eval: add commit0 benchmark (#5153)

Co-authored-by: Xingyao Wang <xingyao6@illinois.edu>
Co-authored-by: Xingyao Wang <xingyao@all-hands.dev>
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Nan Jiang 2024-11-22 14:49:45 -05:00 committed by GitHub
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.gitignore vendored
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@ -175,6 +175,7 @@ evaluation/gaia/data
evaluation/gorilla/data
evaluation/toolqa/data
evaluation/scienceagentbench/benchmark
evaluation/commit0_bench/repos
# openhands resolver
output/

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# Commit0 Evaluation with OpenHands
This folder contains the evaluation harness that we built on top of the original [Commit0](https://commit-0.github.io/) ([paper](TBD)).
The evaluation consists of three steps:
1. Environment setup: [install python environment](../README.md#development-environment), [configure LLM config](../README.md#configure-openhands-and-your-llm).
2. [Run Evaluation](#run-inference-on-commit0-instances): Generate a edit patch for each Commit0 Repo, and get the evaluation results
## Setup Environment and LLM Configuration
Please follow instruction [here](../README.md#setup) to setup your local development environment and LLM.
## OpenHands Commit0 Instance-level Docker Support
OpenHands supports using the Commit0 Docker for **[inference](#run-inference-on-commit0-instances).
This is now the default behavior.
## Run Inference on Commit0 Instances
Make sure your Docker daemon is running, and you have ample disk space (at least 200-500GB, depends on the Commit0 set you are running on) for the [instance-level docker image](#openhands-commit0-instance-level-docker-support).
When the `run_infer.sh` script is started, it will automatically pull the `lite` split in Commit0. For example, for instance ID `commit-0/minitorch`, it will try to pull our pre-build docker image `wentingzhao/minitorch` from DockerHub. This image will be used create an OpenHands runtime image where the agent will operate on.
```bash
./evaluation/commit0_bench/scripts/run_infer.sh [repo_split] [model_config] [git-version] [agent] [eval_limit] [max_iter] [num_workers] [dataset] [dataset_split]
# Example
./evaluation/commit0_bench/scripts/run_infer.sh lite llm.eval_sonnet HEAD CodeActAgent 16 100 8 wentingzhao/commit0_combined test
```
where `model_config` is mandatory, and the rest are optional.
- `repo_split`, e.g. `lite`, is the split of the Commit0 dataset you would like to evaluate on. Available options are `lite`, `all` and each individual repo.
- `model_config`, e.g. `eval_gpt4_1106_preview`, is the config group name for your
LLM settings, as defined in your `config.toml`.
- `git-version`, e.g. `HEAD`, is the git commit hash of the OpenHands version you would
like to evaluate. It could also be a release tag like `0.6.2`.
- `agent`, e.g. `CodeActAgent`, is the name of the agent for benchmarks, defaulting
to `CodeActAgent`.
- `eval_limit`, e.g. `10`, limits the evaluation to the first `eval_limit` instances. By
default, the script evaluates the `lite` split of the Commit0 dataset (16 repos). Note:
in order to use `eval_limit`, you must also set `agent`.
- `max_iter`, e.g. `20`, is the maximum number of iterations for the agent to run. By
default, it is set to 30.
- `num_workers`, e.g. `3`, is the number of parallel workers to run the evaluation. By
default, it is set to 1.
- `dataset`, a huggingface dataset name. e.g. `wentingzhao/commit0_combined`, specifies which dataset to evaluate on.
- `dataset_split`, split for the huggingface dataset. Notice only `test` is supported for Commit0.
Note that the `USE_INSTANCE_IMAGE` environment variable is always set to `true` for Commit0.
Let's say you'd like to run 10 instances using `llm.eval_sonnet` and CodeActAgent,
then your command would be:
```bash
./evaluation/commit0_bench/scripts/run_infer.sh lite llm.eval_sonnet HEAD CodeActAgent 10 30 1 wentingzhao/commit0_combined test
```
### Run Inference on `RemoteRuntime` (experimental)
This is in limited beta. Contact Xingyao over slack if you want to try this out!
