integrate LocAgent into OpenHands (#7371)

Co-authored-by: czlll <gangda@huaihe.usc.edu>
Co-authored-by: Hoang Tran <descience.thh10@gmail.com>
This commit is contained in:
Zhaoling Chen 2025-05-23 23:42:58 +08:00 committed by GitHub
parent fa5b52298e
commit efe287ce34
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TASK_INSTRUECTION="""
Given the following GitHub problem description, your objective is to localize the specific files, classes or functions, and lines of code that need modification or contain key information to resolve the issue.
Follow these steps to localize the issue:
## Step 1: Categorize and Extract Key Problem Information
- Classify the problem statement into the following categories:
Problem description, error trace, code to reproduce the bug, and additional context.
- Identify modules in the '{package_name}' package mentioned in each category.
- Use extracted keywords and line numbers to search for relevant code references for additional context.
## Step 2: Locate Referenced Modules
- Accurately determine specific modules
- Explore the repo to familiarize yourself with its structure.
- Analyze the described execution flow to identify specific modules or components being referenced.
- Pay special attention to distinguishing between modules with similar names using context and described execution flow.
- Output Format for collected relevant modules:
- Use the format: 'file_path:QualifiedName'
- E.g., for a function `calculate_sum` in the `MathUtils` class located in `src/helpers/math_helpers.py`, represent it as: 'src/helpers/math_helpers.py:MathUtils.calculate_sum'.
## Step 3: Analyze and Reproducing the Problem
- Clarify the Purpose of the Issue
- If expanding capabilities: Identify where and how to incorporate new behavior, fields, or modules.
- If addressing unexpected behavior: Focus on localizing modules containing potential bugs.
- Reconstruct the execution flow
- Identify main entry points triggering the issue.
- Trace function calls, class interactions, and sequences of events.
- Identify potential breakpoints causing the issue.
Important: Keep the reconstructed flow focused on the problem, avoiding irrelevant details.
## Step 4: Locate Areas for Modification
- Locate specific files, functions, or lines of code requiring changes or containing critical information for resolving the issue.
- Consider upstream and downstream dependencies that may affect or be affected by the issue.
- If applicable, identify where to introduce new fields, functions, or variables.
- Think Thoroughly: List multiple potential solutions and consider edge cases that could impact the resolution.
## Output Format for Final Results:
Your final output should list the locations requiring modification, wrapped with triple backticks ```
Each location should include the file path, class name (if applicable), function name, or line numbers, ordered by importance.
Your answer would better include about 5 files.
### Examples:
```
full_path1/file1.py
line: 10
class: MyClass1
function: my_function1
full_path2/file2.py
line: 76
function: MyClass2.my_function2
full_path3/file3.py
line: 24
line: 156
function: my_function3
```
Return just the location(s)
Note: Your thinking should be thorough and so it's fine if it's very long.
"""
FAKE_USER_MSG_FOR_LOC = (
'Verify if the found locations contain all the necessary information to address the issue, and check for any relevant references in other parts of the codebase that may not have appeared in the search results. '
'If not, continue searching for additional locations related to the issue.\n'
'Verify that you have carefully analyzed the impact of the found locations on the repository, especially their dependencies. '
'If you think you have solved the task, please send your final answer (including the former answer and reranking) to user through message and then call `finish` to finish.\n'
'IMPORTANT: YOU SHOULD NEVER ASK FOR HUMAN HELP.\n'
)

