Functional agent run

from vectorshift.agent import Agent, AgentType, IoConfig, LlmInfo
from vectorshift.agent.tool import ToolInput, ToolInputType
from vectorshift.agent.tools import ExaAiTool

# Create a tool
search = ExaAiTool(
    tool_name="exa_ai_search",
    query=ToolInput(type=ToolInputType.DYNAMIC, description="Search query"),
)

# Create a functional agent
agent = Agent.new(
    name="Topic briefing",
    type=AgentType.FUNCTIONAL,
    llm_info=LlmInfo(provider="openai", model_id="gpt-4o"),
    tools=[search],
    instructions=(
        "For the given topic, search the web if you need "
        "fresh facts, then write a short brief."
    ),
    inputs={
        "topic": IoConfig(io_type="string", description="Subject to brief"),
    },
    outputs={
        "brief": IoConfig(io_type="string", description="Markdown brief"),
    },
)
print(f"Created agent: {agent.name}")

# Run the agent with structured inputs
result = agent.run(inputs={"topic": "Solid-state batteries"})

# Outputs come back keyed by the declared name; the SDK remaps the
# engine's ``output_<oid>`` keys via the agent's outputs metadata.
if result.status == "success":
    print(f"\nBrief:\n{result.outputs.get('brief', '(no brief returned)')}")
else:
    print(f"\nError: {result.error}")

print(f"\nRun ID: {result.run_id}")

# Clean up
agent.delete()
print("Done.")