```bash
./evaluation/commit0_bench/scripts/run_infer.sh [repo_split] [model_config] [git-version] [agent] [eval_limit] [max_iter] [num_workers] [dataset] [dataset_split]
# Example - This runs evaluation on CodeActAgent for 10 instances on "wentingzhao/commit0_combined"'s test set, with max 30 iteration per instances, with 1 number of workers running in parallel
ALLHANDS_API_KEY="YOUR-API-KEY" RUNTIME=remote SANDBOX_REMOTE_RUNTIME_API_URL="https://runtime.eval.all-hands.dev" EVAL_DOCKER_IMAGE_PREFIX="docker.io/wentingzhao" \
./evaluation/commit0_bench/scripts/run_infer.sh lite llm.eval_sonnet HEAD CodeActAgent 10 30 1 wentingzhao/commit0_combined test
```
To clean-up all existing runtime you've already started, run:
```bash
ALLHANDS_API_KEY="YOUR-API-KEY" ./evaluation/commit0_bench/scripts/cleanup_remote_runtime.sh
```
### Specify a subset of tasks to run infer
If you would like to specify a list of tasks you'd like to benchmark on, you just need to pass selected repo through `repo_split` option.

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import asyncio
import json
import os
from collections import Counter
from typing import Any
import pandas as pd
from commit0.harness.constants import SPLIT
from datasets import load_dataset
import openhands.agenthub
from evaluation.utils.shared import (
EvalException,
EvalMetadata,
EvalOutput,
assert_and_raise,
codeact_user_response,
make_metadata,
prepare_dataset,
reset_logger_for_multiprocessing,
run_evaluation,
update_llm_config_for_completions_logging,
)
from openhands.controller.state.state import State
from openhands.core.config import (
AgentConfig,
AppConfig,
SandboxConfig,
get_llm_config_arg,
get_parser,
)
from openhands.core.logger import openhands_logger as logger
from openhands.core.main import create_runtime, run_controller
from openhands.events.action import CmdRunAction, MessageAction
from openhands.events.observation import CmdOutputObservation, ErrorObservation
from openhands.events.serialization.event import event_to_dict
from openhands.runtime.base import Runtime
from openhands.utils.async_utils import call_async_from_sync
from openhands.utils.shutdown_listener import sleep_if_should_continue
USE_HINT_TEXT = os.environ.get('USE_HINT_TEXT', 'false').lower() == 'true'
USE_INSTANCE_IMAGE = os.environ.get('USE_INSTANCE_IMAGE', 'false').lower() == 'true'
RUN_WITH_BROWSING = os.environ.get('RUN_WITH_BROWSING', 'false').lower() == 'true'
AGENT_CLS_TO_FAKE_USER_RESPONSE_FN = {
'CodeActAgent': codeact_user_response,
'CodeActCommit0Agent': codeact_user_response,
}
def _get_commit0_workspace_dir_name(instance: pd.Series) -> str:
return instance['repo'].split('/')[1]
def get_instruction(instance: pd.Series, metadata: EvalMetadata):
workspace_dir_name = _get_commit0_workspace_dir_name(instance)
# Prepare instruction
test_cmd = instance['test']['test_cmd']
test_dir = instance['test']['test_dir']
# Instruction based on Anthropic's official trajectory
# https://github.com/eschluntz/swe-bench-experiments/tree/main/evaluation/verified/20241022_tools_claude-3-5-sonnet-updated/trajs
instruction = (
'<uploaded_files>\n'
f'/workspace/{workspace_dir_name}\n'
'</uploaded_files>\n'
f"I've uploaded a python code repository in the directory {workspace_dir_name}. Here is your task:\n\n"
'Here is your task:\n\n'
' You need to complete the implementations for all functions (i.e., those with pass\n'
' statements) and pass the unit tests.\n\n'
' Do not change the names of existing functions or classes, as they may be referenced\n'
' from other code like unit tests, etc.\n\n'
' When you generate code, you must maintain the original formatting of the function\n'
' stubs (such as whitespaces), otherwise we will not able to search/replace blocks\n'
' for code modifications, and therefore you will receive a score of 0 for your generated\n'
' code.'