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import asyncio
import json
import os
import tempfile
from typing import Any
import pandas as pd
import toml
from datasets import load_dataset
import openhands.agenthub
from evaluation.benchmarks.swe_bench.resource.mapping import (
get_instance_resource_factor,
)
from evaluation.utils.shared import (
EvalException,
EvalMetadata,
EvalOutput,
assert_and_raise,
codeact_user_response,
get_default_sandbox_config_for_eval,
get_metrics,
is_fatal_evaluation_error,
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,
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'
RUN_WITH_BROWSING = os.environ.get('RUN_WITH_BROWSING', 'false').lower() == 'true'
INDEX_BASE_DIR = os.environ.get('INDEX_BASE_DIR', '')
AGENT_CLS_TO_FAKE_USER_RESPONSE_FN = {
'CodeActAgent': codeact_user_response,
'LocAgent': codeact_user_response,
}
def _get_swebench_workspace_dir_name(instance: pd.Series) -> str:
return f'{instance.repo}__{instance.version}'.replace('/', '__')
def get_instruction(instance: pd.Series, metadata: EvalMetadata):
workspace_dir_name = _get_swebench_workspace_dir_name(instance)
instruction = f"""
Consider the following issue description:
<issue_description>
{instance.problem_statement}
</issue_description>
Your objective is to localize the specific files, classes or functions, and lines of code that need modification or contain key information to resolve the issue.
Follow these steps to localize the issue:
## Step 1: Categorize and Extract Key Problem Information
- Classify the problem statement into the following categories:
Problem description, error trace, code to reproduce the bug, and additional context.
- Identify modules in the "{instance.instance_id.split('_')[0]}" package mentioned in each category.
- Use extracted keywords and line numbers to search for relevant code references for additional context.
## Step 2: Locate Referenced Modules
- Accurately determine specific modules
- Explore the repo to familiarize yourself with its structure.
- Analyze the described execution flow to identify specific modules or components being referenced.
- Pay special attention to distinguishing between modules with similar names using context and described execution flow.
- Output Format for collected relevant modules:
- Use the format: 'file_path:QualifiedName'
- E.g., for a function `calculate_sum` in the `MathUtils` class located in `src/helpers/math_helpers.py`, represent it as: 'src/helpers/math_helpers.py:MathUtils.calculate_sum'.
## Step 3: Analyze and Reproducing the Problem
- Clarify the Purpose of the Issue
- If expanding capabilities: Identify where and how to incorporate new behavior, fields, or modules.
- If addressing unexpected behavior: Focus on localizing modules containing potential bugs.
- Reconstruct the execution flow
- Identify main entry points triggering the issue.
- Trace function calls, class interactions, and sequences of events.
- Identify potential breakpoints causing the issue.
Important: Keep the reconstructed flow focused on the problem, avoiding irrelevant details.
## Step 4: Locate Areas for Modification
- Locate specific files, functions, or lines of code requiring changes or containing critical information for resolving the issue.
- Consider upstream and downstream dependencies that may affect or be affected by the issue.
- If applicable, identify where to introduce new fields, functions, or variables.
- Think Thoroughly: List multiple potential solutions and consider edge cases that could impact the resolution.
## Output Format for Final Results:
Your final output should list the locations requiring modification, wrapped with triple backticks ```
Each location should include the file path, class name (if applicable), function name, or line numbers, ordered by importance.
Your answer would better include about 5 files.
### Examples:
```
full_path1/file1.py
line: 10
class: MyClass1
function: my_function1
full_path2/file2.py
line: 76
function: MyClass2.my_function2
full_path3/file3.py
line: 24
line: 156
function: my_function3
```
Return just the location(s)
Note: Your thinking should be thorough and so it's fine if it's very long.
"""
instruction += (
'IMPORTANT: You should ONLY interact with the environment provided to you AND NEVER ASK FOR HUMAN HELP.\n'
"Don't include any lambda functions!\n"
'You should NOT modify any files!\n'
)
if RUN_WITH_BROWSING:
instruction += """
<IMPORTANT!>
You SHOULD NEVER attempt to browse the web.
</IMPORTANT!>
"""
return instruction
# TODO: migrate all swe-bench docker to ghcr.io/openhands
DEFAULT_DOCKER_IMAGE_PREFIX = os.environ.get(
'EVAL_DOCKER_IMAGE_PREFIX', 'docker.io/xingyaoww/'
)
logger.info(f'Default docker image prefix: {DEFAULT_DOCKER_IMAGE_PREFIX}')
def get_instance_docker_image(instance_id: str, official_image: bool = False) -> str:
if official_image:
# Official SWE-Bench image
# swebench/sweb.eval.x86_64.django_1776_django-11333:v1
docker_image_prefix = 'docker.io/swebench/'
repo, name = instance_id.split('__')
image_name = f'sweb.eval.x86_64.{repo}_1776_{name}:latest'
logger.warning(f'Using official SWE-Bench image: {image_name}')
else:
# OpenHands version of the image
docker_image_prefix = DEFAULT_DOCKER_IMAGE_PREFIX
image_name = 'sweb.eval.x86_64.' + instance_id
image_name = image_name.replace(
'__', '_s_'
) # to comply with docker image naming convention
return (docker_image_prefix.rstrip('/') + '/' + image_name).lower()
def get_config(
instance: pd.Series,
metadata: EvalMetadata,
) -> AppConfig:
# We use a different instance image for the each instance of swe-bench eval
use_official_image = bool(
'verified' in metadata.dataset.lower() or 'lite' in metadata.dataset.lower()
)
base_container_image = get_instance_docker_image(
instance['instance_id'], use_official_image
)
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.'
)
sandbox_config = get_default_sandbox_config_for_eval()
sandbox_config.base_container_image = base_container_image
sandbox_config.enable_auto_lint = True
sandbox_config.use_host_network = False
# Add platform to the sandbox config to solve issue 4401
sandbox_config.platform = 'linux/amd64'
sandbox_config.remote_runtime_resource_factor = get_instance_resource_factor(
dataset_name=metadata.dataset,
instance_id=instance['instance_id'],
)
workspace_dir_name = _get_swebench_workspace_dir_name(instance)
sandbox_config.runtime_startup_env_vars = {
'REPO_PATH': f'/workspace/{workspace_dir_name}/',
}
config = AppConfig(
default_agent=metadata.agent_class,
run_as_openhands=False,
max_iterations=metadata.max_iterations,
runtime=os.environ.get('RUNTIME', 'docker'),
sandbox=sandbox_config,
# 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(
enable_jupyter=False,
enable_browsing=RUN_WITH_BROWSING,
enable_llm_editor=False,
condenser=metadata.condenser_config,
enable_prompt_extensions=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_swebench_workspace_dir_name(instance)
obs: CmdOutputObservation
# Set instance id
action = CmdRunAction(
command=f"""echo 'export SWE_INSTANCE_ID={instance['instance_id']}' >> ~/.bashrc && echo 'export PIP_CACHE_DIR=~/.cache/pip' >> ~/.bashrc && echo "alias git='git --no-pager'" >> ~/.bashrc"""
)
action.set_hard_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 export SWE_INSTANCE_ID: {str(obs)}'
)
action = CmdRunAction(command="""export USER=$(whoami); echo USER=${USER} """)
action.set_hard_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 export USER: {str(obs)}')
# inject the init script
script_dir = os.path.dirname(__file__)
# inject the instance info
action = CmdRunAction(command='mkdir -p /swe_util/eval_data/instances')
action.set_hard_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 create /swe_util/eval_data/instances: {str(obs)}',
)
swe_instance_json_name = 'swe-bench-instance.json'
with tempfile.TemporaryDirectory() as temp_dir:
# Construct the full path for the desired file name within the temporary directory
temp_file_path = os.path.join(temp_dir, swe_instance_json_name)
# Write to the file with the desired name within the temporary directory
with open(temp_file_path, 'w') as f:
if not isinstance(instance, dict):
json.dump([instance.to_dict()], f)
else:
json.dump([instance], f)
# Copy the file to the desired location
runtime.copy_to(temp_file_path, '/swe_util/eval_data/instances/')
# inject the instance swe entry
runtime.copy_to(
str(os.path.join(script_dir, 'scripts/setup/instance_swe_entry.sh')),
'/swe_util/',
)
action = CmdRunAction(command='cat ~/.bashrc')
