Setup agents

Agents are the AI systems, LLMs or agents you want to test and evaluate. They are configured through an API endpoint.

In this section, we will walk you through how to setup agents using the SDK.

Let’s start by initializing the Hub client or take a look at the Quickstart & setup section to see how to install the SDK and connect to the Hub.

from giskard_hub import HubClient

hub = HubClient()

Create an agent

You can create an agent using the hub.models.create() method. Example:

model = hub.models.create(
    project_id=project.id,
    name="My Agent",
    description="An agent for demo purposes",
    url="https://my-agent-endpoint.example.com/agent_v1",
    supported_languages=["en", "fr"],
    # if your agent endpoint needs special headers:
    headers={"X-API-Key": "MY_TOKEN"},
)

After creating the agent, you can test it by running a chat:

response = model.chat(
    messages=[
        dict(role="user", content="What is the capital of France?"),
        dict(role="assistant", content="Paris"),
        dict(role="user", content="What is the capital of Germany?"),
    ],
)
print(response)

If all is working well, this will return something like:

ModelOutput(
    message=ChatMessage(
        role='assistant',
        content='The capital of Germany is Berlin.'
    ),
    metadata={}
)

For detailed information about agent management methods, see the Resources reference section.

Next steps

Now that you have created an agent, you can continue by setting up your knowledge base or creating test cases and datasets.