From 4177e082a1c434dc61680368f18dc4cf497b4277 Mon Sep 17 00:00:00 2001 From: Chris Lee Date: Wed, 26 Feb 2025 23:54:08 -0800 Subject: [PATCH 01/16] convert to modal.Dict snapshot manager --- .../examples/swebench_agent_run/run_eval.py | 67 ++++++++++++++--- .../examples/swebench_agent_run/sandbox.py | 74 +++++++++++++++++++ .../swebench_agent_run/snapshot_manager.py | 57 ++++++++++++++ 3 files changed, 187 insertions(+), 11 deletions(-) create mode 100644 codegen-examples/examples/swebench_agent_run/sandbox.py create mode 100644 codegen-examples/examples/swebench_agent_run/snapshot_manager.py diff --git a/codegen-examples/examples/swebench_agent_run/run_eval.py b/codegen-examples/examples/swebench_agent_run/run_eval.py index 0c2132694..a4e1108d5 100644 --- a/codegen-examples/examples/swebench_agent_run/run_eval.py +++ b/codegen-examples/examples/swebench_agent_run/run_eval.py @@ -1,13 +1,18 @@ import asyncio import json import traceback -from pathlib import Path import uuid -import modal -import click from datetime import datetime -from codegen.extensions.swebench.utils import SWEBenchDataset, SweBenchExample, get_swe_bench_examples +from pathlib import Path + +import click +import modal from codegen.extensions.swebench.report import generate_report +from codegen.extensions.swebench.utils import ( + SWEBenchDataset, + SweBenchExample, + get_swe_bench_examples, +) PREDS_DNAME = Path(__file__).parent / "predictions" LOG_DIR = Path(__file__).parent / "logs" @@ -61,11 +66,26 @@ async def process_batch(examples: list[SweBenchExample], batch_size=10): print("Traceback:") print("".join(error_info["traceback"])) - results.append({"instance_id": example.instance_id, "status": "error", "error_info": error_info}) + results.append( + { + "instance_id": example.instance_id, + "status": "error", + "error_info": error_info, + } + ) else: if result is None: print(f"Warning: Null result for {example.instance_id}") - results.append({"instance_id": example.instance_id, "status": "error", "error_info": {"error_type": "NullResult", "error_message": "Process returned None"}}) + results.append( + { + "instance_id": example.instance_id, + "status": "error", + "error_info": { + "error_type": "NullResult", + "error_message": "Process returned None", + }, + } + ) else: results.append(result) @@ -81,14 +101,24 @@ async def process_batch(examples: list[SweBenchExample], batch_size=10): { "instance_id": example.instance_id, "status": "error", - "error_info": {"error_type": type(e).__name__, "error_message": str(e), "traceback": traceback.format_exc(), "batch_failure": True}, + "error_info": { + "error_type": type(e).__name__, + "error_message": str(e), + "traceback": traceback.format_exc(), + "batch_failure": True, + }, } ) return results -async def run_eval(use_existing_preds: str | None, dataset: str, length: int, instance_id: str | None = None): +async def run_eval( + use_existing_preds: str | None, + dataset: str, + length: int, + instance_id: str | None = None, +): run_id = use_existing_preds or str(uuid.uuid4()) predictions_dir = PREDS_DNAME / f"results_{run_id}" dataset = SWEBenchDataset(dataset) @@ -155,10 +185,25 @@ async def run_eval(use_existing_preds: str | None, dataset: str, length: int, in @click.command() -@click.option("--use-existing-preds", help="The run ID of the existing predictions to use.", type=str, default=None) -@click.option("--dataset", help="The dataset to use.", type=click.Choice([dataset.value for dataset in SWEBenchDataset]), default=SWEBenchDataset.LITE.value) +@click.option( + "--use-existing-preds", + help="The run ID of the existing predictions to use.", + type=str, + default=None, +) +@click.option( + "--dataset", + help="The dataset to use.", + type=click.Choice([dataset.value for dataset in SWEBenchDataset]), + default=SWEBenchDataset.LITE.value, +) @click.option("--length", help="The number of examples to process.", type=int, default=10) -@click.option("--instance-id", help="The instance ID of the example to process.", type=str, default=None) +@click.option( + "--instance-id", + help="The instance ID of the example to process.", + type=str, + default=None, +) def run_eval_command(use_existing_preds, dataset, length, instance_id): asyncio.run(run_eval(use_existing_preds, dataset, length, instance_id)) diff --git a/codegen-examples/examples/swebench_agent_run/sandbox.py b/codegen-examples/examples/swebench_agent_run/sandbox.py new file mode 100644 index 000000000..fc8d96af8 --- /dev/null +++ b/codegen-examples/examples/swebench_agent_run/sandbox.py @@ -0,0 +1,74 @@ +from contextlib import asynccontextmanager + +import modal +from codegen.extensions.swebench.utils import SweBenchExample + +from .snapshot_manager import ( + ModalDictSnapshotManager, + SnapshotManager, +) + +BASE_IMAGE: modal.Image = modal.Image.debian_slim(python_version="3.13").apt_install("git") + +try: + # To ensure secrets are consistent across runs, we look up existing secret + secret = modal.Secret.from_name("swebench-agent-run-secrets") +except modal.exception.NotFoundError: + secret = modal.Secret.from_dotenv() + +app = modal.App.lookup(name="swebench-agent-run", create_if_missing=True) + + +class SandboxManager: + keep_alive: bool + + def __init__( + self, + keep_alive: bool = False, + snapshot_manager: SnapshotManager | None = None, + ): + self.keep_alive = keep_alive + self.snapshot_manager = snapshot_manager or ModalDictSnapshotManager() + + async def create_sandbox(self, example: SweBenchExample) -> modal.Sandbox: + existing_snapshot_uid = await self.snapshot_manager.get_snapshot_uid(example) + if existing_snapshot_uid: + return await modal.Sandbox._experimental_from_snapshot(existing_snapshot_uid) + + # TODO: test if this get local version works / add ability to install specific version + with modal.enable_output(): + return await modal.Sandbox.create( + app=app, + image=BASE_IMAGE.run_commands(f"cd /root; git clone {example.repo} && cd {example.repo} && git checkout {example.environment_setup_commit}"), + secrets=[secret], + tags={"repo": example.repo, "commit": example.environment_setup_commit}, + ) + + @asynccontextmanager + async def get_sandbox(self, example: SweBenchExample): + async for sandbox in modal.Sandbox.list( + app_id=app.app_id, + tags={"repo": example.repo, "commit": example.environment_setup_commit}, + ): + break + else: + sandbox = await self.create_sandbox(example) + + try: + await sandbox.wait() + yield sandbox + finally: + if not self.keep_alive: + # Killing sandbox, so take a snapshot and save it + await sandbox.exec( + "bash", + "-c", + f"cd /root/{example.repo}; git stash", # cheeky little stash + ) + snapshot = await sandbox._experimental_snapshot() # commit any codegen updates + + await self.snapshot_manager.save_snapshot_uid(example, snapshot.object_id) + + # Codebase.from_repo doesn't use git to fetch/checkout the repo. + # We could replace this with our own git commands to control the file state + await sandbox.terminate() diff --git a/codegen-examples/examples/swebench_agent_run/snapshot_manager.py b/codegen-examples/examples/swebench_agent_run/snapshot_manager.py new file mode 100644 index 000000000..dbc1d8fe5 --- /dev/null +++ b/codegen-examples/examples/swebench_agent_run/snapshot_manager.py @@ -0,0 +1,57 @@ +import io +import json +from collections import defaultdict + +import modal +from codegen.extensions.swebench.utils import SweBenchExample + + +class SnapshotManager: + async def get_snapshot_uid(self, example: SweBenchExample) -> str: + raise NotImplementedError("Not implemented") + + async def save_snapshot_uid(self, example: SweBenchExample, snapshot_uid: str) -> None: + raise NotImplementedError("Not implemented") + + +class VolumeSnapshotManager(SnapshotManager): + def __init__(self, volume_name: str = "swebench-agent-snapshot-volume"): + self.snapshot_volume = modal.Volume.from_name(volume_name, create_if_missing=True) + self.snapshot_meta_file_path: str = "/root/snapshot_meta.json" + + async def get_snapshot_uid(self, example: SweBenchExample) -> str: + snapshot_meta = await self.read_snapshot_meta() + return snapshot_meta[example.repo][example.base_commit] + + async def save_snapshot_uid(self, example: SweBenchExample, snapshot_uid: