From c404ee7310ceef595c217139c3985e649f24e4f0 Mon Sep 17 00:00:00 2001 From: Aaron Schlesinger <70865+arschles@users.noreply.github.com> Date: Sun, 9 Aug 2026 13:47:43 -0700 Subject: [PATCH 1/4] adding tau3-airline as a custom_code benchmark --- cli/README.md | 2 +- cli/examples/configs/tau3_airline/.gitignore | 5 + cli/examples/configs/tau3_airline/README.md | 53 + .../configs/tau3_airline/pyproject.toml | 32 + .../configs/tau3_airline/quantiles.toml | 17 + .../configs/tau3_airline/tau3_airline.py | 202 +++ .../tau3_airline/tests/test_tau3_airline.py | 106 ++ cli/examples/configs/tau3_airline/uv.lock | 1265 +++++++++++++++++ 8 files changed, 1681 insertions(+), 1 deletion(-) create mode 100644 cli/examples/configs/tau3_airline/.gitignore create mode 100644 cli/examples/configs/tau3_airline/README.md create mode 100644 cli/examples/configs/tau3_airline/pyproject.toml create mode 100644 cli/examples/configs/tau3_airline/quantiles.toml create mode 100644 cli/examples/configs/tau3_airline/tau3_airline.py create mode 100644 cli/examples/configs/tau3_airline/tests/test_tau3_airline.py create mode 100644 cli/examples/configs/tau3_airline/uv.lock diff --git a/cli/README.md b/cli/README.md index c3ff939..82e38c4 100644 --- a/cli/README.md +++ b/cli/README.md @@ -70,7 +70,7 @@ prompt_template_file = "prompts/qa.txt" style = { type = "similarity", golden_column = "answer", metric = { type = "cosine", embedding_model = "fastembed" } } ``` -See the [configuration guide](https://quantiles.io/documentation/configuration) for file location, supported fields, validation behavior, and examples. See the [model configuration guide](https://quantiles.io/documentation/model-configuration) for guidance on setting up provider models, managing credentials, and troubleshooting configuration issues. Additional runnable configurations are available in the [custom-code example](./examples/configs/custom_code/quantiles.toml) and [custom no-code examples](../custom-nocode-examples/quantiles.toml). +See the [configuration guide](https://quantiles.io/documentation/configuration) for file location, supported fields, validation behavior, and examples. See the [model configuration guide](https://quantiles.io/documentation/model-configuration) for guidance on setting up provider models, managing credentials, and troubleshooting configuration issues. Additional runnable configurations are available in the [custom-code example](./examples/configs/custom_code/quantiles.toml), the [τ³ airline adapter](./examples/configs/tau3_airline/README.md), and the [custom no-code examples](../custom-nocode-examples/quantiles.toml). ### Remote benchmark fallback diff --git a/cli/examples/configs/tau3_airline/.gitignore b/cli/examples/configs/tau3_airline/.gitignore new file mode 100644 index 0000000..c46bebe --- /dev/null +++ b/cli/examples/configs/tau3_airline/.gitignore @@ -0,0 +1,5 @@ +.tau3/ +.venv/ +.pytest_cache/ +.ruff_cache/ +__pycache__/ diff --git a/cli/examples/configs/tau3_airline/README.md b/cli/examples/configs/tau3_airline/README.md new file mode 100644 index 0000000..d26535b --- /dev/null +++ b/cli/examples/configs/tau3_airline/README.md @@ -0,0 +1,53 @@ +# τ³ Airline `custom_code` example + +This example wraps the official [`tau2` `v1.0.1` tag](https://github.com/sierra-research/tau2-bench/tree/v1.0.1) airline runner in one durable Quantiles step. The adapter environment installs that immutable Git tag because τ³ is not published as a `tau2==1.0.1` package on PyPI. τ³ remains responsible for loading tasks, simulating the user, providing airline tools and state, and calculating rewards; the adapter records the official result and emits `average_reward`, `success_rate`, and `simulation_count`. + +The adapter intentionally starts with one task and one trial. It accepts these input fields: + +- `data_dir`: the `data/` directory in a local checkout of the pinned τ³ release. +- `agent_model` and `user_model`: provider-prefixed model names such as `openai:gpt-4.1`; the adapter converts `:` to the LiteLLM `/` convention. +- `num_tasks`, `num_trials`, `max_steps`, `max_concurrency`, and `seed`: positive integers. +- `task_ids`: an optional non-empty list of τ³ task IDs. + +## Run + +Install `uv`, make Python 3.12 available to it, and run the following one-time setup from this directory: + +```bash +git clone --branch v1.0.1 --depth 1 https://github.com/sierra-research/tau2-bench.git .tau3/tau2-bench +``` + +The adapter installs the τ³ Python modules from the same immutable tag and reads benchmark tasks and databases from this ignored checkout. This is necessary because the Git-installed Python wheel does not contain the upstream `data/` tree. The adapter also constrains the environment to Python 3.12 because the pinned τ³ release imports the removed `audioop` standard-library module on Python 3.13, including in text mode. + +Configure the API keys required by the two selected models, then run: + +```bash +qt run tau3-airline +``` + +For example, both default models require `OPENAI_API_KEY`. A run calls external model providers and may incur charges. Quantiles remains local-first for its run metadata, step output, and metrics, while the configured τ³ models are an explicit networked exception. + +Override the defaults with `--input`: + +```bash +qt run tau3-airline --input '{"agent_model":"openai:gpt-4.1","user_model":"openai:gpt-4.1","task_ids":["0"],"num_trials":1}' +``` + +Inspect or compare the resulting runs: + +```bash +qt show +qt compare +``` + +This minimal adapter stores the complete upstream result inside one Quantiles step. It does not create one step per simulation, stream message or tool-call events, provide an external-agent bridge, or isolate the Python process from the host. + +## Test + +The focused tests mock the τ³ runner and do not call a model provider: + +```bash +uv run pytest +uv run ruff check . +uv run ruff format . --check +``` diff --git a/cli/examples/configs/tau3_airline/pyproject.toml b/cli/examples/configs/tau3_airline/pyproject.toml new file mode 100644 index 0000000..db54c2c --- /dev/null +++ b/cli/examples/configs/tau3_airline/pyproject.toml @@ -0,0 +1,32 @@ +[project] +name = "quantiles-tau3-airline-example" +version = "0.1.0" +description = "Minimal Quantiles custom_code adapter for the tau3 airline benchmark" +requires-python = ">=3.12,<3.13" +dependencies = [ + "quantiles", + "tau2", +] + +[dependency-groups] +dev = [ + "pytest>=9.0.2,<10.0.0", + "ruff>=0.15.12,<0.16.0", +] + +[tool.uv.sources] +quantiles = { path = "../../../../python", editable = true } +tau2 = { git = "https://github.com/sierra-research/tau2-bench.git", tag = "v1.0.1" } + +[tool.ruff] +target-version = "py312" +line-length = 100 +indent-width = 2 + +[tool.ruff.format] +indent-style = "space" +quote-style = "double" + +[tool.pytest.ini_options] +testpaths = ["tests"] +pythonpath = ["."] diff --git a/cli/examples/configs/tau3_airline/quantiles.toml b/cli/examples/configs/tau3_airline/quantiles.toml new file mode 100644 index 0000000..374c541 --- /dev/null +++ b/cli/examples/configs/tau3_airline/quantiles.toml @@ -0,0 +1,17 @@ +# This example intentionally defaults to one task and one trial. Both the agent +# and user simulator call the configured provider model, so a real run can incur +# provider charges. + +[benchmarks.tau3-airline] +type = "custom_code" +command = ["uv", "run", "python", "tau3_airline.py"] + +[benchmarks.tau3-airline.input] +data_dir = ".tau3/tau2-bench/data" +agent_model = "openai:gpt-4.1" +user_model = "openai:gpt-4.1" +num_tasks = 1 +num_trials = 1 +max_steps = 100 +max_concurrency = 1 +seed = 300 diff --git a/cli/examples/configs/tau3_airline/tau3_airline.py b/cli/examples/configs/tau3_airline/tau3_airline.py new file mode 100644 index 0000000..daca85e --- /dev/null +++ b/cli/examples/configs/tau3_airline/tau3_airline.py @@ -0,0 +1,202 @@ +"""Minimal Quantiles custom_code adapter for the official tau3 airline runner.""" + +import asyncio +import os +from dataclasses import asdict, dataclass +from pathlib import Path +from typing import Protocol, cast + +from quantiles import JsonValue, WorkflowContext, emit, entrypoint, step, workflow + + +@dataclass(frozen=True) +class Tau3AirlineConfig: + data_dir: str = ".tau3/tau2-bench/data" + agent_model: str = "openai/gpt-4.1" + user_model: str = "openai/gpt-4.1" + num_tasks: int = 1 + num_trials: int = 1 + max_steps: int = 100 + max_concurrency: int = 1 + seed: int = 300 + task_ids: tuple[str, ...] | None = None + + def to_json(self) -> dict[str, JsonValue]: + value = asdict(self) + if self.task_ids is not None: + value["task_ids"] = list(self.task_ids) + return cast(dict[str, JsonValue], value) + + +class Tau3Results(Protocol): + def model_dump(self, *, mode: str) -> dict[str, JsonValue]: ... + + +class RunDomain(Protocol): + def __call__(self, config: object) -> Tau3Results: ... + + +class TextRunConfigFactory(Protocol): + def __call__(self, **kwargs: object) -> object: ... + + +def _model_name(value: JsonValue, field: str, default: str) -> str: + if value is None: + return default + if not isinstance(value, str) or not value.strip(): + raise ValueError(f"{field} must be a non-empty string") + model = value.strip() + if ":" in model and "/" not in model.split(":", 1)[0]: + provider, name = model.split(":", 1) + if provider and name: + return f"{provider}/{name}" + return model + + +def _string(value: JsonValue, field: str, default: str) -> str: + if value is None: + return default + if not isinstance(value, str) or not value.strip(): + raise ValueError(f"{field} must be a non-empty string") + return value.strip() + + +def _positive_int(value: JsonValue, field: str, default: int) -> int: + if value is None: + return default + if isinstance(value, bool) or not isinstance(value, int) or value <= 0: + raise ValueError(f"{field} must be a positive integer") + return value + + +def _task_ids(value: JsonValue) -> tuple[str, ...] | None: + if value is None: + return None + if not isinstance(value, list) or not value: + raise ValueError("task_ids must be a non-empty list of strings") + if not all(isinstance(task_id, str) and task_id for task_id in value): + raise ValueError("task_ids must be a non-empty list of strings") + return tuple(cast(list[str], value)) + + +def