Chainlit LLM Application 🚀🤖

A Python application built with Chainlit for interacting with Large Language Models.

Project Structure

.  
├── apis/         # API integrations including Google News  
├── graphs/       # Graph implementations for conversation flows
├── core/         # Core methods
├── llm/          # LLm clients
├── profiles/     # Chat profile configurations  
├── prompts/      # LLM prompt templates and loader  
├── public/       # Static assets and avatars  
├── settings/     # Application settings and configurations  
├── main.py       # Entry point of the application
└── README.md     # Project documentation

Getting Started

Install Dependencies

cd prospectio-chatbot 
poetry install
cp .env.example .env

Get your Gemini key if you want to gemini-1.5-flash

https://aistudio.google.com/

Get your Mistral API key

https://auth.mistral.ai/ui/login

Configure Environment

• Copy for chatbot .env.example to .env
• Update the environment variables as needed

Docker

• Copy for chatbot .env.example to .env.docker
• change hostnames to match services in docker-compose.yml

First build a network for prospectio :

docker network create prospectio

docker-compose up

Run the Chatbot

poetry run chainlit run chainlit.py -w

• Access the application at http://localhost:8000
• Default login/password prospectio/prospectio