action.set_hard_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 cat ~/.bashrc: {str(obs)}')
action = CmdRunAction(command='source ~/.bashrc')
action.set_hard_timeout(600)
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
if isinstance(obs, ErrorObservation):
logger.error(f'Failed to source ~/.bashrc: {str(obs)}')
assert_and_raise(obs.exit_code == 0, f'Failed to source ~/.bashrc: {str(obs)}')
action = CmdRunAction(command='source /swe_util/instance_swe_entry.sh')
action.set_hard_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 source /swe_util/instance_swe_entry.sh: {str(obs)}',
)
action = CmdRunAction(command=f'cd /workspace/{workspace_dir_name}')
action.set_hard_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 reset --hard')
action.set_hard_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 reset --hard: {str(obs)}')
action = CmdRunAction(
command='for remote_name in $(git remote); do git remote remove "${remote_name}"; done'
)
action.set_hard_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 remove git remotes: {str(obs)}')
# Copy the processed indexes if available
action = CmdRunAction(command='mkdir _index_data/graph_index_v2.3')
obs = runtime.run_action(action)
# Check if an existing graph index file is available
graph_index_file_path = os.path.join(
INDEX_BASE_DIR, 'graph_index_v2.3', f"{instance['instance_id']}.pkl"
)
if INDEX_BASE_DIR and os.path.exists(graph_index_file_path):
logger.info(
f"Copying graph index from {graph_index_file_path} to /workspace/{workspace_dir_name}/_index_data/graph_index_v2.3"
)
runtime.copy_to(
graph_index_file_path,
f'/workspace/{workspace_dir_name}/_index_data/graph_index_v2.3',
)
action = CmdRunAction(
command=f'mv _index_data/graph_index_v2.3/{instance["instance_id"]}.pkl _index_data/graph_index_v2.3/code_graph.pkl'
)
obs = runtime.run_action(action)
bm25_index_dir = os.path.join(INDEX_BASE_DIR, 'BM25_index', instance['instance_id'])
runtime.copy_to(
bm25_index_dir, f'/workspace/{workspace_dir_name}/_index_data', recursive=True
)
action = CmdRunAction(
command=f'mv _index_data/{instance["instance_id"]} _index_data/bm25_index'
)
action.set_hard_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 mv file: {str(obs)}')
action = CmdRunAction(command='which python')
action.set_hard_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 and 'testbed' in obs.content,
f'Expected to find python interpreter from testbed, but got: {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_swebench_workspace_dir_name(instance)
action = CmdRunAction(command=f'cd /workspace/{workspace_dir_name}')
action.set_hard_timeout(600)
logger.info(action, extra={'msg_type': 'ACTION'})
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
if obs.exit_code == -1:
# The previous command is still running
# We need to kill previous command
logger.info('The previous command is still running, trying to kill it...')
action = CmdRunAction(command='C-c')
obs = runtime.run_action(action)
logger.info(obs, extra={'msg_type': 'OBSERVATION'})
# Then run the command again
action = CmdRunAction(command=f'cd /workspace/{workspace_dir_name}')
action.set_hard_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 cd to /workspace/{workspace_dir_name}: {str(obs)}',
)
action = CmdRunAction(command='git config --global core.pager ""')
action.set_hard_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 config --global core.pager "": {str(obs)}',
)
# First check for any git repositories in subdirectories
action = CmdRunAction(command='find . -type d -name .git -not -path "./.git"')
action.set_hard_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 find git repositories: {str(obs)}',
)
git_dirs = [p for p in obs.content.strip().split('\n') if p]
if git_dirs:
# Remove all .git directories in subdirectories
for git_dir in git_dirs:
action = CmdRunAction(command=f'rm -rf "{git_dir}"')
action.set_hard_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 remove git directory {git_dir}: {str(obs)}',
)
# add all files
action = CmdRunAction(command='git add -A')
action.set_hard_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)}',
)
n_retries = 0
git_patch = None
while n_retries < 5:
action = CmdRunAction(
command=f'git diff --no-color --cached {instance["base_commit"]}'
)
action.set_hard_timeout(max(300 + 100 * n_retries, 600))
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)')
logger.info('-' * 30)
logger.info('END Runtime Completion Fn')
logger.info('-' * 30)
return {'git_patch': git_patch}
def process_instance(
instance: pd.Series,
metadata: EvalMetadata,
reset_logger: bool = True,
runtime_failure_count: int = 0,
) -> 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}.')
# Increase resource_factor with increasing attempt_id
if runtime_failure_count > 0:
config.sandbox.remote_runtime_resource_factor = min(
config.sandbox.remote_runtime_resource_factor * (2**runtime_failure_count),
8,
)
logger.warning(
f'This is the {runtime_failure_count + 1}th attempt for instance {instance.instance_id}, setting resource factor to {config.sandbox.remote_runtime_resource_factor}'
)
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 is_fatal_evaluation_error(state.last_error):
raise EvalException('Fatal error detected: ' + state.last_error)
# ======= THIS IS SWE-Bench specific =======
# Get git patch
return_val = complete_runtime(runtime, instance)
git_patch = return_val['git_patch']
logger.info(
f'Got git diff for instance {instance.instance_id}:\n--------\n{git_patch}\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 = {
'git_patch': git_patch,
}
# 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 = get_metrics(state)
# Save the output
output = EvalOutput(
instance_id=instance.instance_id,
instruction=instruction,
instance=instance.to_dict(), # SWE Bench specific
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 filter_dataset(dataset: pd.DataFrame, filter_column: str) -> pd.DataFrame:
file_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'config.toml')
if os.path.exists(file_path):
with open(file_path, 'r') as file:
data = toml.load(file)
if 'selected_ids' in data:
selected_ids = data['selected_ids']
logger.info(
f'Filtering {len(selected_ids)} tasks from "selected_ids"...'
)
subset = dataset[dataset[filter_column].isin(selected_ids)]
logger.info(f'Retained {subset.shape[0]} tasks after filtering')
return subset
skip_ids = os.environ.get('SKIP_IDS', '').split(',')
if len(skip_ids) > 0:
logger.info(f'Filtering {len(skip_ids)} tasks from "SKIP_IDS"...')
return dataset[~dataset[filter_column].isin(skip_ids)]
return dataset
# A list of instances that are known to be tricky to infer
# (will cause runtime failure even with resource factor = 8)
SWEGYM_EXCLUDE_IDS = [
'dask__dask-10422',
'pandas-dev__pandas-50548',
'pandas-dev__pandas-53672',
'pandas-dev__pandas-54174',
'pandas-dev__pandas-55518',
'pandas-dev__pandas-58383',
'pydata__xarray-6721',
'pytest-dev__pytest-10081',
'pytest-dev__pytest-7236',
]
if __name__ == '__main__':
parser = get_parser()
parser.add_argument(
'--dataset',
type=str,
default='princeton-nlp/SWE-bench',
help='data set to evaluate on, either full-test or lite-test',
)
parser.add_argument(
'--split',
type=str,
default='test',
help='split to evaluate on',
)
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)
swe_bench_tests = filter_dataset(dataset.to_pandas(), 'instance_id')
logger.info(
f'Loaded dataset {args.dataset} with split {args.split}: {len(swe_bench_tests)} tasks'
)
if 'SWE-Gym' in args.dataset:
swe_bench_tests = swe_bench_tests[
~swe_bench_tests['instance_id'].isin(SWEGYM_EXCLUDE_IDS)
]
logger.info(
f'{len(swe_bench_tests)} tasks left after excluding SWE-Gym excluded tasks'
)
llm_config = None
if args.llm_config:
llm_config = get_llm_config_arg(args.llm_config)
llm_config.log_completions = True
# modify_params must be False for evaluation purpose, for reproducibility and accurancy of results
llm_config.modify_params = False
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.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')
print(f'### OUTPUT FILE: {output_file} ###')
instances = prepare_dataset(swe_bench_tests, output_file, args.eval_n_limit)
if len(instances) > 0 and not isinstance(
instances['PASS_TO_PASS'][instances['PASS_TO_PASS'].index[0]], str
):
for col in ['PASS_TO_PASS', 'FAIL_TO_PASS']:
instances[col] = instances[col].apply(lambda x: str(x))
run_evaluation(
instances,
metadata,
output_file,
args.eval_num_workers,
process_instance,
timeout_seconds=8 * 60 * 60, # 8 hour PER instance should be more than enough
max_retries=5,
)