str) -> None: + snapshot_meta = await self.read_snapshot_meta() + snapshot_meta[example.repo][example.environment_setup_commit] = snapshot_uid + async with self.snapshot_volume.batch_upload() as upload: + await upload.put_file( + io.BytesIO(json.dumps(snapshot_meta).encode("utf-8")), + self.snapshot_meta_file_path, + ) + await self.snapshot_volume.commit() + + async def read_snapshot_meta(self) -> dict[str, dict[str, str]]: + bytes_io = io.BytesIO() + try: + await self.snapshot_volume.read_file_into_fileobj(self.snapshot_meta_file_path, bytes_io) + snapshot_meta = json.loads(bytes_io.getvalue().decode("utf-8")) + except FileNotFoundError: + snapshot_meta = {} + return defaultdict(lambda: defaultdict(lambda: None), snapshot_meta) + + +class ModalDictSnapshotManager(SnapshotManager): + def __init__(self, name: str = "swebench-agent-snapshot-dict"): + self.snapshot_dict = modal.Dict.from_name(name, create_if_missing=True) + + async def get_snapshot_uid(self, example: SweBenchExample) -> str | None: + try: + return self.snapshot_dict[(example.repo, example.environment_setup_commit)] + except KeyError: + return None + + async def save_snapshot_uid(self, example: SweBenchExample, snapshot_uid: str) -> None: + self.snapshot_dict[(example.repo, example.environment_setup_commit)] = snapshot_uid From b5f1828bbaae1d9e0ca087ca6583bb313ee2179f Mon Sep 17 00:00:00 2001 From: Chris Lee Date: Thu, 27 Feb 2025 16:27:01 -0800 Subject: [PATCH 02/16] fix: implement modified swebench harness evaluation --- .../examples/swebench_agent_run/run_eval.py | 67 +--- .../run_swebench_modal_harness.py | 300 ++++++++++++++++++ .../examples/swebench_agent_run/sandbox.py | 74 ----- .../swebench_agent_run/snapshot_manager.py | 28 +- 4 files changed, 325 insertions(+), 144 deletions(-) create mode 100644 codegen-examples/examples/swebench_agent_run/run_swebench_modal_harness.py delete mode 100644 codegen-examples/examples/swebench_agent_run/sandbox.py diff --git a/codegen-examples/examples/swebench_agent_run/run_eval.py b/codegen-examples/examples/swebench_agent_run/run_eval.py index a4e1108d5..0c2132694 100644 --- a/codegen-examples/examples/swebench_agent_run/run_eval.py +++ b/codegen-examples/examples/swebench_agent_run/run_eval.py @@ -1,18 +1,13 @@ import asyncio import json import traceback -import uuid -from datetime import datetime from pathlib import Path - -import click +import uuid import modal +import click +from datetime import datetime +from codegen.extensions.swebench.utils import SWEBenchDataset, SweBenchExample, get_swe_bench_examples from codegen.extensions.swebench.report import generate_report -from codegen.extensions.swebench.utils import ( - SWEBenchDataset, - SweBenchExample, - get_swe_bench_examples, -) PREDS_DNAME = Path(__file__).parent / "predictions" LOG_DIR = Path(__file__).parent / "logs" @@ -66,26 +61,11 @@ async def process_batch(examples: list[SweBenchExample], batch_size=10): print("Traceback:") print("".join(error_info["traceback"])) - results.append( - { - "instance_id": example.instance_id, - "status": "error", - "error_info": error_info, - } - ) + results.append({"instance_id": example.instance_id, "status": "error", "error_info": error_info}) else: if result is None: print(f"Warning: Null result for {example.instance_id}") - results.append( - { - "instance_id": example.instance_id, - "status": "error", - "error_info": { - "error_type": "NullResult", - "error_message": "Process returned None", - }, - } - ) + results.append({"instance_id": example.instance_id, "status": "error", "error_info": {"error_type": "NullResult", "error_message": "Process returned None"}}) else: results.append(result) @@ -101,24 +81,14 @@ async def process_batch(examples: list[SweBenchExample], batch_size=10): { "instance_id": example.instance_id, "status": "error", - "error_info": { - "error_type": type(e).__name__, - "error_message": str(e), - "traceback": traceback.format_exc(), - "batch_failure": True, - }, + "error_info": {"error_type": type(e).__name__, "error_message": str(e), "traceback": traceback.format_exc(), "batch_failure": True}, } ) return results -async def run_eval( - use_existing_preds: str | None, - dataset: str, - length: int, - instance_id: str | None = None, -): +async def run_eval(use_existing_preds: str | None, dataset: str, length: int, instance_id: str | None = None): run_id = use_existing_preds or str(uuid.uuid4()) predictions_dir = PREDS_DNAME / f"results_{run_id}" dataset = SWEBenchDataset(dataset) @@ -185,25 +155,10 @@ async def run_eval( @click.command() -@click.option( - "--use-existing-preds", - help="The run ID of the existing predictions to use.", - type=str, - default=None, -) -@click.option( - "--dataset", - help="The dataset to use.", - type=click.Choice([dataset.value for dataset in SWEBenchDataset]), - default=SWEBenchDataset.LITE.value, -) +@click.option("--use-existing-preds", help="The run ID of the existing predictions to use.", type=str, default=None) +@click.option("--dataset", help="The dataset to use.", type=click.Choice([dataset.value for dataset in SWEBenchDataset]), default=SWEBenchDataset.LITE.value) @click.option("--length", help="The number of examples to process.", type=int, default=10) -@click.option( - "--instance-id", - help="The instance ID of the example to process.", - type=str, - default=None, -) +@click.option("--instance-id", help="The instance ID of the example to process.", type=str, default=None) def run_eval_command(use_existing_preds, dataset, length, instance_id): asyncio.run(run_eval(use_existing_preds, dataset, length, instance_id)) diff --git a/codegen-examples/examples/swebench_agent_run/run_swebench_modal_harness.py b/codegen-examples/examples/swebench_agent_run/run_swebench_modal_harness.py new file mode 100644 index 000000000..81f196045 --- /dev/null +++ b/codegen-examples/examples/swebench_agent_run/run_swebench_modal_harness.py @@ -0,0 +1,300 @@ +""" +Largely copied from swebench/harness/modal_eval/run_evaluation_modal.py + +Points of difference: + - We added CGModalSandboxRuntime class that is used to populate the sandbox with the snapshot. + - We are adding custom post-processing of the TestOutput in run_instances_modal +""" + +import json +import time +import traceback +from typing import cast + +import modal +from swebench.harness.constants import ( + APPLY_PATCH_FAIL, + APPLY_PATCH_PASS, + SWEbenchInstance, +) +from swebench.harness.docker_build import setup_logger +from swebench.harness.grading import get_eval_report +from swebench.harness.modal_eval.run_evaluation_modal import ( + LOCAL_SANDBOX_ENTRYPOINT_PATH, + REMOTE_SANDBOX_ENTRYPOINT_PATH, + ModalSandboxRuntime, + TestOutput, + get_log_dir, +) +from swebench.harness.test_spec.test_spec import TestSpec, make_test_spec +from swebench.harness.utils import EvaluationError + +from .snapshot_manager import ModalDictSnapshotManager + +app = modal.App.from_name("swebench-agent-run", create_if_missing=True) + + +class CGModalSandboxRuntime(ModalSandboxRuntime): + def __init__( + self, + example: SWEbenchInstance, + timeout: int | None = None, + verbose: bool = True, + ): + self.example = example + self.snapshot_manager = ModalDictSnapshotManager() + self.test_spec = make_test_spec(example) + self.sandbox = self._get_sandbox(timeout) + self.verbose = verbose + self._stream_tasks = [] + + # Hack for pylint + self.write_file("/sys/fs/cgroup/cpu/cpu.shares", "2048") + + @property + def image(self) -> modal.Image: + return ModalSandboxRuntime.get_instance_image(self.test_spec) + + def _get_sandbox(self, timeout: int | None = None): + """ + Populate sandbox ourselves + """ + uid = self.snapshot_manager.get_snapshot_uid(self.example) + if uid is None: + sandbox = super()._get_sandbox(timeout) + snapshot = sandbox._experimental_snapshot() + self.snapshot_manager.save_snapshot_uid(self.example, snapshot.object_id) + else: + return modal.Sandbox._experimental_from_snapshot(uid) + + +@app.function( + image=modal.Image.debian_slim(python_version="3.13").add_local_file( + LOCAL_SANDBOX_ENTRYPOINT_PATH, + REMOTE_SANDBOX_ENTRYPOINT_PATH, + ), + timeout=120 + * 60, # Much larger than default timeout to account for image build time +) +def run_instance_modal( + test_spec: TestSpec, + pred: dict, + run_id: str, + timeout: int | None = None, +) -> TestOutput: + """ + Run a single instance with the given prediction. + + Args: + test_spec (TestSpec): TestSpec instance + pred (dict): Prediction w/ model_name_or_path, model_patch, instance_id + run_id (str): Run ID + timeout (int): Timeout for running tests + """ + instance_id = test_spec.instance_id + log_dir = get_log_dir(pred, run_id, instance_id) + log_dir.mkdir(parents=True, exist_ok=True) + + log_file = log_dir / "run_instance.log" + + logger = setup_logger(instance_id, log_file, add_stdout=True) + + try: + runner = CGModalSandboxRuntime(test_spec, timeout) + except Exception as e: + print(f"Error creating sandbox: {e}") + raise EvaluationError( + instance_id, + f"Error creating sandbox: {e}", + logger, + ) from e + + patch_diff = pred.get("model_patch", "") + + try: + patch_file = "/tmp/patch.diff" + runner.write_file(patch_file, patch_diff) + + apply_patch_output, returncode = runner.exec( + "cd /testbed && git apply -v /tmp/patch.diff", + ) + + if returncode != 0: + logger.info("Failed to apply patch to container, trying again...") + + apply_patch_output, returncode = runner.exec( + "cd /testbed && patch --batch --fuzz=5 -p1 -i /tmp/patch.diff", + ) + + if returncode != 0: + logger.info(f"{APPLY_PATCH_FAIL}:\n{apply_patch_output}") + raise EvaluationError( + instance_id, + f"{APPLY_PATCH_FAIL}:\n{apply_patch_output}", + logger, + ) + else: + logger.info(f"{APPLY_PATCH_PASS}:\n{apply_patch_output}") + else: + logger.info(f"{APPLY_PATCH_PASS}:\n{apply_patch_output}") + + # Get git diff before running eval script + git_diff_output_before, returncode = runner.exec( + "cd /testbed && git diff", + ) + logger.info(f"Git diff before:\n{git_diff_output_before}") + + eval_file = "/root/eval.sh" + eval_script = test_spec.eval_script + # django hack + eval_script = eval_script.replace("locale-gen", "locale-gen en_US.UTF-8") + runner.write_file(eval_file, eval_script) + + start_time = time.time() + + run_command = "cd /testbed" + # pylint hack + if "pylint" in test_spec.instance_id: + run_command += " && PYTHONPATH=" + # increase recursion limit for testing + run_command += " && python3 -c 'import sys; sys.setrecursionlimit(10000)'" + # run eval script + run_command += " && /bin/bash /root/eval.sh" + test_output, returncode = runner.exec(run_command) + + total_runtime = time.time() - start_time + + test_output_path = log_dir / "test_output.txt" + logger.info(f"Test runtime: {total_runtime:_.2f} seconds") + with open(test_output_path, "w") as f: + f.write(test_output) + logger.info(f"Test output for {instance_id} written to {test_output_path}") + print(f"Test output for {instance_id} written to {test_output_path}") + + # Get git diff after running eval script + git_diff_output_after, returncode = runner.exec("cd /testbed && git diff") + + # Check if git diff changed after running eval script + logger.info(f"Git diff after:\n{git_diff_output_after}") + if git_diff_output_after != git_diff_output_before: + logger.info("Git diff changed after running eval script") + + # Get report from test output + logger.info(f"Grading answer for {instance_id}...") + report = get_eval_report( + test_spec=test_spec, + prediction=pred, + test_log_path=test_output_path, + include_tests_status=True, + ) + logger.info( + f"report: {report}\nResult for {instance_id}: resolved: {report[instance_id]['resolved']}" + ) + + return TestOutput( + instance_id=instance_id, + test_output=test_output, + report_json_str=json.dumps(report, indent=4), + run_instance_log=log_file.read_text(), + patch_diff=patch_diff, + log_dir=log_dir, + errored=False, + ) + except modal.exception.SandboxTimeoutError as e: + raise EvaluationError( + instance_id, + f"Test timed out after {timeout} seconds.", + logger, + ) from e + except EvaluationError: + error_msg = traceback.format_exc() + logger.info(error_msg) + return TestOutput( + instance_id=instance_id, + test_output="", + report_json_str="", + run_instance_log=log_file.read_text(), + patch_diff=patch_diff, + log_dir=log_dir, + errored=True, + ) + except Exception as e: + error_msg = f"Error in evaluating model for {instance_id}: {e}\n{traceback.format_exc()}\nCheck ({logger.log_file}) for more information." + logger.error(error_msg) + return TestOutput( + instance_id=instance_id, + test_output="", + report_json_str="", + run_instance_log=log_file.read_text(), + patch_diff=patch_diff, + log_dir=log_dir, + errored=True, + ) + + +def run_instances_modal( + predictions: dict, + instances: list, + full_dataset: list, + run_id: str, + timeout: int, +): + """ + Run all instances for the given predictions on Modal. + + Args: + predictions (dict): Predictions dict generated by the model + instances (list): List of instances + run_id (str): Run ID + timeout (int): Timeout for running tests + """ + test_specs = list(map(make_test_spec, instances)) + + with modal.enable_output(): + with app.run(): + run_test_specs = [] + + # Check for instances that have already been run + for test_spec in test_specs: + log_dir = get_log_dir( + predictions[test_spec.instance_id], run_id, test_spec.instance_id + ) + if log_dir.exists(): + continue + run_test_specs.append(test_spec) + + if run_test_specs: + # Run instances that haven't been run yet + results = run_instance_modal.starmap( + [ + ( + test_spec, + predictions[test_spec.instance_id], + run_id, + timeout, + ) + for test_spec in run_test_specs + ], + ) + + for result in results: + result = cast(TestOutput, result) + + # log_dir = result.log_dir + # log_dir.mkdir(parents=True, exist_ok=True) + # with open(log_dir / "run_instance.log", "w") as f: + # f.write(result.run_instance_log) + # with open(log_dir / "test_output.txt", "w") as f: + # f.write(result.test_output) + # with open(log_dir / "patch.diff", "w") as f: + # f.write(result.patch_diff) + # with open(log_dir / "report.json", "w") as f: + # try: + # report_json = json.loads(result.report_json_str) + # json.dump(report_json, f, indent=4) + # except Exception: + # # This happens if the test fails with any exception + # print(f"{result.instance_id}: no report.json") + + # TODO: DO SOMETHING WITH OUTPUTS AND LOGS. + # TODO: SAVE THINGS TO POSTGRESQL FOR DASHBOARD diff --git a/codegen-examples/examples/swebench_agent_run/sandbox.py b/codegen-examples/examples/swebench_agent_run/sandbox.py deleted file mode 100644 index fc8d96af8..000000000 --- a/codegen-examples/examples/swebench_agent_run/sandbox.py +++ /dev/null @@ -1,74 +0,0 @@ -from contextlib import asynccontextmanager - -import modal -from codegen.extensions.swebench.utils import SweBenchExample - -from .snapshot_manager import ( - ModalDictSnapshotManager, - SnapshotManager, -) - -BASE_IMAGE: modal.Image = modal.Image.debian_slim(python_version="3.13").apt_install("git") - -try: - # To ensure secrets are consistent across runs, we look up existing secret - secret = modal.Secret.from_name("swebench-agent-run-secrets") -except modal.exception.NotFoundError: - secret = modal.Secret.from_dotenv() - -app = modal.App.lookup(name="swebench-agent-run", create_if_missing=True) - - -class SandboxManager: - keep_alive: bool - - def __init__( - self, - keep_alive: bool = False, - snapshot_manager: SnapshotManager | None = None, - ): - self.keep_alive = keep_alive - self.snapshot_manager = snapshot_manager or ModalDictSnapshotManager() - - async def create_sandbox(self, example: SweBenchExample) -> modal.Sandbox: - existing_snapshot_uid = await self.snapshot_manager.get_snapshot_uid(example) - if existing_snapshot_uid: - return await modal.Sandbox._experimental_from_snapshot(existing_snapshot_uid) - - # TODO: test if this get local version works / add ability to install specific version - with modal.enable_output(): - return await modal.Sandbox.create( - app=app, - image=BASE_IMAGE.run_commands(f"cd /root; git clone {example.repo} && cd {example.repo} && git checkout {example.environment_setup_commit}"), - secrets=[secret], - tags={"repo": example.repo, "commit": example.environment_setup_commit}, - ) - - @asynccontextmanager - async def get_sandbox(self, example: SweBenchExample): - async for sandbox in