| import gradio as gr | |
| def talk(message, history): | |
| return "hi" | |
| DESCRIPTION = """ | |
| # This is a very long 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) |