'\n\n'
'Here is the command to run the unit tests:\n'
'<test_command>\n'
f'{test_cmd} {test_dir}\n'
'</test_command>\n\n'
'Make a local git commit for each agent step for all code changes. If there is not change in current step, do not make a commit.'
)
if RUN_WITH_BROWSING:
instruction += (
'<IMPORTANT!>\n'
'You SHOULD NEVER attempt to browse the web. '
'</IMPORTANT!>\n'
)
return instruction
# TODO: migrate all swe-bench docker to ghcr.io/openhands
DOCKER_IMAGE_PREFIX = os.environ.get(
'EVAL_DOCKER_IMAGE_PREFIX', 'docker.io/wentingzhao/'
)
logger.info(f'Using docker image prefix: {DOCKER_IMAGE_PREFIX}')
def get_instance_docker_image(repo_name: str) -> str:
return (DOCKER_IMAGE_PREFIX.rstrip('/') + '/' + repo_name).lower() + ':v0'
def get_config(
instance: pd.Series,
metadata: EvalMetadata,
) -> AppConfig:
# COMMIT0_CONTAINER_IMAGE = 'wentingzhao/'
assert USE_INSTANCE_IMAGE
# We use a different instance image for the each instance of commit0 eval
repo_name = instance['repo'].split('/')[1]
base_container_image = get_instance_docker_image(repo_name)
logger.info(
f'Using instance container image: {base_container_image}. '
f'Please make sure this image exists. '
f'Submit an issue on https://github.com/All-Hands-AI/OpenHands if you run into any issues.'
)
# else:
# raise
# base_container_image = SWE_BENCH_CONTAINER_IMAGE
# logger.info(f'Using swe-bench container image: {base_container_image}')
config = AppConfig(
default_agent=metadata.agent_class,
run_as_openhands=False,
max_iterations=metadata.max_iterations,
runtime=os.environ.get('RUNTIME', 'eventstream'),
sandbox=SandboxConfig(
base_container_image=base_container_image,
enable_auto_lint=True,
use_host_network=False,
# large enough timeout, since some testcases take very long to run
timeout=300,
api_key=os.environ.get('ALLHANDS_API_KEY', None),
remote_runtime_api_url=os.environ.get('SANDBOX_REMOTE_RUNTIME_API_URL'),
keep_runtime_alive=False,
remote_runtime_init_timeout=3600,
),
# do not mount workspace
workspace_base=None,
workspace_mount_path=None,
)
config.set_llm_config(
update_llm_config_for_completions_logging(
metadata.llm_config, metadata.eval_output_dir, instance['instance_id']
)
)
agent_config = AgentConfig(
codeact_enable_jupyter=False,
codeact_enable_browsing=RUN_WITH_BROWSING,
codeact_enable_llm_editor=False,
)
config.set_agent_config(agent_config)
return config
def initialize_runtime(
runtime: Runtime,
instance: pd.Series, # this argument is not required
):
"""Initialize the runtime for the agent.
This function is called before the runtime is used to run the agent.
