Dynamic Customer Support Chatbot

An intelligent customer support assistant powered by Llama-3.1-8B-Instruct (via Hugging Face). This chatbot features persistent memory, maintaining context across conversations, and offers a clean, interactive user interface built with Streamlit.

🚀 Features

• Advanced LLM Integration: Leverages the Meta Llama 3.1 model for high-quality, natural language responses.
• Interactive Web UI: Built with Streamlit for a responsive and user-friendly chat interface.
• Persistent Session Memory: Maintains conversation context within the active session.
• Environment Secure: API keys are managed securely via .env files.

🛠️ Prerequisites

Before running the chatbot, ensure you have Python 3.8+ installed. You will also need a Hugging Face Access Token.

Required Python Packages

Install the necessary dependencies using pip:

pip install streamlit langchain-huggingface python-dotenv

API Configuration

1. Get your API token from Hugging Face.
2. Create a .env file in the same directory as the script.
3. Add your token to the .env file:

HUGGINGFACEHUB_API_TOKEN=your_hugging_face_token_here

💻 Usage

To start the chatbot locally, use the Streamlit CLI:

streamlit run full_dynamic_customer_support_chatbot.py

• Interact: Type your query in the chat input box.
• Exit: Close the browser tab to end the session.

⚠️ Cautions and Limitations

Please be aware of the following usage limits and design constraints:

1. Llama Open Source Limitations:

   • Inherited Constraints: As this application is built on top of Llama 3.1, it has the same limitations as the base open-source Llama models. This includes potential bias, knowledge cutoffs, and the possibility of generating incorrect or nonsensical information (hallucinations).

2. API Rate Limits:

   • This application uses the free Hugging Face Inference API. You may encounter rate limits or slower response times during peak usage hours.
   • Token Limit: The model is configured with a max_new_tokens limit. Extremely long responses may be truncated.

3. Data Privacy:

   • Session Storage: While this demo runs in the browser, always be cautious when sharing sensitive personal information with any AI chatbot.

4. Memory Management:

   • Conversation history is held in the session state. Refreshing the page will reset the conversation.