modal.Sandbox.list( - app_id=app.app_id, - tags={"repo": example.repo, "commit": example.environment_setup_commit}, - ): - break - else: - sandbox = await self.create_sandbox(example) - - try: - await sandbox.wait() - yield sandbox - finally: - if not self.keep_alive: - # Killing sandbox, so take a snapshot and save it - await sandbox.exec( - "bash", - "-c", - f"cd /root/{example.repo}; git stash", # cheeky little stash - ) - snapshot = await sandbox._experimental_snapshot() # commit any codegen updates - - await self.snapshot_manager.save_snapshot_uid(example, snapshot.object_id) - - # Codebase.from_repo doesn't use git to fetch/checkout the repo. - # We could replace this with our own git commands to control the file state - await sandbox.terminate() diff --git a/codegen-examples/examples/swebench_agent_run/snapshot_manager.py b/codegen-examples/examples/swebench_agent_run/snapshot_manager.py index dbc1d8fe5..37138ba33 100644 --- a/codegen-examples/examples/swebench_agent_run/snapshot_manager.py +++ b/codegen-examples/examples/swebench_agent_run/snapshot_manager.py @@ -3,14 +3,14 @@ from collections import defaultdict import modal -from codegen.extensions.swebench.utils import SweBenchExample +from swebench.harness.constants import SWEbenchInstance class SnapshotManager: - async def get_snapshot_uid(self, example: SweBenchExample) -> str: + def get_snapshot_uid(self, example: SWEbenchInstance) -> str: raise NotImplementedError("Not implemented") - async def save_snapshot_uid(self, example: SweBenchExample, snapshot_uid: str) -> None: + def save_snapshot_uid(self, example: SWEbenchInstance, snapshot_uid: str) -> None: raise NotImplementedError("Not implemented") @@ -19,24 +19,24 @@ def __init__(self, volume_name: str = "swebench-agent-snapshot-volume"): self.snapshot_volume = modal.Volume.from_name(volume_name, create_if_missing=True) self.snapshot_meta_file_path: str = "/root/snapshot_meta.json" - async def get_snapshot_uid(self, example: SweBenchExample) -> str: - snapshot_meta = await self.read_snapshot_meta() + def get_snapshot_uid(self, example: SWEbenchInstance) -> str: + snapshot_meta = self.read_snapshot_meta() return snapshot_meta[example.repo][example.base_commit] - async def save_snapshot_uid(self, example: SweBenchExample, snapshot_uid: str) -> None: - snapshot_meta = await self.read_snapshot_meta() + def save_snapshot_uid(self, example: SWEbenchInstance, snapshot_uid: str) -> None: + snapshot_meta = self.read_snapshot_meta() snapshot_meta[example.repo][example.environment_setup_commit] = snapshot_uid - async with self.snapshot_volume.batch_upload() as upload: - await upload.put_file( + with self.snapshot_volume.batch_upload() as upload: + upload.put_file( io.BytesIO(json.dumps(snapshot_meta).encode("utf-8")), self.snapshot_meta_file_path, ) - await self.snapshot_volume.commit() + self.snapshot_volume.commit() - async def read_snapshot_meta(self) -> dict[str, dict[str, str]]: + def read_snapshot_meta(self) -> dict[str, dict[str, str]]: bytes_io = io.BytesIO() try: - await self.snapshot_volume.read_file_into_fileobj(self.snapshot_meta_file_path, bytes_io) + self.snapshot_volume.read_file_into_fileobj(self.snapshot_meta_file_path, bytes_io) snapshot_meta = json.loads(bytes_io.getvalue().decode("utf-8")) except FileNotFoundError: snapshot_meta = {} @@ -47,11 +47,11 @@ class ModalDictSnapshotManager(SnapshotManager): def __init__(self, name: str = "swebench-agent-snapshot-dict"): self.snapshot_dict = modal.Dict.from_name(name, create_if_missing=True) - async def get_snapshot_uid(self, example: SweBenchExample) -> str | None: + def get_snapshot_uid(self, example: SWEbenchInstance) -> str | None: try: return self.snapshot_dict[(example.repo, example.environment_setup_commit)] except KeyError: return None - async def save_snapshot_uid(self, example: SweBenchExample, snapshot_uid: str) -> None: + def save_snapshot_uid(self, example: SWEbenchInstance, snapshot_uid: str) -> None: self.snapshot_dict[(example.repo, example.environment_setup_commit)] = snapshot_uid From a54c71d7f311d70c903f52a46505f56b7148592b Mon Sep 17 00:00:00 2001 From: clee-codegen <185840274+clee-codegen@users.noreply.github.com> Date: Fri, 28 Feb 2025 00:31:19 +0000 Subject: [PATCH 03/16] Automated pre-commit update --- .../swebench_agent_run/run_swebench_modal_harness.py | 11 +++-------- 1 file changed, 3 insertions(+), 8 deletions(-) diff --git a/codegen-examples/examples/swebench_agent_run/run_swebench_modal_harness.py b/codegen-examples/examples/swebench_agent_run/run_swebench_modal_harness.py index 81f196045..8bd6a8699 100644 --- a/codegen-examples/examples/swebench_agent_run/run_swebench_modal_harness.py +++ b/codegen-examples/examples/swebench_agent_run/run_swebench_modal_harness.py @@ -73,8 +73,7 @@ def _get_sandbox(self, timeout: int | None = None): LOCAL_SANDBOX_ENTRYPOINT_PATH, REMOTE_SANDBOX_ENTRYPOINT_PATH, ), - timeout=120 - * 60, # Much larger than default timeout to account for image build time + timeout=120 * 60, # Much larger than default timeout to account for image build time ) def run_instance_modal( test_spec: TestSpec, @@ -187,9 +186,7 @@ def run_instance_modal( test_log_path=test_output_path, include_tests_status=True, ) - logger.info( - f"report: {report}\nResult for {instance_id}: resolved: {report[instance_id]['resolved']}" - ) + logger.info(f"report: {report}\nResult for {instance_id}: resolved: {report[instance_id]['resolved']}") return TestOutput( instance_id=instance_id, @@ -256,9 +253,7 @@ def run_instances_modal( # Check for instances that have already been run for test_spec in test_specs: - log_dir = get_log_dir( - predictions[test_spec.instance_id], run_id, test_spec.instance_id - ) + log_dir = get_log_dir(predictions[test_spec.instance_id], run_id, test_spec.instance_id) if log_dir.exists(): continue run_test_specs.append(test_spec) From cdcf2d03c56c74cd35bbc20c129c5498d5ef02fe Mon Sep 17 00:00:00 2001 From: Chris Lee Date: Thu, 27 Feb 2025 16:40:54 -0800 Subject: [PATCH 04/16] base_commit -> environment_setup_commit --- .../examples/swebench_agent_run/snapshot_manager.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/codegen-examples/examples/swebench_agent_run/snapshot_manager.py b/codegen-examples/examples/swebench_agent_run/snapshot_manager.py index 37138ba33..50fb96a59 100644 --- a/codegen-examples/examples/swebench_agent_run/snapshot_manager.py +++ b/codegen-examples/examples/swebench_agent_run/snapshot_manager.py @@ -21,7 +21,7 @@ def __init__(self, volume_name: str = "swebench-agent-snapshot-volume"): def get_snapshot_uid(self, example: SWEbenchInstance) -> str: snapshot_meta = self.read_snapshot_meta() - return snapshot_meta[example.repo][example.base_commit] + return snapshot_meta[example.repo][example.environment_setup_commit] def save_snapshot_uid(self, example: SWEbenchInstance, snapshot_uid: str) -> None: snapshot_meta = self.read_snapshot_meta() From 9049f1d6593b3ebe8633e707eaf1de7effcbe69e Mon Sep 17 00:00:00 2001 From: Chris Lee Date: Sun, 2 Mar 2025 10:31:16 -0800 Subject: [PATCH 05/16] feat: codegen parse oss repos via CLI and modal (#545) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit # Motivation The **Codegen on OSS** package provides a pipeline that: - **Collects repository URLs** from different sources (e.g., CSV files or GitHub searches). - **Parses repositories** using the codegen tool. - **Profiles performance** and logs metrics for each parsing run. - **Logs errors** to help pinpoint parsing failures or performance bottlenecks. # Content see [codegen-on-oss/README.md](https://github.com/codegen-sh/codegen-sdk/blob/acfe3dc07b65670af33b977fa1e7bc8627fd714e/codegen-on-oss/README.md) # Testing `uv run modal run modal_run.py` No unit tests yet 😿 # Please check the following before marking your PR as ready for review - [ ] I have added tests for my changes - [x] I have updated the documentation or added new documentation as needed --- codegen-on-oss/.dockerignore | 5 + codegen-on-oss/.gitignore | 140 + codegen-on-oss/Dockerfile | 34 + codegen-on-oss/Makefile | 38 + codegen-on-oss/README.md | 337 ++ codegen-on-oss/codecov.yaml | 9 + codegen-on-oss/codegen_modal_deploy.py | 74 + codegen-on-oss/codegen_modal_run.py | 29 + codegen-on-oss/codegen_on_oss/__init__.py | 0 