Documentation Index
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Core types used throughout the HUD SDK.
Task
Created by calling an Environment. Holds configuration for running an evaluation.
from hud import Environment
env = Environment("my-env")
task = env("scenario_name", arg1="value") # Returns Task
| Field | Type | Description |
|---|
env | Environment | dict | None | Source environment |
scenario | str | None | Scenario name to run |
args | dict[str, Any] | Script arguments |
trace_id | str | None | Trace identifier |
job_id | str | None | Parent job ID |
group_id | str | None | Group ID for parallel runs |
index | int | Index in parallel execution |
variants | dict[str, Any] | None | Variant assignment |
EvalContext
Returned by hud.eval(). Extends Environment with evaluation tracking.
async with hud.eval(task) as ctx:
print(ctx.prompt) # Task prompt
print(ctx.variants) # Current variant
ctx.reward = 1.0 # Set reward
| Property | Type | Description |
|---|
trace_id | str | Unique trace identifier |
eval_name | str | Evaluation name |
prompt | str | None | Task prompt |
variants | dict[str, Any] | Current variant assignment |
reward | float | None | Evaluation reward |
answer | str | None | Submitted answer |
error | BaseException | None | Error if failed |
results | list[EvalContext] | Results from parallel runs |
headers | dict[str, str] | Trace headers |
from hud.types import MCPToolCall
call = MCPToolCall(
name="navigate",
arguments={"url": "https://example.com"}
)
| Field | Type | Description |
|---|
id | str | Unique identifier (auto-generated) |
name | str | Tool name |
arguments | dict[str, Any] | Tool arguments |
from hud.types import MCPToolResult
result = MCPToolResult(
content=[TextContent(text="Success", type="text")],
isError=False
)
| Field | Type | Description |
|---|
content | list[ContentBlock] | Result content blocks |
structuredContent | dict | None | Structured result data |
isError | bool | Whether the call failed |
Trace
Returned by agent.run(). Contains the result of an agent execution.
from hud.types import Trace
result = await agent.run(task, max_steps=20)
print(result.reward, result.done)
| Field | Type | Description |
|---|
reward | float | Evaluation score (0.0-1.0) |
done | bool | Whether execution completed |
content | str | None | Final response content |
isError | bool | Whether an error occurred |
citations | list[dict[str, Any]] | Provider-normalized citations from final inference |
info | dict[str, Any] | Additional metadata |
trace | list[TraceStep] | Execution trace steps |
messages | list[Any] | Final conversation state |
InferenceResult
Returned by agent get_response() methods. Represents the result of a single LLM inference call.
from hud.types import InferenceResult
| Field | Type | Description |
|---|
tool_calls | list[MCPToolCall] | Tools to execute |
done | bool | Whether agent should stop |
content | str | None | Response text |
reasoning | str | None | Model reasoning/thinking |
citations | list[dict[str, Any]] | Provider-normalized citations |
info | dict[str, Any] | Provider-specific metadata |
isError | bool | Error flag |
Note: AgentResponse is available as a backwards-compatible alias for InferenceResult.
AgentType
Enum of supported agent types.
from hud.types import AgentType
agent_cls = AgentType.CLAUDE.cls
agent = agent_cls.create()
| Value | Agent Class |
|---|
AgentType.CLAUDE | ClaudeAgent |
AgentType.OPENAI | OpenAIAgent |
AgentType.OPERATOR | OperatorAgent |
AgentType.GEMINI | GeminiAgent |
AgentType.GEMINI_CUA | GeminiCUAAgent |
AgentType.OPENAI_COMPATIBLE | OpenAIChatAgent |
ContentBlock
MCP content types (from mcp.types):
from mcp.types import TextContent, ImageContent
# Text
TextContent(text="Hello", type="text")
# Image
ImageContent(data="base64...", mimeType="image/png", type="image")
EvaluationResult
Returned by evaluation tools.
from hud.tools.types import EvaluationResult
result = EvaluationResult(
reward=0.8,
done=True,
content="Task completed",
info={"score": 80}
)
| Field | Type | Description |
|---|
reward | float | Score (0.0-1.0) |
done | bool | Task complete |
content | str | None | Details |
info | dict | Metadata |
See Also
