@EricGustin you can use this cli command:
```
uv run arcade evals mcp_building_evals_results/eval_toolkit_iteration_dict.py \
-p openai:gpt-4o,gpt-4o-mini \
-p anthropic:claude-sonnet-4-20250514 \
-k openai:$OPENAI_API_KEY \
-k anthropic:$ANTHROPIC_API_KEY \
-d \
--num-runs 3 \
--seed random \
--multi-run-pass-rule majority \
--max-concurrent 6 \
-o mcp_building_evals_results/results
```
<!-- CURSOR_SUMMARY -->
---
> [!NOTE]
> **Medium Risk**
> Touches core eval execution and all result formatters while adding new
CLI inputs and output schema (`run_stats`/`critic_stats` and capture
`runs`), so regressions could affect evaluation results and report
compatibility despite being additive and validated.
>
> **Overview**
> Adds **multi-run evaluation support** to `arcade evals` via new flags
`--num-runs`, `--seed`, and `--multi-run-pass-rule`, with upfront
validation and plumbing through the CLI runner into eval/capture suite
execution.
>
> Fixes provider selection UX/bug by making `--use-provider/-p`
**repeatable** (instead of a space-delimited string), updates
docs/examples accordingly, and extends capture mode to optionally record
**per-run tool calls** (`CapturedRun`) when `num_runs > 1`.
>
> Enhances all output formatters (HTML/Markdown/Text/JSON) to
**propagate and display** per-case `run_stats` and `critic_stats`,
including new HTML UI for run tabs/cards and comparative tables showing
mean ± stddev when multi-run data is present.
>
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
2ee1654b7d1fbb9538373507355636164b16a066. This will update automatically
on new commits. Configure
[here](https://cursor.com/dashboard?tab=bugbot).</sup>
<!-- /CURSOR_SUMMARY -->
133 lines
3.9 KiB
Python
133 lines
3.9 KiB
Python
"""Comparative case builder for multi-track evaluations.
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Provides a fluent API for defining evaluation cases that run against
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multiple tool tracks with track-specific expected results and critics.
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"""
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from __future__ import annotations
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from collections.abc import Sequence
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from typing import TYPE_CHECKING, Any
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from arcade_evals._evalsuite._types import (
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ComparativeCase,
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EvalRubric,
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ExpectedMCPToolCall,
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ExpectedToolCall,
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)
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if TYPE_CHECKING:
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from arcade_evals.critic import Critic
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class ComparativeCaseBuilder:
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"""Fluent builder for creating comparative cases.
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Example:
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builder = ComparativeCaseBuilder(
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suite=suite,
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name="weather_query",
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user_message="What's the weather?",
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)
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builder.for_track(
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"Google Weather",
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expected_tool_calls=[...],
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critics=[...],
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).for_track(
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"OpenWeather",
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expected_tool_calls=[...],
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critics=[...],
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)
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"""
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def __init__(
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self,
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suite: Any, # EvalSuite - avoid circular import
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name: str,
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user_message: str,
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system_message: str = "",
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additional_messages: list[dict[str, Any]] | None = None,
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rubric: EvalRubric | None = None,
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) -> None:
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"""Initialize the builder.
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Args:
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suite: The parent EvalSuite.
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name: Unique case name.
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user_message: User message (shared across tracks).
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system_message: System message (shared across tracks).
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additional_messages: Additional context (shared).
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rubric: Default rubric (shared, can be overridden).
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"""
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self._suite = suite
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self._case = ComparativeCase(
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name=name,
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user_message=user_message,
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system_message=system_message,
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additional_messages=additional_messages or [],
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rubric=rubric,
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)
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def for_track(
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self,
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track_name: str,
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expected_tool_calls: Sequence[ExpectedToolCall | ExpectedMCPToolCall],
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critics: list[Critic] | None = None,
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) -> ComparativeCaseBuilder:
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"""Add track-specific configuration.
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Args:
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track_name: The track name (must be registered via add_*_tools).
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expected_tool_calls: Expected tool calls for this track.
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critics: Critics for this track.
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Returns:
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Self for method chaining.
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Raises:
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ValueError: If track doesn't exist.
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"""
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# Validate track exists
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if not self._suite._track_manager.has_track(track_name):
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available = self._suite._track_manager.get_track_names()
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raise ValueError(
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f"Track '{track_name}' not found. "
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f"Available tracks: {available}. "
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f"Register tracks first using add_*_tools(track=...)."
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)
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self._case.add_track_config(
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track_name=track_name,
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expected_tool_calls=expected_tool_calls,
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critics=critics,
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)
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return self
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def build(self) -> ComparativeCase:
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"""Build and return the comparative case.
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Returns:
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The configured ComparativeCase.
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Raises:
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ValueError: If no tracks configured.
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"""
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if not self._case.track_configs:
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raise ValueError(
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f"No tracks configured for comparative case '{self._case.name}'. "
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f"Use .for_track() to add at least one track configuration."
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)
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return self._case
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@property
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def case(self) -> ComparativeCase:
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"""Access the underlying case for inspection.
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Note: This is primarily for testing. The case may be incomplete
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if tracks haven't been configured yet. Use build() to validate
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and finalize the case.
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Returns:
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The ComparativeCase (may be incomplete).
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"""
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return self._case
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