"""
logger.info('-' * 30)
logger.info('BEGIN Runtime Initialization Fn')
logger.info('-' * 30)
workspace_dir_name = _get_commit0_workspace_dir_name(instance)
obs: CmdOutputObservation
action = CmdRunAction(
command=f'git clone -b commit0_combined https://github.com/{instance["repo"]}.git'
)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
assert_and_raise(
obs.exit_code == 0,
f'Failed to git clone -b commit0_combined https://github.com/{instance["repo"]}.git: {str(obs)}',
)
action = CmdRunAction(command=f'cd /workspace/{workspace_dir_name}')
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
assert_and_raise(
obs.exit_code == 0,
f'Failed to cd to /workspace/{workspace_dir_name}: {str(obs)}',
)
action = CmdRunAction(command='git checkout -b openhands')
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
assert_and_raise(
obs.exit_code == 0, f'Failed to git checkout new branch openhands: {str(obs)}'
)
# Install commit0
action = CmdRunAction(command='/root/.cargo/bin/uv pip install commit0')
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
# logger.info(obs, extra={'msg_type': 'OBSERVATION'})
assert_and_raise(
obs.exit_code == 0,
f'Failed to install commit0: {str(obs)}',
)
logger.info('-' * 30)
logger.info('END Runtime Initialization Fn')
logger.info('-' * 30)
def complete_runtime(
runtime: Runtime,
instance: pd.Series, # this argument is not required, but it is used to get the workspace_dir_name
) -> dict[str, Any]:
"""Complete the runtime for the agent.
This function is called before the runtime is used to run the agent.
If you need to do something in the sandbox to get the correctness metric after
the agent has run, modify this function.
"""
logger.info('-' * 30)
logger.info('BEGIN Runtime Completion Fn')
logger.info('-' * 30)
obs: CmdOutputObservation
workspace_dir_name = _get_commit0_workspace_dir_name(instance)
action = CmdRunAction(command='git add .')
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
assert_and_raise(
isinstance(obs, CmdOutputObservation) and obs.exit_code == 0,
f'Failed to git add -A: {str(obs)}',
)
action = CmdRunAction(command='git commit -m "openhands edits"')
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
assert_and_raise(
isinstance(obs, CmdOutputObservation)
and (obs.exit_code == 0 or obs.exit_code == 1),
f'Failed to git commit -m "openhands": {str(obs)}',
)
# Generate diff patch compared to base commit, excluding spec.pdf.bz2 files
n_retries = 0
git_patch = None
while n_retries < 5:
action = CmdRunAction(
command=f"git diff {instance['base_commit']} HEAD -- . ':(exclude)spec.pdf.bz2'"
)
action.timeout = 600 + 100 * n_retries
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
# logger.info(obs, extra={'msg_type': 'OBSERVATION'})
n_retries += 1
if isinstance(obs, CmdOutputObservation):
if obs.exit_code == 0:
git_patch = obs.content.strip()
break
else:
logger.info('Failed to get git diff, retrying...')
sleep_if_should_continue(10)
elif isinstance(obs, ErrorObservation):
logger.error(f'Error occurred: {obs.content}. Retrying...')
sleep_if_should_continue(10)
else:
assert_and_raise(False, f'Unexpected observation type: {str(obs)}')
assert_and_raise(git_patch is not None, 'Failed to get git diff (None)')
test_dir = instance['test']['test_dir']
action = CmdRunAction(
command=f"{instance['test']['test_cmd']} --json-report --json-report-file=report.json --continue-on-collection-errors {test_dir} > test_output.txt 2>&1"
)
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
assert_and_raise(
isinstance(obs, CmdOutputObservation),
f'Failed to run test command: {str(obs)}',
)
# Read test output
action = CmdRunAction(command='cat test_output.txt')
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
# logger.info(obs, extra={'msg_type': 'OBSERVATION'})
assert_and_raise(
isinstance(obs, CmdOutputObservation),
f'Failed to read test output: {str(obs)}',
)
test_output = obs.content.strip()
# logger.info(f'Test output: {test_output}')
# Save pytest exit code
action = CmdRunAction(command='echo $?')
