AI Refinery

https://sdk.airefinery.accenture.com/ai_refinery_101/

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### 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())

```

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### 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"

```

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