parse_config(input_value: JsonValue) -> Tau3AirlineConfig: + if input_value is None: + values: dict[str, JsonValue] = {} + elif isinstance(input_value, dict): + values = input_value + else: + raise ValueError("workflow input must be a JSON object") + + return Tau3AirlineConfig( + data_dir=_string(values.get("data_dir"), "data_dir", ".tau3/tau2-bench/data"), + agent_model=_model_name(values.get("agent_model"), "agent_model", "openai/gpt-4.1"), + user_model=_model_name(values.get("user_model"), "user_model", "openai/gpt-4.1"), + num_tasks=_positive_int(values.get("num_tasks"), "num_tasks", 1), + num_trials=_positive_int(values.get("num_trials"), "num_trials", 1), + max_steps=_positive_int(values.get("max_steps"), "max_steps", 100), + max_concurrency=_positive_int(values.get("max_concurrency"), "max_concurrency", 1), + seed=_positive_int(values.get("seed"), "seed", 300), + task_ids=_task_ids(values.get("task_ids")), + ) + + +def summarize_results(upstream: dict[str, JsonValue]) -> dict[str, JsonValue]: + raw_simulations = upstream.get("simulations", []) + simulations = raw_simulations if isinstance(raw_simulations, list) else [] + rewards: list[float] = [] + + for simulation in simulations: + if not isinstance(simulation, dict): + continue + reward_info = simulation.get("reward_info") + if not isinstance(reward_info, dict): + continue + reward = reward_info.get("reward") + if isinstance(reward, int | float) and not isinstance(reward, bool): + rewards.append(float(reward)) + + count = len(rewards) + average_reward = sum(rewards) / count if count else 0.0 + successful = sum(reward == 1.0 for reward in rewards) + return { + "simulation_count": count, + "average_reward": average_reward, + "success_rate": successful / count if count else 0.0, + } + + +def _load_tau3() -> tuple[RunDomain, TextRunConfigFactory]: + from tau2.data_model.simulation import TextRunConfig + from tau2.run import run_domain + + return cast(RunDomain, run_domain), cast(TextRunConfigFactory, TextRunConfig) + + +def _configure_tau3_data(data_dir: str) -> Path: + path = Path(data_dir).expanduser().resolve() + if not path.is_dir(): + raise FileNotFoundError( + f"tau3 data directory not found at {path}; follow this example's setup instructions" + ) + os.environ["TAU2_DATA_DIR"] = str(path) + return path + + +def run_tau3(config: Tau3AirlineConfig) -> dict[str, JsonValue]: + _configure_tau3_data(config.data_dir) + run_domain, text_run_config = _load_tau3() + upstream_config = text_run_config( + domain="airline", + task_split_name="base", + task_ids=list(config.task_ids) if config.task_ids is not None else None, + num_tasks=config.num_tasks, + num_trials=config.num_trials, + agent="llm_agent", + user="user_simulator", + llm_agent=config.agent_model, + llm_user=config.user_model, + max_steps=config.max_steps, + max_concurrency=config.max_concurrency, + seed=config.seed, + auto_review=False, + verbose_logs=False, + ) + upstream = run_domain(upstream_config).model_dump(mode="json") + return { + "benchmark": "tau3-airline", + "config": config.to_json(), + "summary": summarize_results(upstream), + "upstream": upstream, + } + + +async def handler(input_value: JsonValue, ctx: WorkflowContext) -> JsonValue: + config = parse_config(input_value) + + async def execute() -> JsonValue: + return await asyncio.to_thread(run_tau3, config) + + result = await step( + ctx, + step_key="run-official-tau3-airline", + input_value=config.to_json(), + execute=execute, + ) + if not isinstance(result, dict): + raise TypeError("tau3 step returned a non-object result") + summary = result.get("summary") + if not isinstance(summary, dict): + raise TypeError("tau3 step result is missing its summary") + + for metric_name in ("average_reward", "success_rate", "simulation_count"): + value = summary.get(metric_name) + if isinstance(value, int | float) and not isinstance(value, bool): + await emit(ctx, metric_name, float(value)) + + return result + + +tau3_airline = workflow("tau3-airline", handler) + +if __name__ == "__main__": + entrypoint(tau3_airline) diff --git a/cli/examples/configs/tau3_airline/tests/test_tau3_airline.py b/cli/examples/configs/tau3_airline/tests/test_tau3_airline.py new file mode 100644 index 0000000..3e6273e --- /dev/null +++ b/cli/examples/configs/tau3_airline/tests/test_tau3_airline.py @@ -0,0 +1,106 @@ +from dataclasses import dataclass +from pathlib import Path + +import pytest + +import tau3_airline + + +def test_parse_config_uses_small_defaults_and_normalizes_models() -> None: + config = tau3_airline.parse_config( + { + "agent_model": "anthropic:claude-sonnet-4-5", + "user_model": "openai:gpt-4.1", + } + ) + + assert config.agent_model == "anthropic/claude-sonnet-4-5" + assert config.user_model == "openai/gpt-4.1" + assert config.num_tasks == 1 + assert config.num_trials == 1 + assert config.task_ids is None + + +def test_parse_config_accepts_task_ids() -> None: + config = tau3_airline.parse_config({"task_ids": ["0", "1"], "seed": 42}) + + assert config.task_ids == ("0", "1") + assert config.seed == 42 + + +@pytest.mark.parametrize( + ("input_value", "message"), + [ + ({"num_tasks": 0}, "num_tasks must be a positive integer"), + ({"num_trials": True}, "num_trials must be a positive integer"), + ({"task_ids": []}, "task_ids must be a non-empty list of strings"), + ([], "workflow input must be a JSON object"), + ], +) +def test_parse_config_rejects_invalid_input(input_value: object, message: str) -> None: + with pytest.raises(ValueError, match=message): + tau3_airline.parse_config(input_value) # type: ignore[arg-type] + + +def test_summarize_results_uses_official_rewards() -> None: + summary = tau3_airline.summarize_results( + { + "simulations": [ + {"reward_info": {"reward": 1.0}}, + {"reward_info": {"reward": 0.0}}, + {"reward_info": None}, + ] + } + ) + + assert summary == { + "simulation_count": 2, + "average_reward": 0.5, + "success_rate": 0.5, + } + + +@dataclass +class _FakeResults: + payload: dict[str, object] + + def model_dump(self, *, mode: str) -> dict[str, object]: + assert mode == "json" + return self.payload + + +def test_run_tau3_delegates_to_official_runner( + monkeypatch: pytest.MonkeyPatch, tmp_path: Path +) -> None: + captured: dict[str, object] = {} + + def fake_config(**kwargs: object) -> object: + captured.update(kwargs) + return captured + + def fake_run_domain(config: object) -> _FakeResults: + assert config is captured + return _FakeResults({"simulations": [{"reward_info": {"reward": 1.0}}]}) + + monkeypatch.setattr(tau3_airline, "_load_tau3", lambda: (fake_run_domain, fake_config)) + + data_dir = tmp_path / "data" + data_dir.mkdir() + result = tau3_airline.run_tau3(tau3_airline.Tau3AirlineConfig(data_dir=str(data_dir))) + + assert captured["domain"] == "airline" + assert captured["task_split_name"] == "base" + assert captured["agent"] == "llm_agent" + assert captured["user"] == "user_simulator" + assert result["summary"] == { + "simulation_count": 1, + "average_reward": 1.0, + "success_rate": 1.0, + } + + +def test_run_tau3_requires_upstream_data_checkout(tmp_path: Path) -> None: + config = tau3_airline.Tau3AirlineConfig(data_dir=str(tmp_path / "missing")) + + with pytest.raises(FileNotFoundError, match="tau3 data directory not found"): + tau3_airline.run_tau3(config) diff --git a/cli/examples/configs/tau3_airline/uv.lock b/cli/examples/configs/tau3_airline/uv.lock new file mode 100644 index 0000000..a67a610 --- /dev/null +++ b/cli/examples/configs/tau3_airline/uv.lock @@ -0,0 +1,1265 @@ +version = 1 +revision = 3 +requires-python = "==3.12.*" +resolution-markers = [ + "sys_platform == 'win32'", + "sys_platform == 'emscripten'", + "sys_platform != 'emscripten' and sys_platform != 'win32'", +] + +[[package]] +name = "addict" +version = "2.4.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = 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"2026-05-18T20:08:57.045Z" }, +] From 461d58145351f21909073ed3f14e0810052f2ffa Mon Sep 17 00:00:00 2001 From: Aaron Schlesinger <70865+arschles@users.noreply.github.com> Date: Sun, 9 Aug 2026 13:49:28 -0700 Subject: [PATCH 2/4] progress --- cli/examples/configs/tau3_airline/README.md | 2 +- .../configs/tau3_airline/tau3_airline.py | 30 ++++++++++ .../tau3_airline/tests/test_tau3_airline.py | 60 +++++++++++++++++++ 3 files changed, 91 insertions(+), 1 deletion(-) diff --git a/cli/examples/configs/tau3_airline/README.md b/cli/examples/configs/tau3_airline/README.md index d26535b..40ccfa5 100644 --- a/cli/examples/configs/tau3_airline/README.md +++ b/cli/examples/configs/tau3_airline/README.md @@ -40,7 +40,7 @@ qt show qt compare ``` -This minimal adapter stores the complete upstream result inside one Quantiles step. It does not create one step per simulation, stream message or tool-call events, provide an external-agent bridge, or isolate the Python process from the host. +This minimal adapter stores the complete upstream result inside one Quantiles step. If τ³ reports an `infrastructure_error`, such as a provider authentication or model-access failure, the adapter fails the Quantiles step and run instead of recording a zero-score result. It does not create one step per simulation, stream message or tool-call events, provide an external-agent bridge, or isolate the Python process from the host. ## Test diff --git a/cli/examples/configs/tau3_airline/tau3_airline.py b/cli/examples/configs/tau3_airline/tau3_airline.py index daca85e..275e0f4 100644 --- a/cli/examples/configs/tau3_airline/tau3_airline.py +++ b/cli/examples/configs/tau3_airline/tau3_airline.py @@ -125,6 +125,29 @@ def summarize_results(upstream: dict[str, JsonValue]) -> dict[str, JsonValue]: } +def infrastructure_failures(upstream: dict[str, JsonValue]) -> list[dict[str, JsonValue]]: + raw_simulations = upstream.get("simulations", []) + simulations = raw_simulations if isinstance(raw_simulations, list) else [] + failures: list[dict[str, JsonValue]] = [] + + for simulation in simulations: + if not isinstance(simulation, dict): + continue + if simulation.get("termination_reason") != "infrastructure_error": + continue + info = simulation.get("info") + error = info.get("error") if isinstance(info, dict) else None + failures.append( + { + "task_id": simulation.get("task_id"), + "trial": simulation.get("trial"), + "error": error