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
# logger.info(obs, extra={'msg_type': 'OBSERVATION'})
assert_and_raise(
isinstance(obs, CmdOutputObservation) and obs.exit_code == 0,
f'Failed to save pytest exit code: {str(obs)}',
)
pytest_exit_code = obs.content.strip()
# logger.info(f'Pytest exit code: {pytest_exit_code}')
# Read the test report
action = CmdRunAction(command='cat report.json')
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
# logger.info(obs, extra={'msg_type': 'OBSERVATION'})
assert_and_raise(
isinstance(obs, CmdOutputObservation),
f'Failed to read test report: {str(obs)}',
)
# Get test IDs from instance
repo_name = instance['repo'].split('/')[1]
repo_name = repo_name.replace('.', '-')
action = CmdRunAction(command=f'commit0 get-tests {repo_name}')
action.timeout = 600
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
# logger.info(obs, extra={'msg_type': 'OBSERVATION'})
test_ids = obs.content.strip().split('\n')
try:
report = json.loads(obs.content)
tests = {x['nodeid']: x['call'] for x in report['tests'] if 'call' in x}
# Calculate test statistics
status = []
runtimes = []
no_runs = 0
for test_id in test_ids:
if test_id in tests and tests[test_id] is not None:
status.append(tests[test_id]['outcome'])
runtimes.append(tests[test_id]['duration'])
no_runs += 1
else:
status.append('failed')
runtimes.append(0)
status_counts = Counter(status)
total_runtime = sum(runtimes) if no_runs > 0 else 0
num_passed = status_counts.get('passed', 0) + status_counts.get('xfail', 0)
passed_ratio = num_passed / len(status) if status else 0
eval_result = {
'name': workspace_dir_name,
'sum': total_runtime,
'passed': passed_ratio,
'num_passed': num_passed,
'num_tests': len(test_ids),
}
except json.JSONDecodeError:
logger.error('Failed to parse test report JSON')
eval_result = {
'name': workspace_dir_name,
'sum': 0,
'passed': 0,
'num_passed': 0,
'num_tests': len(test_ids),
}
# Create tarball of workspace
temp_zip = runtime.copy_from(f'/workspace/{workspace_dir_name}')
commit0_dir = os.path.dirname(__file__)
persistent_zip = os.path.join(commit0_dir, f'{workspace_dir_name}.zip')
with open(temp_zip, 'rb') as src, open(persistent_zip, 'wb') as dst:
dst.write(src.read())
zip_file = persistent_zip
return {
'eval_result': eval_result,
'git_patch': git_patch,
'test_output': test_output,
'pytest_exit_code': pytest_exit_code,
'zip_file': zip_file,
}
def process_instance(
instance: pd.Series,
metadata: EvalMetadata,
reset_logger: bool = True,
) -> EvalOutput:
config = get_config(instance, metadata)
# Setup the logger properly, so you can run multi-processing to parallelize the evaluation
if reset_logger:
log_dir = os.path.join(metadata.eval_output_dir, 'infer_logs')
reset_logger_for_multiprocessing(logger, instance.instance_id, log_dir)
else:
logger.info(f'Starting evaluation for instance {instance.instance_id}.')
