Sentiment Extraction

The project uses deepseek-r1:1.5 as the base llm model to extract sentiments out from text and next.js 16, a react based framework for the web ui to interact with the model.

Steps to setup the project

Setting up the backend (model)

1. Install ollama in your system from https://ollama.com/download NEW:
2. Go to fine_tuning folder's README.md and follow the instructions to fine-tune the model. OLD:
3. Pull the deepseek-r1:1.5b model using the comand ollama pull deepseek-r1:1.5b.
4. To make sure the model has been pulled, run ollama run deepseek-r1:1.5b . If everything is right, you should be able to interact with the model locally.
5. While being inside the backend folder, run ollama create -f Modelfile sentiment-engine-old. This command creates a model with defined configuration in the Modelfile on top of deepseek-r1:1.5b with the name of sentiment-engine.
6. If everything is right, you should be able to interact with this new model by running ollama run sentiment-engine

Great we're done with setting up the backend!

Setting up the frontend.

1. cd into the frontend directory cd frontend.
2. run npm i --legacy-peer-deps to install all the packages. (Make sure you have node and npm installed in your system).
3. run npm run dev. This should start a local server at port 3000.
4. If everything is right you should be able to interact with the model on http://localhost:3000

Contributing

1. fork the repository.
2. create a new branch and implement your changes.
3. merge your changes to main.
4. create a pull request.