if isinstance(error, str) else "unknown infrastructure error", + } + ) + + return failures + + def _load_tau3() -> tuple[RunDomain, TextRunConfigFactory]: from tau2.data_model.simulation import TextRunConfig from tau2.run import run_domain @@ -162,6 +185,13 @@ def run_tau3(config: Tau3AirlineConfig) -> dict[str, JsonValue]: verbose_logs=False, ) upstream = run_domain(upstream_config).model_dump(mode="json") + failures = infrastructure_failures(upstream) + if failures: + first = failures[0] + raise RuntimeError( + f"tau3 reported {len(failures)} infrastructure failure(s); " + f"task {first['task_id']}, trial {first['trial']}: {first['error']}" + ) return { "benchmark": "tau3-airline", "config": config.to_json(), diff --git a/cli/examples/configs/tau3_airline/tests/test_tau3_airline.py b/cli/examples/configs/tau3_airline/tests/test_tau3_airline.py index 3e6273e..daccab7 100644 --- a/cli/examples/configs/tau3_airline/tests/test_tau3_airline.py +++ b/cli/examples/configs/tau3_airline/tests/test_tau3_airline.py @@ -60,6 +60,34 @@ def test_summarize_results_uses_official_rewards() -> None: } +def test_infrastructure_failures_extracts_upstream_error() -> None: + failures = tau3_airline.infrastructure_failures( + { + "simulations": [ + { + "task_id": "0", + "trial": 0, + "termination_reason": "infrastructure_error", + "info": {"error": "provider denied model access"}, + }, + { + "task_id": "1", + "trial": 0, + "termination_reason": "agent_stop", + }, + ] + } + ) + + assert failures == [ + { + "task_id": "0", + "trial": 0, + "error": "provider denied model access", + } + ] + + @dataclass class _FakeResults: payload: dict[str, object] @@ -104,3 +132,35 @@ def test_run_tau3_requires_upstream_data_checkout(tmp_path: Path) -> None: with pytest.raises(FileNotFoundError, match="tau3 data directory not found"): tau3_airline.run_tau3(config) + + +def test_run_tau3_raises_for_upstream_infrastructure_failure( + monkeypatch: pytest.MonkeyPatch, tmp_path: Path +) -> None: + def fake_config(**kwargs: object) -> object: + return kwargs + + def fake_run_domain(_config: object) -> _FakeResults: + return _FakeResults( + { + "simulations": [ + { + "task_id": "0", + "trial": 0, + "termination_reason": "infrastructure_error", + "info": {"error": "provider denied model access"}, + } + ] + } + ) + + monkeypatch.setattr(tau3_airline, "_load_tau3", lambda: (fake_run_domain, fake_config)) + data_dir = tmp_path / "data" + data_dir.mkdir() + config = tau3_airline.Tau3AirlineConfig(data_dir=str(data_dir)) + + with pytest.raises( + RuntimeError, + match=r"tau3 reported 1 infrastructure failure\(s\); task 0, trial 0: provider denied", + ): + tau3_airline.run_tau3(config) From a831ea2d63a668a6faa560ae31eafd4557cc4571 Mon Sep 17 00:00:00 2001 From: Aaron Schlesinger <70865+arschles@users.noreply.github.com> Date: Mon, 10 Aug 2026 20:55:17 -0700 Subject: [PATCH 3/4] centralizing stuff --- README.md | 2 +- cli/README.md | 2 +- .../configs/tau3_airline/quantiles.toml | 17 - custom-code-examples/.gitignore | 1 + custom-code-examples/README.md | 15 + custom-code-examples/quantiles.toml | 26 ++ custom-code-examples/swebench-pro/.gitignore | 4 + custom-code-examples/swebench-pro/README.md | 33 ++ .../swebench-pro/pyproject.toml | 26 ++ .../swebench-pro/swebench_pro.py | 342 ++++++++++++++++++ .../swebench-pro/tests/test_swebench_pro.py | 65 ++++ .../t3-airline}/.gitignore | 0 .../t3-airline}/README.md | 10 +- .../t3-airline}/pyproject.toml | 4 +- .../t3-airline/t3_airline.py | 8 +- .../t3-airline/tests/test_t3_airline.py | 26 +- .../t3-airline}/uv.lock | 6 +- mise.toml | 2 +- 18 files changed, 542 insertions(+), 47 deletions(-) delete mode 100644 cli/examples/configs/tau3_airline/quantiles.toml create mode 100644 custom-code-examples/.gitignore create mode 100644 custom-code-examples/README.md create mode 100644 custom-code-examples/quantiles.toml create mode 100644 custom-code-examples/swebench-pro/.gitignore create mode 100644 custom-code-examples/swebench-pro/README.md create mode 100644 custom-code-examples/swebench-pro/pyproject.toml create mode 100644 custom-code-examples/swebench-pro/swebench_pro.py create mode 100644 custom-code-examples/swebench-pro/tests/test_swebench_pro.py rename {cli/examples/configs/tau3_airline => custom-code-examples/t3-airline}/.gitignore (100%) rename {cli/examples/configs/tau3_airline => custom-code-examples/t3-airline}/README.md (90%) rename {cli/examples/configs/tau3_airline => custom-code-examples/t3-airline}/pyproject.toml (85%) rename cli/examples/configs/tau3_airline/tau3_airline.py => custom-code-examples/t3-airline/t3_airline.py (98%) rename cli/examples/configs/tau3_airline/tests/test_tau3_airline.py => custom-code-examples/t3-airline/tests/test_t3_airline.py (82%) rename {cli/examples/configs/tau3_airline => custom-code-examples/t3-airline}/uv.lock (99%) diff --git a/README.md b/README.md index 8cdfebf..58e92f3 100644 --- a/README.md +++ b/README.md @@ -106,7 +106,7 @@ See the following resources for more details: - [Configuration guide](https://quantiles.io/documentation/configuration) - Detailed configuration instructions and reference documentation for supported fields, validation rules, and examples. - [Model configuration guide](https://quantiles.io/documentation/model-configuration) - Configure provider models and credentials, and troubleshoot common setup issues. -- [Custom-code configuration example](./cli/examples/configs/custom_code/quantiles.toml) - A complete Python SDK evaluation configuration. +- [Custom-code benchmark examples](./custom-code-examples/README.md) - Runnable Python SDK evaluations with a shared configuration. - [Custom no-code examples](./custom-nocode-examples/quantiles.toml) - Complete dataset, prompt, model, and scoring configurations. #### Registry benchmarks diff --git a/cli/README.md b/cli/README.md index 82e38c4..5efd08d 100644 --- a/cli/README.md +++ b/cli/README.md @@ -70,7 +70,7 @@ prompt_template_file = "prompts/qa.txt" style = { type = "similarity", golden_column = "answer", metric = { type = "cosine", embedding_model = "fastembed" } } ``` -See the [configuration guide](https://quantiles.io/documentation/configuration) for file location, supported fields, validation behavior, and examples. See the [model configuration guide](https://quantiles.io/documentation/model-configuration) for guidance on setting up provider models, managing credentials, and troubleshooting configuration issues. Additional runnable configurations are available in the [custom-code example](./examples/configs/custom_code/quantiles.toml), the [τ³ airline adapter](./examples/configs/tau3_airline/README.md), and the [custom no-code examples](../custom-nocode-examples/quantiles.toml). +See the [configuration guide](https://quantiles.io/documentation/configuration) for file location, supported fields, validation behavior, and examples. See the [model configuration guide](https://quantiles.io/documentation/model-configuration) for guidance on setting up provider models, managing credentials, and troubleshooting configuration issues. Additional runnable configurations are available in the [custom-code example](./examples/configs/custom_code/quantiles.toml), the [custom-code benchmark examples](../custom-code-examples/README.md), and the [custom no-code examples](../custom-nocode-examples/quantiles.toml). ### Remote benchmark fallback diff --git a/cli/examples/configs/tau3_airline/quantiles.toml b/cli/examples/configs/tau3_airline/quantiles.toml deleted file mode 100644 index 374c541..0000000 --- a/cli/examples/configs/tau3_airline/quantiles.toml +++ /dev/null @@ -1,17 +0,0 @@ -# This example intentionally defaults to one task and one trial. Both the agent -# and user simulator call the configured provider model, so a real run can incur -# provider charges. - -[benchmarks.tau3-airline] -type = "custom_code" -command = ["uv", "run", "python", "tau3_airline.py"] - -[benchmarks.tau3-airline.input] -data_dir = ".tau3/tau2-bench/data" -agent_model = "openai:gpt-4.1" -user_model = "openai:gpt-4.1" -num_tasks = 1 -num_trials = 1 -max_steps = 100 -max_concurrency = 1 -seed = 300 diff --git a/custom-code-examples/.gitignore b/custom-code-examples/.gitignore new file mode 100644 index 0000000..1d97d73 --- /dev/null +++ b/custom-code-examples/.gitignore @@ -0,0 +1 @@ +.quantiles/ diff --git a/custom-code-examples/README.md b/custom-code-examples/README.md new file mode 100644 index 0000000..1da702d --- /dev/null +++ b/custom-code-examples/README.md @@ -0,0 +1,15 @@ +# Quantiles custom-code examples + +This directory contains runnable `custom_code` benchmarks. Each benchmark has an isolated Python project, while the top-level [`quantiles.toml`](./quantiles.toml) provides a single place to run and compare them. + +Run commands from this directory: + +```bash +qt run t3-airline +qt run swebench-pro +``` + +- [`t3-airline`](./t3-airline/README.md) wraps the official τ³ airline benchmark. It requires a one-time data checkout and configured model-provider credentials, and its default run calls external models. +- [`swebench-pro`](./swebench-pro/README.md) runs a one-task gold-patch smoke test with the official SWE-Bench Pro evaluator. Its first run downloads the public harness, dataset, Python dependencies, and a Docker image; it does not call a model. + +Quantiles stores both benchmarks' local run history in this directory's ignored `.quantiles/` workspace. Benchmark-specific environments, caches, and generated results stay inside their respective subdirectories and are also ignored. diff --git a/custom-code-examples/quantiles.toml b/custom-code-examples/quantiles.toml new file mode 100644 index 0000000..1236f5f --- /dev/null +++ b/custom-code-examples/quantiles.toml @@ -0,0 +1,26 @@ +# Custom-code benchmarks in this directory run in isolated uv projects while +# sharing the same local Quantiles workspace and run history. + +[benchmarks.t3-airline] +type = "custom_code" +command = ["uv", "run", "--project", "t3-airline", "python", "t3-airline/t3_airline.py"] + +[benchmarks.t3-airline.input] +data_dir = "t3-airline/.tau3/tau2-bench/data" +agent_model = "openai:gpt-4.1" +user_model = "openai:gpt-4.1" +num_tasks = 1 +num_trials = 1 +max_steps = 100 +max_concurrency = 1 +seed = 300 + +[benchmarks.swebench-pro] +type = "custom_code" +command = ["uv", "run", "--project", "swebench-pro", "python", "swebench-pro/swebench_pro.py"] + +[benchmarks.swebench-pro.input] +cache_dir = "swebench-pro/.swebench-pro-cache" +output_dir = "swebench-pro/.swebench-pro-results" +num_workers = 1 +use_local_docker = true diff --git a/custom-code-examples/swebench-pro/.gitignore b/custom-code-examples/swebench-pro/.gitignore new file mode 100644 index 0000000..43c9061 --- /dev/null +++ b/custom-code-examples/swebench-pro/.gitignore @@ -0,0 +1,4 @@ +.swebench-pro-cache/ +.swebench-pro-results/ +.venv/ +__pycache__/ diff --git a/custom-code-examples/swebench-pro/README.md b/custom-code-examples/swebench-pro/README.md new file mode 100644 index 0000000..43409aa --- /dev/null +++ b/custom-code-examples/swebench-pro/README.md @@ -0,0 +1,33 @@ +# SWE-Bench Pro `custom_code` example + +This example is a thin adapter around Scale's official SWE-Bench Pro evaluator. With Docker running, start the one-task gold-patch smoke test from the `custom-code-examples` directory: + +```bash +qt run swebench-pro +``` + +The first run clones [`scaleapi/SWE-bench_Pro-os`](https://github.com/scaleapi/SWE-bench_Pro-os), creates an isolated environment for its dependencies, downloads the public dataset, extracts the first gold patch, and pulls the task's Docker image. These network-dependent setup operations can take several minutes. Later runs reuse `.swebench-pro-cache/` and `.swebench-pro-results/` in this directory. + +The adapter records the official evaluator invocation as a durable Quantiles step and emits `resolution_rate`, `resolved_count`, and `total_count`. It does not call a model or require a provider API key. The upstream project currently marks local Docker evaluation as beta, and the evaluator runs benchmark code inside containers. + +To grade your own predictions instead of the default gold patch, override the paths: + +```bash +qt run swebench-pro --input '{ + "repo_path": "/path/to/SWE-bench_Pro-os", + "evaluator_python": "/path/to/SWE-bench_Pro-os/.venv/bin/python", + "raw_sample_path": "/path/to/samples.jsonl", + "patch_path": "/path/to/predictions.json", + "output_dir": "swebench-pro/.swebench-pro-results", + "num_workers": 1, + "use_local_docker": true +}' +``` + +Run the focused offline tests from this subdirectory: + +```bash +uv run python -m unittest discover -s tests -v +uv run ruff check . +uv run ruff format . --check +``` diff --git a/custom-code-examples/swebench-pro/pyproject.toml b/custom-code-examples/swebench-pro/pyproject.toml new file mode 100644 index 0000000..44eaf1c --- /dev/null +++ b/custom-code-examples/swebench-pro/pyproject.toml @@ -0,0 +1,26 @@ +[project] +name = "quantiles-swebench-pro-example" +version = "0.1.0" +description = "Minimal Quantiles custom_code adapter for SWE-Bench Pro" +requires-python = ">=3.12" +dependencies = [ + "pydantic>=2.13.4", + "quantiles", +] + +[dependency-groups] +dev = [ + "ruff>=0.15.12,<0.16.0", +] + +[tool.uv.sources] +quantiles = { path = "../../python", editable = true } + +[tool.ruff] +target-version = "py312" +line-length = 100 +indent-width = 2 + +[tool.ruff.format] +indent-style = "space" +quote-style = "double" diff --git a/custom-code-examples/swebench-pro/swebench_pro.py b/custom-code-examples/swebench-pro/swebench_pro.py new file mode 100644 index 0000000..6263f1a --- /dev/null +++ b/custom-code-examples/swebench-pro/swebench_pro.py @@ -0,0 +1,342 @@ +"""Run the official SWE-Bench Pro patch evaluator as a Quantiles workflow.""" + +import asyncio +import json +import shutil +import sys +from collections.abc import Awaitable, Callable +from dataclasses import dataclass +from pathlib import Path +from typing import cast + +from pydantic import BaseModel, Field +from quantiles import emit, entrypoint, step, workflow +from quantiles.types import JsonValue +from quantiles.workflow_context import WorkflowContext + +_UPSTREAM_REPOSITORY = "https://github.com/scaleapi/SWE-bench_Pro-os.git" + + +class SweBenchProInput(BaseModel): + """Optional overrides for Scale's official SWE-Bench Pro evaluator.""" + + cache_dir: str = ".swebench-pro-cache" + repo_path: str | None = None + evaluator_python: str | None = None + raw_sample_path: str | None = None + patch_path: str | None = None + output_dir: str = ".swebench-pro-results" + dockerhub_username: str = "jefzda" + num_workers: int = Field(default=1, ge=1) + use_local_docker: bool = True + docker_platform: str | None = None + block_network: bool = False + redo: bool = False + + +@dataclass(frozen=True) +class EvaluatorPaths: + repo: Path + python: Path + raw_samples: Path + patches: Path + output: Path + + +def _resolve_path(value: str, base_dir: Path) -> Path: + path = Path(value).expanduser() + return path.resolve() if path.is_absolute() else (base_dir / path).resolve() + + +def _require_file(path: Path, description: str) -> None: + if not path.is_file(): + raise ValueError(f"{description} does not exist: {path}") + + +def _summarize_results(results_path: Path) -> dict[str, JsonValue]: + raw_results = json.loads(results_path.read_text()) + if not isinstance(raw_results, dict) or not all( + isinstance(instance_id, str) and isinstance(resolved, bool) + for instance_id, resolved in raw_results.items() + ): + raise ValueError(f"Unexpected SWE-Bench Pro results in {results_path}") + + results = cast(dict[str, bool], raw_results) + total_count = len(results) + if total_count == 0: + raise ValueError("SWE-Bench Pro evaluator returned no results") + + resolved_count = sum(results.values()) + return cast( + dict[str, JsonValue], + { + "resolution_rate": resolved_count / total_count, + "resolved_count": resolved_count, + "total_count": total_count, + "results_path": str(results_path), + "results": results, + }, + ) + + +def _write_first_gold_patch(source_path: Path, destination_path: Path) -> None: + raw_patches = json.loads(source_path.read_text()) + if not isinstance(raw_patches, list) or not raw_patches: + raise ValueError(f"No gold patches found in {source_path}") + + first_patch = raw_patches[0] + if not isinstance(first_patch, dict): + raise ValueError(f"Unexpected gold patch in {source_path}") + instance_id = first_patch.get("instance_id") + patch = first_patch.get("patch") + prefix = first_patch.get("prefix") + if not isinstance(instance_id, str) or not isinstance(patch, str): + raise ValueError(f"Unexpected gold patch in {source_path}") + if prefix is not None and not isinstance(prefix, str): + raise ValueError(f"Unexpected gold patch prefix in {source_path}") + + destination_path.write_text( + json.dumps( + [{"instance_id": instance_id, "patch": patch, "prefix": prefix or "gold"}], + indent=2, + ) + ) + + +async def _run_command(command: list[str], *, cwd: Path, description: str) -> str: + process = await asyncio.create_subprocess_exec( + *command, + cwd=cwd, + stdout=asyncio.subprocess.PIPE, + stderr=asyncio.subprocess.PIPE, + ) + stdout, stderr = await process.communicate() + stdout_text = stdout.decode(errors="replace") + stderr_text = stderr.decode(errors="replace") + if process.returncode != 0: + raise RuntimeError( + f"{description} failed with exit code {process.returncode}.\n" + f"stdout tail:\n{stdout_text[-2000:]}\n" + f"stderr tail:\n{stderr_text[-2000:]}" + ) + return stdout_text + + +async def _ensure_upstream_repo(repo_path: Path, cache_dir: Path) -> None: + evaluator_path = repo_path / "swe_bench_pro_eval.py" + if evaluator_path.is_file(): + return + if repo_path.exists(): + raise ValueError( + f"SWE-Bench Pro cache is incomplete: {repo_path}. " + "Remove that cache directory and retry." + ) + + git = shutil.which("git") + if git is None: + raise ValueError("git is required to download the SWE-Bench Pro evaluator") + cache_dir.mkdir(parents=True, exist_ok=True) + print("Downloading the official SWE-Bench Pro evaluator...", flush=True) + await _run_command( + [git, "clone", "--depth", "1", _UPSTREAM_REPOSITORY, str(repo_path)], + cwd=cache_dir, + description="SWE-Bench Pro clone", + ) + + +async def _ensure_upstream_environment(repo_path: Path, evaluator_python: Path) -> None: + ready_marker = evaluator_python.parent / ".quantiles-ready" + if evaluator_python.is_file() and ready_marker.is_file(): + return + + uv = shutil.which("uv") + if uv is None: + raise ValueError("uv is required to prepare the SWE-Bench Pro evaluator") + requirements = repo_path / "requirements.txt" + _require_file(requirements, "SWE-Bench Pro requirements file") + + if not evaluator_python.is_file(): + print("Creating an isolated SWE-Bench Pro Python environment...", flush=True) + await _run_command( + [uv, "venv", str(evaluator_python.parent), "--python", sys.executable], + cwd=repo_path, + description="SWE-Bench Pro environment creation", + ) + + print("Installing the SWE-Bench Pro evaluator dependencies...", flush=True) + await _run_command( + [ + uv, + "pip", + "install", + "--python", + str(evaluator_python), + "-r", + str(requirements), + ], + cwd=repo_path, + description="SWE-Bench Pro dependency installation", + ) + ready_marker.write_text("ready\n") + + +async def _ensure_gold_smoke_patch( + repo_path: Path, evaluator_python: Path, patch_path: Path +) -> None: + if patch_path.is_file(): + return + + all_gold_patches = patch_path.parent / "gold_patches.json" + extractor = repo_path / "helper_code" / "extract_gold_patches.py" + _require_file(extractor, "SWE-Bench Pro gold patch extractor") + patch_path.parent.mkdir(parents=True, exist_ok=True) + + if not all_gold_patches.is_file(): + print( + "Downloading the public SWE-Bench Pro dataset and extracting gold patches...", + flush=True, + ) + await _run_command( + [str(evaluator_python), str(extractor), "--output", str(all_gold_patches)], + cwd=repo_path, + description="SWE-Bench Pro gold patch extraction", + ) + + _write_first_gold_patch(all_gold_patches, patch_path) + + +async def _prepare_paths(config: SweBenchProInput) -> EvaluatorPaths: + caller_dir = Path.cwd() + cache_dir = _resolve_path(config.cache_dir, caller_dir) + repo_path = ( + _resolve_path(config.repo_path, caller_dir) + if config.repo_path is not None + else cache_dir / "SWE-bench_Pro-os" + ) + evaluator_python = ( + _resolve_path(config.evaluator_python, caller_dir) + if config.evaluator_python is