app.py

import gradio as gr


def talk(message, history):
    return "hi"


DESCRIPTION = """
A rag pipeline with a chatbot feature

Resources used to build this project :

* embedding model : https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1
* dataset : https://huggingface.co/datasets/not-lain/wikipedia-small-3000-embedded (used mxbai-colbert-large-v1 to create the embedding column )
* faiss docs : https://huggingface.co/docs/datasets/v2.18.0/en/package_reference/main_classes#datasets.Dataset.add_faiss_index 
* chatbot : https://huggingface.co/google/gemma-7b-it

If you want to support my work consider clicking on the heart react button ❤️🤗

(testing the ui)
"""


demo = gr.ChatInterface(
    fn=talk,
    chatbot=gr.Chatbot(
    ),
    description=DESCRIPTION,
)
demo.launch(debug=True)