This application integrates a PDF chat functionality using LanceDB with advanced RAG (Retrieval-Augmented Generation) methods and leverages the Paler Text-to-Speech (TTS) model for audio output.
It is designed to enable high-quality text and speech interaction with PDF documents.
Hybrid Search: Combines vector-based and keyword searches to improve result relevance.
Full-Text Search (FTS): Utilizes Tavity for enhanced text search capabilities within documents.
Colbert Reranker: Improves the accuracy of search results by reranking them based on relevance.
Langchain Prompts: Controls LLM (Large Language Model) outputs using customized prompts for more tailored interactions.
Paler Text-to-Speech (TTS): A lightweight, high-quality TTS model that mimics various speech styles and attributes.
Clone the repository and install the required packages:
pip install -r requirements.txt
Start the application by running the main script. This will launch a Gradio interface accessible via a web browser:
create .env file & pass the openai_api_key. or simply rename the .env-example file to .env
python3 main.py # Gradio app will run
The application provides two types of outputs from the processed PDF documents:
Text: Extracted and processed text displayed in a user-friendly format. Audio: Natural sounding speech generated from the text, customizable by speaker characteristics such as gender and pitch.