codegen-on-oss/codegen_on_oss/bucket_store.py | 26 + codegen-on-oss/codegen_on_oss/cache.py | 5 + codegen-on-oss/codegen_on_oss/cli.py | 128 + codegen-on-oss/codegen_on_oss/errors.py | 6 + codegen-on-oss/codegen_on_oss/metrics.py | 198 + .../codegen_on_oss/outputs/__init__.py | 0 codegen-on-oss/codegen_on_oss/outputs/base.py | 16 + .../codegen_on_oss/outputs/csv_output.py | 30 + .../codegen_on_oss/outputs/sql_output.py | 113 + codegen-on-oss/codegen_on_oss/parser.py | 86 + .../codegen_on_oss/sources/__init__.py | 16 + codegen-on-oss/codegen_on_oss/sources/base.py | 65 + .../codegen_on_oss/sources/csv_source.py | 39 + .../codegen_on_oss/sources/github_source.py | 59 + .../codegen_on_oss/sources/single_source.py | 31 + codegen-on-oss/docker-compose.yaml | 9 + codegen-on-oss/input.csv | 2 + codegen-on-oss/modal_run.py | 151 + codegen-on-oss/pyproject.toml | 125 + codegen-on-oss/scripts/create_db.py | 18 + codegen-on-oss/scripts/db | 7 + codegen-on-oss/tests/test_cli.py | 0 codegen-on-oss/tox.ini | 19 + codegen-on-oss/uv.lock | 3221 +++++++++++++++++ 33 files changed, 5036 insertions(+) create mode 100644 codegen-on-oss/.dockerignore create mode 100644 codegen-on-oss/.gitignore create mode 100644 codegen-on-oss/Dockerfile create mode 100644 codegen-on-oss/Makefile create mode 100644 codegen-on-oss/README.md create mode 100644 codegen-on-oss/codecov.yaml create mode 100644 codegen-on-oss/codegen_modal_deploy.py create mode 100644 codegen-on-oss/codegen_modal_run.py create mode 100644 codegen-on-oss/codegen_on_oss/__init__.py create mode 100644 codegen-on-oss/codegen_on_oss/bucket_store.py create mode 100644 codegen-on-oss/codegen_on_oss/cache.py create mode 100644 codegen-on-oss/codegen_on_oss/cli.py create mode 100644 codegen-on-oss/codegen_on_oss/errors.py create mode 100644 codegen-on-oss/codegen_on_oss/metrics.py create mode 100644 codegen-on-oss/codegen_on_oss/outputs/__init__.py create mode 100644 codegen-on-oss/codegen_on_oss/outputs/base.py create mode 100644 codegen-on-oss/codegen_on_oss/outputs/csv_output.py create mode 100644 codegen-on-oss/codegen_on_oss/outputs/sql_output.py create mode 100644 codegen-on-oss/codegen_on_oss/parser.py create mode 100644 codegen-on-oss/codegen_on_oss/sources/__init__.py create mode 100644 codegen-on-oss/codegen_on_oss/sources/base.py create mode 100644 codegen-on-oss/codegen_on_oss/sources/csv_source.py create mode 100644 codegen-on-oss/codegen_on_oss/sources/github_source.py create mode 100644 codegen-on-oss/codegen_on_oss/sources/single_source.py create mode 100644 codegen-on-oss/docker-compose.yaml create mode 100644 codegen-on-oss/input.csv create mode 100644 codegen-on-oss/modal_run.py create mode 100644 codegen-on-oss/pyproject.toml create mode 100644 codegen-on-oss/scripts/create_db.py create mode 100755 codegen-on-oss/scripts/db create mode 100644 codegen-on-oss/tests/test_cli.py create mode 100644 codegen-on-oss/tox.ini create mode 100644 codegen-on-oss/uv.lock diff --git a/codegen-on-oss/.dockerignore b/codegen-on-oss/.dockerignore new file mode 100644 index 000000000..7b435ab1e --- /dev/null +++ b/codegen-on-oss/.dockerignore @@ -0,0 +1,5 @@ +.git/ +repositories/ +.venv/ +.vscode/ +output/ diff --git a/codegen-on-oss/.gitignore b/codegen-on-oss/.gitignore new file mode 100644 index 000000000..780eabf11 --- /dev/null +++ b/codegen-on-oss/.gitignore @@ -0,0 +1,140 @@ +docs/source + +# From https://raw.githubusercontent.com/github/gitignore/main/Python.gitignore + +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +cover/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +.pybuilder/ +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# pytype static type analyzer +.pytype/ + +# Cython debug symbols +cython_debug/ + +# Vscode config files +.vscode/ + +# PyCharm +# JetBrains specific template is maintained in a separate JetBrains.gitignore that can +# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore +# and can be added to the global gitignore or merged into this file. For a more nuclear +# option (not recommended) you can uncomment the following to ignore the entire idea folder. +#.idea/ diff --git a/codegen-on-oss/Dockerfile b/codegen-on-oss/Dockerfile new file mode 100644 index 000000000..458758a84 --- /dev/null +++ b/codegen-on-oss/Dockerfile @@ -0,0 +1,34 @@ +# Install uv +FROM python:3.12-slim AS installer +COPY --from=ghcr.io/astral-sh/uv:latest /uv /bin/uv + +# Change the working directory to the `app` directory +WORKDIR /app + +# Copy the lockfile and `pyproject.toml` into the image +COPY uv.lock /app/uv.lock +COPY pyproject.toml /app/pyproject.toml + +# Install dependencies +RUN apt-get update && apt-get install -y git \ + && uv sync --frozen --no-install-project \ + && apt-get clean \ + && rm -rf /var/lib/apt/lists/* + + +FROM python:3.12-slim + +ENV PATH="/venv/bin:/app/scripts:$PATH" +# Copy the project into the image +COPY --from=installer /app/.venv/ /venv + +RUN apt-get update && apt-get install -y postgresql-client \ + && rm -rf /var/lib/apt/lists/* \ + && apt-get clean + + +WORKDIR /app + +COPY . . + +CMD ["python", "modal_run.py"] diff --git a/codegen-on-oss/Makefile b/codegen-on-oss/Makefile new file mode 100644 index 000000000..dba86014c --- /dev/null +++ b/codegen-on-oss/Makefile @@ -0,0 +1,38 @@ +.PHONY: install +install: ## Install the virtual environment and install the pre-commit hooks + @echo "🚀 Creating virtual environment using uv" + @uv sync + @uv run pre-commit install + +.PHONY: check +check: ## Run code quality tools. + @echo "🚀 Checking lock file consistency with 'pyproject.toml'" + @uv lock --locked + @echo "🚀 Linting code: Running pre-commit" + @uv run pre-commit run -a + @echo "🚀 Static type checking: Running mypy" + @uv run mypy + @echo "🚀 Checking for obsolete dependencies: Running deptry" + @uv run deptry . + +.PHONY: test +test: ## Test the code with pytest + @echo "🚀 Testing code: Running pytest" + @uv run python -m pytest --cov --cov-config=pyproject.toml --cov-report=xml + +.PHONY: build +build: clean-build ## Build wheel file + @echo "🚀 Creating wheel file" + @uvx --from build pyproject-build --installer uv + +.PHONY: clean-build +clean-build: ## Clean build artifacts + @echo "🚀 Removing build artifacts" + @uv run python -c "import shutil; import os; shutil.rmtree('dist') if os.path.exists('dist') else None" + +.PHONY: help +help: + @uv run python -c "import re; \ + [[print(f'\033[36m{m[0]:<20}\033[0m {m[1]}') for m in re.findall(r'^([a-zA-Z_-]+):.*?## (.*)$$', open(makefile).read(), re.M)] for makefile in ('$(MAKEFILE_LIST)').strip().split()]" + +.DEFAULT_GOAL := help diff --git a/codegen-on-oss/README.md b/codegen-on-oss/README.md new file mode 100644 index 000000000..a7700eb77 --- /dev/null +++ b/codegen-on-oss/README.md @@ -0,0 +1,337 @@ +# Overview + +The **Codegen on OSS** package provides a modular pipeline that: + +- **Collects repository URLs** from different sources (e.g., CSV files or GitHub searches). +- **Parses repositories** using the codegen tool. +- **Profiles performance** and logs metrics for each parsing run. +- **Logs errors** to help pinpoint parsing failures or performance bottlenecks. + +______________________________________________________________________ + +## Package Structure + +The package is composed of several modules: + +- `sources` + + - Defines the Repository source classes and settings. Settings are all configurable via environment variables + + - Github Source + + ```python + class GithubSettings(SourceSettings): + language: Literal["python", "typescript"] = "python" + heuristic: Literal[ + "stars", + "forks", + "updated", + # "watchers", + # "contributors", + # "commit_activity", + # "issues", + # "dependency", + ] = "stars" + github_token: str | None = None + ``` + + - The three options available now are the three supported by the Github API. + - Future Work Additional options will require different strategies + + - CSV Source + + - Simply reads repo URLs from CSV + +- `cache` + + - Currently only specifies the cache directory. It is used for caching git repositories pulled by the pipeline `--force-pull` can be used to re-pull from the remote. + +- `cli` + + - Built with Click, the CLI provides two main commands: + - `run-one`: Parses a single