diff --git a/packages/prime/pyproject.toml b/packages/prime/pyproject.toml index 21bd9401..1fc165b4 100644 --- a/packages/prime/pyproject.toml +++ b/packages/prime/pyproject.toml @@ -4,7 +4,7 @@ name = "prime" dynamic = ["version"] description = "Prime Intellect CLI + SDK" readme = "README.md" -requires-python = ">=3.10" +requires-python = ">=3.11,<3.14" license = "MIT" authors = [ { name = "Prime Intellect", email = "contact@primeintellect.ai" } @@ -35,11 +35,9 @@ classifiers = [ "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", "Programming Language :: Python :: 3", - "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", "Programming Language :: Python :: 3.13", - "Programming Language :: Python :: 3.14", "Topic :: Software Development :: Libraries :: Python Modules" ] @@ -64,7 +62,7 @@ dev = [ prime-sandboxes = { workspace = true } prime-evals = { workspace = true } prime-tunnel = { workspace = true } -verifiers = { git = "https://github.com/PrimeIntellect-ai/verifiers.git", tag = "v0.1.14" } +verifiers = { git = "https://github.com/PrimeIntellect-ai/verifiers.git", rev = "bbfd564" } [build-system] requires = ["hatchling"] diff --git a/packages/prime/src/prime_cli/commands/evals.py b/packages/prime/src/prime_cli/commands/evals.py index 3c1977a3..ec9412fe 100644 --- a/packages/prime/src/prime_cli/commands/evals.py +++ b/packages/prime/src/prime_cli/commands/evals.py @@ -32,10 +32,12 @@ clean_logs, get_new_log_lines, ) +from ..utils.v1_results import is_v1_eval_dir from ..verifiers_bridge import ( DEFAULT_ENV_DIR_PATH, DEFAULT_MODEL, - _is_config_target, + _parse_value_option, + _partition_eval_args, _resolve_environment_reference, _split_owner_and_name, is_help_request, @@ -957,6 +959,14 @@ def _validate_eval_path(path_str: str) -> Path: """Validate and return the evaluation directory path.""" path = Path(path_str) + candidate = path.parent if path.is_file() else path + if is_v1_eval_dir(candidate): + raise ValueError( + f"'{candidate}' is a v1 eval run (config.toml + results.jsonl). Pushing v1 eval " + "results to the platform isn't supported yet — the platform backend isn't v1-aware. " + "Inspect them locally with `prime eval view`." + ) + if path.is_file(): # Auto-correct: if user passed metadata.json or results.jsonl, use parent directory if path.name in ("metadata.json", "results.jsonl"): @@ -1389,6 +1399,46 @@ def stop_cmd( raise typer.Exit(1) from exc +def _hosted_eval_config_from_run_args( + environment: str, + passthrough_args: list[str], + *, + sampling_args: Optional[str], + eval_name: Optional[str], + timeout_minutes: Optional[int], + allow_sandbox_access: bool, + allow_instances_access: bool, + allow_tunnel_access: bool, + custom_secrets: Optional[str], +) -> HostedEvalConfig: + """Build a ``HostedEvalConfig`` from the same parsed run config the local v1 path consumes. + + Hosted submission is gated until the platform backend understands the v1 eval format; this keeps + the request/payload machinery wired and surfaces config errors early.""" + parsed = _partition_eval_args(passthrough_args) + sampling = dict(parsed.sampling) + if sampling_args: + sampling.update(json.loads(sampling_args)) + + def _count(flag: str, default: int) -> int: + raw = _parse_value_option(parsed.forwarded, flag, None) + return int(raw) if raw is not None else default + + return HostedEvalConfig( + environment_id=environment, + inference_model=parsed.model or DEFAULT_MODEL, + num_examples=_count("--num-tasks", HOSTED_RUN_DEFAULT_NUM_EXAMPLES), + rollouts_per_example=_count("--num-rollouts", HOSTED_RUN_DEFAULT_ROLLOUTS_PER_EXAMPLE), + name=eval_name, + timeout_minutes=timeout_minutes, + allow_sandbox_access=allow_sandbox_access, + allow_instances_access=allow_instances_access, + allow_tunnel_access=allow_tunnel_access, + custom_secrets=_parse_string_map_option(custom_secrets, "--custom-secrets"), + sampling_args=sampling or None, + ) + + @app.command( "run", help="Run an evaluation with API models (default provider = Prime Inference)", @@ -1489,7 +1539,6 @@ def run_eval_cmd( console.print(f"[dim]Example: {EVAL_RUN_EXAMPLE_COMMAND}[/dim]") raise typer.Exit(2) - env_dir_path: Optional[str] = None poll_interval_was_provided = ( ctx.get_parameter_source("poll_interval") == ParameterSource.COMMANDLINE ) @@ -1517,336 +1566,27 @@ def run_eval_cmd( raise typer.Exit(1) if hosted: - _reject_legacy_unsupported_hosted_flags(passthrough_args) - parsed_verifiers_args, cli_overrides, option_names_by_dest = ( - _parse_verifiers_eval_namespace( - environment, - passthrough_args, - sampling_args, - ) + # Build the hosted request from the same parsed run config the local v1 path uses, then + # gate submission: the platform backend isn't v1-aware yet, so hosted v1 evals aren't + # supported. The HostedEvalConfig / payload / polling machinery stays in place for when the + # platform learns the v1 eval format. + hosted_config = _hosted_eval_config_from_run_args( + environment, + passthrough_args, + sampling_args=sampling_args, + eval_name=eval_name, + timeout_minutes=timeout_minutes, + allow_sandbox_access=allow_sandbox_access, + allow_instances_access=allow_instances_access, + allow_tunnel_access=allow_tunnel_access, + custom_secrets=custom_secrets, ) - _reject_unsupported_hosted_verifiers_args(cli_overrides, option_names_by_dest) - env_dir_path = ( - parsed_verifiers_args.env_dir_path if "env_dir_path" in cli_overrides else None + raise NotImplementedError( + "Hosted v1 evaluations are not supported yet: the platform backend isn't v1-aware " + f"(parsed request for model {hosted_config.inference_model!r}). " + "Run locally with `prime eval run ` (without --hosted)." ) - cli_headers = None - if "header" in cli_overrides: - cli_headers = _coerce_hosted_headers({"header": parsed_verifiers_args.header}) - - hosted_target_configs: list[dict[str, Any]] = [] - if _is_config_target(environment): - hosted_target_configs = _load_hosted_eval_configs(environment) - else: - hosted_target_configs = [ - { - "env_id": environment, - "env_dir_path": env_dir_path, - "model": DEFAULT_MODEL, - "num_examples": HOSTED_RUN_DEFAULT_NUM_EXAMPLES, - "rollouts_per_example": HOSTED_RUN_DEFAULT_ROLLOUTS_PER_EXAMPLE, - "env_args": None, - "timeout_minutes": None, - "allow_sandbox_access": True, - "allow_instances_access": False, - "allow_tunnel_access": True, - "sampling_args": None, - "max_concurrent": None, - "max_retries": None, - "state_columns": None, - "independent_scoring": False, - "verbose": False, - "headers": None, - "extra_env_kwargs": None, - "api_client_type": None, - "api_base_url": None, - "api_key_var": None, - "eval_name": None, - } - ] - - parsed_custom_secrets = _parse_string_map_option(custom_secrets, "--custom-secrets") - - effective_targets: list[dict[str, Any]] = [] - for target_config in hosted_target_configs: - try: - default_num_examples = int( - target_config.get("num_examples", HOSTED_RUN_DEFAULT_NUM_EXAMPLES) - ) - default_rollouts_per_example = int( - target_config.get( - "rollouts_per_example", - HOSTED_RUN_DEFAULT_ROLLOUTS_PER_EXAMPLE, - ) - ) - num_examples = ( - parsed_verifiers_args.num_examples - if "num_examples" in cli_overrides - else default_num_examples - ) - rollouts_per_example = ( - parsed_verifiers_args.rollouts_per_example - if "rollouts_per_example" in cli_overrides - else default_rollouts_per_example - ) - except ValueError as exc: - console.print( - "[red]Error:[/red] --num-examples and --rollouts-per-example must be integers" - ) - raise typer.Exit(1) from exc - - if num_examples < -1 or rollouts_per_example < 1: - console.print( - "[red]Error:[/red] --num-examples must be >= -1 and " - "--rollouts-per-example must be >= 1" - ) - raise typer.Exit(1) - - explicit_sampling_args = "sampling_args" in cli_overrides - base_sampling_args_raw = ( - parsed_verifiers_args.sampling_args - if explicit_sampling_args - else target_config.get("sampling_args") - ) - if base_sampling_args_raw is None: - base_sampling_args = None - elif isinstance(base_sampling_args_raw, dict): - base_sampling_args = base_sampling_args_raw - else: - console.print("[red]Error:[/red] `sampling_args` must be a JSON object") - raise typer.Exit(1) - from verifiers.cli.commands.eval import merge_sampling_args - - effective_sampling_args = ( - merge_sampling_args( - base_sampling_args, - max_tokens=( - parsed_verifiers_args.max_tokens if "max_tokens" in cli_overrides else None - ), - temperature=( - parsed_verifiers_args.temperature - if "temperature" in cli_overrides - else None - ), - prefer_existing_keys=explicit_sampling_args, - ) - or None - ) - - effective_targets.append( - { - "env_id": target_config["env_id"], - "env_dir_path": target_config.get("env_dir_path") or env_dir_path, - "model": ( - parsed_verifiers_args.model - if "model" in cli_overrides - else target_config["model"] - ), - "num_examples": num_examples, - "rollouts_per_example": rollouts_per_example, - "env_args": ( - parsed_verifiers_args.env_args - if "env_args" in cli_overrides - else target_config.get("env_args") - ), - "timeout_minutes": ( - timeout_minutes - if timeout_minutes is not None - else target_config.get("timeout_minutes") - ), - "allow_sandbox_access": ( - allow_sandbox_access - if allow_sandbox_access - else target_config.get("allow_sandbox_access", True) - ), - "allow_instances_access": ( - allow_instances_access - if allow_instances_access - else target_config.get("allow_instances_access", False) - ), - "allow_tunnel_access": ( - allow_tunnel_access - if allow_tunnel_access - else target_config.get("allow_tunnel_access", True) - ), - "custom_secrets": parsed_custom_secrets, - "sampling_args": effective_sampling_args, - "max_concurrent": ( - parsed_verifiers_args.max_concurrent - if "max_concurrent" in cli_overrides - else target_config.get("max_concurrent") - ), - "max_retries": ( - parsed_verifiers_args.max_retries - if "max_retries" in