pip
• DeepSeek R1 Model (local installation)
• Virtual environment (optional but recommended)

git clone https://github.com/yashksaini-coder/streamlit-deepseek-r1.git cd streamlit-deepseek-r1

python -m venv venv source venv/bin/activate # On Windows use `venv\Scripts\activate`

pip install -r requirements.txt

Ensure that you have downloaded and installed the DeepSeek R1 model locally. Follow the official DeepSeek R1 installation guide: DeepSeek AI.

Once everything is set up, start the Streamlit app:

streamlit run app.py

This will launch the app in your default web browser.

1. Open the app in your browser.
2. Enter a text prompt in the input box.
3. Click the Submit button to generate a response.
4. View the AI-generated response on the screen.

DeepSeek-R1-demo/ ├── .python-version ├── .venv/ │ ├── .gitignore │ ├─] CACHEDIR.TAG (ignored) │ ├─] etc/ (ignored) │ ├─] include/ (ignored) │ ├─] Lib/ (ignored) │ ├─] pyvenv.cfg (ignored) │ ├─] Scripts/ (ignored) │ └─] share/ (ignored) ├── LICENSE ├── main.py ├── pyproject.toml ├── README.md ├── requirements.txt └── uv.lock 

Ensure the requirements.txt contains:

streamlit langchain_core langchain_community langchain_ollama 

Feel free to submit issues, feature requests, or contribute via pull requests!

This project is licensed under the GNU GENERAL PUBLIC LICENSE.

For any queries, reach out via Twitter or visit Linkedin.