repository specified by URL. + - `run`: Iterates over repositories obtained from a selected source and parses each one. + +- **`metrics`** + + - Provides profiling tools to measure performance during the parse: + - `MetricsProfiler`: A context manager that creates a profiling session. + - `MetricsProfile`: Represents a "span" or a "run" of a specific repository. Records step-by-step metrics (clock duration, CPU time, memory usage) and writes them to a CSV file specified by `--output-path` + +- **`parser`** + + Contains the `CodegenParser` class that orchestrates the parsing process: + + - Clones the repository (or forces a pull if specified). + - Initializes a `Codebase` (from the codegen tool). + - Runs post-initialization validation. + - Integrates with the `MetricsProfiler` to log measurements at key steps. + +______________________________________________________________________ + +## Getting Started + +1. **Configure the Repository Source** + + Decide whether you want to read from a CSV file or query GitHub: + + - For CSV, ensure that your CSV file (default: `input.csv`) exists and contains repository URLs in its first column \[`repo_url`\] and commit hash \[`commit_hash`\] (or empty) in the second column. + - For GitHub, configure your desired settings (e.g., `language`, `heuristic`, and optionally a GitHub token) via environment variables (`GITHUB_` prefix) + +1. **Run the Parser** + + Use the CLI to start parsing: + + - To parse one repository: + + ```bash + uv run cgparse run-one --help + ``` + + - To parse multiple repositories from a source: + + ```bash + uv run cgparse run --help + ``` + +1. **Review Metrics and Logs** + + After parsing, check the CSV (default: `metrics.csv` ) to review performance measurements per repository. Error logs are written to the specified error output file (default: `errors.log`) + +______________________________________________________________________ + +## Running on Modal + +```shell +$ uv run modal run modal_run.py +``` + +Codegen runs this parser on modal using the CSV source file `input.csv` tracked in this repository. + +### Modal Configuration + +- **Compute Resources**: Allocates 4 CPUs and 16GB of memory. +- **Secrets & Volumes**: Uses secrets (for bucket credentials) and mounts a volume for caching repositories. +- **Image Setup**: Builds on a Debian slim image with Python 3.12, installs required packages (`uv` and `git` ) +- **Environment Configuration**: Environment variables (e.g., GitHub settings) are injected at runtime. + +The function `parse_repo_on_modal` performs the following steps: + +1. **Environment Setup**: Updates environment variables and configures logging using Loguru. +1. **Source Initialization**: Creates a repository source based on the provided type (e.g., GitHub). +1. **Metrics Profiling**: Instantiates `MetricsProfiler` to capture and log performance data. +1. **Repository Parsing**: Iterates over repository URLs and parses each using the `CodegenParser`. +1. **Error Handling**: Logs any exceptions encountered during parsing. +1. **Result Upload**: Uses the `BucketStore` class to upload the configuration, logs, and metrics to an S3 bucket. + +### Bucket Storage + +**Bucket (public):** [codegen-oss-parse](https://s3.amazonaws.com/codegen-oss-parse/) + +The results of each run are saved under the version of `codegen` lib that the run installed and the source type it was run with. Within this prefix: + +- Source Settings + - `https://s3.amazonaws.com/codegen-oss-parse/{version}/{source}/config.json` +- Metrics + - `https://s3.amazonaws.com/codegen-oss-parse/{version}/{source}/metrics.csv` +- Logs + - `https://s3.amazonaws.com/codegen-oss-parse/{version}/{source}/output.logs` + +______________________________________________________________________ + +### Running it yourself + +You can also run `modal_run.py` yourself. It is designed to be run via Modal for cloud-based parsing. It offers additional configuration methods: + +```shell +$ uv run modal run modal_run.py +``` + +- **CSV and Repository Volumes:** + The script defines two Modal volumes: + + - `codegen-oss-input-volume`: For uploading and reloading CSV inputs. + - `codegen-oss-repo-volume`: For caching repository data during parsing. + The repository and input volume names are configurable via environment variables (`CODEGEN_MODAL_REPO_VOLUME` and `CODEGEN_MODAL_INPUT_VOLUME`). + +- **Secrets Handling:** + The script loads various credentials via Modal secrets. It first checks for a pre-configured Modal secret (`codegen-oss-bucket-credentials` configurable via environment variable `CODEGEN_MODAL_SECRET_NAME`) and falls back to dynamically created Modal secret from local `.env` or environment variables if not found. + +- **Entrypoint Parameters:** + The main function supports multiple source types: + + - **csv:** Uploads a CSV file (`--csv-file input.csv`) for batch processing. + - **single:** Parses a single repository specified by its URL (`--single-url "https://github.com/codegen-sh/codegen-sdk.git"`) and an optional commit hash (`--single-commit ...`) + - **github:** Uses GitHub settings, language (`--github-language python`) and heuristic (`--github-heuristic stars`) to query for top repositories. + +- **Result Storage:** + Upon completion, logs and metrics are automatically uploaded to the S3 bucket specified by the environment variable `BUCKET_NAME` (default: `codegen-oss-parse`). This allows for centralized storage and easy retrieval of run outputs. The AWS Credentials provided in the secret are used for this operation. + +______________________________________________________________________ + +## Extensibility + +**Adding New Sources:** + +You can define additional repository sources by subclassing `RepoSource` and providing a corresponding settings class. Make sure to set the `source_type` and register your new source by following the pattern established in `CSVInputSource` or `GithubSource`. + +**Improving Testing:** + +The detailed metrics collected can help you understand where parsing failures occur or where performance lags. Use these insights to improve error handling and optimize the codegen parsing logic. + +**Containerization and Automation:** + +There is a Dockerfile that can be used to create an image capable of running the parse tests. Runtime environment variables can be used to configure the run and output. + +**Input & Configuration** + +Explore a better CLI for providing options to the Modal run. + +______________________________________________________________________ + +## Example Log Output + +```shell +[codegen-on-oss*] codegen/codegen-on-oss/$ uv run cgparse run --source csv + 21:32:36 INFO Cloning repository https://github.com/JohnSnowLabs/spark-nlp.git + 21:36:57 INFO { + "profile_name": "https://github.com/JohnSnowLabs/spark-nlp.git", + "step": "codebase_init", + "delta_time": 7.186550649999845, + "cumulative_time": 7.186550649999845, + "cpu_time": 180.3553702, + "memory_usage": 567525376, + "memory_delta": 317095936, + "error": null +} + 21:36:58 INFO { + "profile_name": "https://github.com/JohnSnowLabs/spark-nlp.git", + "step": "post_init_validation", + "delta_time": 0.5465090990001045, + "cumulative_time": 7.733059748999949, + "cpu_time": 180.9174761, + "memory_usage": 569249792, + "memory_delta": 1724416, + "error": null +} + 21:36:58 ERROR Repository: https://github.com/JohnSnowLabs/spark-nlp.git +Traceback (most recent call last): + + File "/home/codegen/codegen/codegen-on-oss/.venv/bin/cgparse", line 10, in + sys.exit(cli()) + │ │ └ + │ └ + └ + File "/home/codegen/codegen/codegen-on-oss/.venv/lib/python3.12/site-packages/click/core.py", line 1161, in __call__ + return self.main(*args, **kwargs) + │ │ │ └ {} + │ │ └ () + │ └ + └ + File "/home/codegen/codegen/codegen-on-oss/.venv/lib/python3.12/site-packages/click/core.py", line 1082, in main + rv = self.invoke(ctx) + │ │ └ + │ └ + └ + File "/home/codegen/codegen/codegen-on-oss/.venv/lib/python3.12/site-packages/click/core.py", line 1697, in invoke + return _process_result(sub_ctx.command.invoke(sub_ctx)) + │ │ │ │ └ + │ │ │ └ + │ │ └ + │ └ + └ ._process_result at 0x7f466597fb00> + File "/home/codegen/codegen/codegen-on-oss/.venv/lib/python3.12/site-packages/click/core.py", line 