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import json
import gradio as gr
from distilabel.llms import TransformersLLM
from distilabel.steps.tasks.argillalabeller import ArgillaLabeller
llm = TransformersLLM(model="microsoft/Phi-3-mini-4k-instruct")
task = ArgillaLabeller(llm=llm)
task.load()
@spaces.GPU
def process_records_gradio(records, example_records, field, question):
try:
# Convert string inputs to dictionaries
records = json.loads(records)
example_records = json.loads(example_records) if example_records else None
field = json.loads(field) if field else None
question = json.loads(question) if question else None
if not field and not question:
return "Error: Either field or question must be provided"
task.set_runtime_parameters(
{
"fields": [field] if field else None,
"question": question,
"example_records": example_records,
}
)
results = []
for record in records:
output = next(task.process(inputs=[{"records": record}]))
results.append(output[0]["suggestions"])
return json.dumps({"results": results}, indent=2)
except Exception as e:
return f"Error: {str(e)}"
interface = gr.Interface(
fn=process_records_gradio,
inputs=[
gr.Code(label="Records (JSON)", language="json", lines=5),
gr.Code(label="Example Records (JSON, optional)", language="json", lines=5),
gr.Code(label="Field (JSON, optional)", language="json"),
gr.Code(label="Question (JSON, optional)", language="json"),
],
outputs=gr.Code(label="Suggestions", language="json", lines=10),
title="Record Processing Interface",
description="Enter JSON data for records, example records, field, and question. At least one of field or question must be provided.",
)
if __name__ == "__main__":
interface.launch()
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