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@ -0,0 +1,117 @@
#!/usr/bin/env bash
set -eo pipefail
source "evaluation/utils/version_control.sh"
MODEL_CONFIG=$1
COMMIT_HASH=$2
AGENT=$3
EVAL_LIMIT=$4
MAX_ITER=$5
NUM_WORKERS=$6
DATASET=$7
SPLIT=$8
N_RUNS=$9
if [ -z "$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 "$MAX_ITER" ]; then
echo "MAX_ITER not specified, use default 100"
MAX_ITER=100
fi
if [ -z "$RUN_WITH_BROWSING" ]; then
echo "RUN_WITH_BROWSING not specified, use default false"
RUN_WITH_BROWSING=false
fi
if [ -z "$DATASET" ]; then
echo "DATASET not specified, use default princeton-nlp/SWE-bench_Lite"
DATASET="princeton-nlp/SWE-bench_Lite"
fi
if [ -z "$SPLIT" ]; then
echo "SPLIT not specified, use default test"
SPLIT="test"
fi
export RUN_WITH_BROWSING=$RUN_WITH_BROWSING
echo "RUN_WITH_BROWSING: $RUN_WITH_BROWSING"
get_openhands_version
echo "AGENT: $AGENT"
echo "OPENHANDS_VERSION: $OPENHANDS_VERSION"
echo "MODEL_CONFIG: $MODEL_CONFIG"
echo "DATASET: $DATASET"
echo "SPLIT: $SPLIT"
# Default to NOT use Hint
if [ -z "$USE_HINT_TEXT" ]; then
export USE_HINT_TEXT=false
fi
echo "USE_HINT_TEXT: $USE_HINT_TEXT"
EVAL_NOTE="$OPENHANDS_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/benchmarks/swe_bench/run_localize.py \
--agent-cls $AGENT \
--llm-config $MODEL_CONFIG \
--max-iterations $MAX_ITER \
--eval-num-workers $NUM_WORKERS \
--eval-note $eval_note \
--dataset $DATASET \
--split $SPLIT"
if [ -n "$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 $N_RUNS"
fi
# Skip runs if the run number is in the SKIP_RUNS list
# read from env variable SKIP_RUNS as a comma separated list of run numbers
SKIP_RUNS=(${SKIP_RUNS//,/ })
for i in $(seq 1 $N_RUNS); do
if [[ " ${SKIP_RUNS[@]} " =~ " $i " ]]; then
echo "Skipping run $i"
continue
fi
current_eval_note="$EVAL_NOTE-run_$i"
echo "EVAL_NOTE: $current_eval_note"
run_eval $current_eval_note
done
checkout_original_branch

