RAG Application

This project allows you to chat with multiple PDF documents using Streamlit and various natural language processing libraries.

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/your-repository.git
   cd your-repository

2. Install dependencies:

   pip install -r requirements.txt

3. Run the application:

   streamlit run application.py

Usage

1. Upload your PDF documents in the sidebar.

2. Enter your question in the text input box.

3. Click the "Process" button to generate a response.

Features

• Chat with Multiple PDFs: Engage in a conversation about the contents of uploaded PDF documents.
• Natural Language Processing: Utilizes advanced NLP models to understand and respond to user queries.
• Interactive Interface: Built with Streamlit, providing a user-friendly interface for interaction.
• Document Processing: Automatically processes uploaded PDF documents, extracting text and creating a searchable database.

Working

1. Document Processing: Upon uploading PDF documents, the application automatically extracts text from them using the Langchain Community library's PyPDFDirectoryLoader and RecursiveCharacterTextSplitter.

2. Vectorization: The extracted text is chunked and converted into vectors using the Hugging Face transformers library, specifically the HuggingFaceInferenceAPIEmbeddings.

3. Conversation Setup: A conversational chain is established using Langchain Community's ConversationalRetrievalChain and ChatOpenAI to facilitate user interaction.

4. User Interaction: Users can enter questions about the uploaded documents in the text input box. The application then utilizes the conversational chain to generate responses based on the content of the documents.