cli_overrides - else target_config.get("max_retries") - ), - "state_columns": ( - parsed_verifiers_args.state_columns - if "state_columns" in cli_overrides - else target_config.get("state_columns") - ), - "independent_scoring": ( - parsed_verifiers_args.independent_scoring - if "independent_scoring" in cli_overrides - else target_config.get("independent_scoring", False) - ), - "verbose": ( - parsed_verifiers_args.verbose - if "verbose" in cli_overrides - else target_config.get("verbose", False) - ), - "headers": ( - cli_headers if "header" in cli_overrides else target_config.get("headers") - ), - "extra_env_kwargs": ( - parsed_verifiers_args.extra_env_kwargs - if "extra_env_kwargs" in cli_overrides - else target_config.get("extra_env_kwargs") - ), - "api_client_type": ( - parsed_verifiers_args.api_client_type - if "api_client_type" in cli_overrides - else target_config.get("api_client_type") - ), - "api_base_url": ( - parsed_verifiers_args.api_base_url - if "api_base_url" in cli_overrides - else target_config.get("api_base_url") - ), - "api_key_var": ( - parsed_verifiers_args.api_key_var - if "api_key_var" in cli_overrides - else target_config.get("api_key_var") - ), - "eval_name": eval_name or target_config.get("eval_name"), - } - ) - - if follow and len(effective_targets) > 1: - console.print( - "[red]Error:[/red] `--follow` is only supported for a single hosted evaluation" - ) - raise typer.Exit(1) - - grouped_targets: dict[tuple[Any, ...], dict[str, Any]] = {} - target_order: list[tuple[Any, ...]] = [] - for target in effective_targets: - group_key = ( - target["model"], - target["num_examples"], - target["rollouts_per_example"], - _freeze_json_value(target.get("env_args")), - target.get("timeout_minutes"), - target.get("allow_sandbox_access", True), - target.get("allow_instances_access", False), - target.get("allow_tunnel_access", True), - _freeze_json_value(target.get("sampling_args")), - target.get("max_concurrent"), - target.get("max_retries"), - _freeze_json_value(target.get("state_columns")), - target.get("independent_scoring", False), - target.get("verbose", False), - _freeze_json_value(target.get("headers")), - _freeze_json_value(target.get("extra_env_kwargs")), - target.get("api_client_type"), - target.get("api_base_url"), - target.get("api_key_var"), - target.get("eval_name"), - ) - if group_key not in grouped_targets: - grouped_targets[group_key] = { - "target": target, - "targets": [], - "platform_slugs": [], - "environment_ids": [], - } - target_order.append(group_key) - grouped_targets[group_key]["targets"].append(target) - - try: - for group_key in target_order: - group = grouped_targets[group_key] - for grouped_target in group["targets"]: - platform_slug, environment_id = _resolve_hosted_environment( - grouped_target["env_id"], - env_dir_path=grouped_target["env_dir_path"], - env_path=env_path, - ) - group["platform_slugs"].append(platform_slug) - group["environment_ids"].append(environment_id) - except APIError as exc: - console.print(f"[red]Error:[/red] {exc}") - raise typer.Exit(1) from exc - - all_platform_slugs: list[str] = [] - all_evaluation_ids: list[str] = [] - try: - for group_key in target_order: - group = grouped_targets[group_key] - target = group["target"] - hosted_config = HostedEvalConfig( - environment_id=group["environment_ids"][0], - inference_model=target["model"], - num_examples=target["num_examples"], - rollouts_per_example=target["rollouts_per_example"], - env_args=target.get("env_args"), - name=target.get("eval_name"), - timeout_minutes=target.get("timeout_minutes"), - allow_sandbox_access=target.get("allow_sandbox_access", True), - allow_instances_access=target.get("allow_instances_access", False), - allow_tunnel_access=target.get("allow_tunnel_access", True), - custom_secrets=target.get("custom_secrets"), - sampling_args=target.get("sampling_args"), - max_concurrent=target.get("max_concurrent"), - max_retries=target.get("max_retries"), - state_columns=target.get("state_columns"), - independent_scoring=target.get("independent_scoring", False), - verbose=target.get("verbose", False), - headers=target.get("headers"), - extra_env_kwargs=target.get("extra_env_kwargs"), - api_client_type=target.get("api_client_type"), - api_base_url=target.get("api_base_url"), - api_key_var=target.get("api_key_var"), - ) - result = _create_hosted_evaluations( - hosted_config, - environment_ids=group["environment_ids"], - ) - all_platform_slugs.extend(group["platform_slugs"]) - all_evaluation_ids.extend(result.get("evaluation_ids") or [result["evaluation_id"]]) - except APIError as exc: - console.print(f"[red]Hosted evaluation failed:[/red] {exc}") - raise typer.Exit(1) from exc - - if follow: - console.print("[green]✓ Hosted evaluation started[/green]") - console.print(f"[cyan]Environment:[/cyan] {all_platform_slugs[0]}") - console.print(f"[cyan]Evaluation ID:[/cyan] {all_evaluation_ids[0]}") - console.print() - _display_logs( - all_evaluation_ids[0], - tail=HOSTED_LOGS_DEFAULT_TAIL_LINES, - follow=True, - poll_interval=poll_interval, - ) - return - - console.print("[green]✓ Hosted evaluation started[/green]") - if len(all_platform_slugs) == 1: - console.print(f"[cyan]Environment:[/cyan] {all_platform_slugs[0]}") - console.print(f"[cyan]Evaluation ID:[/cyan] {all_evaluation_ids[0]}") - console.print( - f"[green]View results:[/green] {get_eval_viewer_url(all_evaluation_ids[0])}" - ) - console.print("[dim]View logs:[/dim] prime eval logs " + all_evaluation_ids[0] + " -f") - return - - console.print(f"[cyan]Environments:[/cyan] {', '.join(all_platform_slugs)}") - console.print(f"[cyan]Evaluation IDs:[/cyan] {', '.join(all_evaluation_ids)}") - console.print("[dim]View logs:[/dim] prime eval logs -f") - return - run_eval_passthrough( environment=environment, passthrough_args=local_passthrough_args, diff --git a/packages/prime/src/prime_cli/lab_setup.py b/packages/prime/src/prime_cli/lab_setup.py index c0874d80..8800b249 100644 --- a/packages/prime/src/prime_cli/lab_setup.py +++ b/packages/prime/src/prime_cli/lab_setup.py @@ -1386,8 +1386,10 @@ def _ensure_uv_project(workspace: Path, emit: Emit, runner: Runner) -> None: else: emit("Found pyproject.toml\n") - emit("Adding verifiers dependency\n") - _check_command(["uv", "add", "verifiers"], workspace, emit, runner) + # verifiers provides the v1 eval entrypoint; tasksets/harnesses ship the built-in v1 plugins + # (e.g. the `default` harness) that `prime eval run` resolves. + emit("Adding verifiers, tasksets, and harnesses dependencies\n") + _check_command(["uv", "add", "verifiers", "tasksets", "harnesses"], workspace, emit, runner) def _post_setup_call_to_action(options: LabSetupOptions) -> Panel: diff --git a/packages/prime/src/prime_cli/utils/v1_results.py b/packages/prime/src/prime_cli/utils/v1_results.py new file mode 100644 index 00000000..f0795a2b --- /dev/null +++ b/packages/prime/src/prime_cli/utils/v1_results.py @@ -0,0 +1,204 @@ +"""Read verifiers v1 eval output (`config.toml` + a `Trace`-per-line `results.jsonl`). + +A v1 run dir is `outputs/----/` (or `…--legacy` for a v0 env +run through the bridge) holding `config.toml` + `results.jsonl`, where each line is a serialized +`verifiers.v1.trace.Trace`. This differs from the v0 layout (`outputs/evals/--/` +with `results.jsonl` of `RolloutOutput` + a precomputed `metadata.json`). + +The Lab viewer renders the v0 record shape, so `v1_trace_to_record` adapts a `Trace` to that shape +(`prompt` / `completion` / `reward` / `metrics` / `info` / `error`), and `v1_run_metadata` +synthesizes the run-level `metadata.json` the viewer expects from `config.toml` + the trace rewards. +""" + +from __future__ import annotations + +import json +from pathlib import Path +from typing import Any + +V1_CONFIG_NAME = "config.toml" +RESULTS_NAME = "results.jsonl" + + +def is_v1_eval_dir(run_dir: Path) -> bool: + """A v1 run dir has a `config.toml` next to `results.jsonl` (v0 writes `metadata.json`).""" + return (run_dir / V1_CONFIG_NAME).is_file() and (run_dir / RESULTS_NAME).is_file() + + +def load_config(run_dir: Path) -> dict[str, Any]: + try: + import tomllib + except ModuleNotFoundError: # py<3.11 + import tomli as tomllib # type: ignore[no-redef] + try: + with (run_dir / V1_CONFIG_NAME).open("rb") as handle: + data = tomllib.load(handle) + except (OSError, ValueError): + return {} + return data if isinstance(data, dict) else {} + + +def is_v1_trace(record: dict[str, Any]) -> bool: + """A serialized v1 `Trace` carries a `nodes` graph and no top-level `prompt` (which every v0 + `RolloutOutput` has).""" + return "nodes" in record and "prompt" not in record + + +def _main_branch_messages(nodes: list[dict[str, Any]]) -> tuple[list[dict], list[dict]]: + """Split the trace's first root→leaf branch into (prompt, completion) messages: prompt is the + supplied prefix (`sampled` is False) up to the first sampled node, completion is everything from + the first sampled node on (assistant turns plus any tool results between them).""" + if not nodes: + return [], [] + parents = {node.get("parent") for node in nodes} + leaf = next((i for i in range(len(nodes)) if i not in parents), len(nodes) - 1) + + chain: list[dict[str, Any]] = [] + idx: Any = leaf + seen = set() + while isinstance(idx, int) and 0 <= idx < len(nodes) and idx not in seen: + seen.add(idx) + chain.append(nodes[idx]) + idx = nodes[idx].get("parent") + chain.reverse() + + prompt: list[dict] = [] + completion: list[dict] = [] + started = False + for node in chain: + message = node.get("message") + if not isinstance(message, dict): + continue + if node.get("sampled"): + started = True + (completion if started else prompt).append(message) + return prompt, completion + + +def _error_record(error: Any) -> dict[str, Any] | None: + if not isinstance(error, dict): + return None + return {"error": error.get("type", ""), "message": error.get("message", "")} + + +def