DocuQuery is a tool designed to facilitate intelligent question-answering from various document formats. Whether you have a PDF, TXT file, or even a URL link, DocuQuery allows you to upload the content and seamlessly ask questions related to the document's context.
- Document Upload: Upload PDF, TXT files, or provide a URL link to the document.
- Question-Answering: Utilizes advanced natural language processing to answer questions based on the uploaded document.
- OpenAI Integration: Employs Llama 3, an open-source model with OpenAI embeddings, to enhance language understanding.
- Faiss Database: Implements Faiss for efficient storage and retrieval of document embeddings.
- Streamlit UI: User-friendly interface powered by Streamlit for smooth navigation and interaction.
- Tracking and Monitoring: Integration with LangSmith for tracking and monitoring functionalities.
- LangChain Integration: Utilizes LangChain document loader, text splitter chains, etc., for enhanced document processing.
- Ensure you have Python installed on your system.
- Clone the repository:
git clone https://github.com/your_username/DocuQuery-Intelligent-Document-Q-A.git
- Navigate to the project directory:
cd DocuQuery
- Install the required dependencies:
pip install -r requirements.txt
DocuQuery requires OpenAI and Groq API keys to function properly. Follow the steps below to configure the API keys:
-
OpenAI API Key
- Sign up for an API key from OpenAI here.
- Once you have the key, set it as an environment variable:
export OPENAI_API_KEY='your_openai_api_key'
-
Groq API Key
- Sign up for an API key from Groq here.
- Once you have the key, set it as an environment variable:
export GROQ_API_KEY='your_groq_api_key'
- After installing the dependencies, run the Streamlit app:
streamlit run app.py
- Access the application through the provided URL in your browser.
- Upload your document (PDF, TXT file, or URL link).
- Ask questions related to the content of the document.
- Receive intelligent answers generated by DocuQuery.