not None + else repo_path / ".venv" / "bin" / "python" + ) + + await _ensure_upstream_repo(repo_path, cache_dir) + if config.evaluator_python is None: + await _ensure_upstream_environment(repo_path, evaluator_python) + else: + _require_file(evaluator_python, "SWE-Bench Pro Python interpreter") + + raw_sample_path = ( + _resolve_path(config.raw_sample_path, caller_dir) + if config.raw_sample_path is not None + else repo_path / "helper_code" / "sweap_eval_full_v2.jsonl" + ) + patch_path = ( + _resolve_path(config.patch_path, caller_dir) + if config.patch_path is not None + else cache_dir / "one_gold_patch.json" + ) + if config.patch_path is None: + await _ensure_gold_smoke_patch(repo_path, evaluator_python, patch_path) + + return EvaluatorPaths( + repo=repo_path, + python=evaluator_python, + raw_samples=raw_sample_path, + patches=patch_path, + output=_resolve_path(config.output_dir, caller_dir), + ) + + +async def _run_official_evaluator(config: SweBenchProInput) -> JsonValue: + paths = await _prepare_paths(config) + evaluator_path = paths.repo / "swe_bench_pro_eval.py" + scripts_dir = paths.repo / "run_scripts" + + _require_file(evaluator_path, "Official SWE-Bench Pro evaluator") + _require_file(paths.python, "SWE-Bench Pro Python interpreter") + _require_file(paths.raw_samples, "Raw SWE-Bench Pro sample file") + _require_file(paths.patches, "SWE-Bench Pro predictions file") + if not scripts_dir.is_dir(): + raise ValueError( + f"SWE-Bench Pro run scripts directory does not exist: {scripts_dir}" + ) + + if config.use_local_docker: + docker = shutil.which("docker") + if docker is None: + raise ValueError("Docker is required for local SWE-Bench Pro evaluation") + await _run_command( + [docker, "info"], cwd=paths.repo, description="Docker availability check" + ) + + paths.output.mkdir(parents=True, exist_ok=True) + command = [ + str(paths.python), + str(evaluator_path), + f"--raw_sample_path={paths.raw_samples}", + f"--patch_path={paths.patches}", + f"--output_dir={paths.output}", + f"--scripts_dir={scripts_dir}", + f"--num_workers={config.num_workers}", + f"--dockerhub_username={config.dockerhub_username}", + ] + if config.use_local_docker: + command.append("--use_local_docker") + if config.docker_platform is not None: + command.append(f"--docker_platform={config.docker_platform}") + if config.block_network: + command.append("--block_network") + if config.redo: + command.append("--redo") + + print("Running the official SWE-Bench Pro evaluator...", flush=True) + await _run_command( + command, cwd=paths.repo, description="Official SWE-Bench Pro evaluator" + ) + + results_path = paths.output / "eval_results.json" + _require_file(results_path, "SWE-Bench Pro results file") + summary = _summarize_results(results_path) + summary["repo_path"] = str(paths.repo) + summary["patch_path"] = str(paths.patches) + return cast(JsonValue, summary) + + +async def handler(input_value: JsonValue, ctx: WorkflowContext) -> JsonValue: + config = SweBenchProInput.model_validate(input_value or {}) + summary = await step( + ctx, + step_key="evaluate-patches", + input_value=cast(JsonValue, config.model_dump(mode="json")), + execute=cast( + Callable[[], Awaitable[JsonValue]], + lambda: _run_official_evaluator(config), + ), + ) + if not isinstance(summary, dict): + raise ValueError("SWE-Bench Pro evaluation step returned an invalid summary") + + resolution_rate = summary.get("resolution_rate") + resolved_count = summary.get("resolved_count") + total_count = summary.get("total_count") + if not isinstance(resolution_rate, int | float): + raise ValueError("SWE-Bench Pro summary is missing resolution_rate") + if not isinstance(resolved_count, int | float): + raise ValueError("SWE-Bench Pro summary is missing resolved_count") + if not isinstance(total_count, int | float): + raise ValueError("SWE-Bench Pro summary is missing total_count") + if any( + isinstance(value, bool) + for value in (resolution_rate, resolved_count, total_count) + ): + raise ValueError("SWE-Bench Pro evaluation summary is missing numeric metrics") + + await emit(ctx, "resolution_rate", float(resolution_rate)) + await emit(ctx, "resolved_count", float(resolved_count)) + await emit(ctx, "total_count", float(total_count)) + return cast(JsonValue, summary) + + +if __name__ == "__main__": + swebench_pro = workflow("swebench-pro", handler) + entrypoint(swebench_pro) diff --git a/custom-code-examples/swebench-pro/tests/test_swebench_pro.py b/custom-code-examples/swebench-pro/tests/test_swebench_pro.py new file mode 100644 index 0000000..0cc19ed --- /dev/null +++ b/custom-code-examples/swebench-pro/tests/test_swebench_pro.py @@ -0,0 +1,65 @@ +import json +import unittest +from pathlib import Path +from tempfile import TemporaryDirectory + +from swebench_pro import _summarize_results, _write_first_gold_patch + + +class SweBenchProTest(unittest.TestCase): + def test_write_first_gold_patch(self) -> None: + with TemporaryDirectory() as directory: + temp_dir = Path(directory) + source = temp_dir / "gold.json" + destination = temp_dir / "one.json" + source.write_text( + json.dumps( + [ + { + "instance_id": "first", + "patch": "first patch", + "prefix": "gold", + }, + { + "instance_id": "second", + "patch": "second patch", + "prefix": "gold", + }, + ] + ) + ) + + _write_first_gold_patch(source, destination) + + self.assertEqual( + json.loads(destination.read_text()), + [{"instance_id": "first", "patch": "first patch", "prefix": "gold"}], + ) + + def test_summarize_results(self) -> None: + with TemporaryDirectory() as directory: + results = Path(directory) / "eval_results.json" + results.write_text(json.dumps({"first": True, "second": False})) + + self.assertEqual( + _summarize_results(results), + { + "resolution_rate": 0.5, + "resolved_count": 1, + "total_count": 2, + "results_path": str(results), + "results": {"first": True, "second": False}, + }, + ) + + def test_summarize_results_rejects_empty_results(self) -> None: + with TemporaryDirectory() as directory: + results = Path(directory) / "eval_results.json" + results.write_text("{}") + + with self.assertRaisesRegex(ValueError, "returned no results"): + _summarize_results(results) + + +if __name__ == "__main__": + unittest.main() diff --git a/cli/examples/configs/tau3_airline/.gitignore b/custom-code-examples/t3-airline/.gitignore similarity index 100% rename from cli/examples/configs/tau3_airline/.gitignore rename to custom-code-examples/t3-airline/.gitignore diff --git a/cli/examples/configs/tau3_airline/README.md b/custom-code-examples/t3-airline/README.md similarity index 90% rename from cli/examples/configs/tau3_airline/README.md rename to custom-code-examples/t3-airline/README.md index 40ccfa5..22b6a87 100644 --- a/cli/examples/configs/tau3_airline/README.md +++ b/custom-code-examples/t3-airline/README.md @@ -1,4 +1,4 @@ -# τ³ Airline `custom_code` example +# T3 Airline `custom_code` example This example wraps the official [`tau2` `v1.0.1` tag](https://github.com/sierra-research/tau2-bench/tree/v1.0.1) airline runner in one durable Quantiles step. The adapter environment installs that immutable Git tag because τ³ is not published as a `tau2==1.0.1` package on PyPI. τ³ remains responsible for loading tasks, simulating the user, providing airline tools and state, and calculating rewards; the adapter records the official result and emits `average_reward`, `success_rate`, and `simulation_count`. @@ -11,10 +11,10 @@ The adapter intentionally starts with one task and one trial. It accepts these i ## Run -Install `uv`, make Python 3.12 available to it, and run the following one-time setup from this directory: +Install `uv`, make Python 3.12 available to it, and run the following one-time setup from the `custom-code-examples` directory: ```bash -git clone --branch v1.0.1 --depth 1 https://github.com/sierra-research/tau2-bench.git .tau3/tau2-bench +git clone --branch v1.0.1 --depth 1 https://github.com/sierra-research/tau2-bench.git t3-airline/.tau3/tau2-bench ``` The adapter installs the τ³ Python modules from the same immutable tag and reads benchmark tasks and databases from this ignored checkout. This is necessary because the Git-installed Python wheel does not contain the upstream `data/` tree. The adapter also constrains the environment to Python 3.12 because the pinned τ³ release imports the removed `audioop` standard-library module on Python 3.13, including in text mode. @@ -22,7 +22,7 @@ The adapter installs the τ³ Python modules from the same immutable tag and rea Configure the API keys required by the two selected models, then run: ```bash -qt run tau3-airline +qt run t3-airline ``` For example, both default models require `OPENAI_API_KEY`. A run calls external model providers and may incur charges. Quantiles remains local-first for its run metadata, step output, and metrics, while the configured τ³ models are an explicit networked exception. @@ -30,7 +30,7 @@ For example, both default models require `OPENAI_API_KEY`. A run calls external Override the defaults with `--input`: ```bash -qt run tau3-airline --input '{"agent_model":"openai:gpt-4.1","user_model":"openai:gpt-4.1","task_ids":["0"],"num_trials":1}' +qt run t3-airline --input '{"agent_model":"openai:gpt-4.1","user_model":"openai:gpt-4.1","task_ids":["0"],"num_trials":1}' ``` Inspect or compare the resulting runs: diff --git a/cli/examples/configs/tau3_airline/pyproject.toml b/custom-code-examples/t3-airline/pyproject.toml similarity index 85% rename from cli/examples/configs/tau3_airline/pyproject.toml rename to custom-code-examples/t3-airline/pyproject.toml index db54c2c..01d561c 100644 --- a/cli/examples/configs/tau3_airline/pyproject.toml +++ b/custom-code-examples/t3-airline/pyproject.toml @@ -1,5 +1,5 @@ [project] -name = "quantiles-tau3-airline-example" +name = "quantiles-t3-airline-example" version = "0.1.0" description = "Minimal Quantiles custom_code adapter for the tau3 airline benchmark" requires-python = ">=3.12,<3.13" @@ -15,7 +15,7 @@ dev = [ ] [tool.uv.sources] -quantiles = { path = "../../../../python", editable = true } +quantiles = { path = "../../python", editable = true } tau2 = { git = "https://github.com/sierra-research/tau2-bench.git", tag = "v1.0.1" } [tool.ruff] diff --git a/cli/examples/configs/tau3_airline/tau3_airline.py