### Deploy Search Agent using Python Source: https://sdk.airefinery.accenture.com/ai_refinery_101/index Deploys an AI Refinery project with a configured SearchAgent. This Python script uses the DistillerClient to upload the YAML configuration, register a project, and then query the deployed agent for information. It requires an API key loaded from a .env file. ```python import asyncio import os from air import DistillerClient from dotenv import load_dotenv load_dotenv() # loads your API_KEY from your local '.env' file api_key=str(os.getenv("API_KEY")) async def search_demo(): # Instantiate a DistillerClient to communicate # with AI Refinery platform distiller_client = DistillerClient(api_key=api_key) # upload your config file to register a new AI Refinery project distiller_client.create_project(config_path="example.yaml", project="example") # assuming the YAML is stored in the file "example.yaml" # connect to the created project async with distiller_client( project="example", uuid="test_user" ) as dc: responses = await dc.query(query="Who won the FIFA world cup 2022?") # send a query to project async for response in responses: print(response['content']) if __name__ == "__main__": asyncio.run(search_demo()) ``` -------------------------------- ### Configure Search Agent with YAML Source: https://sdk.airefinery.accenture.com/ai_refinery_101/index Defines a SearchAgent for web queries within the AI Refinery project configuration. This YAML structure specifies the agent class and assigns it a name, which is then referenced in the orchestrator's agent list for deployment. ```yaml utility_agents: # configure your utility agents in this list - agent_class: SearchAgent # The class of the agent agent_name: "Search Agent" # A name that you choose for the agent orchestrator: agent_list: # list the configured agents here - agent_name: "Search Agent" ``` === COMPLETE CONTENT === This response contains all available snippets from this library. No additional content exists. Do not make further requests.