v1_trace_to_record(trace: dict[str, Any]) -> dict[str, Any]: + """Adapt a serialized v1 `Trace` to the v0 `RolloutOutput`-shaped record the viewer reads.""" + task = trace.get("task") if isinstance(trace.get("task"), dict) else {} + prompt, completion = _main_branch_messages(trace.get("nodes") or []) + # The viewer flattens reward/@metric values into one `metrics` table; rewards is the weighted + # per-@reward breakdown, metrics the unweighted side metrics. + metrics: dict[str, Any] = {} + metrics.update(trace.get("rewards") or {}) + metrics.update(trace.get("metrics") or {}) + + record: dict[str, Any] = { + "example_id": task.get("idx", 0), + "prompt": prompt, + "completion": completion, + "reward": trace.get("reward", 0.0), + "metrics": metrics, + "info": trace.get("info") or {}, + "is_completed": trace.get("is_completed"), + "is_truncated": trace.get("is_truncated"), + "stop_condition": trace.get("stop_condition"), + } + answer = task.get("answer") + if answer is not None: + record["answer"] = answer + error = _error_record(trace.get("error")) + if error is not None: + record["error"] = error + return record + + +def v1_run_identity(config: dict[str, Any]) -> tuple[str, str, str | None]: + """(env_id, model, harness) for a v1 run, from its `config.toml`.""" + taskset = config.get("taskset") if isinstance(config.get("taskset"), dict) else {} + harness = config.get("harness") if isinstance(config.get("harness"), dict) else {} + env_id = taskset.get("id") or config.get("id") or "-" + return str(env_id), str(config.get("model") or "-"), harness.get("id") + + +def v1_config_metadata(config: dict[str, Any]) -> dict[str, Any]: + """The run-level metadata derivable from `config.toml` alone (no `results.jsonl` scan) — used at + discovery so listing many runs stays cheap. Reward aggregates are filled in lazily per selected + run by `v1_run_metadata` / the viewer's stats worker.""" + env_id, model, harness = v1_run_identity(config) + num_tasks = config.get("num_tasks") + metadata: dict[str, Any] = { + "env_id": env_id, + "env": env_id, + "model": model, + "harness": harness, + "framework": "verifiers", + "format": "v1", + "rollouts_per_example": config.get("num_rollouts", 1), + } + if num_tasks is not None: + metadata["num_examples"] = num_tasks + if isinstance(config.get("sampling"), dict): + metadata["sampling_args"] = config["sampling"] + client = config.get("client") if isinstance(config.get("client"), dict) else {} + if client.get("base_url"): + metadata["base_url"] = client["base_url"] + return metadata + + +def v1_run_metadata(config: dict[str, Any], results_path: Path) -> dict[str, Any]: + """Synthesize the run-level `metadata.json` the viewer expects from `config.toml` plus the + rewards/metrics scanned from `results.jsonl`.""" + env_id, model, harness = v1_run_identity(config) + rewards: list[float] = [] + metric_totals: dict[str, float] = {} + metric_counts: dict[str, int] = {} + task_idxs: set[Any] = set() + + try: + with results_path.open(encoding="utf-8") as handle: + for line in handle: + line = line.strip() + if not line: + continue + try: + trace = json.loads(line) + except json.JSONDecodeError: + continue + if not isinstance(trace, dict): + continue + reward = trace.get("reward") + if isinstance(reward, (int, float)): + rewards.append(float(reward)) + task = trace.get("task") + if isinstance(task, dict) and "idx" in task: + task_idxs.add(task["idx"]) + merged = {**(trace.get("rewards") or {}), **(trace.get("metrics") or {})} + for name, value in merged.items(): + if isinstance(value, (int, float)): + metric_totals[name] = metric_totals.get(name, 0.0) + float(value) + metric_counts[name] = metric_counts.get(name, 0) + 1 + except OSError: + pass + + num_tasks = config.get("num_tasks") + metadata: dict[str, Any] = { + "env_id": env_id, + "env": env_id, + "model": model, + "harness": harness, + "framework": "verifiers", + "format": "v1", + "num_examples": num_tasks if num_tasks is not None else len(task_idxs), + "rollouts_per_example": config.get("num_rollouts", 1), + } + if rewards: + metadata["avg_reward"] = sum(rewards) / len(rewards) + if metric_totals: + metadata["avg_metrics"] = { + name: metric_totals[name] / metric_counts[name] for name in metric_totals + } + if isinstance(config.get("sampling"), dict): + metadata["sampling_args"] = config["sampling"] + client = config.get("client") if isinstance(config.get("client"), dict) else {} + if client.get("base_url"): + metadata["base_url"] = client["base_url"] + return metadata diff --git a/packages/prime/src/prime_cli/verifiers_bridge.py b/packages/prime/src/prime_cli/verifiers_bridge.py index fe01b9aa..953ba46b 100644 --- a/packages/prime/src/prime_cli/verifiers_bridge.py +++ b/packages/prime/src/prime_cli/verifiers_bridge.py @@ -2,13 +2,13 @@ from __future__ import annotations +import json import os import re import subprocess import sys -import uuid +import tempfile from dataclasses import dataclass -from datetime import datetime from pathlib import Path from typing import Optional @@ -20,10 +20,13 @@ from .api.inference import InferenceAPIError, InferenceClient, InferencePaymentRequiredError from .client import APIClient, APIError -from .utils.env_metadata import find_environment_metadata, get_environment_metadata -from .utils.eval_push import push_eval_results_to_hub +from .utils.env_metadata import get_environment_metadata from .utils.plain import get_console -from .verifiers_plugin import PrimeVerifiersPlugin, load_verifiers_prime_plugin +from .verifiers_plugin import ( + PrimeVerifiersPlugin, + load_verifiers_prime_plugin, + resolve_workspace_python, +) console = get_console() @@ -235,15 +238,6 @@ def _parse_value_option( return None -def _has_flag(args: list[str], long_flag: str, short_flag: str) -> bool: - for arg in args: - if arg == long_flag or arg == short_flag: - return True - if arg.startswith(f"{long_flag}="): - return True - return False - - def _resolve_endpoint_alias(args: list[str], model: str) -> Optional[EndpointResolution]: endpoints_path = _parse_value_option(args, "--endpoints-path", "-e") or DEFAULT_ENDPOINTS_PATH try: @@ -265,9 +259,17 @@ def _resolve_endpoint_alias(args: list[str], model: str) -> Optional[EndpointRes return None endpoint = endpoint_group[0] + # v1 verifiers' load_endpoints returns pydantic EndpointConfig (`.base_url`); older builds + # returned plain dicts (`url`). Support both. + if isinstance(endpoint, dict): + endpoint_model = endpoint.get("model") + endpoint_url = endpoint.get("url") or endpoint.get("base_url") + else: + endpoint_model = getattr(endpoint, "model", None) + endpoint_url = getattr(endpoint, "base_url", None) or getattr(endpoint, "url", None) return EndpointResolution( - model=str(endpoint.get("model") or model), - base_url=str(endpoint.get("url") or "").rstrip("/"), + model=str(endpoint_model or model), + base_url=str(endpoint_url or "").rstrip("/"), ) @@ -788,11 +790,6 @@ def _collect_eval_config_envs(config_path: Path, fallback_env_dir: str) -> list[ return resolved -def _env_name_from_reference(env_reference: str) -> str: - base_ref, _version = _split_version(env_reference) - return base_ref.rsplit("/", 1)[-1] - - def _collect_gepa_config_env(config_path: Path, fallback_env_dir: str) -> Optional[tuple[str, str]]: try: raw = toml.load(config_path) @@ -900,45 +897,167 @@ def _preflight_inference_billing( raise typer.Exit(1) from exc -def _build_job_id(env_name: str, model: str) -> str: - eval_timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") - job_uuid = str(uuid.uuid4())[:8] - sanitized_env = env_name.replace("-", "_").replace("/", "_") - sanitized_model = model.replace("/", "_").replace("-", "_") - return f"{sanitized_env}_{sanitized_model}_{eval_timestamp}_{job_uuid}" +@dataclass +class _EvalArgs: + """A `prime eval run` arg list partitioned for the v1 `eval` entrypoint. + + Convenience flags (the v0 `vf-eval` surface prime users know — `-m`, `-b`, `-k`, + `--sampling-args`, …) are captured into a temp config TOML; genuine v1 flags + (`--num-tasks`, `--harness.id`, `--client.*`, `@ file.toml`, …) are forwarded verbatim + and override the temp config.""" + + model: Optional[str] = None + base_url: Optional[str] = None + provider: Optional[str] = None + api_key_var: Optional[str] = None + endpoints_path: Optional[str] = None + env_dir_path: Optional[str] = None + sampling: dict = None # type: ignore[assignment] + headers: dict = None # type: ignore[assignment] + forwarded: list[str] = None # type: ignore[assignment] + native_taskset: bool = False + references_config: bool = False + + +def _take_value_flag( + args: list[str], idx: int, long_flag: str, short_flag: Optional[str] +) -> tuple[Optional[str], int]: + """If `args[idx]` is `long_flag`/`short_flag`, return its value and the number of tokens it + spans (`("--flag", "v")` → 2, `"--flag=v"` / `"-fv"` → 1); otherwise `(None, 0)`.""" + tok = args[idx] + if tok == long_flag or (short_flag and tok == short_flag): + return (args[idx + 1] if idx + 1 < len(args) else None), 2 + if tok.startswith(f"{long_flag}="): + return tok.split("=", 1)[1], 1 + if short_flag and not tok.startswith("--") and tok.startswith(short_flag) and len(tok) > len( + short_flag + ): + return tok[len(short_flag) :], 1 + return None, 0 + + +def _partition_eval_args(raw_args: list[str]) -> _EvalArgs: + parsed = _EvalArgs(sampling={}, headers={}, forwarded=[]) + captures = [ + ("--model", "-m", "model"), + ("--api-base-url", "-b", "base_url"), + ("--provider", "-p", "provider"), + ("--api-key-var", "-k", "api_key_var"), + ("--endpoints-path", "-e", "endpoints_path"), + ("--env-dir-path", None, "env_dir_path"), + ] + # v0 vf-eval count flags → their v1 EvalConfig names. + translations = [ + ("--num-examples", "-n", "--num-tasks"), + ("--rollouts-per-example", "-r", "--num-rollouts"), + ] + + i = 0 + while i < len(raw_args): + tok = raw_args[i] + if tok == "@" or tok.startswith("@"): # a v1 `@ file.toml` config reference + parsed.references_config = True + parsed.forwarded.append(tok) + if tok == "@" and i + 1 < len(raw_args): + parsed.forwarded.append(raw_args[i + 1]) + i += 1 + i += 1 + continue + if tok == "--taskset.id" or tok.startswith("--taskset."): # opt in to a native v1 taskset + parsed.native_taskset = True + parsed.forwarded.append(tok) + i += 1 + continue + value, used = _take_value_flag(raw_args, i, "--sampling-args", None) + if used: + if value: + parsed.sampling.update(json.loads(value)) + i += used + continue + value, used = _take_value_flag(raw_args, i, "--header", None) + if used: + if value and ":" in value: + name, val = value.split(":", 1) + parsed.headers[name.strip()] = val.strip() + i += used + continue -def _format_push_command(resolved: ResolvedEnvironment) -> str: - if resolved.local_env_path is not None: - base = f"prime env push --path {resolved.local_env_path}" - else: - base = "prime env push" - if resolved.platform_slug: - parts = _split_owner_and_name(resolved.platform_slug) - if parts is not None: - base += f" --owner {parts[0]}" - return base + matched = False + for long_flag, short_flag, attr in captures: + value, used = _take_value_flag(raw_args, i, long_flag, short_flag) + if used: + setattr(parsed, attr, value) + i += used + matched = True + break + if matched: + continue + for long_flag, short_flag, target in translations: + value, used = _take_value_flag(raw_args, i, long_flag, short_flag) + if used: + if value is not None: + parsed.forwarded += [target, value] + i += used + matched = True + break + if matched: + continue + if tok == "--save-results": # v0-only; v1 always writes results.jsonl + i += 1 + continue + parsed.forwarded.append(tok) + i += 1 + return parsed -def _print_environment_source_footer(resolved: Optional[ResolvedEnvironment]) -> None: - if resolved is None: - return - if resolved.platform_url: - console.print(f"[dim]Environment URL: {resolved.platform_url}[/dim]") - if resolved.recommend_push: - if resolved.push_reason == "ahead" and resolved.platform_slug: - console.print( - f"[yellow]Local environment is ahead of {resolved.platform_slug}.[/yellow]" - ) - elif resolved.push_reason == "local_only": - console.print("[yellow]Local environment is not linked to an upstream.[/yellow]") - else: - console.print( - "[yellow]Local environment differs from the current platform version.[/yellow]" - ) - console.print( - f"[dim]Publish the current local version with:[/dim] {_format_push_command(resolved)}" - ) +def _v1_client_value(forwarded: list[str], field: str) -> Optional[str]: + """A `--client.` value the user passed through verbatim (overrides the temp config).""" + return _parse_value_option(forwarded, f"--client.{field}", None) + + +def _write_temp_eval_config( + *, + legacy_id: Optional[str], + model: str, + base_url: Optional[str], + api_key_var: Optional[str], + headers: dict, + sampling: dict, +) -> Path: + """Write prime's derived convenience config as a v1 eval `@ file.toml`. Nested values + (`client.headers`, `sampling.extra_body`) and dash-cased header names round-trip through TOML, + which dotted CLI flags mangle.""" + data: dict = {"model": model} + if legacy_id: # v0 env id → the bridge's legacy path (`is_legacy`) + data["id"] = legacy_id + client: dict = {} + if base_url: + client["base_url"] = base_url + if api_key_var: + client["api_key_var"] = api_key_var + if headers: + client["headers"] = headers + if client: + data["client"] = client + if sampling: + data["sampling"] = sampling + + fd, path = tempfile.mkstemp(prefix="prime-eval-", suffix=".toml") + with os.fdopen(fd, "w") as handle: + toml.dump(data, handle) + return Path(path) + + +def _v1_eval_command(args: list[str]) -> list[str]: + """Invoke the v1 `eval` entrypoint in the workspace venv. `verifiers.v1.cli.eval` has no + `__main__` guard, so call `main()` directly rather than `python -m`.""" + return [ + resolve_workspace_python(), + "-c", + "from verifiers.v1.cli.eval import main; main()", + *args, + ] def run_eval_passthrough( @@ -958,107 +1077,104 @@ def run_eval_passthrough( ) raise typer.Exit(1) - args, env, model, base_url = _add_default_inference_and_key_args(passthrough_args, config) + parsed = _partition_eval_args(passthrough_args) + env = os.environ.copy() + + model = parsed.model or DEFAULT_MODEL configured_base_url = (config.inference_url or "").strip().rstrip("/") + model, base_url, api_key_var = _resolve_inference_target(parsed, config, env, model) _validate_model(model, base_url, configured_base_url) _preflight_inference_billing(model, base_url, configured_base_url) - env_dir_path = _env_dir_path_arg(args) - run_target = environment - upstream_slug: Optional[str] = None - env_name_for_upload: Optional[str] = None - resolved_env: Optional[ResolvedEnvironment] = None - config_envs: list[tuple[str, str]] = [] + env_dir_path = parsed.env_dir_path or DEFAULT_ENV_DIR_PATH + # The v1 `eval` entrypoint runs a native taskset (`--taskset.id`) or, for prime's v0 hub/local + # environments, the v0 env via the bridge (`--id`); both write the same `results.jsonl` / + # `config.toml`. We default to the legacy `--id` path so existing environments keep working. if _is_config_target(environment): - config_envs = _collect_eval_config_envs(Path(environment), env_dir_path) - for env_ref, ref_env_dir in config_envs: + for env_ref, ref_env_dir in _collect_eval_config_envs(Path(environment), env_dir_path): _prepare_single_environment(plugin, env_ref, ref_env_dir) - else: + eval_args = ["@", environment, *parsed.forwarded] + _run_command(_v1_eval_command(eval_args), env=env) + _print_eval_complete() + return + + legacy_id: Optional[str] = None + if not parsed.native_taskset: resolved_env = _prepare_single_environment(plugin, environment, env_dir_path) - run_target = resolved_env.env_name - upstream_slug = resolved_env.upstream_slug - env_name_for_upload = resolved_env.env_name + legacy_id = resolved_env.env_name if resolved_env.env_display_id: - args.extend( - ["--header", f"{INTERNAL_ENV_DISPLAY_HEADER}: {resolved_env.env_display_id}"] - ) - - if not skip_upload and not _has_flag(args, "--save-results", "-s"): - args.append("-s") - - job_target = env_name_for_upload - if job_target is None and config_envs: - job_target = _env_name_from_reference(config_envs[0][0]) - if job_target is None: - job_target = Path(environment).stem - job_id = _build_job_id(job_target, model) - args.extend(["--header", f"X-PI-Job-Id: {job_id}"]) + parsed.headers.setdefault(INTERNAL_ENV_DISPLAY_HEADER, resolved_env.env_display_id) if config.team_id: - args.extend(["--header", f"X-Prime-Team-ID: {config.team_id}"]) - - console.print(f"[dim]Eval job_id: {job_id}[/dim]") - command = plugin.build_module_command(plugin.eval_module, [run_target, *args]) - _run_command(command, env=env) - + parsed.headers.setdefault("X-Prime-Team-ID", config.team_id) + + tmp_config = _write_temp_eval_config( + legacy_id=legacy_id, + model=model, + base_url=base_url, + api_key_var=api_key_var, + headers=parsed.headers, + sampling=parsed.sampling, + ) if skip_upload: - _print_environment_source_footer(resolved_env) - console.print("[dim]Skipped uploading evaluation results[/dim]") - return - - if _is_config_target(environment): console.print( - "[yellow]Evaluation completed. Automatic upload is skipped for " - "config-driven runs.[/yellow]" + "[dim]--skip-upload has no effect: v1 eval results stay local until platform " + "push is supported.[/dim]" ) - return - - if resolved_env is not None and resolved_env.recommend_push: - _print_environment_source_footer(resolved_env) + try: + _run_command(_v1_eval_command(["@", str(tmp_config), *parsed.forwarded]), env=env) + finally: + tmp_config.unlink(missing_ok=True) + _print_eval_complete() + + +def _resolve_inference_target( + parsed: _EvalArgs, config: Config, env: dict[str, str], model: str +) -> tuple[str, str, str]: + """Resolve (model, base_url, api_key_var) from prime's convenience flags, the configured + inference endpoint, or a user-supplied `--client.*` override. Defaults the key var to + `PRIME_API_KEY` and injects it into the child env.""" + base = parsed.base_url + if base: + base = base.rstrip("/") + elif parsed.provider is not None: + base = _provider_base_url(parsed.provider) or "" + elif endpoint := _resolve_endpoint_alias(_endpoint_lookup_args(parsed), model): + model, base = endpoint.model, endpoint.base_url + elif user_base := _v1_client_value(parsed.forwarded, "base_url"): + base = user_base.rstrip("/") + elif config.inference_url: + base = config.inference_url.strip().rstrip("/") + else: console.print( - "[yellow]Evaluation completed. Automatic upload is skipped until the local " - "environment is published.[/yellow]" + "[red]Inference URL not configured.[/red] Check [bold]prime config view[/bold]." ) - return + raise typer.Exit(1) - upload_env_name = env_name_for_upload or environment - if upstream_slug is None: - check_path = Path(env_path) if env_path else Path.cwd() - metadata = find_environment_metadata( - env_name=upload_env_name, - env_path=check_path, - module_name=upload_env_name.replace("-", "_"), - ) - if metadata and metadata.get("owner") and metadata.get("name"): - upstream_slug = f"{metadata.get('owner')}/{metadata.get('name')}" - console.print(f"[dim]Using upstream environment {upstream_slug}[/dim]") + api_key_var = parsed.api_key_var or _v1_client_value(parsed.forwarded, "api_key_var") + if api_key_var is None: + env["PRIME_API_KEY"] = config.api_key + api_key_var = "PRIME_API_KEY" + return model, base, api_key_var - if upstream_slug is None: - _print_environment_source_footer(resolved_env) - console.print( - "[dim]No upstream environment found. " - "Skipped uploading evaluation results to platform.\n" - "Use `prime env push` to set an upstream, or use `--env-path` to specify the " - "correct environment path.