b/custom-code-examples/t3-airline/t3_airline.py similarity index 98% rename from cli/examples/configs/tau3_airline/tau3_airline.py rename to custom-code-examples/t3-airline/t3_airline.py index 275e0f4..ec19c47 100644 --- a/cli/examples/configs/tau3_airline/tau3_airline.py +++ b/custom-code-examples/t3-airline/t3_airline.py @@ -193,7 +193,7 @@ def run_tau3(config: Tau3AirlineConfig) -> dict[str, JsonValue]: f"task {first['task_id']}, trial {first['trial']}: {first['error']}" ) return { - "benchmark": "tau3-airline", + "benchmark": "t3-airline", "config": config.to_json(), "summary": summarize_results(upstream), "upstream": upstream, @@ -208,7 +208,7 @@ async def execute() -> JsonValue: result = await step( ctx, - step_key="run-official-tau3-airline", + step_key="run-official-t3-airline", input_value=config.to_json(), execute=execute, ) @@ -226,7 +226,7 @@ async def execute() -> JsonValue: return result -tau3_airline = workflow("tau3-airline", handler) +t3_airline = workflow("t3-airline", handler) if __name__ == "__main__": - entrypoint(tau3_airline) + entrypoint(t3_airline) diff --git a/cli/examples/configs/tau3_airline/tests/test_tau3_airline.py b/custom-code-examples/t3-airline/tests/test_t3_airline.py similarity index 82% rename from cli/examples/configs/tau3_airline/tests/test_tau3_airline.py rename to custom-code-examples/t3-airline/tests/test_t3_airline.py index daccab7..2bf1060 100644 --- a/cli/examples/configs/tau3_airline/tests/test_tau3_airline.py +++ b/custom-code-examples/t3-airline/tests/test_t3_airline.py @@ -3,11 +3,11 @@ import pytest -import tau3_airline +import t3_airline def test_parse_config_uses_small_defaults_and_normalizes_models() -> None: - config = tau3_airline.parse_config( + config = t3_airline.parse_config( { "agent_model": "anthropic:claude-sonnet-4-5", "user_model": "openai:gpt-4.1", @@ -22,7 +22,7 @@ def test_parse_config_uses_small_defaults_and_normalizes_models() -> None: def test_parse_config_accepts_task_ids() -> None: - config = tau3_airline.parse_config({"task_ids": ["0", "1"], "seed": 42}) + config = t3_airline.parse_config({"task_ids": ["0", "1"], "seed": 42}) assert config.task_ids == ("0", "1") assert config.seed == 42 @@ -39,11 +39,11 @@ def test_parse_config_accepts_task_ids() -> None: ) def test_parse_config_rejects_invalid_input(input_value: object, message: str) -> None: with pytest.raises(ValueError, match=message): - tau3_airline.parse_config(input_value) # type: ignore[arg-type] + t3_airline.parse_config(input_value) # type: ignore[arg-type] def test_summarize_results_uses_official_rewards() -> None: - summary = tau3_airline.summarize_results( + summary = t3_airline.summarize_results( { "simulations": [ {"reward_info": {"reward": 1.0}}, @@ -61,7 +61,7 @@ def test_summarize_results_uses_official_rewards() -> None: def test_infrastructure_failures_extracts_upstream_error() -> None: - failures = tau3_airline.infrastructure_failures( + failures = t3_airline.infrastructure_failures( { "simulations": [ { @@ -110,11 +110,11 @@ def fake_run_domain(config: object) -> _FakeResults: assert config is captured return _FakeResults({"simulations": [{"reward_info": {"reward": 1.0}}]}) - monkeypatch.setattr(tau3_airline, "_load_tau3", lambda: (fake_run_domain, fake_config)) + monkeypatch.setattr(t3_airline, "_load_tau3", lambda: (fake_run_domain, fake_config)) data_dir = tmp_path / "data" data_dir.mkdir() - result = tau3_airline.run_tau3(tau3_airline.Tau3AirlineConfig(data_dir=str(data_dir))) + result = t3_airline.run_tau3(t3_airline.Tau3AirlineConfig(data_dir=str(data_dir))) assert captured["domain"] == "airline" assert captured["task_split_name"] == "base" @@ -128,10 +128,10 @@ def fake_run_domain(config: object) -> _FakeResults: def test_run_tau3_requires_upstream_data_checkout(tmp_path: Path) -> None: - config = tau3_airline.Tau3AirlineConfig(data_dir=str(tmp_path / "missing")) + config = t3_airline.Tau3AirlineConfig(data_dir=str(tmp_path / "missing")) with pytest.raises(FileNotFoundError, match="tau3 data directory not found"): - tau3_airline.run_tau3(config) + t3_airline.run_tau3(config) def test_run_tau3_raises_for_upstream_infrastructure_failure( @@ -154,13 +154,13 @@ def fake_run_domain(_config: object) -> _FakeResults: } ) - monkeypatch.setattr(tau3_airline, "_load_tau3", lambda: (fake_run_domain, fake_config)) + monkeypatch.setattr(t3_airline, "_load_tau3", lambda: (fake_run_domain, fake_config)) data_dir = tmp_path / "data" data_dir.mkdir() - config = tau3_airline.Tau3AirlineConfig(data_dir=str(data_dir)) + config = t3_airline.Tau3AirlineConfig(data_dir=str(data_dir)) with pytest.raises( RuntimeError, match=r"tau3 reported 1 infrastructure failure\(s\); task 0, trial 0: provider denied", ): - tau3_airline.run_tau3(config) + t3_airline.run_tau3(config) diff --git a/cli/examples/configs/tau3_airline/uv.lock b/custom-code-examples/t3-airline/uv.lock similarity index 99% rename from cli/examples/configs/tau3_airline/uv.lock rename to custom-code-examples/t3-airline/uv.lock index a67a610..f541759 100644 --- a/cli/examples/configs/tau3_airline/uv.lock +++ b/custom-code-examples/t3-airline/uv.lock @@ -809,7 +809,7 @@ wheels = [ [[package]] name = "quantiles" version = "0.1.0" -source = { editable = "../../../../python" } +source = { editable = "../../python" } dependencies = [ { name = "aiohttp" }, { name = "numpy" }, @@ -836,7 +836,7 @@ dev = [ ] [[package]] -name = "quantiles-tau3-airline-example" +name = "quantiles-t3-airline-example" version = "0.1.0" source = { virtual = "." } dependencies = [ @@ -852,7 +852,7 @@ dev = [ [package.metadata] requires-dist = [ - { name = "quantiles", editable = "../../../../python" }, + { name = "quantiles", editable = "../../python" }, { name = "tau2", git = "https://github.com/sierra-research/tau2-bench.git?tag=v1.0.1" }, ] diff --git a/mise.toml b/mise.toml index c684e2f..eb5ab87 100644 --- a/mise.toml +++ b/mise.toml @@ -1,7 +1,7 @@ monorepo_root = true [monorepo] -config_roots = [".", "cli", "typescript", "python", "python-examples"] +config_roots = [".", "cli", "typescript", "python", "python-examples", "custom-code-examples/t3-airline", "custom-code-examples/swebench-pro"] [tools] # needed by the `.use_buf()` call in cli/build.rs From 5b6bd4b60ba0a9f7d8d759a430c3174758c2e655 Mon Sep 17 00:00:00 2001 From: Aaron Schlesinger <70865+arschles@users.noreply.github.com> Date: Mon, 10 Aug 2026 20:57:24 -0700 Subject: [PATCH 4/4] progress --- .../swebench-pro/swebench_pro.py | 538 +++++---- .../swebench-pro/tests/test_swebench_pro.py | 94 +- custom-code-examples/swebench-pro/uv.lock | 1001 +++++++++++++++++ 3 files changed, 1312 insertions(+), 321 deletions(-) create mode 100644 custom-code-examples/swebench-pro/uv.lock diff --git a/custom-code-examples/swebench-pro/swebench_pro.py b/custom-code-examples/swebench-pro/swebench_pro.py index 6263f1a..20bed1c 100644 --- a/custom-code-examples/swebench-pro/swebench_pro.py +++ b/custom-code-examples/swebench-pro/swebench_pro.py @@ -18,325 +18,315 @@ class SweBenchProInput(BaseModel): - """Optional overrides for Scale's official SWE-Bench Pro evaluator.""" - - cache_dir: str = ".swebench-pro-cache" - repo_path: str | None = None - evaluator_python: str | None = None - raw_sample_path: str | None = None - patch_path: str | None = None - output_dir: str = ".swebench-pro-results" - dockerhub_username: str = "jefzda" - num_workers: int = Field(default=1, ge=1) - use_local_docker: bool = True - docker_platform: str | None = None - block_network: bool = False - redo: bool = False + """Optional overrides for Scale's official SWE-Bench Pro evaluator.""" + + cache_dir: str = ".swebench-pro-cache" + repo_path: str | None = None + evaluator_python: str | None = None + raw_sample_path: str | None = None + patch_path: str | None = None + output_dir: str = ".swebench-pro-results" + dockerhub_username: str = "jefzda" + num_workers: int = Field(default=1, ge=1) + use_local_docker: bool = True + docker_platform: str | None = None + block_network: bool = False + redo: bool = False @dataclass(frozen=True) class EvaluatorPaths: - repo: Path - python: Path - raw_samples: Path - patches: Path - output: Path + repo: Path + python: Path + raw_samples: Path + patches: Path + output: Path def _resolve_path(value: str, base_dir: Path) -> Path: - path = Path(value).expanduser() - return path.resolve() if path.is_absolute() else (base_dir / path).resolve() + path = Path(value).expanduser() + return path.resolve() if path.is_absolute() else (base_dir / path).resolve() def _require_file(path: Path, description: str) -> None: - if not path.is_file(): - raise ValueError(f"{description} does not exist: {path}") + if not path.is_file(): + raise ValueError(f"{description} does not exist: {path}") def _summarize_results(results_path: Path) -> dict[str, JsonValue]: - raw_results = json.loads(results_path.read_text()) - if not isinstance(raw_results, dict) or not all( - isinstance(instance_id, str) and isinstance(resolved, bool) - for instance_id, resolved in raw_results.items() - ): - raise ValueError(f"Unexpected SWE-Bench Pro results in {results_path}") - - results = cast(dict[str, bool], raw_results) - total_count = len(results) - if total_count == 0: - raise ValueError("SWE-Bench Pro evaluator returned no results") - - resolved_count = sum(results.values()) - return cast( - dict[str, JsonValue], - { - "resolution_rate": resolved_count / total_count, - "resolved_count": resolved_count, - "total_count": total_count, - "results_path": str(results_path), - "results": results, - }, - ) + raw_results = json.loads(results_path.read_text()) + if not isinstance(raw_results, dict) or not all( + isinstance(instance_id, str) and isinstance(resolved, bool) + for instance_id, resolved in raw_results.items() + ): + raise ValueError(f"Unexpected SWE-Bench Pro results in {results_path}") + + results = cast(dict[str, bool], raw_results) + total_count = len(results) + if total_count == 0: + raise ValueError("SWE-Bench Pro evaluator returned no results") + + resolved_count = sum(results.values()) + return cast( + dict[str, JsonValue], + { + "resolution_rate": resolved_count / total_count, + "resolved_count": resolved_count, + "total_count": total_count, + "results_path": str(results_path), + "results": results, + }, + ) def _write_first_gold_patch(source_path: Path, destination_path: Path) -> None: - raw_patches = json.loads(source_path.read_text()) - if not isinstance(raw_patches, list) or not raw_patches: - raise ValueError(f"No gold patches found in {source_path}") - - first_patch = raw_patches[0] - if not isinstance(first_patch, dict): - raise ValueError(f"Unexpected gold patch in {source_path}") - instance_id = first_patch.get("instance_id") - patch = first_patch.get("patch") - prefix = first_patch.get("prefix") - if not isinstance(instance_id, str) or not isinstance(patch, str): - raise ValueError(f"Unexpected gold patch in {source_path}") - if prefix is not None and not isinstance(prefix, str): - raise ValueError(f"Unexpected gold patch prefix in {source_path}") - - destination_path.write_text( - json.dumps( - [{"instance_id": instance_id, "patch": patch, "prefix": prefix or "gold"}], - indent=2, - ) + raw_patches = json.loads(source_path.read_text()) + if not isinstance(raw_patches, list) or not raw_patches: + raise ValueError(f"No gold patches found in {source_path}") + + first_patch = raw_patches[0] + if not isinstance(first_patch, dict): + raise ValueError(f"Unexpected gold patch in {source_path}") + instance_id = first_patch.get("instance_id") + patch = first_patch.get("patch") + prefix = first_patch.get("prefix") + if not isinstance(instance_id, str) or not isinstance(patch, str): + raise ValueError(f"Unexpected gold patch in {source_path}") + if prefix is not None and not isinstance(prefix, str): + raise ValueError(f"Unexpected gold patch prefix in {source_path}") + + destination_path.write_text( + json.dumps( + [{"instance_id": instance_id, "patch": patch, "prefix": prefix or "gold"}], + indent=2, ) + ) async def _run_command(command: list[str], *, cwd: Path, description: str) -> str: - process = await asyncio.create_subprocess_exec( - *command, - cwd=cwd, - stdout=asyncio.subprocess.PIPE, - stderr=asyncio.subprocess.PIPE, + process = await asyncio.create_subprocess_exec( + *command, + cwd=cwd, + stdout=asyncio.subprocess.PIPE, + stderr=asyncio.subprocess.PIPE, + ) + stdout, stderr = await process.communicate() + stdout_text = stdout.decode(errors="replace") + stderr_text = stderr.decode(errors="replace") + if process.returncode != 0: + raise RuntimeError( + f"{description} failed with exit code {process.returncode}.\n" + f"stdout tail:\n{stdout_text[-2000:]}\n" + f"stderr tail:\n{stderr_text[-2000:]}" ) - stdout, stderr = await process.communicate() - stdout_text = stdout.decode(errors="replace") - stderr_text = stderr.decode(errors="replace") - if process.returncode != 0: - raise RuntimeError( - f"{description} failed with exit code {process.returncode}.\n" - f"stdout tail:\n{stdout_text[-2000:]}\n" - f"stderr tail:\n{stderr_text[-2000:]}" - ) - return stdout_text + return stdout_text async def _ensure_upstream_repo(repo_path: Path, cache_dir: Path) -> None: - evaluator_path = repo_path / "swe_bench_pro_eval.py" - if evaluator_path.is_file(): - return - if repo_path.exists(): - raise ValueError( - f"SWE-Bench Pro cache is incomplete: {repo_path}. " - "Remove that cache directory and retry." - ) - - git = shutil.which("git") - if git is None: - raise ValueError("git is required to download the SWE-Bench Pro evaluator") - cache_dir.mkdir(parents=True, exist_ok=True) - print("Downloading the official SWE-Bench Pro evaluator...", flush=True) - await _run_command( - [git, "clone", "--depth", "1", _UPSTREAM_REPOSITORY, str(repo_path)], - cwd=cache_dir, - description="SWE-Bench Pro clone", + evaluator_path = repo_path / "swe_bench_pro_eval.py" + if evaluator_path.is_file(): + return + if repo_path.exists(): + raise ValueError( + f"SWE-Bench Pro cache is incomplete: {repo_path}. Remove that cache directory and retry." ) + git = shutil.which("git") + if git is None: + raise ValueError("git is required to download the SWE-Bench Pro evaluator") + cache_dir.mkdir(parents=True, exist_ok=True) + print("Downloading the official SWE-Bench Pro evaluator...", flush=True) + await _run_command( + [git, "clone", "--depth", "1", _UPSTREAM_REPOSITORY, str(repo_path)], + cwd=cache_dir, + description="SWE-Bench Pro clone", + ) + async def _ensure_upstream_environment(repo_path: Path, evaluator_python: Path) -> None: - ready_marker = evaluator_python.parent / ".quantiles-ready" - if evaluator_python.is_file() and ready_marker.is_file(): - return - - uv = shutil.which("uv") - if uv is None: - raise ValueError("uv is required to prepare the SWE-Bench Pro evaluator") - requirements = repo_path / "requirements.txt" - _require_file(requirements, "SWE-Bench Pro requirements file") - - if not evaluator_python.is_file(): - print("Creating an isolated SWE-Bench Pro Python environment...", flush=True) - await _run_command( - [uv, "venv", str(evaluator_python.parent), "--python", sys.executable], - cwd=repo_path, - description="SWE-Bench Pro environment creation", - ) - - print("Installing the SWE-Bench Pro evaluator dependencies...", flush=True) + ready_marker = evaluator_python.parent / ".quantiles-ready" + if evaluator_python.is_file() and ready_marker.is_file(): + return + + uv = shutil.which("uv") + if uv is None: + raise ValueError("uv is required to prepare the SWE-Bench Pro evaluator") + requirements = repo_path / "requirements.txt" + _require_file(requirements, "SWE-Bench Pro requirements file") + + if not evaluator_python.is_file(): + print("Creating an isolated SWE-Bench Pro Python environment...", flush=True) await _run_command( - [ - uv, - "pip", - "install", - "--python", - str(evaluator_python), - "-r", - str(requirements), - ], - cwd=repo_path, - description="SWE-Bench Pro dependency installation", + [uv, "venv", str(evaluator_python.parent), "--python", sys.executable], + cwd=repo_path, + description="SWE-Bench Pro environment creation", ) - ready_marker.write_text("ready\n") + + print("Installing the SWE-Bench Pro evaluator dependencies...", flush=True) + await _run_command( + [ + uv, + "pip", + "install", + "--python", + str(evaluator_python), + "-r", + str(requirements), + ], + cwd=repo_path, + description="SWE-Bench Pro dependency installation", + ) + ready_marker.write_text("ready\n") async def _ensure_gold_smoke_patch( - repo_path: Path, evaluator_python: Path, patch_path: Path + repo_path: Path, evaluator_python: Path, patch_path: Path ) -> None: - if patch_path.is_file(): - return - - all_gold_patches = patch_path.parent / "gold_patches.json" - extractor = repo_path / "helper_code" / "extract_gold_patches.py" - _require_file(extractor, "SWE-Bench Pro gold patch extractor") - patch_path.parent.mkdir(parents=True, exist_ok=True) - - if not all_gold_patches.is_file(): - print( - "Downloading the public SWE-Bench Pro dataset and extracting gold patches...", - flush=True, - ) - await _run_command( - [str(evaluator_python), str(extractor), "--output", str(all_gold_patches)], - cwd=repo_path, - description="SWE-Bench Pro gold patch extraction", - ) - - _write_first_gold_patch(all_gold_patches, patch_path) - - -async def _prepare_paths(config: SweBenchProInput) -> EvaluatorPaths: - caller_dir = Path.cwd() - cache_dir = _resolve_path(config.cache_dir, caller_dir) - repo_path = ( - _resolve_path(config.repo_path, caller_dir) - if config.repo_path is not None - else cache_dir / "SWE-bench_Pro-os" + if patch_path.is_file(): + return + + all_gold_patches = patch_path.parent / "gold_patches.json" + extractor = repo_path / "helper_code" / "extract_gold_patches.py" + _require_file(extractor, "SWE-Bench Pro gold patch extractor") + patch_path.parent.mkdir(parents=True, exist_ok=True) + + if not all_gold_patches.is_file(): + print( + "Downloading the public SWE-Bench Pro dataset and extracting gold patches...", + flush=True, ) - evaluator_python = ( - _resolve_path(config.evaluator_python, caller_dir) - if config.evaluator_python is not None - else repo_path / ".venv" / "bin" / "python" + await _run_command( + [str(evaluator_python), str(extractor), "--output", str(all_gold_patches)], + cwd=repo_path, + description="SWE-Bench Pro gold patch extraction", ) - await _ensure_upstream_repo(repo_path, cache_dir) - if config.evaluator_python is None: - await _ensure_upstream_environment(repo_path, evaluator_python) - else: - _require_file(evaluator_python, "SWE-Bench Pro Python interpreter") + _write_first_gold_patch(all_gold_patches, patch_path) - raw_sample_path = ( - _resolve_path(config.raw_sample_path, caller_dir) - if config.raw_sample_path is not None - else repo_path / "helper_code" / "sweap_eval_full_v2.jsonl" - ) - patch_path = ( - _resolve_path(config.patch_path, caller_dir) - if config.patch_path is not None - else cache_dir / "one_gold_patch.json" - ) - if config.patch_path is None: - await _ensure_gold_smoke_patch(repo_path, evaluator_python, patch_path) - - return EvaluatorPaths( - repo=repo_path, - python=evaluator_python, - raw_samples=raw_sample_path, - patches=patch_path, - output=_resolve_path(config.output_dir, caller_dir), - ) + +async def _prepare_paths(config: SweBenchProInput) -> EvaluatorPaths: + caller_dir = Path.cwd() + cache_dir = _resolve_path(config.cache_dir, caller_dir) + repo_path = ( + _resolve_path(config.repo_path, caller_dir) + if config.repo_path is not None + else cache_dir / "SWE-bench_Pro-os" + ) + evaluator_python = ( + _resolve_path(config.evaluator_python, caller_dir) + if config.evaluator_python is not None + else repo_path / ".venv" / "bin" / "python" + ) + + await _ensure_upstream_repo(repo_path, cache_dir) + if config.evaluator_python is None: + await _ensure_upstream_environment(repo_path, evaluator_python) + else: + _require_file(evaluator_python, "SWE-Bench Pro Python interpreter") + + raw_sample_path = ( + _resolve_path(config.raw_sample_path, caller_dir) + if config.raw_sample_path is not None + else repo_path / "helper_code" / "sweap_eval_full_v2.jsonl" + ) + patch_path = ( + _resolve_path(config.patch_path, caller_dir) + if config.patch_path is not None + else cache_dir / "one_gold_patch.json" + ) + if config.patch_path is None: + await _ensure_gold_smoke_patch(repo_path, evaluator_python, patch_path) + + return EvaluatorPaths( + repo=repo_path, + python=evaluator_python, + raw_samples=raw_sample_path, + patches=patch_path, + output=_resolve_path(config.output_dir, caller_dir), + ) async