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72 lines
2.0 KiB
72 lines
2.0 KiB
"""
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* WORKING
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What this script does:
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Structured output example
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Requirements:
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Add the folowing API key(s) in your .env file:
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- OPENAI_API_KEY (this example works best with Openai bc it uses openai function calling structure)
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Note:
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If you are running playground examples in the project files directly (without swarms installed via PIP),
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make sure to add the project root to your PYTHONPATH by running the following command in the project's root directory:
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'export PYTHONPATH=$(pwd):$PYTHONPATH'
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"""
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################ Adding project root to PYTHONPATH ################################
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# If you are running playground examples in the project files directly, use this:
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import sys
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import os
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sys.path.insert(0, os.getcwd())
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################ Adding project root to PYTHONPATH ################################
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from pydantic import BaseModel, Field
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from swarms import Agent, OpenAIChat
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# Initialize the schema for the person's information
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class PersonInfo(BaseModel):
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"""
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To create a PersonInfo, you need to return a JSON object with the following format:
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{
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"function_call": "PersonInfo",
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"parameters": {
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...
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}
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}
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"""
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name: str = Field(..., title="Name of the person")
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agent: int = Field(..., title="Age of the person")
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is_student: bool = Field(..., title="Whether the person is a student")
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courses: list[str] = Field(
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..., title="List of courses the person is taking"
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)
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# Initialize the agent
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agent = Agent(
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agent_name="Person Information Generator",
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system_prompt=(
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"Generate a person's information"
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),
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llm=OpenAIChat(),
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max_loops=1,
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verbose=True,
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# List of pydantic models that the agent can use
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list_base_models=[PersonInfo],
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output_validation=True
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)
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# Define the task to generate a person's information
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task = "Generate a person's information"
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# Run the agent to generate the person's information
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generated_data = agent.run(task)
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# Print the generated data
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print(type(generated_data))
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print(f"Generated data: {generated_data}")
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