🤖 DeepSeek Chatbot: Python + Streamlit App

About

The DeepSeek Chatbot is a beginner-friendly project designed to teach the fundamentals of an AI development ecosystem. This application is local chatbot powered by a DeepSeek model and served via a Streamlit UI.

🛠️ Key Technologies

Tool	Purpose
Python	Core application logic and scripting.
Streamlit	Creating the local development server and interactive user interface.
GPT4ALL	Providing a simplified local API server to serve the DeepSeek model.
DeepSeek-R1-Distill-Qwen-1.5B	The core large language model (LLM) that powers the chatbot.

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Prerequisites

Ensure the following tools and resources are available before starting the installation:

• Python: Version $\geq 3.10$ recommended.
• Pip: Python's package installer.
• GPT4ALL: The application and model management tool.
• Model: The DeepSeek-R1-Distill-Qwen-1.5B model file.
• Code Editor: E.g., VSCode.

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Installation and Setup

Follow these steps to set up the project environment and run the chatbot.

1. Set up the Virtual Environment

It's best practice to use a virtual environment to manage project dependencies.

# Create the virtual environment (named 'venv')
python -m venv venv

# Activate the virtual environment
# On macOS/Linux:
source venv/bin/activate
# On Windows (Command Prompt):
venv\Scripts\activate
# On Windows (PowerShell):
.\venv\Scripts\Activate.ps1

2. Install Python Dependencies

With the virtual environment active, install all required packages listed in requirements.txt.

pip install -r requirements.txt

3. Configure the Model

This application uses the DeepSeek-R1-Distill-Qwen-1.5B model, which must be managed by the GPT4ALL application.

1. Download GPT4ALL: Install the desktop application from the GPT4ALL documentation site.
2. Download the Model:
   • Open the GPT4ALL application.
   • Navigate to the model downloads.
   • Search for and download the DeepSeek-R1-Distill-Qwen-1.5B model.
   • Note: Ensure the model file is saved in the default GPT4ALL model directory or update the model path in your application's configuration file (e.g., config.py or similar).

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Running the Application

Once the environment is set up and the model is configured, you can launch the Streamlit app.

streamlit run app.py

The app will automatically open in your default web browser (usually at http://localhost:8501).