We are looking to enhance our RAG (Retrieval-Augmented Generation) system with conversation history awareness. The goal is to allow the system to properly handle, and answer follow-up questions based on previous interactions, ensuring a seamless flow of information.
What is Needed
The task is to implement a conversation history-aware RAG solution that tracks and remembers previous conversations, allowing it to provide context-aware answers to follow-up questions. Efficiently manages conversation history to avoid performance issues, especially when handling long conversations.
How to Contribute
Get Familiar: Review the existing RAG system, focusing on how queries are currently processed and how session management (if any) is implemented.
Implement: Add functionality to track conversation history and ensure the RAG system can reference this history when responding to follow-up questions.
Test Your Code: Ensure that conversation history is preserved across queries and that the RAG solution provides accurate and context-aware answers.
Submit a Pull Request: Once your implementation is complete, submit a pull request with your changes, along with relevant documentation explaining your solution.
Getting Started
Before you begin, ensure that you have read through the Contribution Guidelines and have a good understanding of the RAG system architecture.
We are looking forward to your contributions! Happy Hacking! π
Implement Conversation History-Aware RAG Solution π
Project Overview
We are looking to enhance our RAG (Retrieval-Augmented Generation) system with conversation history awareness. The goal is to allow the system to properly handle, and answer follow-up questions based on previous interactions, ensuring a seamless flow of information.
What is Needed
The task is to implement a conversation history-aware RAG solution that tracks and remembers previous conversations, allowing it to provide context-aware answers to follow-up questions. Efficiently manages conversation history to avoid performance issues, especially when handling long conversations.
How to Contribute
Getting Started
Before you begin, ensure that you have read through the Contribution Guidelines and have a good understanding of the RAG system architecture.
We are looking forward to your contributions! Happy Hacking! π