[/dim]" - ) - return - if resolved_env is not None and resolved_env.platform_url: - console.print(f"[dim]Environment URL: {resolved_env.platform_url}[/dim]") +def _endpoint_lookup_args(parsed: _EvalArgs) -> list[str]: + """The minimal arg list `_resolve_endpoint_alias` needs to find the endpoints file.""" + if parsed.endpoints_path: + return ["--endpoints-path", parsed.endpoints_path] + return [] - try: - push_eval_results_to_hub( - env_name=upload_env_name, - model=model, - job_id=job_id, - env_path=Path(env_path) if env_path else None, - upstream_slug=upstream_slug, - ) - except Exception as exc: - console.print(f"[red]Failed to push results to hub:[/red] {exc}") - console.print("[yellow]Evaluation completed but results were not pushed.[/yellow]") - raise typer.Exit(1) from exc + +def _print_eval_complete() -> None: + console.print( + "\n[green]✓ Evaluation complete.[/green] " + "Inspect results with [bold]prime eval view[/bold]." + ) + console.print( + "[dim]Pushing v1 eval results to the platform is not supported yet " + "(the platform isn't v1-aware).[/dim]" + ) def run_gepa_passthrough(environment_or_config: str, passthrough_args: list[str]) -> None: diff --git a/packages/prime/src/prime_cli/verifiers_plugin.py b/packages/prime/src/prime_cli/verifiers_plugin.py index 378d3163..235d249a 100644 --- a/packages/prime/src/prime_cli/verifiers_plugin.py +++ b/packages/prime/src/prime_cli/verifiers_plugin.py @@ -47,7 +47,7 @@ def resolve_workspace_python(cwd: Path | None = None) -> str: """Prefer workspace Python only when it can run verifiers command modules.""" workspace = (cwd or Path.cwd()).resolve() workspace_str = str(workspace) - module = "verifiers.cli.commands.eval" + module = "verifiers.v1.cli.eval" def _usable(candidate: Path) -> bool: return candidate.exists() and _python_can_import_module( diff --git a/packages/prime/src/prime_lab_app/data.py b/packages/prime/src/prime_lab_app/data.py index 7c625449..2bb8afc5 100644 --- a/packages/prime/src/prime_lab_app/data.py +++ b/packages/prime/src/prime_lab_app/data.py @@ -16,6 +16,12 @@ from prime_cli.client import APIClient, APIError from prime_cli.core import Config from prime_cli.utils.time_utils import format_time_ago +from prime_cli.utils.v1_results import ( + is_v1_eval_dir, + load_config, + v1_config_metadata, + v1_run_identity, +) from prime_evals import EvalsClient from .cache import ( @@ -1002,20 +1008,21 @@ def discover_local_eval_runs( outputs_dir: str = "./outputs", limit: int = 30, ) -> list[dict[str, Any]]: - roots: list[Path] = [] + runs: list[dict[str, Any]] = [] env_root = (workspace / env_dir).resolve() + + # v0 layout: outputs/evals/--//{metadata.json, results.jsonl} + v0_roots: list[Path] = [] if _safe_is_dir(env_root): for env_path in _safe_sorted_children(env_root): candidate = env_path / "outputs" / "evals" if _safe_is_dir(candidate): - roots.append(candidate) - - global_root = (workspace / outputs_dir / "evals").resolve() - if _safe_is_dir(global_root): - roots.append(global_root) + v0_roots.append(candidate) + global_evals = (workspace / outputs_dir / "evals").resolve() + if _safe_is_dir(global_evals): + v0_roots.append(global_evals) - runs: list[dict[str, Any]] = [] - for root in roots: + for root in v0_roots: for env_model_dir in _safe_sorted_children(root): if not _safe_is_dir(env_model_dir) or "--" not in env_model_dir.name: continue @@ -1030,14 +1037,46 @@ def discover_local_eval_runs( or not _safe_is_file(results_path) ): continue - metadata = _read_json_file(metadata_path) runs.append( { "env_id": env_id, "model": model, "run_id": run_dir.name, "path": str(run_dir), - "metadata": metadata, + "metadata": _read_json_file(metadata_path), + } + ) + if len(runs) >= limit: + return runs + + # v1 layout: outputs/----//{config.toml, results.jsonl}. Run + # identity comes from config.toml, not the dir name (the model embeds `--`). `evals/` is v0. + v1_roots: list[Path] = [] + if _safe_is_dir(env_root): + for env_path in _safe_sorted_children(env_root): + candidate = env_path / "outputs" + if _safe_is_dir(candidate): + v1_roots.append(candidate) + global_outputs = (workspace / outputs_dir).resolve() + if _safe_is_dir(global_outputs): + v1_roots.append(global_outputs) + + for root in v1_roots: + for name_dir in _safe_sorted_children(root): + if not _safe_is_dir(name_dir) or name_dir.name == "evals": + continue + for run_dir in _safe_sorted_children(name_dir, reverse=True): + if not _safe_is_dir(run_dir) or not is_v1_eval_dir(run_dir): + continue + config = load_config(run_dir) + env_id, model, _harness = v1_run_identity(config) + runs.append( + { + "env_id": env_id, + "model": model, + "run_id": run_dir.name, + "path": str(run_dir), + "metadata": v1_config_metadata(config), } ) if len(runs) >= limit: diff --git a/packages/prime/src/prime_lab_app/eval_records.py b/packages/prime/src/prime_lab_app/eval_records.py index 4cedc03e..fa5a5138 100644 --- a/packages/prime/src/prime_lab_app/eval_records.py +++ b/packages/prime/src/prime_lab_app/eval_records.py @@ -7,6 +7,14 @@ from pathlib import Path from typing import Any +from prime_cli.utils.v1_results import ( + is_v1_eval_dir, + is_v1_trace, + load_config, + v1_run_metadata, + v1_trace_to_record, +) + from .models import LabItem @@ -34,6 +42,9 @@ def from_item(cls, item: LabItem) -> "LocalEvalRun": def load_metadata(self) -> dict[str, Any]: if self.metadata is not None: return self.metadata + if is_v1_eval_dir(self.path): # v1 has config.toml, not a precomputed metadata.json + self.metadata = v1_run_metadata(load_config(self.path), self.path / "results.jsonl") + return self.metadata meta_path = self.path / "metadata.json" try: loaded = json.loads(meta_path.read_text(encoding="utf-8")) @@ -176,6 +187,8 @@ def get(self, index: int) -> dict[str, Any]: finally: self._fh.seek(position) data = data if isinstance(data, dict) else {} + if is_v1_trace(data): # adapt a v1 Trace to the v0 record shape the viewer renders + data = v1_trace_to_record(data) self._cache[index] = data return data diff --git a/packages/prime/tests/test_eval_billing.py b/packages/prime/tests/test_eval_billing.py index 0bc74366..b8dae150 100644 --- a/packages/prime/tests/test_eval_billing.py +++ b/packages/prime/tests/test_eval_billing.py @@ -1,3 +1,5 @@ +from pathlib import Path + import httpx import pytest import typer @@ -183,10 +185,15 @@ def __init__(self, timeout=None): install_mode="local", ), ) - monkeypatch.setattr( - "prime_cli.verifiers_bridge._run_command", - lambda command, env=None: captured.update({"command": command, "env": env}), - ) + + def fake_run_command(command, env=None): + # Read the temp v1 eval config (passed via `@ `) before the bridge unlinks it. + config_path = command[command.index("@") + 1] + captured.update( + {"command": command, "env": env, "config": Path(config_path).read_text()} + ) + + monkeypatch.setattr("prime_cli.verifiers_bridge._run_command", fake_run_command) run_eval_passthrough( environment="goblin-questions", @@ -196,12 +203,14 @@ def __init__(self, timeout=None): ) command = captured["command"] - assert command[:3] == ["verifiers.cli.commands.eval", "goblin-questions", "-m"] - assert "gpt-4.1-mini" in command - assert "-b" not in command - assert "--api-base-url" not in command - assert "-k" not in command - assert "--api-key-var" not in command + assert command[1] == "-c" + assert "verifiers.v1.cli.eval" in command[2] + config = captured["config"] + # The endpoint registry alias resolves the model to its base_url (and skips the Prime + # Inference preflight, which would raise above). + assert 'base_url = "https://api.openai.com/v1"' in config + assert 'id = "goblin-questions"' in config + assert 'model = "gpt-4.1-mini"' in config assert captured["env"]["PRIME_API_KEY"] == "test-api-key" @@ -473,55 +482,6 @@ def chat_completion(self, payload, stream=False): assert seen_billing_timeouts[1].read == 300.0 -@pytest.mark.parametrize("env_id_field", ["env_id", "id"]) -def test_eval_config_job_id_uses_config_env_id(monkeypatch, tmp_path, env_id_field): - monkeypatch.setattr( - "prime_cli.verifiers_bridge.load_verifiers_prime_plugin", lambda console: DummyPlugin() - ) - monkeypatch.setattr("prime_cli.verifiers_bridge.Config", lambda: DummyConfig()) - monkeypatch.setattr("prime_cli.verifiers_bridge._validate_model", lambda *args: None) - monkeypatch.setattr( - "prime_cli.verifiers_bridge._preflight_inference_billing", - lambda *args: None, - ) - - config_path = tmp_path / "reverse-text.toml" - config_path.write_text( - f""" -model = "openai/gpt-4.1-mini" - -[[eval]] -{env_id_field} = "primeintellect/wordle" -""".strip(), - encoding="utf-8", - ) - - prepared = [] - commands = [] - - def fake_prepare(_plugin, env_reference, env_dir_path): - prepared.append((env_reference, env_dir_path)) - - def fake_run_command(command, env=None): - commands.append(command) - - monkeypatch.setattr("prime_cli.verifiers_bridge._prepare_single_environment", fake_prepare) - monkeypatch.setattr("prime_cli.verifiers_bridge._run_command", fake_run_command) - - run_eval_passthrough( - environment=str(config_path), - passthrough_args=[], - skip_upload=True, - env_path=None, - ) - - assert prepared == [("primeintellect/wordle", "./environments")] - assert commands - assert commands[0][1] == str(config_path) - assert any(arg.startswith("X-PI-Job-Id: wordle_") for arg in commands[0]), commands[0] - assert not any(arg.startswith("X-PI-Job-Id: reverse_text_") for arg in commands[0]), commands[0] - - def test_eval_provider_short_flag_is_not_treated_as_env_dir(monkeypatch, tmp_path): monkeypatch.setattr( "prime_cli.verifiers_bridge.load_verifiers_prime_plugin", lambda console: DummyPlugin() diff --git a/packages/prime/tests/test_hosted_eval.py b/packages/prime/tests/test_hosted_eval.py index 148e2428..97425089 100644 --- a/packages/prime/tests/test_hosted_eval.py +++ b/packages/prime/tests/test_hosted_eval.py @@ -100,234 +100,14 @@ def list_evaluations(self, **_kwargs): assert "LOCAL" in result.output -def test_eval_run_hosted_invokes_hosted_runner(monkeypatch): - captured = {} - monkeypatch.setattr( - "prime_cli.commands.evals._resolve_hosted_environment", - lambda environment, env_dir_path=None, env_path=None: ( - "primeintellect/gsm8k", - "env-123", - ), - ) - def fake_run_hosted_evaluation(config, environment_ids=None): - captured["environment_id"] = config.environment_id - captured["environment_ids"] = environment_ids - captured["inference_model"] = config.inference_model - captured["num_examples"] = config.num_examples - captured["rollouts_per_example"] = config.rollouts_per_example - captured["allow_sandbox_access"] = config.allow_sandbox_access - captured["allow_instances_access"] = config.allow_instances_access - captured["allow_tunnel_access"] = config.allow_tunnel_access - return {"evaluation_id": "eval-123"} - monkeypatch.setattr( - "prime_cli.commands.evals._create_hosted_evaluations", - fake_run_hosted_evaluation, - ) - result = runner.invoke( - app, - ["eval", "run", "primeintellect/gsm8k", "--hosted", "-m", "openai/gpt-4.1-mini"], - env={"PRIME_DISABLE_VERSION_CHECK": "1"}, - ) - - assert result.exit_code == 0, result.output - assert captured["environment_id"] == "env-123" - assert captured["environment_ids"] == ["env-123"] - assert captured["inference_model"] == "openai/gpt-4.1-mini" - assert captured["num_examples"] == 5 - assert captured["rollouts_per_example"] == 3 - assert captured["allow_sandbox_access"] is True - assert captured["allow_instances_access"] is False - assert captured["allow_tunnel_access"] is True - assert "Hosted evaluation started" in result.output - assert "prime eval logs eval-123 -f" in result.output - - -def test_eval_run_hosted_passes_runtime_args_from_cli(monkeypatch): - captured = {} - monkeypatch.setattr( - "prime_cli.commands.evals._resolve_hosted_environment", - lambda environment, env_dir_path=None, env_path=None: ( - "primeintellect/gsm8k", - "env-123", - ), - ) - def fake_run_hosted_evaluation(config, environment_ids=None): - captured["max_concurrent"] = config.max_concurrent - captured["max_retries"] = config.max_retries - captured["state_columns"] = config.state_columns - captured["independent_scoring"] = config.independent_scoring - captured["verbose"] = config.verbose - captured["headers"] = config.headers - captured["sampling_args"] = config.sampling_args - return {"evaluation_id": "eval-123"} - monkeypatch.setattr( - "prime_cli.commands.evals._create_hosted_evaluations", - fake_run_hosted_evaluation, - ) - result = runner.invoke( - app, - [ - "eval", - "run", - "primeintellect/gsm8k", - "--hosted", - "--max-concurrent", - "100", - "--max-retries", - "3", - "--state-columns", - "turn,timing", - "--independent-scoring", - "--verbose", - "--header", - "X-Test: one", - "--max-tokens", - "4096", - "--temperature", - "0.2", - ], - env={"PRIME_DISABLE_VERSION_CHECK": "1"}, - ) - - assert result.exit_code == 0, result.output - assert captured == { - "max_concurrent": 100, - "max_retries": 3, - "state_columns": ["turn", "timing"], - "independent_scoring": True, - "verbose": True, - "headers": ["X-Test: one"], - "sampling_args": {"max_tokens": 4096, "temperature": 0.2}, - } - - -def test_eval_run_hosted_passes_api_base_url_and_key_var(monkeypatch): - captured = {} - - monkeypatch.setattr( - "prime_cli.commands.evals._resolve_hosted_environment", - lambda environment, env_dir_path=None, env_path=None: ( - "primeintellect/gsm8k", - "env-123", - ), - ) - - def fake_run_hosted_evaluation(config, environment_ids=None): - captured["api_base_url"] = config.api_base_url - captured["api_key_var"] = config.api_key_var - return {"evaluation_id": "eval-123"} - - monkeypatch.setattr( - "prime_cli.commands.evals._create_hosted_evaluations", - fake_run_hosted_evaluation, - ) - - result = runner.invoke( - app, - [ - "eval", - "run", - "primeintellect/gsm8k", - "--hosted", - "-m", - "openai/gpt-4.1-mini", - "-b", - "https://api.openai.com/v1", - "-k", - "OPENAI_API_KEY", - ], - env={"PRIME_DISABLE_VERSION_CHECK": "1"}, - ) - - assert result.exit_code == 0, result.output - assert captured["api_base_url"] == "https://api.openai.com/v1" - assert captured["api_key_var"] == "OPENAI_API_KEY" - - -def test_eval_run_hosted_passes_allow_tunnel_access(monkeypatch): - captured = {} - - monkeypatch.setattr( - "prime_cli.commands.evals._resolve_hosted_environment", - lambda environment, env_dir_path=None, env_path=None: ( - "primeintellect/gsm8k", - "env-123", - ), - ) - - def fake_run_hosted_evaluation(config, environment_ids=None): - captured["allow_tunnel_access"] = config.allow_tunnel_access - return {"evaluation_id": "eval-123"} - - monkeypatch.setattr( - "prime_cli.commands.evals._create_hosted_evaluations", - fake_run_hosted_evaluation, - ) - - result = runner.invoke( - app, - [ - "eval", - "run", - "primeintellect/gsm8k", - "--hosted", - "--allow-tunnel-access", - ], - env={"PRIME_DISABLE_VERSION_CHECK": "1"}, - ) - - assert result.exit_code == 0, result.output - assert captured["allow_tunnel_access"] is True - - -def test_eval_run_hosted_passes_extra_env_kwargs(monkeypatch): - captured = {} - - monkeypatch.setattr( - "prime_cli.commands.evals._resolve_hosted_environment", - lambda environment, env_dir_path=None, env_path=None: ( - "primeintellect/gsm8k", - "env-123", - ), - ) - - def fake_run_hosted_evaluation(config, environment_ids=None): - captured["extra_env_kwargs"] = config.extra_env_kwargs - return {"evaluation_id": "eval-123"} - - monkeypatch.setattr( - "prime_cli.commands.evals._create_hosted_evaluations", - fake_run_hosted_evaluation, - ) - - result = runner.invoke( - app, - [ - "eval", - "run", - "primeintellect/gsm8k", - "--hosted", - "-m", - "openai/gpt-4.1-mini", - "-x", - '{"task_library":"ronig","keep_remote_artifacts":true}', - ], - env={"PRIME_DISABLE_VERSION_CHECK": "1"}, - ) - - assert result.exit_code == 0, result.output - assert captured["extra_env_kwargs"] == { - "task_library": "ronig", - "keep_remote_artifacts": True, - } def test_create_hosted_evaluation_adds_team_id_to_payload(monkeypatch): @@ -584,598 +364,26 @@ def post(self, endpoint, json=None): assert result["evaluation_ids"] == ["eval-123", "eval-456"] -def test_eval_run_hosted_follow_streams_logs(monkeypatch): - captured = {} - - monkeypatch.setattr( - "prime_cli.commands.evals._resolve_hosted_environment", - lambda environment, env_dir_path=None, env_path=None: ( - "primeintellect/gsm8k", - "env-123", - ), - ) - - def fake_run_hosted_evaluation(config, environment_ids=None): - captured["num_examples"] = config.num_examples - captured["rollouts_per_example"] = config.rollouts_per_example - captured["environment_ids"] = environment_ids - return {"evaluation_id": "eval-123"} - - monkeypatch.setattr( - "prime_cli.commands.evals._create_hosted_evaluations", - fake_run_hosted_evaluation, - ) - - def fake_display_logs(eval_id, tail, follow, poll_interval=5.0): - captured["display_eval_id"] = eval_id - captured["display_tail"] = tail - captured["display_follow"] = follow - captured["display_poll_interval"] = poll_interval - - monkeypatch.setattr("prime_cli.commands.evals._display_logs", fake_display_logs) - - result = runner.invoke( - app, - [ - "eval", - "run", - "primeintellect/gsm8k", - "--hosted", - "--follow", - "-n", - "7", - "-r", - "2", - ], - env={"PRIME_DISABLE_VERSION_CHECK": "1"}, - ) - - assert result.exit_code == 0, result.output - assert captured["num_examples"] == 7 - assert captured["rollouts_per_example"] == 2 - assert captured["environment_ids"] == ["env-123"] - assert captured["display_eval_id"] == "eval-123" - assert captured["display_tail"] == 1000 - assert captured["display_follow"] is True - assert captured["display_poll_interval"] == 10.0 - - -def test_eval_run_hosted_supports_single_eval_toml(monkeypatch, tmp_path): - captured = {} - config_path = tmp_path / "eval.toml" - config_path.write_text( - ( - """ -model = "openai/gpt-4.1-mini" -num_examples = 7 -rollouts_per_example = 2 -timeout_minutes = 180 -allow_sandbox_access = true -allow_instances_access = true -allow_tunnel_access = true -eval_name = "math500 smoke test" -""" - + "sampling_args = { " - + 'extra_body = { provider = { order = ["azure"], ' - + "allow_fallbacks = false, require_parameters = true } } }\n" - + 'extra_env_kwargs = { task_library = "ronig", keep_remote_artifacts = true }\n\n' - + "[[eval]]\n" - + 'env_id = "gsm8k"\n' - + 'env_args = { split = "test" }' - ) - ) - - def fake_resolve(environment, env_dir_path=None, env_path=None): - captured["environment"] = environment - captured["env_dir_path"] = env_dir_path - captured["env_path"] = env_path - return ("primeintellect/gsm8k", "env-123") - - def fake_run_hosted_evaluation(config, environment_ids=None): - captured["environment_id"] = config.environment_id - captured["environment_ids"] = environment_ids - captured["inference_model"] = config.inference_model - captured["num_examples"] = config.num_examples - captured["rollouts_per_example"] = config.rollouts_per_example - captured["env_args"] = config.env_args - captured["timeout_minutes"] = config.timeout_minutes - captured["allow_sandbox_access"] = config.allow_sandbox_access - captured["allow_instances_access"] = config.allow_instances_access - captured["allow_tunnel_access"] = config.allow_tunnel_access - captured["sampling_args"] = config.sampling_args - captured["extra_env_kwargs"] = config.extra_env_kwargs - captured["name"] = config.name - return {"evaluation_id": "eval-123"} - - monkeypatch.setattr("prime_cli.commands.evals._resolve_hosted_environment", fake_resolve) - monkeypatch.setattr( - "prime_cli.commands.evals._create_hosted_evaluations", - fake_run_hosted_evaluation, - ) - - result = runner.invoke( - app, - ["eval", "run", str(config_path), "--hosted"], - env={"PRIME_DISABLE_VERSION_CHECK": "1"}, - ) - - assert result.exit_code == 0, result.output - assert captured == { - "environment": "gsm8k", - "env_dir_path": None, - "env_path": None, - "environment_id": "env-123", - "environment_ids": ["env-123"], - "inference_model": "openai/gpt-4.1-mini", - "num_examples": 7, - "rollouts_per_example": 2, - "env_args": {"split": "test"}, - "timeout_minutes": 180, - "allow_sandbox_access": True, - "allow_instances_access": True, - "allow_tunnel_access": True, - "sampling_args": { - "extra_body": { - "provider": { - "order": ["azure"], - "allow_fallbacks": False, - "require_parameters": True, - } - } - }, - "extra_env_kwargs": { - "task_library": "ronig", - "keep_remote_artifacts": True, - }, - "name": "math500 smoke test", - } - - -def test_eval_run_hosted_cli_overrides_supported_toml_fields(monkeypatch, tmp_path): - captured = {} - config_path = tmp_path / "eval.toml" - config_path.write_text( - """ -model = "openai/gpt-4.1-mini" -num_examples = 7 -rollouts_per_example = 2 -timeout_minutes = 180 -allow_sandbox_access = true -allow_instances_access = true -allow_tunnel_access = true -eval_name = "from toml" - -[[eval]] -env_id = "gsm8k" -env_args = { split = "test" } -""".strip() - ) - - def fake_resolve(environment, env_dir_path=None, env_path=None): - return ("primeintellect/gsm8k", "env-123") - - def fake_run_hosted_evaluation(config, environment_ids=None): - captured["environment_ids"] = environment_ids - captured["inference_model"] = config.inference_model - captured["num_examples"] = config.num_examples - captured["rollouts_per_example"] = config.rollouts_per_example - captured["env_args"] = config.env_args - captured["timeout_minutes"] = config.timeout_minutes - captured["allow_sandbox_access"] = config.allow_sandbox_access - captured["allow_instances_access"] = config.allow_instances_access - captured["allow_tunnel_access"] = config.allow_tunnel_access - captured["sampling_args"] = config.sampling_args - captured["extra_env_kwargs"] = config.extra_env_kwargs - captured["name"] = config.name - return {"evaluation_id": "eval-123"} - - monkeypatch.setattr("prime_cli.commands.evals._resolve_hosted_environment", fake_resolve) - monkeypatch.setattr( - "prime_cli.commands.evals._create_hosted_evaluations", - fake_run_hosted_evaluation, - ) - - result = runner.invoke( - app, - [ - "eval", - "run", - str(config_path), - "--hosted", - "-m", - "anthropic/claude-sonnet-4", - "-n", - "3", - "-r", - "4", - "--env-args", - '{"split":"validation"}', - "--timeout-minutes", - "240", - "--sampling-args", - '{"temperature":0.2,"extra_body":{"provider":{"order":["azure"],"allow_fallbacks":false,"require_parameters":true}}}', - "--extra-env-kwargs", - '{"task_library":"ronig","keep_remote_artifacts":true}', - "--eval-name", - "from cli", - ], - env={"PRIME_DISABLE_VERSION_CHECK": "1"}, - ) - - assert result.exit_code == 0, result.output - assert captured == { - "environment_ids": ["env-123"], - "inference_model": "anthropic/claude-sonnet-4", - "num_examples": 3, - "rollouts_per_example": 4, - "env_args": {"split": "validation"}, - "timeout_minutes": 240, - "allow_sandbox_access": True, - "allow_instances_access": True, - "allow_tunnel_access": True, - "sampling_args": { - "temperature": 0.2, - "extra_body": { - "provider": { - "order": ["azure"], - "allow_fallbacks": False, - "require_parameters": True, - } - }, - }, - "extra_env_kwargs": { - "task_library": "ronig", - "keep_remote_artifacts": True, - }, - "name": "from cli", - } - - -def test_eval_run_hosted_supports_additional_toml_fields_and_sampling_aliases( - monkeypatch, tmp_path -): - captured = {} - config_path = tmp_path / "eval.toml" - config_path.write_text( - ( - """ -model = "openai/gpt-4.1-mini" -num_examples = 7 -rollouts_per_example = 2 -max_concurrent = 100 -max_retries = 3 -state_columns = ["turn", "timing"] -independent_scoring = true -verbose = true -header = ["X-Test: one"] -max_tokens = 4096 -temperature = 0.2 -""" - + 'sampling_args = { extra_body = { provider = { order = ["azure"], ' - + "allow_fallbacks = false, require_parameters = true } } }\n" - + """ -[[eval]] -env_id = "gsm8k" -""" - ).strip() - ) - - def fake_resolve(environment, env_dir_path=None, env_path=None): - return ("primeintellect/gsm8k", "env-123") - - def fake_run_hosted_evaluation(config, environment_ids=None): - captured["max_concurrent"] = config.max_concurrent - captured["max_retries"] = config.max_retries - captured["state_columns"] = config.state_columns - captured["independent_scoring"] = config.independent_scoring - captured["verbose"] = config.verbose - captured["headers"] = config.headers - captured["sampling_args"] = config.sampling_args - return {"evaluation_id": "eval-123"} - - monkeypatch.setattr("prime_cli.commands.evals._resolve_hosted_environment", fake_resolve) - monkeypatch.setattr( - "prime_cli.commands.evals._create_hosted_evaluations", - fake_run_hosted_evaluation, - ) - - result = runner.invoke( - app, - ["eval", "run", str(config_path), "--hosted"], - env={"PRIME_DISABLE_VERSION_CHECK": "1"}, - ) - - assert result.exit_code == 0, result.output - assert captured == { - "max_concurrent": 100, - "max_retries": 3, - "state_columns": ["turn", "timing"], - "independent_scoring": True, - "verbose": True, - "headers": ["X-Test: one"], - "sampling_args": { - "max_tokens": 4096, - "temperature": 0.2, - "extra_body": { - "provider": { - "order": ["azure"], - "allow_fallbacks": False, - "require_parameters": True, - } - }, - }, - } - - -def test_eval_run_hosted_supports_multi_eval_toml_with_shared_config(monkeypatch, tmp_path): - captured = {} - config_path = tmp_path / "eval.toml" - config_path.write_text( - """ -model = "openai/gpt-4.1-mini" -num_examples = 5 -rollouts_per_example = 3 - -[[eval]] -env_id = "gsm8k" - -[[eval]] -env_id = "math500" -""".strip() - ) - - resolved_calls = [] - def fake_resolve(environment, env_dir_path=None, env_path=None): - resolved_calls.append((environment, env_dir_path, env_path)) - return (f"primeintellect/{environment}", f"env-{environment}") - def fake_run_hosted_evaluation(config, environment_ids=None): - captured["environment_id"] = config.environment_id - captured["environment_ids"] = environment_ids - captured["inference_model"] = config.inference_model - captured["num_examples"] = config.num_examples - captured["rollouts_per_example"] = config.rollouts_per_example - return {"evaluation_id": "eval-123", "evaluation_ids": ["eval-123", "eval-456"]} - monkeypatch.setattr("prime_cli.commands.evals._resolve_hosted_environment", fake_resolve) - monkeypatch.setattr( - "prime_cli.commands.evals._create_hosted_evaluations", - fake_run_hosted_evaluation, - ) - result = runner.invoke( - app, - ["eval", "run", str(config_path), "--hosted"], - env={"PRIME_DISABLE_VERSION_CHECK": "1"}, - ) - assert result.exit_code == 0, result.output - assert resolved_calls == [ - ("gsm8k", None, None), - ("math500", None, None), - ] - assert captured == { - "environment_id": "env-gsm8k", - "environment_ids": ["env-gsm8k", "env-math500"], - "inference_model": "openai/gpt-4.1-mini", - "num_examples": 5, - "rollouts_per_example": 3, - } - assert "Evaluation IDs:" in result.output - assert "eval-123, eval-456" in result.output -def test_eval_run_hosted_supports_multi_eval_toml_with_different_settings(monkeypatch, tmp_path): - captured_calls = [] - config_path = tmp_path / "eval.toml" - config_path.write_text( - """ -[[eval]] -env_id = "gsm8k" -num_examples = 5 -[[eval]] -env_id = "math500" -num_examples = 10 -""".strip() - ) - def fake_resolve(environment, env_dir_path=None, env_path=None): - return (f"primeintellect/{environment}", f"env-{environment}") - def fake_run_hosted_evaluation(config, environment_ids=None): - captured_calls.append( - { - "environment_id": config.environment_id, - "environment_ids": environment_ids, - "num_examples": config.num_examples, - "rollouts_per_example": config.rollouts_per_example, - } - ) - return { - "evaluation_id": f"eval-{len(captured_calls)}", - "evaluation_ids": [f"eval-{len(captured_calls)}"], - } - monkeypatch.setattr("prime_cli.commands.evals._resolve_hosted_environment", fake_resolve) - monkeypatch.setattr( - "prime_cli.commands.evals._create_hosted_evaluations", - fake_run_hosted_evaluation, - ) - - result = runner.invoke( - app, - ["eval", "run", str(config_path), "--hosted"], - env={"PRIME_DISABLE_VERSION_CHECK": "1"}, - ) - assert result.exit_code == 0, result.output - assert captured_calls == [ - { - "environment_id": "env-gsm8k", - "environment_ids": ["env-gsm8k"], - "num_examples": 5, - "rollouts_per_example": 3, - }, - { - "environment_id": "env-math500", - "environment_ids": ["env-math500"], - "num_examples": 10, - "rollouts_per_example": 3, - }, - ] - assert "Evaluation IDs:" in result.output - assert "eval-1, eval-2" in result.output - - -def test_eval_run_hosted_rejects_invalid_supported_toml_field_types(tmp_path): - config_path = tmp_path / "eval.toml" - config_path.write_text( - """ -timeout_minutes = "180" - -[[eval]] -env_id = "gsm8k" -""".strip() - ) - - result = runner.invoke( - app, - ["eval", "run", str(config_path), "--hosted"], - env={"PRIME_DISABLE_VERSION_CHECK": "1"}, - ) - assert result.exit_code == 1 - assert "`timeout_minutes` must be an integer" in result.output - - -def test_eval_run_hosted_rejects_non_json_serializable_sampling_args_in_toml(tmp_path): - config_path = tmp_path / "eval.toml" - config_path.write_text( - """ -sampling_args = { until = 1979-05-27T07:32:00Z } - -[[eval]] -env_id = "gsm8k" -""".strip() - ) - - result = runner.invoke( - app, - ["eval", "run", str(config_path), "--hosted"], - env={"PRIME_DISABLE_VERSION_CHECK": "1"}, - ) - - assert result.exit_code == 1 - assert "`sampling_args`" in result.output - assert "JSON-serializable" in result.output - - -def