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import json
import time
import gradio as gr
import pandas as pd
from autotab import AutoTab
def auto_tabulator_completion(
in_file_path: str,
instruction: str,
max_examples: int,
model_name: str,
generation_config: dict,
request_interval: float,
save_every: int,
api_key: str,
base_url: str,
) -> tuple[str, str, str, pd.DataFrame]:
output_file_name = "ouput.xlsx"
autotab = AutoTab(
in_file_path=in_file_path,
out_file_path=output_file_name,
instruction=instruction,
max_examples=max_examples,
model_name=model_name,
generation_config=json.loads(generation_config),
request_interval=request_interval,
save_every=save_every,
api_key=api_key,
base_url=base_url,
)
start = time.time()
autotab.run()
time_taken = time.strftime("%H:%M:%S", time.gmtime(time.time() - start))
return time_taken, output_file_name, autotab.query_example, autotab.data[:15]
# Gradio interface
inputs = [
gr.File(label="Input Excel File"),
gr.Textbox(
value="You are a helpful assistant. Help me finish the task.",
label="Instruction",
),
gr.Slider(value=5, minimum=1, maximum=50, step=1, label="Max Examples"),
gr.Textbox(value="Qwen/Qwen2-7B-Instruct", label="Model Name"),
gr.Textbox(
value='{"temperature": 0, "max_tokens": 128}',
label="Generation Config in Dict",
),
gr.Slider(value=0.1, minimum=0, maximum=10, label="Request Interval in Seconds"),
gr.Slider(value=100, minimum=1, maximum=1000, step=1, label="Save Every N Steps"),
gr.Textbox(
value="sk-exhahhjfqyanmwewndukcqtrpegfdbwszkjucvcpajdufiah", label="API Key"
),
gr.Textbox(value="https://public-beta-api.siliconflow.cn/v1", label="Base URL"),
]
outputs = [
gr.Textbox(label="Time Taken"),
gr.File(label="Output Excel File"),
gr.Textbox(label="Query Example"),
gr.Dataframe(label="First 15 rows."),
]
gr.Interface(
fn=auto_tabulator_completion,
inputs=inputs,
outputs=outputs,
title="Auto Tabulator Completion",
description="Automatically complete missing output values in tabular data based on in-context learning.",
).launch()
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