Presidential Speeches RAG

This repository contains a Streamlit application that allows users to ask questions about US presidents. The application uses a pre-trained model to find relevant excerpts from presidential speeches and generate responses to the user's questions.

Features

• Question-Answering System: Users can ask questions about US presidents, and the application will generate responses based on relevant excerpts from presidential speeches.

• Customization: Users can provide additional context for the model and choose from a list of pre-trained models.

• Similarity Search: The application uses a Pinecone vector store to find the most relevant excerpts from presidential speeches based on the user's question.

Code Overview

The main script of the application is app.py. Here's a brief overview of its main functions:

• get_relevant_excerpts(user_question, docsearch): This function takes a user's question and a Pinecone vector store as input, performs a similarity search on the vector store using the user's question, and returns the most relevant excerpts from presidential speeches.

• get_relevant_excerpts(user_question, docsearch): This function takes a user's question and a Pinecone vector store as input, performs a similarity search on the vector store using the user's question, and returns the most relevant excerpts from presidential speeches.

• presidential_speech_chat_completion(client, model, user_question, relevant_excerpts, additional_context): This function takes a Groq client, a pre-trained model, a user's question, relevant excerpts from presidential speeches, and additional context as input. It generates a response to the user's question based on the relevant excerpts and the additional context