This project aims to create a powerful Document Q&A Chatbot utilizing the capabilities of Llama3, Langchain, and the Groq API. The chatbot is designed to efficiently parse and comprehend documents, providing precise answers to user queries.

Llama3 Integration: Leveraging Llama3 for natural language processing and understanding.

Langchain: Utilizing Langchain for managing chains of LLMs, APIs, and custom actions.

Groq API: Integrating with the Groq API to accelerate and optimize machine learning model inference.

End-to-End Pipeline: A complete pipeline from document ingestion to question answering.

Document Ingestion: Documents are uploaded and preprocessed for efficient querying.

Question Understanding: The chatbot uses Llama3 to comprehend and break down the user query.

Answer Retrieval: Langchain orchestrates the flow between components, ensuring accurate answers.

Optimized Inference: The Groq API enhances the performance of the underlying models, delivering quick responses.

Python 3.8+

Pip

Groq API credentials

git clone https://github.com/TLILIFIRAS/Document-Q-A-Chatbot-using-Llama3-Langchain-and-Groq-API.git cd Document-Q-A-Chatbot-using-Llama3-Langchain-and-Groq-API

pip install -r requirements.txt

Create a .env file in the root directory with your Groq API and OpenAI API credentials:

GROQ_API_KEY=your_api_key_here OPENAI_API_KEY=your_llama3_api_key_here

python application.py

Place your Documents: Place your documents in the input folder .

Ask Questions: Type your question in the chat interface.

Receive Answers: The chatbot will process your query and return the most relevant answer from the document.

**User:** What are the main benefits of using Llama3? **Chatbot:** Llama3 offers advanced natural language processing capabilities, enabling high accuracy in text comprehension and generation. It is also highly scalable for various NLP tasks.