View File

@ -7,6 +7,7 @@ from openhands.agenthub import ( # noqa: E402
browsing_agent,
codeact_agent,
dummy_agent,
loc_agent,
readonly_agent,
visualbrowsing_agent,
)
@ -19,4 +20,5 @@ __all__ = [
'browsing_agent',
'visualbrowsing_agent',
'readonly_agent',
'loc_agent',
]

View File

@ -266,5 +266,5 @@ class CodeActAgent(Agent):
def response_to_actions(self, response: 'ModelResponse') -> list['Action']:
return codeact_function_calling.response_to_actions(
response, mcp_tool_names=list(self.mcp_tools.keys())
response, mcp_tool_names=list(self.mcp_tools.keys()),
)

View File

@ -0,0 +1,14 @@
# LocAgent Framework
This folder is an implementation of Locagent. It is based on ([LocAgent](https://arxiv.org/abs/2503.09089), [tweet](https://x.com/XiangruTang/status/1900392655009333338)), a framework that addresses code localization through graph-based representation. By parsing codebases into directed heterogeneous graphs, LocAgent creates a lightweight representation that captures code structures and their dependencies, enabling LLM agents to effectively search and locate relevant entities through powerful multi-hop reasoning.
<!-- ## Overview -->
## Built-in Tools
The agent provides several built-in tools:
1. `search_code_snippets`
2. `get_entity_contents`
3. `explore_tree_structure`

View File

@ -0,0 +1,4 @@
from openhands.agenthub.loc_agent.loc_agent import LocAgent
from openhands.controller.agent import Agent
Agent.register('LocAgent', LocAgent)

View File

@ -0,0 +1,126 @@
"""This file contains the function calling implementation for different actions.
This is similar to the functionality of `CodeActResponseParser`.
"""
import json
from litellm import (
ChatCompletionToolParam,
ModelResponse,
)
from openhands.agenthub.codeact_agent.tools import FinishTool
from openhands.agenthub.codeact_agent.function_calling import combine_thought
from openhands.agenthub.loc_agent.tools import (
SearchEntityTool,
SearchRepoTool,
create_explore_tree_structure_tool,
)
from openhands.core.exceptions import (
FunctionCallNotExistsError,
)
from openhands.core.logger import openhands_logger as logger
from openhands.events.action import (
Action,
AgentFinishAction,
IPythonRunCellAction,
MessageAction,
)
from openhands.events.tool import ToolCallMetadata
def response_to_actions(
response: ModelResponse, mcp_tool_names: list[str] | None = None,
) -> list[Action]:
actions: list[Action] = []
assert len(response.choices) == 1, 'Only one choice is supported for now'
choice = response.choices[0]
assistant_msg = choice.message
if hasattr(assistant_msg, 'tool_calls') and assistant_msg.tool_calls:
# Check if there's assistant_msg.content. If so, add it to the thought
thought = ''
if isinstance(assistant_msg.content, str):
thought = assistant_msg.content
elif isinstance(assistant_msg.content, list):
for msg in assistant_msg.content:
if msg['type'] == 'text':
thought += msg['text']
# Process each tool call to OpenHands action
for i, tool_call in enumerate(assistant_msg.tool_calls):
action: Action
logger.debug(f'Tool call in function_calling.py: {tool_call}')
try:
arguments = json.loads(tool_call.function.arguments)
except json.decoder.JSONDecodeError as e:
raise RuntimeError(
f'Failed to parse tool call arguments: {tool_call.function.arguments}'
) from e
# ================================================
# LocAgent's Tools
# ================================================
ALL_FUNCTIONS = [
'explore_tree_structure',
'search_code_snippets',
'get_entity_contents',
]
if tool_call.function.name in ALL_FUNCTIONS:
# We implement this in agent_skills, which can be used via Jupyter
func_name = tool_call.function.name
code = f'print({func_name}(**{arguments}))'
logger.debug(f'TOOL CALL: {func_name} with code: {code}')
action = IPythonRunCellAction(code=code)
# ================================================
# AgentFinishAction
# ================================================
elif tool_call.function.name == FinishTool['function']['name']:
action = AgentFinishAction(
final_thought=arguments.get('message', ''),
task_completed=arguments.get('task_completed', None),
)
else:
raise FunctionCallNotExistsError(
f'Tool {tool_call.function.name} is not registered. (arguments: {arguments}). Please check the tool name and retry with an existing tool.'
)
# We only add thought to the first action
if i == 0:
action = combine_thought(action, thought)
# Add metadata for tool calling
action.tool_call_metadata = ToolCallMetadata(
tool_call_id=tool_call.id,
function_name=tool_call.function.name,
model_response=response,
total_calls_in_response=len(assistant_msg.tool_calls),
)
actions.append(action)
else:
actions.append(
MessageAction(
content=str(assistant_msg.content) if assistant_msg.content else '',
wait_for_response=True,
)
)
# Add response id to actions
# This will ensure we can match both actions without tool calls (e.g. MessageAction)
# and actions with tool calls (e.g. CmdRunAction, IPythonRunCellAction, etc.)
# with the token usage data
for action in actions:
action.response_id = response.id
assert len(actions) >= 1
return actions
def get_tools() -> list[ChatCompletionToolParam]:
tools = [FinishTool]
tools.append(SearchRepoTool)
tools.append(SearchEntityTool)
tools.append(create_explore_tree_structure_tool(use_simplified_description=True))
return tools

