🧠 ChatGPT AI Assistant — Python Chatbot with Gradio & Console Interface

A simple yet powerful AI Chatbot built in Python using the OpenAI API, offering both console (terminal) and web-based (Gradio) interfaces. This project demonstrates end-to-end integration of large language models (LLMs) into user applications for text-based interaction.

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📁 Project Structure

├── console.py               # Terminal-based chatbot using OpenAI API
├── gradio.py                # Web interface chatbot using Gradio
├── fleet.py                 # (Optional) Multi-interface or extended bot management
├── Project proposal - 2023.pdf  # Original academic project documentation

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🚀 Features

• 💬 Real-time chatbot interaction in terminal (console.py)
• 🌐 Web-based interactive chatbot UI with Gradio (gradio.py)
• ⚙️ Simple integration with OpenAI’s GPT models (GPT-3.5-Turbo)
• 🧩 Extendable architecture — can integrate multiple interfaces (e.g., Flet, Flask, Docker)
• 📚 Educational base for LLM app development

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🧰 Libraries and Dependencies

Make sure you have Python 3.8+ installed, then install the following libraries:

pip install openai gradio

If you plan to extend the project:

pip install torch transformers flet flask

Core Libraries Used

Library	Purpose
openai	Connects to the OpenAI GPT API for natural language interaction
gradio	Builds simple web interfaces for ML and AI applications
torch	(Optional) Backend for local model integration
transformers	(Optional) Use open-source LLMs (e.g., Falcon, LLaMA, GPT-2)
flet	(Optional) Build desktop or browser-based UI
flask	(Optional) API server or containerized deployment

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⚙️ Setup & Configuration

1. Clone the repository:

   git clone https://github.com/yourusername/chatgpt-ai-assistant.git
   cd chatgpt-ai-assistant

2. Install dependencies:

   pip install -r requirements.txt

   (Or manually install openai and gradio as above.)

3. Set your OpenAI API key: Replace the placeholder key in both scripts:

   openai.api_key = "YOUR_OPENAI_API_KEY"

   or export it as an environment variable:

   export OPENAI_API_KEY="your_api_key_here"

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💻 Usage

🧩 Console Version

Run the chatbot directly in your terminal:

python console.py

Example:

User: What is artificial intelligence?
ChatGPT: Artificial intelligence is the simulation of human intelligence processes by machines...

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🌐 Gradio Web Interface

Launch the chatbot in a browser-based UI:

python gradio.py

Then open the local URL shown in the terminal (usually http://127.0.0.1:7860/).

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🧠 How It Works

1. The user’s input is collected (via console or Gradio UI).
2. The message is sent to OpenAI’s chat.completions.create() endpoint.
3. The GPT model (gpt-3.5-turbo) processes and returns the response.
4. The reply is displayed back to the user in real time.

This simple flow allows developers to easily embed conversational AI into any Python app.

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🏗️ Future Extensions

• Integrate open-source models (Falcon, Vicuna, LLaMA) via HuggingFace.
• Add memory and context management.
• Deploy with Flask or FastAPI as a REST API service.
• Wrap as a desktop app using Flet.
• Containerize with Docker for easy deployment.

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🧩 Example Code Snippet (Console Version)

import openai

openai.api_key = "YOUR_OPENAI_API_KEY"
messages = [{"role": "system", "content": "You are a helpful assistant."}]

while True:
    message = input("User: ")
    if message:
        messages.append({"role": "user", "content": message})
        chat = openai.chat.completions.create(model="gpt-3.5-turbo", messages=messages)
        reply = chat.choices[0].message.content
        print(f"ChatGPT: {reply}")
        messages.append({"role": "assistant", "content": reply})

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📖 References

• OpenAI API Documentation
• Gradio Documentation
• Hugging Face Transformers
• Flet Framework