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| import gradio as gr | |
| import table_load as tl | |
| css=""" | |
| #col-container {max-width: 700px; margin-left: auto; margin-right: auto;} | |
| """ | |
| title = """ | |
| <div style="text-align: center;max-width: 700px;"> | |
| <h1>Analyze your CSV</h1> | |
| <p style="text-align: center;">Please specify OpenAI Key before use</p> | |
| </div> | |
| """ | |
| with gr.Blocks(css=css) as demo: | |
| with gr.Column(elem_id="col-container"): | |
| gr.HTML(title) | |
| with gr.Column(): | |
| openai_key = gr.Textbox(label="You OpenAI API key", type="password") | |
| raw_table = gr.File(label="Load a table file (xls or csv)", file_types=['.csv, xlsx, xls'], type="file") | |
| with gr.Row(): | |
| langchain_status = gr.Textbox(label="Status", placeholder="", interactive=False) | |
| load_table = gr.Button("Load table to langchain") | |
| chatbot = gr.Chatbot([], elem_id="chatbot").style(height=350) | |
| with gr.Column(scale=0.85): | |
| question = gr.Textbox(show_label=False, placeholder="Type your question and hit Enter").style(container=False) | |
| with gr.Column(scale=0.15, min_width=0): | |
| clr_btn = gr.Button("Clear History") | |
| load_table.click(tl.load_file, None, langchain_status, queue=False) | |
| load_table.click(tl.table_loader, inputs=[raw_table, openai_key], outputs=[langchain_status], queue=False) | |
| question.submit(tl.respond, [question, chatbot], [question, chatbot]) | |
| clr_btn.click(lambda: None, None, chatbot, queue=False) | |
| demo.launch() |