wehub-resource-sync
65 lines
1.9 KiB
Python
65 lines
1.9 KiB
Python
import asyncio
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from pydantic import BaseModel, Field
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from agents import Agent, Runner
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"""
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This example shows structured input for agent-as-tool calls.
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"""
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class TranslationInput(BaseModel):
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text: str = Field(description="Text to translate.")
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source: str = Field(description="Source language code or name.")
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target: str = Field(description="Target language code or name.")
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translator = Agent(
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name="translator",
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instructions=(
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"Translate the input text into the target language. "
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"If the target is not clear, ask the user for clarification."
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),
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)
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orchestrator = Agent(
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name="orchestrator",
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instructions=(
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"You are a task dispatcher. Always call the tool with sufficient input. "
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"Do not handle the translation yourself."
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),
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tools=[
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translator.as_tool(
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tool_name="translate_text",
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tool_description=(
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"Translate text between languages. Provide text, source language, "
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"and target language."
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),
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parameters=TranslationInput,
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# By default, the input schema will be included in a simpler format.
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# Set include_input_schema to true to include the full JSON Schema:
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# include_input_schema=True,
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# Build a custom prompt from structured input data:
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# input_builder=lambda options: (
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# f'Translate the text "{options["params"]["text"]}" '
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# f'from {options["params"]["source"]} to {options["params"]["target"]}.'
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# ),
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)
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],
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)
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async def main() -> None:
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query = 'Translate "Hola" from Spanish to French.'
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response1 = await Runner.run(translator, query)
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print(f"Translator agent direct run: {response1.final_output}")
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response2 = await Runner.run(orchestrator, query)
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print(f"Translator agent as tool: {response2.final_output}")
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if __name__ == "__main__":
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asyncio.run(main())
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