View File

@ -0,0 +1,39 @@
from openhands.agenthub.codeact_agent import CodeActAgent
import openhands.agenthub.loc_agent.function_calling as locagent_function_calling
from openhands.core.config import AgentConfig
from openhands.core.logger import openhands_logger as logger
from openhands.llm.llm import LLM
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from openhands.events.action import Action
from openhands.llm.llm import ModelResponse
class LocAgent(CodeActAgent):
VERSION = '1.0'
def __init__(
self,
llm: LLM,
config: AgentConfig,
) -> None:
"""Initializes a new instance of the LocAgent class.
Parameters:
- llm (LLM): The llm to be used by this agent
- config (AgentConfig): The configuration for the agent
"""
super().__init__(llm, config)
self.tools = locagent_function_calling.get_tools()
logger.debug(
f'TOOLS loaded for LocAgent: {", ".join([tool.get("function").get("name") for tool in self.tools])}'
)
def response_to_actions(self, response: 'ModelResponse') -> list['Action']:
return locagent_function_calling.response_to_actions(
response, mcp_tool_names=list(self.mcp_tools.keys()),
)

View File

@ -0,0 +1,8 @@
from .explore_structure import create_explore_tree_structure_tool
from .search_content import SearchEntityTool, SearchRepoTool
__all__ = [
'SearchEntityTool',
'SearchRepoTool',
'create_explore_tree_structure_tool',
]