def _run_official_evaluator(config: SweBenchProInput) -> JsonValue: - paths = await _prepare_paths(config) - evaluator_path = paths.repo / "swe_bench_pro_eval.py" - scripts_dir = paths.repo / "run_scripts" - - _require_file(evaluator_path, "Official SWE-Bench Pro evaluator") - _require_file(paths.python, "SWE-Bench Pro Python interpreter") - _require_file(paths.raw_samples, "Raw SWE-Bench Pro sample file") - _require_file(paths.patches, "SWE-Bench Pro predictions file") - if not scripts_dir.is_dir(): - raise ValueError( - f"SWE-Bench Pro run scripts directory does not exist: {scripts_dir}" - ) - - if config.use_local_docker: - docker = shutil.which("docker") - if docker is None: - raise ValueError("Docker is required for local SWE-Bench Pro evaluation") - await _run_command( - [docker, "info"], cwd=paths.repo, description="Docker availability check" - ) - - paths.output.mkdir(parents=True, exist_ok=True) - command = [ - str(paths.python), - str(evaluator_path), - f"--raw_sample_path={paths.raw_samples}", - f"--patch_path={paths.patches}", - f"--output_dir={paths.output}", - f"--scripts_dir={scripts_dir}", - f"--num_workers={config.num_workers}", - f"--dockerhub_username={config.dockerhub_username}", - ] - if config.use_local_docker: - command.append("--use_local_docker") - if config.docker_platform is not None: - command.append(f"--docker_platform={config.docker_platform}") - if config.block_network: - command.append("--block_network") - if config.redo: - command.append("--redo") - - print("Running the official SWE-Bench Pro evaluator...", flush=True) - await _run_command( - command, cwd=paths.repo, description="Official SWE-Bench Pro evaluator" - ) - - results_path = paths.output / "eval_results.json" - _require_file(results_path, "SWE-Bench Pro results file") - summary = _summarize_results(results_path) - summary["repo_path"] = str(paths.repo) - summary["patch_path"] = str(paths.patches) - return cast(JsonValue, summary) + paths = await _prepare_paths(config) + evaluator_path = paths.repo / "swe_bench_pro_eval.py" + scripts_dir = paths.repo / "run_scripts" + + _require_file(evaluator_path, "Official SWE-Bench Pro evaluator") + _require_file(paths.python, "SWE-Bench Pro Python interpreter") + _require_file(paths.raw_samples, "Raw SWE-Bench Pro sample file") + _require_file(paths.patches, "SWE-Bench Pro predictions file") + if not scripts_dir.is_dir(): + raise ValueError(f"SWE-Bench Pro run scripts directory does not exist: {scripts_dir}") + + if config.use_local_docker: + docker = shutil.which("docker") + if docker is None: + raise ValueError("Docker is required for local SWE-Bench Pro evaluation") + await _run_command([docker, "info"], cwd=paths.repo, description="Docker availability check") + + paths.output.mkdir(parents=True, exist_ok=True) + command = [ + str(paths.python), + str(evaluator_path), + f"--raw_sample_path={paths.raw_samples}", + f"--patch_path={paths.patches}", + f"--output_dir={paths.output}", + f"--scripts_dir={scripts_dir}", + f"--num_workers={config.num_workers}", + f"--dockerhub_username={config.dockerhub_username}", + ] + if config.use_local_docker: + command.append("--use_local_docker") + if config.docker_platform is not None: + command.append(f"--docker_platform={config.docker_platform}") + if config.block_network: + command.append("--block_network") + if config.redo: + command.append("--redo") + + print("Running the official SWE-Bench Pro evaluator...", flush=True) + await _run_command(command, cwd=paths.repo, description="Official SWE-Bench Pro evaluator") + + results_path = paths.output / "eval_results.json" + _require_file(results_path, "SWE-Bench Pro results file") + summary = _summarize_results(results_path) + summary["repo_path"] = str(paths.repo) + summary["patch_path"] = str(paths.patches) + return cast(JsonValue, summary) async def handler(input_value: JsonValue, ctx: WorkflowContext) -> JsonValue: - config = SweBenchProInput.model_validate(input_value or {}) - summary = await step( - ctx, - step_key="evaluate-patches", - input_value=cast(JsonValue, config.model_dump(mode="json")), - execute=cast( - Callable[[], Awaitable[JsonValue]], - lambda: _run_official_evaluator(config), - ), - ) - if not isinstance(summary, dict): - raise ValueError("SWE-Bench Pro evaluation step returned an invalid summary") - - resolution_rate = summary.get("resolution_rate") - resolved_count = summary.get("resolved_count") - total_count = summary.get("total_count") - if not isinstance(resolution_rate, int | float): - raise ValueError("SWE-Bench Pro summary is missing resolution_rate") - if not isinstance(resolved_count, int | float): - raise ValueError("SWE-Bench Pro summary is missing resolved_count") - if not isinstance(total_count, int | float): - raise ValueError("SWE-Bench Pro summary is missing total_count") - if any( - isinstance(value, bool) - for value in (resolution_rate, resolved_count, total_count) - ): - raise ValueError("SWE-Bench Pro evaluation summary is missing numeric metrics") - - await emit(ctx, "resolution_rate", float(resolution_rate)) - await emit(ctx, "resolved_count", float(resolved_count)) - await emit(ctx, "total_count", float(total_count)) - return cast(JsonValue, summary) + config = SweBenchProInput.model_validate(input_value or {}) + summary = await step( + ctx, + step_key="evaluate-patches", + input_value=cast(JsonValue, config.model_dump(mode="json")), + execute=cast( + Callable[[], Awaitable[JsonValue]], + lambda: _run_official_evaluator(config), + ), + ) + if not isinstance(summary, dict): + raise ValueError("SWE-Bench Pro evaluation step returned an invalid summary") + + resolution_rate = summary.get("resolution_rate") + resolved_count = summary.get("resolved_count") + total_count = summary.get("total_count") + if not isinstance(resolution_rate, int | float): + raise ValueError("SWE-Bench Pro summary is missing resolution_rate") + if not isinstance(resolved_count, int | float): + raise ValueError("SWE-Bench Pro summary is missing resolved_count") + if not isinstance(total_count, int | float): + raise ValueError("SWE-Bench Pro summary is missing total_count") + if any(isinstance(value, bool) for value in (resolution_rate, resolved_count, total_count)): + raise ValueError("SWE-Bench Pro evaluation summary is missing numeric metrics") + + await emit(ctx, "resolution_rate", float(resolution_rate)) + await emit(ctx, "resolved_count", float(resolved_count)) + await emit(ctx, "total_count", float(total_count)) + return cast(JsonValue, summary) if __name__ == "__main__": swebench_pro = workflow("swebench-pro", handler) - entrypoint(swebench_pro) + entrypoint(swebench_pro) diff --git a/custom-code-examples/swebench-pro/tests/test_swebench_pro.py b/custom-code-examples/swebench-pro/tests/test_swebench_pro.py index 0cc19ed..afa2b94 100644 --- a/custom-code-examples/swebench-pro/tests/test_swebench_pro.py +++ b/custom-code-examples/swebench-pro/tests/test_swebench_pro.py @@ -7,59 +7,59 @@ class SweBenchProTest(unittest.TestCase): - def test_write_first_gold_patch(self) -> None: - with TemporaryDirectory() as directory: - temp_dir = Path(directory) - source = temp_dir / "gold.json" - destination = temp_dir / "one.json" - source.write_text( - json.dumps( - [ - { - "instance_id": "first", - "patch": "first patch", - "prefix": "gold", - }, - { - "instance_id": "second", - "patch": "second patch", - "prefix": "gold", - }, - ] - ) - ) + def test_write_first_gold_patch(self) -> None: + with TemporaryDirectory() as directory: + temp_dir = Path(directory) + source = temp_dir / "gold.json" + destination = temp_dir / "one.json" + source.write_text( + json.dumps( + [ + { + "instance_id": "first", + "patch": "first patch", + "prefix": "gold", + }, + { + "instance_id": "second", + "patch": "second patch", + "prefix": "gold", + }, + ] + ) + ) - _write_first_gold_patch(source, destination) + _write_first_gold_patch(source, destination) - self.assertEqual( - json.loads(destination.read_text()), - [{"instance_id": "first", "patch": "first patch", "prefix": "gold"}], - ) + self.assertEqual( + json.loads(destination.read_text()), + [{"instance_id": "first", "patch": "first patch", "prefix": "gold"}], + ) - def test_summarize_results(self) -> None: - with TemporaryDirectory() as directory: - results = Path(directory) / "eval_results.json" - results.write_text(json.dumps({"first": True, "second": False})) + def test_summarize_results(self) -> None: + with TemporaryDirectory() as directory: + results = Path(directory) / "eval_results.json" + results.write_text(json.dumps({"first": True, "second": False})) - self.assertEqual( - _summarize_results(results), - { - "resolution_rate": 0.5, - "resolved_count": 1, - "total_count": 2, - "results_path": str(results), - "results": {"first": True, "second": False}, - }, - ) + self.assertEqual( + _summarize_results(results), + { + "resolution_rate": 0.5, + "resolved_count": 1, + "total_count": 2, + "results_path": str(results), + "results": {"first": True, "second": False}, + }, + ) - def test_summarize_results_rejects_empty_results(self) -> None: - with TemporaryDirectory() as directory: - results = Path(directory) / "eval_results.json" - results.write_text("{}") + def test_summarize_results_rejects_empty_results(self) -> None: + with TemporaryDirectory() as directory: + results = Path(directory) / "eval_results.json" + results.write_text("{}") - with self.assertRaisesRegex(ValueError, "returned no results"): - _summarize_results(results) + with self.assertRaisesRegex(ValueError, "returned no results"): + _summarize_results(results) if __name__ == "__main__": - unittest.main() + unittest.main() diff --git a/custom-code-examples/swebench-pro/uv.lock b/custom-code-examples/swebench-pro/uv.lock new file mode 100644 index 0000000..00a1277 --- /dev/null +++ b/custom-code-examples/swebench-pro/uv.lock @@ -0,0 +1,1001 @@ +version = 1 +revision = 3 +requires-python = ">=3.12" + +[[package]] +name = "aiohappyeyeballs" +version = "2.7.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/ce/f4/eec0465c2f67b2664688d0240b3212d5196fd89e741df67ddb81f8d35658/aiohappyeyeballs-2.7.1.tar.gz", hash = "sha256:065665c041c42a5938ed220bdcd7230f22527fbec085e1853d2402c8a3615d9d", size = 24757, upload-time = 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