runtime = create_runtime(config)
call_async_from_sync(runtime.connect)
try:
initialize_runtime(runtime, instance)
instruction = get_instruction(instance, metadata)
# Here's how you can run the agent (similar to the `main` function) and get the final task state
state: State | None = asyncio.run(
run_controller(
config=config,
initial_user_action=MessageAction(content=instruction),
runtime=runtime,
fake_user_response_fn=AGENT_CLS_TO_FAKE_USER_RESPONSE_FN[
metadata.agent_class
],
)
)
# if fatal error, throw EvalError to trigger re-run
if (
state.last_error
and 'fatal error during agent execution' in state.last_error
and 'stuck in a loop' not in state.last_error
):
raise EvalException('Fatal error detected: ' + state.last_error)
# ======= THIS IS Commit0 specific =======
# Get git patch
return_val = complete_runtime(runtime, instance)
eval_result = return_val['eval_result']
git_patch = return_val['git_patch']
test_output = return_val['test_output']
pytest_exit_code = return_val['pytest_exit_code']
zip_file = return_val['zip_file']
repo_name = instance['repo'].split('/')[1]
zip_dest = os.path.join(
metadata.eval_output_dir, 'repos', repo_name, f'{repo_name}.zip'
)
patch_file = os.path.join(
metadata.eval_output_dir, 'repos', repo_name, f'{repo_name}_patch.diff'
)
test_output_file = os.path.join(
metadata.eval_output_dir, 'repos', repo_name, f'{repo_name}_test_output.txt'
)
pytest_exit_code_file = os.path.join(
metadata.eval_output_dir,
'repos',
repo_name,
f'{repo_name}_pytest_exit_code.txt',
)
os.makedirs(os.path.dirname(zip_dest), exist_ok=True)
os.rename(zip_file, zip_dest)
write_targets = [
(patch_file, git_patch),
(test_output_file, test_output),
(pytest_exit_code_file, pytest_exit_code),
]
for write_target in write_targets:
with open(write_target[0], 'w') as f:
f.write(write_target[1])
logger.info(
f'Got evaluation result for repo {instance.instance_id}:\n--------\n{eval_result}\n--------'
)
finally:
runtime.close()
# ==========================================
# ======= Attempt to evaluate the agent's edits =======
# we use eval_infer.sh to evaluate the agent's edits, not here
# because the agent may alter the environment / testcases
test_result = {
'eval_result': eval_result,
}
# If you are working on some simpler benchmark that only evaluates the final model output (e.g., in a MessageAction)
# You can simply get the LAST `MessageAction` from the returned `state.history` and parse it for evaluation.
if state is None:
raise ValueError('State should not be None.')
# NOTE: this is NO LONGER the event stream, but an agent history that includes delegate agent's events
histories = [event_to_dict(event) for event in state.history]
metrics = state.metrics.get() if state.metrics else None
# Save the output
output = EvalOutput(
instance_id=instance.instance_id,
instruction=instruction,
instance=instance.to_dict(),
test_result=test_result,
metadata=metadata,
history=histories,
metrics=metrics,
error=state.last_error if state and state.last_error else None,
)
return output
def commit0_setup(dataset: pd.DataFrame, repo_split: str) -> pd.DataFrame:
"""Setup Commit0 dataset based on split type.
Args:
dataset: Full Commit0 dataset
repo_split: Split type ('all', 'lite' or specific repo name)
Returns:
Filtered dataset based on split type
"""
filtered_dataset = pd.concat(
