tcu-classifai/gemma-classification

gemma classification

! Note. Currently we are now using Meta's LLaMA 3 to classify questions and summarize transcripts. It is found here

Categorization and Summarization of Transcript API

This is a simple API that categorizes and summarizes a given text. The API is built using Flask. Categorization is done using a fine-tuned GEMMA model and summarization is done using a Huggingface T5 model.

Requirements

Install the required packages using the following command: pip install -r requirements.txt

Install Gemma by cloning it in the same directory as this repository. The Gemma repository can be found here

git clone https://github.com/google/gemma_pytorch.git

Running the API

To run the API, use the following command: python app.py

The API will be running on http://localhost:5002 by default.

Sample request for categorization

curl -X POST -H "Content-Type: application/json" -d '{"question":"What is the square root of 5?"}' http://localhost:5002/categorize

Note: This does better if you include more context (previous sentences) in the question. For example, "Okay, we have learned about the Pythagorean theorem. What is the square root of 5?"

Sample response for categorization

{"response":1} (signifying this is a level 1 question, according to Costa's levels of questioning)

Sample request for summarization

curl localhost:5002/summarize -X POST -H "Content-Type: application/json" -d '{"text":"The quick brown fox jumps over the lazy dog."}'

Sample response for summarization

{"response":"The quick brown fox jumps over the lazy dog. This is 'a classroom transcript,' where I am to sum up what the teachers are teaching."}

Healthcheck

curl localhost:5002/healthcheck

Return

{"status": "ok"}