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| # import for typing | |
| from langchain.chains import RetrievalQAWithSourcesChain | |
| # gradio | |
| import gradio as gr | |
| global qa | |
| from qa import qa | |
| ##### | |
| # | |
| # Gradio fns | |
| #### | |
| def create_gradio_interface(qa:RetrievalQAWithSourcesChain): | |
| """ | |
| Create a gradio interface for the QA model | |
| """ | |
| def add_text(history, text): | |
| history = history + [(text, None)] | |
| return history, "" | |
| def bot(history): | |
| response = infer(history[-1][0], history) | |
| sources = [doc.metadata.get("source") for doc in response['source_documents']] | |
| src_list = '\n'.join(sources) | |
| print_this = response['answer'] + "\n\n\n Sources: \n\n\n" + src_list | |
| history[-1][1] = print_this #response['answer'] | |
| return history | |
| def infer(question, history): | |
| query = question | |
| result = qa({"query": query, "history": history, "question": question}) | |
| return result | |
| css=""" | |
| #col-container {max-width: 700px; margin-left: auto; margin-right: auto;} | |
| """ | |
| title = """ | |
| <div style="text-align: center;max-width: 1920px;"> | |
| <h1>Chat with your Documentation</h1> | |
| <p style="text-align: center;">This is a privately hosten Docs AI Buddy, <br /> | |
| It will help you with any question regarding the documentation of Ray ;)</p> | |
| </div> | |
| """ | |
| with gr.Blocks(css=css) as demo: | |
| with gr.Column(min_width=900, elem_id="col-container"): | |
| gr.HTML(title) | |
| chatbot = gr.Chatbot([], elem_id="chatbot") | |
| #with gr.Row(): | |
| # clear = gr.Button("Clear") | |
| with gr.Row(): | |
| question = gr.Textbox(label="Question", placeholder="Type your question and hit Enter ") | |
| with gr.Row(): | |
| clear = gr.ClearButton([chatbot, question]) | |
| question.submit(add_text, [chatbot, question], [chatbot, question], queue=False).then( | |
| bot, chatbot, chatbot | |
| ) | |
| #clear.click(lambda: None, None, chatbot, queue=False) | |
| return demo | |
| if __name__ == "__main__": | |
| demo = create_gradio_interface(qa) | |
| demo.queue().launch() | |