[
dataset[dataset['repo'].str.split('/').str[1] == repo]
for repo in SPLIT.get(repo_split, [])
]
)
# Drop setup column if it exists
if 'setup' in filtered_dataset.columns:
filtered_dataset = filtered_dataset.drop('setup', axis=1)
# Replace all forward slashes in instance_id with hyphens
filtered_dataset['instance_id'] = filtered_dataset['repo'].str.split('/').str[1]
return filtered_dataset
if __name__ == '__main__':
parser = get_parser()
parser.add_argument(
'--dataset',
type=str,
default='wentingzhao/commit0_combined',
help='dataset to evaluate on, only test split exists for this HF dataset',
)
parser.add_argument(
'--split',
type=str,
default='test',
help='this is the HF dataset split',
)
parser.add_argument(
'--repo-split',
type=str,
default='lite',
help='all, lite, or each repo name',
)
args, _ = parser.parse_known_args()
# NOTE: It is preferable to load datasets from huggingface datasets and perform post-processing
# so we don't need to manage file uploading to OpenHands's repo
dataset = load_dataset(args.dataset, split=args.split)
commit0_datasets = commit0_setup(dataset.to_pandas(), args.repo_split)
logger.info(f'Loaded dataset {args.dataset} with reposplit {args.repo_split}')
llm_config = None
if args.llm_config:
llm_config = get_llm_config_arg(args.llm_config)
llm_config.log_completions = True
if llm_config is None:
raise ValueError(f'Could not find LLM config: --llm_config {args.llm_config}')
details = {}
_agent_cls = openhands.agenthub.Agent.get_cls(args.agent_cls)
dataset_descrption = (
args.dataset.replace('/', '__') + '-' + args.repo_split.replace('/', '__')
)
metadata = make_metadata(
llm_config,
dataset_descrption,
args.agent_cls,
args.max_iterations,
args.eval_note,
args.eval_output_dir,
details=details,
)
output_file = os.path.join(metadata.eval_output_dir, 'output.jsonl')
instances = prepare_dataset(commit0_datasets, output_file, args.eval_n_limit)
run_evaluation(
instances,
metadata,
output_file,
args.eval_num_workers,
process_instance,
timeout_seconds=120 * 60, # 2 hour PER instance should be more than enough
)

View File

@ -0,0 +1,33 @@
#!/bin/bash
# API base URL
BASE_URL="https://runtime.eval.all-hands.dev"
# Get the list of runtimes
response=$(curl --silent --location --request GET "${BASE_URL}/list" \
--header "X-API-Key: ${ALLHANDS_API_KEY}")
n_runtimes=$(echo $response | jq -r '.total')
echo "Found ${n_runtimes} runtimes. Stopping them..."
runtime_ids=$(echo $response | jq -r '.runtimes | .[].runtime_id')
# Function to stop a single runtime
stop_runtime() {
local runtime_id=$1
local counter=$2
echo "Stopping runtime ${counter}/${n_runtimes}: ${runtime_id}"
curl --silent --location --request POST "${BASE_URL}/stop" \
--header "X-API-Key: ${ALLHANDS_API_KEY}" \
--header "Content-Type: application/json" \
--data-raw "{\"runtime_id\": \"${runtime_id}\"}"
echo
}
export -f stop_runtime
export BASE_URL ALLHANDS_API_KEY n_runtimes
# Use GNU Parallel to stop runtimes in parallel
echo "$runtime_ids" | parallel -j 16 --progress stop_runtime {} {#}
echo "All runtimes have been stopped."

View File

@ -0,0 +1,125 @@
#!/bin/bash
set -eo pipefail
source "evaluation/utils/version_control.sh"
REPO_SPLIT=$1
MODEL_CONFIG=$2
COMMIT_HASH=$3
AGENT=$4
EVAL_LIMIT=$5
MAX_ITER=$6
NUM_WORKERS=$7
DATASET=$8
SPLIT=$9
N_RUNS=${10}
if [ -z "$NUM_WORKERS" ]; then
