Project Overview: RAG Agent - Document Assistant
The RAG (Retrieval-Augmented Generation) Agent project has undergone a significant evolution, transforming from a basic PDF chatbot into an advanced assistant. This agent is designed to access conversation history, retrieve context, summarize documents, and answer follow-up questions based on user inquiries and intent detection. You can explore the capabilities of this innovative project by visiting agentic-rag.
Installation Process
To get started with the RAG Agent, you will need an OPENAI_API key. Once you have this, make sure all necessary dependencies are installed. You can easily do this by running the following command in your terminal:
pip install -r requirements.txt
How to Use
Launching the RAG Agent is straightforward. Run the following command to start the Streamlit app in your browser:
python -m streamlit run agentic_rag.py
Once the app is up and running, you can begin by uploading various document formats such as .pdf, .txt, or .docx. From there, you are free to query the agent naturally, whether you need document summaries, answers to specific questions, or responses to follow-up inquiries.
Key Features
- Conversation History: The agent maintains a detailed conversation history, which helps in providing context-based and relevant responses.
- Document Summarization: It offers the ability to summarize documents, giving users clear and concise overviews.
- Follow-up Question Responses: The agent effectively handles follow-up questions by considering previous interactions and the context of the current conversation.
- Logical Intent Determination: It accurately determines the user's intent through logical analysis to ensure precise responses.
- Supported File Types: Users are able to upload
.pdf,.txt, and.docxdocuments directly using the app interface for seamless interaction.
Project History
The evolution of the RAG Agent is an ongoing journey, focused on expanding its capabilities. While the current functionality can be experienced through the provided .py file, additional features and improvements are continuously being developed. Future updates aim to provide a completely functional application, allowing for local execution and an intuitive interface for selecting PDF documents.
Credits
The development of this project is credited to its creator, who has diligently worked to bring this document assistant to life.
License
This project is licensed under the Apache 2.0 License, allowing for both personal and commercial use under the terms specified. Enjoy interacting with your documents using this intelligent RAG Agent!