AgriGenius: AI-Powered Agriculture Chatbot is a Python web application designed to empower farmers with information accessibility. AgriGenius leverages a Retrieval-Augmented Generation model to address farmer's agricultural queries. The RAG model retrieves the most relevant information from a comprehensive repository of agricultural websites and PDF documents and utilizes that information to generate informative and comprehensive responses tailored to each user's specific question with precise answers.
- Fetch content from specified websites.
- Extract text from PDF files.
- Initialize a vector store for efficient information retrieval.
- Set up a Retrieval QA chain using a language model to answer queries related to agriculture.
- Web interface to interact with the system.
Run the following Commands.
STEP 1 - Creating virtual enviroment :
To do so:-
pip install virtualenv virtualenv env
.\env\Scripts\activate.ps1
STEP 2 - Cloning the Repository :
git clone https://github.com/jayeshbhandarkar/AgriGenius.git
cd AgriGenius
STEP 3 - Installing all the Dependancies :
pip install -r requirements.txt
STEP 4 - Run the flask web application
python app.py
STEP 5 - Open Web-Browser (Chrome) and navigate to http://127.0.0.1:5000 to use this web-application.
STEP 6 - Ask questions related to agriculture in the provided input field.
- The language model used is meta-llama/Llama-2-70b-chat-hf.
- The application uses the Together API for LLM services.
- Add your own Together API key in the chat2.py file.
llm = Together(
model="meta-llama/Llama-2-70b-chat-hf",
max_tokens=512,
temperature=0.1,
top_k=1,
together_api_key="YOUR_Together_API_KEY"
)
- The requirements.txt should include all necessary packages such as Flask, requests, PyPDF2, langchain, chroma, and any other dependencies required by your project.
⬤ Please do ⭐ the Repository, if it helped you in anyway.