NUM_WORKERS=1
echo "Number of workers not specified, use default $NUM_WORKERS"
fi
checkout_eval_branch
if [ -z "$AGENT" ]; then
echo "Agent not specified, use default CodeActAgent"
AGENT="CodeActAgent"
fi
if [ -z "$MAX_ITER" ]; then
echo "MAX_ITER not specified, use default 100"
MAX_ITER=100
fi
if [ -z "$USE_INSTANCE_IMAGE" ]; then
echo "USE_INSTANCE_IMAGE not specified, use default true"
USE_INSTANCE_IMAGE=true
fi
if [ -z "$RUN_WITH_BROWSING" ]; then
echo "RUN_WITH_BROWSING not specified, use default false"
RUN_WITH_BROWSING=false
fi
if [ -z "$DATASET" ]; then
echo "DATASET not specified, use default wentingzhao/commit0_combined"
DATASET="wentingzhao/commit0_combined"
fi
if [ -z "$REPO_SPLIT" ]; then
echo "REPO_SPLIT not specified, use default lite"
REPO_SPLIT=0
fi
if [ -z "$SPLIT" ]; then
echo "HF SPLIT not specified, use default test"
SPLIT="test"
fi
export USE_INSTANCE_IMAGE=$USE_INSTANCE_IMAGE
echo "USE_INSTANCE_IMAGE: $USE_INSTANCE_IMAGE"
export RUN_WITH_BROWSING=$RUN_WITH_BROWSING
echo "RUN_WITH_BROWSING: $RUN_WITH_BROWSING"
get_agent_version
echo "AGENT: $AGENT"
echo "AGENT_VERSION: $AGENT_VERSION"
echo "MODEL_CONFIG: $MODEL_CONFIG"
echo "DATASET: $DATASET"
echo "HF SPLIT: $SPLIT"
echo "REPO SPLIT: $REPO_SPLIT"
# Default to NOT use Hint
if [ -z "$USE_HINT_TEXT" ]; then
export USE_HINT_TEXT=false
fi
echo "USE_HINT_TEXT: $USE_HINT_TEXT"
EVAL_NOTE="$AGENT_VERSION"
# if not using Hint, add -no-hint to the eval note
if [ "$USE_HINT_TEXT" = false ]; then
EVAL_NOTE="$EVAL_NOTE-no-hint"
fi
if [ "$RUN_WITH_BROWSING" = true ]; then
EVAL_NOTE="$EVAL_NOTE-with-browsing"
fi
if [ -n "$EXP_NAME" ]; then
EVAL_NOTE="$EVAL_NOTE-$EXP_NAME"
fi
function run_eval() {
local eval_note=$1
COMMAND="poetry run python evaluation/commit0_bench/run_infer.py \
--agent-cls $AGENT \
--llm-config $MODEL_CONFIG \
--max-iterations $MAX_ITER \
--eval-num-workers $NUM_WORKERS \
--eval-note $eval_note \
--dataset $DATASET \
--split $SPLIT \
--repo-split $REPO_SPLIT"
if [ -n "$EVAL_LIMIT" ]; then
echo "EVAL_LIMIT: $EVAL_LIMIT"
COMMAND="$COMMAND --eval-n-limit $EVAL_LIMIT"
fi
# Run the command
eval $COMMAND
}
unset SANDBOX_ENV_GITHUB_TOKEN # prevent the agent from using the github token to push
if [ -z "$N_RUNS" ]; then
N_RUNS=1
echo "N_RUNS not specified, use default $N_RUNS"
fi
for i in $(seq 1 $N_RUNS); do
current_eval_note="$EVAL_NOTE-run_$i"
echo "EVAL_NOTE: $current_eval_note"
run_eval $current_eval_note
done
checkout_original_branch

2127
poetry.lock generated

File diff suppressed because it is too large Load Diff

View File

@ -60,7 +60,7 @@ whatthepatch = "^1.0.6"
protobuf = "^4.21.6,<5.0.0" # chromadb currently fails on 5.0+
opentelemetry-api = "1.25.0"
opentelemetry-exporter-otlp-proto-grpc = "1.25.0"
modal = "^0.64.145"
modal = "^0.66.26"
runloop-api-client = "0.7.0"
pygithub = "^2.5.0"
openhands-aci = "^0.1.1"
@ -95,6 +95,7 @@ reportlab = "*"
[tool.coverage.run]
concurrency = ["gevent"]
[tool.poetry.group.runtime.dependencies]
jupyterlab = "*"
notebook = "*"
@ -125,12 +126,14 @@ ignore = ["D1"]
[tool.ruff.lint.pydocstyle]
convention = "google"
[tool.poetry.group.evaluation.dependencies]
streamlit = "*"
whatthepatch = "*"
retry = "*"
evaluate = "*"
swebench = { git = "https://github.com/All-Hands-AI/SWE-bench.git" }
commit0 = "*"
func_timeout = "*"
sympy = "*"
gdown = "*"