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import gradio as gr |
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from autotab import AutoTab |
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import json |
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import time |
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import pandas as pd |
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def convert_seconds_to_time(seconds): |
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return time.strftime("%H:%M:%S", time.gmtime(seconds)) |
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def auto_tabulator_completion( |
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in_file, |
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instruction, |
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max_examples, |
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model_name, |
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generation_config, |
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save_every, |
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api_key, |
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base_url, |
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) -> tuple[str, str, str, pd.DataFrame]: |
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output_file_name = "ouput.xlsx" |
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autotab = AutoTab( |
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in_file_path=in_file.name, |
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instruction=instruction, |
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out_file_path=output_file_name, |
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max_examples=max_examples, |
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model_name=model_name, |
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api_key=api_key, |
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base_url=base_url, |
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generation_config=json.loads(generation_config), |
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save_every=save_every, |
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) |
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start = time.time() |
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autotab.run() |
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time_taken = time.strftime("%H:%M:%S", time.gmtime(time.time() - start)) |
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return time_taken, output_file_name, autotab.query_example, autotab.data[:15] |
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inputs = [ |
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gr.File(label="Input Excel File"), |
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gr.Textbox( |
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value="You are a helpful assistant. Help me finish the task.", |
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label="Instruction", |
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), |
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gr.Slider(value=5, minimum=1, maximum=50, step=1, label="Max Examples"), |
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gr.Textbox(value="Qwen/Qwen2-7B-Instruct", label="Model Name"), |
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gr.Textbox( |
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value='{"temperature": 0, "max_tokens": 128}', |
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label="Generation Config in Dict", |
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), |
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gr.Slider(value=100, minimum=1, maximum=1000, step=1, label="Save Every N Steps"), |
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gr.Textbox( |
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value="sk-exhahhjfqyanmwewndukcqtrpegfdbwszkjucvcpajdufiah", label="API Key" |
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), |
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gr.Textbox(value="https://public-beta-api.siliconflow.cn/v1", label="Base URL"), |
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] |
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outputs = [ |
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gr.Textbox(label="Time Taken"), |
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gr.File(label="Output Excel File"), |
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gr.Textbox(label="Query Example"), |
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gr.Dataframe(label="First 15 rows."), |
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] |
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gr.Interface( |
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fn=auto_tabulator_completion, |
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inputs=inputs, |
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outputs=outputs, |
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title="Auto Tabulator Completion", |
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description="Automatically complete missing output values in tabular data based on in-context learning.", |
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).launch() |
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