test_eval_run_hosted_rejects_non_json_serializable_extra_env_kwargs_in_toml(tmp_path): - config_path = tmp_path / "eval.toml" - config_path.write_text( - """ -extra_env_kwargs = { until = 1979-05-27T07:32:00Z } - -[[eval]] -env_id = "gsm8k" -""".strip() - ) - - result = runner.invoke( - app, - ["eval", "run", str(config_path), "--hosted"], - env={"PRIME_DISABLE_VERSION_CHECK": "1"}, - ) - - assert result.exit_code == 1 - assert "`extra_env_kwargs`" in result.output - assert "JSON-serializable" in result.output - - -@pytest.mark.parametrize( - ("field_assignment", "expected_field"), - [ - ('provider = "azure"', "provider"), - ("debug = true", "debug"), - ("save_results = false", "save_results"), - ("resume = true", "resume"), - ('resume_path = ""', "resume_path"), - ("save_to_hf_hub = false", "save_to_hf_hub"), - ('hf_hub_dataset_name = ""', "hf_hub_dataset_name"), - ('output_dir = ""', "output_dir"), - ("disable_env_server = false", "disable_env_server"), - ('num_workers = "auto"', "num_workers"), - ], -) -def test_eval_run_hosted_rejects_explicit_unsupported_toml_fields( - tmp_path, field_assignment, expected_field -): - config_path = tmp_path / "eval.toml" - config_path.write_text( - f""" -{field_assignment} - -[[eval]] -env_id = "gsm8k" -""".strip() - ) - - result = runner.invoke( - app, - ["eval", "run", str(config_path), "--hosted"], - env={"PRIME_DISABLE_VERSION_CHECK": "1"}, - ) - assert result.exit_code == 1 - assert "does not support" in result.output - assert f"`{expected_field}`" in result.output -def test_eval_run_hosted_toml_preserves_cli_env_dir_path(monkeypatch, tmp_path): - captured = {} - config_path = tmp_path / "eval.toml" - config_path.write_text( - """ -[[eval]] -env_id = "gsm8k" -""".strip() - ) - def fake_resolve(environment, env_dir_path=None, env_path=None): - captured["environment"] = environment - captured["env_dir_path"] = env_dir_path - captured["env_path"] = env_path - return ("primeintellect/gsm8k", "env-123") - def fake_run_hosted_evaluation(config, environment_ids=None): - return {"evaluation_id": "eval-123"} - monkeypatch.setattr("prime_cli.commands.evals._resolve_hosted_environment", fake_resolve) - monkeypatch.setattr( - "prime_cli.commands.evals._create_hosted_evaluations", - fake_run_hosted_evaluation, - ) - result = runner.invoke( - app, - [ - "eval", - "run", - str(config_path), - "--hosted", - "--env-dir-path", - "/tmp/custom-envs", - ], - env={"PRIME_DISABLE_VERSION_CHECK": "1"}, - ) - assert result.exit_code == 0, result.output - assert captured == { - "environment": "gsm8k", - "env_dir_path": "/tmp/custom-envs", - "env_path": None, - } def test_hosted_eval_config_accepts_id_alias(tmp_path): @@ -1361,61 +569,8 @@ def fake_run_eval_passthrough(environment, passthrough_args, skip_upload, env_pa } -@pytest.mark.parametrize( - ("extra_args", "expected_flag"), - [ - (["--provider", "openai"], "--provider"), - (["--endpoints-path", "./configs/endpoints.toml"], "--endpoints-path"), - (["--output-dir", "/tmp/results"], "--output-dir"), - (["--no-interleave-scoring"], "--no-interleave-scoring"), - (["--save-results"], "--save-results"), - (["--resume", "/tmp/results.json"], "--resume"), - (["--save-to-hf-hub"], "--save-to-hf-hub"), - (["--hf-hub-dataset-name", "dataset-name"], "--hf-hub-dataset-name"), - (["--tui"], "--tui"), - (["--debug"], "--debug"), - (["--disable-env-server"], "--disable-env-server"), - (["--num-workers", "auto"], "--num-workers"), - (["--abbreviated-summary"], "--abbreviated-summary"), - (["--heartbeat-url", "https://example.com/heartbeat"], "--heartbeat-url"), - ], -) -def test_eval_run_hosted_rejects_unsupported_passthrough_flags(extra_args, expected_flag): - result = runner.invoke( - app, - ["eval", "run", "gsm8k", "--hosted", *extra_args], - env={"PRIME_DISABLE_VERSION_CHECK": "1"}, - ) - - assert result.exit_code == 1 - assert "hosted eval CLI does not support" in result.output - assert f"`{expected_flag}`" in result.output -def test_eval_run_hosted_accepts_negative_num_examples_value(monkeypatch): - captured = {} - - def fake_create_hosted_evaluations(config, environment_ids=None): - captured["num_examples"] = config.num_examples - return {"evaluation_id": "eval-123"} - - monkeypatch.setattr( - "prime_cli.commands.evals._create_hosted_evaluations", - fake_create_hosted_evaluations, - ) - monkeypatch.setattr( - "prime_cli.commands.evals._resolve_hosted_environment", - lambda environment, env_dir_path=None, env_path=None: ("primeintellect/gsm8k", "env-123"), - ) - - result = runner.invoke( - app, - ["eval", "run", "gsm8k", "--hosted", "--num-examples", "-1"], - env={"PRIME_DISABLE_VERSION_CHECK": "1"}, - ) - - assert result.exit_code == 0, result.output - assert captured["num_examples"] == -1 def test_eval_run_rejects_hosted_only_flags_without_hosted(): @@ -1448,82 +603,8 @@ def test_eval_run_rejects_tunnel_access_without_hosted(): assert "hosted-only options require `--hosted`" in result.output -def test_eval_run_hosted_passes_env_dir_path_to_resolver(monkeypatch): - captured = {} - def fake_resolve(environment, env_dir_path=None, env_path=None): - captured["environment"] = environment - captured["env_dir_path"] = env_dir_path - captured["env_path"] = env_path - return ("primeintellect/gsm8k", "env-123") - def fake_run_hosted_evaluation(config, environment_ids=None): - return {"evaluation_id": "eval-123"} - - monkeypatch.setattr("prime_cli.commands.evals._resolve_hosted_environment", fake_resolve) - monkeypatch.setattr( - "prime_cli.commands.evals._create_hosted_evaluations", - fake_run_hosted_evaluation, - ) - - result = runner.invoke( - app, - [ - "eval", - "run", - "gsm8k", - "--hosted", - "--env-dir-path", - "/tmp/custom-envs", - ], - env={"PRIME_DISABLE_VERSION_CHECK": "1"}, - ) - - assert result.exit_code == 0, result.output - assert captured == { - "environment": "gsm8k", - "env_dir_path": "/tmp/custom-envs", - "env_path": None, - } - - -def test_eval_run_hosted_passes_env_path_to_resolver(monkeypatch): - captured = {} - - def fake_resolve(environment, env_dir_path=None, env_path=None): - captured["environment"] = environment - captured["env_dir_path"] = env_dir_path - captured["env_path"] = env_path - return ("primeintellect/gsm8k", "env-123") - - def fake_run_hosted_evaluation(config, environment_ids=None): - return {"evaluation_id": "eval-123"} - - monkeypatch.setattr("prime_cli.commands.evals._resolve_hosted_environment", fake_resolve) - monkeypatch.setattr( - "prime_cli.commands.evals._create_hosted_evaluations", - fake_run_hosted_evaluation, - ) - - result = runner.invoke( - app, - [ - "eval", - "run", - "gsm8k", - "--hosted", - "--env-path", - "/tmp/local-env", - ], - env={"PRIME_DISABLE_VERSION_CHECK": "1"}, - ) - - assert result.exit_code == 0, result.output - assert captured == { - "environment": "gsm8k", - "env_dir_path": None, - "env_path": "/tmp/local-env", - } def test_resolve_hosted_environment_warns_when_local_code_differs(monkeypatch, capsys): @@ -1617,22 +698,6 @@ def get(self, endpoint): assert "Publish primeintellect/gsm8k with `prime env push` first." in output -def test_eval_run_hosted_reports_resolve_api_errors(monkeypatch): - monkeypatch.setattr( - "prime_cli.commands.evals._resolve_hosted_environment", - lambda environment, env_dir_path=None, env_path=None: (_ for _ in ()).throw( - APIError("lookup failed") - ), - ) - - result = runner.invoke( - app, - ["eval", "run", "gsm8k", "--hosted"], - env={"PRIME_DISABLE_VERSION_CHECK": "1"}, - ) - - assert result.exit_code == 1 - assert "lookup failed" in result.output def test_eval_stop_command_calls_cancel_endpoint(monkeypatch): @@ -1779,3 +844,17 @@ def test_eval_logs_command_emits_waiting_status_when_logs_are_unchanged(monkeypa assert result.output.count("Line 1") == 1 assert "Evaluation status: RUNNING (waiting for logs...)" in result.output assert "Status: COMPLETED" in result.output + + +def test_eval_run_hosted_raises_not_implemented(): + # The platform backend isn't v1-aware yet, so `--hosted` is gated: the run config is parsed + # (machinery preserved) and then a NotImplementedError is raised before any submission. + result = runner.invoke( + app, + ["eval", "run", "gsm8k", "--hosted", "-m", "openai/gpt-4.1-mini", "-n", "2"], + env={"PRIME_DISABLE_VERSION_CHECK": "1"}, + ) + assert result.exit_code != 0 + assert isinstance(result.exception, NotImplementedError) + assert "not supported yet" in str(result.exception) + assert "openai/gpt-4.1-mini" in str(result.exception) diff --git a/pyproject.toml b/pyproject.toml index 73a99d31..67670e72 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -41,7 +41,7 @@ harnesses = false [tool.uv.sources] prime-tunnel = { workspace = true } -verifiers = { git = "https://github.com/PrimeIntellect-ai/verifiers.git", tag = "v0.1.14" } +verifiers = { git = "https://github.com/PrimeIntellect-ai/verifiers.git", rev = "bbfd564" } [tool.pytest.ini_options] pythonpath = [ diff --git a/uv.lock b/uv.lock index 3ca1f0ea..33d22b57 100644 --- a/uv.lock +++ b/uv.lock @@ -1,10 +1,9 @@ version = 1 revision = 3 -requires-python = ">=3.10" +requires-python = ">=3.11, <3.14" resolution-markers = [ "python_full_version >= '3.12'", - "python_full_version == '3.11.*'", - "python_full_version < '3.11'", + "python_full_version < '3.12'", ] [options] @@ -63,7 +62,6 @@ source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "aiohappyeyeballs" }, { name = "aiosignal" }, - { name = "async-timeout", marker = "python_full_version < '3.11'" }, { name = "attrs" }, { name = "frozenlist" }, { name = "multidict" }, @@ -72,23 +70,6 @@ dependencies = [ ] sdist = { url = "https://files.pythonhosted.org/packages/62/f1/8515650ac3121a9e55c7b217c60e7fae3e0134b5acfe65691781b5356929/aiohttp-3.13.0.tar.gz", hash = "sha256:378dbc57dd8cf341ce243f13fa1fa5394d68e2e02c15cd5f28eae35a70ec7f67", size = 7832348, upload-time = 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