Llama-3 Custom Persona Chatbot 🤖

A modern, sleek Streamlit chatbot application powered by LangChain and Llama 3.1 (via Groq API). This chatbot allows users to choose or customize the AI's persona and specialized role before initiating the conversation, keeping a dynamically-updated chat memory tailored to the selected role.

---

🌟 Key Features

• Dynamic Persona Selection: Select from preset roles like:
  • Helpful Assistant: Friendly, helpful general chatbot.
  • Python Code Tutor: Expert coding companion for writing and debugging.
  • Creative Writer: Brainstorms, writes stories, and composes poetry.
  • Strict Critic: Evaluates ideas with constructive skepticism.
• Custom Persona Configuration: Write a tailored system prompt to define your own customized AI assistant.
• Interactive Sidebar Settings: Switch roles or reset the conversation thread anytime with one click.
• Persistent Chat History: Maintains chat memory throughout the session while hiding system prompts from the UI to ensure a clean chat experience.
• Premium Sleek Interface: Clean dark-mode-optimized UI with custom CSS gradients and responsive badges.

---

🛠️ Tech Stack

• Frontend: Streamlit
• Orchestration: LangChain Core & LangChain Groq Integration
• LLM Provider: Groq API (Running llama-3.1-8b-instant)
• Environment Manager: python-dotenv

---

🚀 Getting Started

Prerequisites

Make sure you have Python 3.8+ installed. You will also need a Groq API Key which you can obtain from the Groq Console.

1. Clone the Repository

git clone <your-repository-url>
cd MY_CHATBOT

2. Set Up a Virtual Environment

Create and activate a virtual environment to manage dependencies cleanly.

• Windows (PowerShell):

  python -m venv venv
  .\venv\Scripts\Activate.ps1

• macOS / Linux:

  python3 -m venv venv
  source venv/bin/activate

3. Install Dependencies

pip install -r requirements.txt

4. Configure Environment Variables

Create a file named .env in the root directory and add your Groq API key:

GROQ_API_KEY=your_actual_groq_api_key_here

5. Run the Application

Start the Streamlit development server:

streamlit run chatbot.py

Once running, the application will automatically open in your default browser at http://localhost:8501.

---

📁 Project Structure

MY_CHATBOT/
│
├── chatbot.py           # Main Streamlit application file
├── requirements.txt     # Python packages list
├── .env                 # Environment variables containing credentials (Ignored by Git)
├── .gitignore           # File specifying which files Git should ignore
└── README.md            # Project documentation (This file)

---

📝 License

This project is open-source and available under the MIT License.