RAG Inteligent Medical Applications

Chatbot Application with Langchain and Ollama RAG System

This project is a chatbot application that utilizes Langchain and Ollama libraries to manage and process user queries using a large language model (LLM). The application uses a knowledge base created from PDF documents embedded into a vector database, allowing for semantic search and context-based question answering.

Key features include:

• Vector Database: The application uses Chroma to create a vector database from PDF documents, enabling efficient semantic search.
• Context-Aware Question Answering: The chatbot can respond to user queries based on the context provided by the embedded documents.
• Feedback System: Users can provide feedback on responses as either "Good" or "Bad" to improve the chatbot's performance.
• PDF Document Management: The application allows users to upload, delete, and manage PDF documents within the vector database.

Table of Contents

• Installation
• Usage
• Contacts

Installation

Instructions on how to install and set up your project:

1. Clone the repository:

   git clone https://github.com/joaommata/Project2024

2. Change into the directory:

   cd yourrepository

3. Install dependencies:

   I don't know how you should do it, yet hahahah

Usage

In order to initialize the chatbot in a local host run the following command :

# Example command to run your project
chainlit run scriptsappRAG.py

Contacts

• João Mata
  • Email: [email protected]