View File

@ -0,0 +1,185 @@
from litellm import (
ChatCompletionToolParam,
ChatCompletionToolParamFunctionChunk,
)
_SIMPLIFIED_STRUCTURE_EXPLORER_DESCRIPTION = """
A unified tool that traverses a pre-built code graph to retrieve dependency structure around specified entities,
with options to explore upstream or downstream, and control traversal depth and filters for entity and dependency types.
"""
_SIMPLIFIED_TREE_EXAMPLE = """
Example Usage:
1. Exploring Downstream Dependencies:
```
explore_tree_structure(
start_entities=['src/module_a.py:ClassA'],
direction='downstream',
traversal_depth=2,
dependency_type_filter=['invokes', 'imports']
)
```
2. Exploring the repository structure from the root directory (/) up to two levels deep:
```
explore_tree_structure(
start_entities=['/'],
traversal_depth=2,
dependency_type_filter=['contains']
)
```
3. Generate Class Diagrams:
```
explore_tree_structure(
start_entities=selected_entity_ids,
direction='both',
traverse_depth=-1,
dependency_type_filter=['inherits']
)
```
"""
_DETAILED_STRUCTURE_EXPLORER_DESCRIPTION = """
Unified repository exploring tool that traverses a pre-built code graph to retrieve dependency structure around specified entities.
The search can be controlled to traverse upstream (exploring dependencies that entities rely on) or downstream (exploring how entities impact others), with optional limits on traversal depth and filters for entity and dependency types.
Code Graph Definition:
* Entity Types: 'directory', 'file', 'class', 'function'.
* Dependency Types: 'contains', 'imports', 'invokes', 'inherits'.
* Hierarchy:
- Directories contain files and subdirectories.
- Files contain classes and functions.
- Classes contain inner classes and methods.
- Functions can contain inner functions.
* Interactions:
- Files/classes/functions can import classes and functions.
- Classes can inherit from other classes.
- Classes and functions can invoke others (invocations in a class's `__init__` are attributed to the class).
Entity ID:
* Unique identifier including file path and module path.
* Here's an example of an Entity ID: `"interface/C.py:C.method_a.inner_func"` identifies function `inner_func` within `method_a` of class `C` in `"interface/C.py"`.
Notes:
* Traversal Control: The `traversal_depth` parameter specifies how deep the function should explore the graph starting from the input entities.
* Filtering: Use `entity_type_filter` and `dependency_type_filter` to narrow down the scope of the search, focusing on specific entity types and relationships.
"""
_DETAILED_TREE_EXAMPLE = """
Example Usage:
1. Exploring Outward Dependencies:
```
explore_tree_structure(
start_entities=['src/module_a.py:ClassA'],
direction='downstream',
traversal_depth=2,
dependency_type_filter=['invokes', 'imports']
)
```
This retrieves the dependencies of `ClassA` up to 2 levels deep, focusing only on classes and functions with 'invokes' and 'imports' relationships.
2. Exploring Inward Dependencies:
```
explore_tree_structure(
start_entities=['src/module_b.py:FunctionY'],
direction='upstream',
traversal_depth=-1
)
```
This finds all entities that depend on `FunctionY` without restricting the traversal depth.
3. Exploring Repository Structure:
```
explore_tree_structure(
start_entities=['/'],
traversal_depth=2,
dependency_type_filter=['contains']
)
```
This retrieves the tree repository structure from the root directory (/), traversing up to two levels deep and focusing only on 'contains' relationship.
4. Generate Class Diagrams:
```
explore_tree_structure(
start_entities=selected_entity_ids,
direction='both',
traverse_depth=-1,
dependency_type_filter=['inherits']
)
```
"""
_STRUCTURE_EXPLORER_PARAMETERS = {
'type': 'object',
'properties': {
'start_entities': {
'description': (
'List of entities (e.g., class, function, file, or directory paths) to begin the search from.\n'
'Entities representing classes or functions must be formatted as "file_path:QualifiedName" (e.g., `interface/C.py:C.method_a.inner_func`).\n'
'For files or directories, provide only the file or directory path (e.g., `src/module_a.py` or `src/`).'
),
'type': 'array',
'items': {'type': 'string'},
},
'direction': {
'description': (
'Direction of traversal in the code graph; allowed options are: `upstream`, `downstream`, `both`.\n'
"- 'upstream': Traversal to explore dependencies that the specified entities rely on (how they depend on others).\n"
"- 'downstream': Traversal to explore the effects or interactions of the specified entities on others (how others depend on them).\n"
"- 'both': Traversal on both direction."
),
'type': 'string',
'enum': ['upstream', 'downstream', 'both'],
'default': 'downstream',
},
'traversal_depth': {
'description': (
'Maximum depth of traversal. A value of -1 indicates unlimited depth (subject to a maximum limit).'
'Must be either `-1` or a non-negative integer (≥ 0).'
),
'type': 'integer',
'default': 2,
},
'entity_type_filter': {
'description': (
"List of entity types (e.g., 'class', 'function', 'file', 'directory') to include in the traversal. If None, all entity types are included."
),
'type': ['array', 'null'],
'items': {'type': 'string'},
'default': None,
},
'dependency_type_filter': {
'description': (
"List of dependency types (e.g., 'contains', 'imports', 'invokes', 'inherits') to include in the traversal. If None, all dependency types are included."
),
'type': ['array', 'null'],
'items': {'type': 'string'},
'default': None,
},
},
'required': ['start_entities'],
}
def create_explore_tree_structure_tool(
use_simplified_description: bool = False,
) -> ChatCompletionToolParam:
description = (
_SIMPLIFIED_STRUCTURE_EXPLORER_DESCRIPTION
if use_simplified_description
else _DETAILED_STRUCTURE_EXPLORER_DESCRIPTION
)
example = (
_SIMPLIFIED_TREE_EXAMPLE
if use_simplified_description
else _DETAILED_TREE_EXAMPLE
)
return ChatCompletionToolParam(
type='function',
function=ChatCompletionToolParamFunctionChunk(
name='explore_tree_structure',
description=description + example,
parameters=_STRUCTURE_EXPLORER_PARAMETERS,
),
)

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@ -0,0 +1,98 @@
from litellm import (
ChatCompletionToolParam,
ChatCompletionToolParamFunctionChunk,
)
_SEARCH_ENTITY_DESCRIPTION = """
Searches the codebase to retrieve the complete implementations of specified entities based on the provided entity names.
The tool can handle specific entity queries such as function names, class names, or file paths.
**Usage Example:**
# Search for a specific function implementation
get_entity_contents(['src/my_file.py:MyClass.func_name'])
# Search for a file's complete content
get_entity_contents(['src/my_file.py'])
**Entity Name Format:**
- To specify a function or class, use the format: `file_path:QualifiedName`
(e.g., 'src/helpers/math_helpers.py:MathUtils.calculate_sum').
- To search for a file's content, use only the file path (e.g., 'src/my_file.py').
"""
SearchEntityTool = ChatCompletionToolParam(
type='function',
function=ChatCompletionToolParamFunctionChunk(
name='get_entity_contents',
description=_SEARCH_ENTITY_DESCRIPTION,
parameters={
'type': 'object',
'properties': {
'entity_names': {
'type': 'array',
'items': {'type': 'string'},
'description': (
'A list of entity names to query. Each entity name can represent a function, class, or file. '
"For functions or classes, the format should be 'file_path:QualifiedName' "
"(e.g., 'src/helpers/math_helpers.py:MathUtils.calculate_sum'). "
"For files, use just the file path (e.g., 'src/my_file.py')."
),
}
},
'required': ['entity_names'],
},
),
)
_SEARCH_REPO_DESCRIPTION = """Searches the codebase to retrieve relevant code snippets based on given queries(terms or line numbers).
** Note:
- Either `search_terms` or `line_nums` must be provided to perform a search.
- If `search_terms` are provided, it searches for code snippets based on each term:
- If `line_nums` is provided, it searches for code snippets around the specified lines within the file defined by `file_path_or_pattern`.
** Example Usage:
# Search for code content contain keyword `order`, `bill`
search_code_snippets(search_terms=["order", "bill"])
# Search for a class
search_code_snippets(search_terms=["MyClass"])
# Search for context around specific lines (10 and 15) within a file
search_code_snippets(line_nums=[10, 15], file_path_or_pattern='src/example.py')
"""
SearchRepoTool = ChatCompletionToolParam(
type='function',
function=ChatCompletionToolParamFunctionChunk(
name='search_code_snippets',
description=_SEARCH_REPO_DESCRIPTION,
parameters={
'type': 'object',
'properties': {
'search_terms': {
'type': 'array',
'items': {'type': 'string'},
'description': 'A list of names, keywords, or code snippets to search for within the codebase. '
'This can include potential function names, class names, or general code fragments. '
'Either `search_terms` or `line_nums` must be provided to perform a search.',
},
'line_nums': {
'type': 'array',
'items': {'type': 'integer'},
'description': 'Specific line numbers to locate code snippets within a specified file. '
'Must be used alongside a valid `file_path_or_pattern`. '
'Either `line_nums` or `search_terms` must be provided to perform a search.',
},
'file_path_or_pattern': {
'type': 'string',
'description': 'A glob pattern or specific file path used to filter search results '
'to particular files or directories. Defaults to "**/*.py", meaning all Python files are searched by default. '
'If `line_nums` are provided, this must specify a specific file path.',
'default': '**/*.py',
},
},
'required': [],
},
),
)

View File

@ -1,6 +1,6 @@
from inspect import signature
from openhands.runtime.plugins.agent_skills import file_ops, file_reader
from openhands.runtime.plugins.agent_skills import file_ops, file_reader, repo_ops
from openhands.runtime.plugins.agent_skills.utils.dependency import import_functions
import_functions(
@ -9,7 +9,11 @@ import_functions(
import_functions(
module=file_reader, function_names=file_reader.__all__, target_globals=globals()
)
__all__ = file_ops.__all__ + file_reader.__all__
import_functions(
module=repo_ops, function_names=repo_ops.__all__, target_globals=globals()
)
__all__ = file_ops.__all__ + file_reader.__all__ + repo_ops.__all__
DOCUMENTATION = ''
for func_name in __all__:

View File

@ -0,0 +1,7 @@
from openhands.runtime.plugins.agent_skills.repo_ops import repo_ops
from openhands.runtime.plugins.agent_skills.utils.dependency import import_functions
import_functions(
module=repo_ops, function_names=repo_ops.__all__, target_globals=globals()
)
__all__ = repo_ops.__all__

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@ -0,0 +1,11 @@
from openhands_aci.indexing.locagent.tools import (
explore_tree_structure,
get_entity_contents,
search_code_snippets,
)
__all__ = [
'get_entity_contents',
'search_code_snippets',
'explore_tree_structure',
]

843
poetry.lock generated

File diff suppressed because it is too large Load Diff

View File

@ -20,12 +20,12 @@ packages = [
[tool.poetry.dependencies]
python = "^3.12,<3.14"
litellm = "^1.60.0, !=1.64.4, !=1.67.*" # avoid 1.64.4 (known bug) & 1.67.* (known bug #10272)
aiohttp = ">=3.9.0,!=3.11.13" # Pin to avoid yanked version 3.11.13
google-generativeai = "*" # To use litellm with Gemini Pro API
google-api-python-client = "^2.164.0" # For Google Sheets API
google-auth-httplib2 = "*" # For Google Sheets authentication
google-auth-oauthlib = "*" # For Google Sheets OAuth
litellm = "^1.60.0, !=1.64.4, !=1.67.*" # avoid 1.64.4 (known bug) & 1.67.* (known bug #10272)
aiohttp = ">=3.9.0,!=3.11.13" # Pin to avoid yanked version 3.11.13
google-generativeai = "*" # To use litellm with Gemini Pro API
google-api-python-client = "^2.164.0" # For Google Sheets API
google-auth-httplib2 = "*" # For Google Sheets authentication
google-auth-oauthlib = "*" # For Google Sheets OAuth
termcolor = "*"
docker = "*"
fastapi = "*"
@ -34,7 +34,7 @@ uvicorn = "*"
types-toml = "*"
numpy = "*"
json-repair = "*"
browsergym-core = "0.13.3" # integrate browsergym-core as the browsing interface
browsergym-core = "0.13.3" # integrate browsergym-core as the browsing interface
html2text = "*"
e2b = ">=1.0.5,<1.4.0"
pexpect = "*"
@ -60,7 +60,7 @@ tornado = "*"
python-dotenv = "*"
pylcs = "^0.1.1"
whatthepatch = "^1.0.6"
protobuf = "^4.21.6,<5.0.0" # chromadb currently fails on 5.0+
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 = ">=0.66.26,<0.78.0"
@ -68,7 +68,7 @@ runloop-api-client = "0.32.0"
libtmux = ">=0.37,<0.40"
pygithub = "^2.5.0"
joblib = "*"
openhands-aci = "0.2.13"
openhands-aci = "0.2.14"
python-socketio = "^5.11.4"
redis = ">=5.2,<7.0"
sse-starlette = "^2.1.3"