1443, in invoke + return ctx.invoke(self.callback, **ctx.params) + │ │ │ │ │ └ {'source': 'csv', 'output_path': 'metrics.csv', 'error_output_path': 'errors.log', 'cache_dir': PosixPath('/home/.cache... + │ │ │ │ └ + │ │ │ └ + │ │ └ + │ └ + └ + File "/home/codegen/codegen/codegen-on-oss/.venv/lib/python3.12/site-packages/click/core.py", line 788, in invoke + return __callback(*args, **kwargs) + │ └ {'source': 'csv', 'output_path': 'metrics.csv', 'error_output_path': 'errors.log', 'cache_dir': PosixPath('/home/.cache... + └ () + + File "/home/codegen/codegen/codegen-on-oss/codegen_on_oss/cli.py", line 121, in run + parser.parse(repo_url) + │ │ └ 'https://github.com/JohnSnowLabs/spark-nlp.git' + │ └ + └ + + File "/home/codegen/codegen/codegen-on-oss/codegen_on_oss/parser.py", line 52, in parse + with self.metrics_profiler.start_profiler( + │ │ └ + │ └ + └ + + File "/home/.local/share/uv/python/cpython-3.12.6-linux-x86_64-gnu/lib/python3.12/contextlib.py", line 158, in __exit__ + self.gen.throw(value) + │ │ │ └ ParseRunError() + │ │ └ + │ └ + └ + +> File "/home/codegen/codegen/codegen-on-oss/codegen_on_oss/metrics.py", line 41, in start_profiler + yield profile + └ + + File "/home/codegen/codegen/codegen-on-oss/codegen_on_oss/parser.py", line 64, in parse + raise ParseRunError(validation_status) + │ └ + └ + +codegen_on_oss.parser.ParseRunError: LOW_IMPORT_RESOLUTION_RATE + 21:36:58 INFO { + "profile_name": "https://github.com/JohnSnowLabs/spark-nlp.git", + "step": "TOTAL", + "delta_time": 7.740976418000173, + "cumulative_time": 7.740976418000173, + "cpu_time": 180.9221699, + "memory_usage": 569249792, + "memory_delta": 0, + "error": "LOW_IMPORT_RESOLUTION_RATE" +} + 21:36:58 INFO Cloning repository https://github.com/Lightning-AI/lightning.git + 21:37:53 INFO { + "profile_name": "https://github.com/Lightning-AI/lightning.git", + "step": "codebase_init", + "delta_time": 24.256577352999557, + "cumulative_time": 24.256577352999557, + "cpu_time": 211.3604081, + "memory_usage": 1535971328, + "memory_delta": 966184960, + "error": null +} + 21:37:53 INFO { + "profile_name": "https://github.com/Lightning-AI/lightning.git", + "step": "post_init_validation", + "delta_time": 0.137609629000508, + "cumulative_time": 24.394186982000065, + "cpu_time": 211.5082702, + "memory_usage": 1536241664, + "memory_delta": 270336, + "error": null +} + 21:37:53 INFO { + "profile_name": "https://github.com/Lightning-AI/lightning.git", + "step": "TOTAL", + "delta_time": 24.394700584999555, + "cumulative_time": 24.394700584999555, + "cpu_time": 211.5088282, + "memory_usage": 1536241664, + "memory_delta": 0, + "error": null +} +``` + +## Example Metrics Output + +| profile_name | step | delta_time | cumulative_time | cpu_time | memory_usage | memory_delta | error | +| ---------------------- | -------------------- | ------------------ | ------------------ | ----------- | ------------ | ------------ | -------------------------- | +| JohnSnowLabs/spark-nlp | codebase_init | 7.186550649999845 | 7.186550649999845 | 180.3553702 | 567525376 | 317095936 | | +| JohnSnowLabs/spark-nlp | post_init_validation | 0.5465090990001045 | 7.733059748999949 | 180.9174761 | 569249792 | 1724416 | | +| JohnSnowLabs/spark-nlp | TOTAL | 7.740976418000173 | 7.740976418000173 | 180.9221699 | 569249792 | 0 | LOW_IMPORT_RESOLUTION_RATE | +| Lightning-AI/lightning | codebase_init | 24.256577352999557 | 24.256577352999557 | 211.3604081 | 1535971328 | 966184960 | | +| Lightning-AI/lightning | post_init_validation | 0.137609629000508 | 24.394186982000065 | 211.5082702 | 1536241664 | 270336 | | +| Lightning-AI/lightning | TOTAL | 24.394700584999555 | 24.394700584999555 | 211.5088282 | 1536241664 | 0 | | diff --git a/codegen-on-oss/codecov.yaml b/codegen-on-oss/codecov.yaml new file mode 100644 index 000000000..058cfb765 --- /dev/null +++ b/codegen-on-oss/codecov.yaml @@ -0,0 +1,9 @@ +coverage: + range: 70..100 + round: down + precision: 1 + status: + project: + default: + target: 90% + threshold: 0.5% diff --git a/codegen-on-oss/codegen_modal_deploy.py b/codegen-on-oss/codegen_modal_deploy.py new file mode 100644 index 000000000..6aa3b3253 --- /dev/null +++ b/codegen-on-oss/codegen_modal_deploy.py @@ -0,0 +1,74 @@ +import sys +from pathlib import Path + +import modal +from loguru import logger + +from codegen_on_oss.cache import cachedir +from codegen_on_oss.metrics import MetricsProfiler +from codegen_on_oss.outputs.sql_output import PostgresSQLOutput +from codegen_on_oss.parser import CodegenParser + +app = modal.App("codegen-oss-parse") + + +codegen_repo_volume = modal.Volume.from_name( + "codegen-oss-repo-volume", + create_if_missing=True, +) + + +aws_secrets = modal.Secret.from_name( + "codegen-oss-parse-secrets", +) + + +@app.function( + name="parse_repo", + concurrency_limit=10, + cpu=4, + memory=16384, + timeout=3600 * 8, + secrets=[aws_secrets], + volumes={ + str(cachedir.absolute()): codegen_repo_volume, + }, + proxy=modal.Proxy.from_name("codegen-parse-proxy"), + image=modal.Image.debian_slim(python_version="3.13") + .pip_install("uv") + .apt_install("git") # required by codegen sdk + .env({"PATH": "/app/.venv/bin:$PATH"}) + .workdir("/app") + .add_local_file("uv.lock", remote_path="/app/uv.lock", copy=True) + .add_local_file("pyproject.toml", remote_path="/app/pyproject.toml", copy=True) + .run_commands("uv sync --frozen --no-install-project --extra sql") + .add_local_python_source("codegen_on_oss", copy=True), + # .add_local_python_source("codegen_on_oss"), + # .add_local_dir("codegen_on_oss", remote_path="/app/codegen_on_oss"), +) +def parse_repo( + repo_url: str, + commit_hash: str | None, + language: str | None = None, +): + """ + Parse repositories on Modal. + + Args: + repo_url: The URL of the repository to parse. + commit_hash: The commit hash of the repository to parse. + """ + logger.add(sys.stdout, format="{time: HH:mm:ss} {level} {message}", level="DEBUG") + + output = PostgresSQLOutput(modal_function_call_id=modal.current_function_call_id()) + metrics_profiler = MetricsProfiler(output) + parser = CodegenParser(Path(cachedir) / "repositories", metrics_profiler) + # Refresh any updating repo data from other instances + codegen_repo_volume.reload() + try: + parser.parse(repo_url, language, commit_hash) + except Exception as e: + logger.exception(f"Error parsing repository {repo_url}: {e}") + finally: + # Commit any cache changes to the repo volume + codegen_repo_volume.commit() diff --git a/codegen-on-oss/codegen_modal_run.py b/codegen-on-oss/codegen_modal_run.py new file mode 100644 index 000000000..ab0ad8ecb --- /dev/null +++ b/codegen-on-oss/codegen_modal_run.py @@ -0,0 +1,29 @@ +import modal + +from codegen_on_oss.sources import GithubSettings, GithubSource + +app = modal.App("codegen-oss-parse") + + +@app.local_entrypoint() +def main( + languages: str = "python,typescript", + heuristic: str = "stars", + num_repos: int = 100, +): + """ + Main entrypoint for the parse app. + """ + parse_repo_on_modal_fn = modal.Function.from_name("codegen-oss-parse", "parse_repo") + for language in languages.split(","): + repo_source = GithubSource( + GithubSettings( + language=language.strip(), heuristic=heuristic, num_repos=num_repos + ) + ) + for repo_url, commit_hash in repo_source: + parse_repo_on_modal_fn.spawn( + repo_url=repo_url, + commit_hash=commit_hash, + language=language, + ) diff --git a/codegen-on-oss/codegen_on_oss/__init__.py b/codegen-on-oss/codegen_on_oss/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/codegen-on-oss/codegen_on_oss/bucket_store.py b/codegen-on-oss/codegen_on_oss/bucket_store.py new file mode 100644 index 000000000..f068fd691 --- /dev/null +++ b/codegen-on-oss/codegen_on_oss/bucket_store.py @@ -0,0 +1,26 @@ +from datetime import datetime +from importlib.metadata import version +from typing import TYPE_CHECKING + +from boto3 import client + +if TYPE_CHECKING: + from types_boto3_s3 import S3Client + + +class BucketStore: + s3_client: "S3Client" + + def __init__(self, bucket_name: str): + self.bucket_name = bucket_name + self.s3_client = client("s3") + self.key_prefix: str = str(version("codegen")) + + def upload_file(self, local_path: str, remote_path: str) -> str: + key = f"{self.key_prefix}/{datetime.now().strftime('%Y-%m-%d-%H-%M-%S')}/{remote_path}" + self.s3_client.upload_file( + local_path, + self.bucket_name, + key, + ) + return key diff --git a/codegen-on-oss/codegen_on_oss/cache.py b/codegen-on-oss/codegen_on_oss/cache.py new file mode 100644 index 000000000..6f1346a98 --- /dev/null +++ b/codegen-on-oss/codegen_on_oss/cache.py @@ -0,0 +1,5 @@ +from pathlib import Path + +from platformdirs import user_cache_dir + +cachedir = Path(user_cache_dir("codegen-on-oss", "codegen")) diff --git a/codegen-on-oss/codegen_on_oss/cli.py b/codegen-on-oss/codegen_on_oss/cli.py new file mode 100644 index 000000000..c1807d13e --- /dev/null +++ b/codegen-on-oss/codegen_on_oss/cli.py @@ -0,0 +1,128 @@ +import sys +from pathlib import Path + +import click +from loguru import logger + +from codegen_on_oss.cache import cachedir +from codegen_on_oss.metrics import MetricsProfiler +from codegen_on_oss.outputs.csv_output import CSVOutput +from codegen_on_oss.parser import CodegenParser +from codegen_on_oss.sources import RepoSource, all_sources + +logger.remove(0) + + +@click.group() +def cli(): + pass + + +@cli.command(name="run-one") +@click.argument("url", type=str) +@click.option( + "--cache-dir", + type=click.Path(dir_okay=True), + help="Cache directory", + default=cachedir, +) +@click.option( + "--output-path", + type=click.Path(dir_okay=True), + help="Output path", + default="metrics.csv", +) +@click.option( + "--commit-hash", + type=str, + help="Commit hash to parse", +) +@click.option( + "--error-output-path", + type=click.Path(dir_okay=True), + help="Error output path", + default=cachedir / "errors.log", +) +@click.option( + "--debug", + is_flag=True, + help="Debug mode", +) +def run_one( + url: str, + cache_dir: str | Path = str(cachedir), + output_path: str = "metrics.csv", + commit_hash: str | None = None, + error_output_path: Path = str(cachedir / "errors.log"), + debug: bool = False, +): + """ + Parse a repository with codegen + """ + logger.add(error_output_path, level="ERROR") + logger.add(sys.stdout, level="DEBUG" if debug else "INFO") + output = CSVOutput(MetricsProfiler.fields(), output_path) + metrics_profiler = MetricsProfiler(output) + + parser = CodegenParser(Path(cache_dir) / "repositories", metrics_profiler) + parser.parse(url, commit_hash) + + +@cli.command() +@click.option( + "--source", + type=click.Choice(list(all_sources.keys())), + default="csv", +) +@click.option( + "--output-path", + type=click.Path(dir_okay=True), + help="Output path", + default="metrics.csv", +) +@click.option( + "--error-output-path", + type=click.Path(dir_okay=True), + help="Error output path", + default="errors.log", +) +@click.option( + "--cache-dir", + type=click.Path(dir_okay=True), + help="Cache directory", + default=cachedir, +) +@click.option( + "--debug", + is_flag=True, + help="Debug mode", +) +def run( + source: str, + output_path: str, + error_output_path: str, + cache_dir: str, + debug: bool, +): + """ + Run codegen parsing pipeline on repositories from a given repository source. + """ + logger.add( + error_output_path, format="{time: HH:mm:ss} {level} {message}", level="ERROR" + ) + logger.add( + sys.stdout, + format="{time: HH:mm:ss} {level} {message}", + level="DEBUG" if debug else "INFO", + ) + + repo_source = RepoSource.from_source_type(source) + output = CSVOutput(MetricsProfiler.fields(), output_path) + metrics_profiler = MetricsProfiler(output) + parser = CodegenParser(Path(cache_dir) / "repositories", metrics_profiler) + for repo_url, commit_hash in repo_source: + parser.parse(repo_url, commit_hash) + + +if __name__ == "__main__": + cli() diff --git a/codegen-on-oss/codegen_on_oss/errors.py b/codegen-on-oss/codegen_on_oss/errors.py new file mode 100644 index 000000000..7e00dc085 --- /dev/null +++ b/codegen-on-oss/codegen_on_oss/errors.py @@ -0,0 +1,6 @@ +class ParseRunError(Exception): + pass + + +class PostValidationError(ParseRunError): + pass diff --git a/codegen-on-oss/codegen_on_oss/metrics.py b/codegen-on-oss/codegen_on_oss/metrics.py new file mode 100644 index 000000000..d77b4e686 --- /dev/null +++ b/codegen-on-oss/codegen_on_oss/metrics.py @@ -0,0 +1,198 @@ +import json +import os +import time +from collections.abc import Generator +from contextlib import contextmanager +from importlib.metadata import version +from typing import TYPE_CHECKING, Any + +import psutil + +from codegen_on_oss.errors import ParseRunError +from codegen_on_oss.outputs.base import BaseOutput + +if TYPE_CHECKING: + # Logger only available in type checking context. + from loguru import Logger # type: ignore[attr-defined] + + +codegen_version = str(version("codegen")) + + +class MetricsProfiler: + """ + A helper to record performance metrics across multiple profiles and write them to a CSV. + + Usage: + + metrics_profiler = MetricsProfiler(output_path="metrics.csv") + + with metrics_profiler.start_profiler(name="profile_1", language="python") as profile: + # Some code block... + profile.measure("step 1") + # More code... + profile.measure("step 2") + + # The CSV "metrics.csv" now contains the measurements for profile_1. + """ + + def __init__(self, output: BaseOutput): + self.output = output + + @contextmanager + def start_profiler( + self, name: str, revision: str, language: str | None, logger: "Logger" + ) -> Generator["MetricsProfile", None, None]: + """ + Starts a new profiling session for a given profile name. + Returns a MetricsProfile instance that you can use to mark measurements. + """ + profile = MetricsProfile(name, revision, language, self.output, logger) + error_msg: str | None = None + try: + yield profile + except ParseRunError as e: + logger.error(f"Repository: {name} {e.args[0]}") # noqa: TRY400 + error_msg = e.args[0] + except Exception as e: + logger.exception(f"Repository: {name}") + error_msg = f"Unhandled Exception {type(e)}" + + finally: + profile.finish(error=error_msg) + + @classmethod + def fields(cls) -> list[str]: + return [ + "repo", + "revision", + "language", + "action", + "codegen_version", + "delta_time", + "cumulative_time", + "cpu_time", + "memory_usage", + "memory_delta", + "error", + ] + + +class MetricsProfile: + """ + Context-managed profile that records measurements at each call to `measure()`. + It tracks the wall-clock duration, CPU time, and memory usage (with delta) at the time of the call. + Upon exiting the context, it also writes all collected metrics, including the total time, + to a CSV file. + """ + + if TYPE_CHECKING: + logger: "Logger" + measurements: list[dict[str, Any]] + + def __init__( + self, + name: str, + revision: str, + language: str, + output: BaseOutput, + logger: "Logger", + ): + self.name = name + self.revision = revision + self.language = language + self.output = output + self.logger = logger + + # Capture initial metrics. + self.start_time = time.perf_counter() + self.start_cpu = time.process_time() + self.start_mem = int( + psutil.Process(os.getpid()).memory_info().rss / (1024 * 1024) + ) + + # For delta calculations, store the last measurement values. + self.last_measure_time = self.start_time + self.last_measure_mem = self.start_mem + + def reset_checkpoint(self): + # Update last measurement time and memory for the next delta. + self.last_measure_time = time.perf_counter() + self.last_measure_mem = self.start_mem + + def measure(self, action_name: str): + """ + Records a measurement for the given step. The measurement includes: + - Delta wall-clock time since the last measurement or the start, + - Cumulative wall-clock time since the start, + - The current CPU usage of the process (using time.process_time()), + - The current memory usage (RSS in bytes), + - The memory delta (difference from the previous measurement). + """ + current_time = time.perf_counter() + current_cpu = float(time.process_time()) + current_mem = int(psutil.Process(os.getpid()).memory_info().rss / (1024 * 1024)) + + # Calculate time deltas. + delta_time = current_time - self.last_measure_time + cumulative_time = current_time - self.start_time + + # Calculate memory delta. + memory_delta = current_mem - self.last_measure_mem + + # Record the measurement. + measurement = { + "repo": self.name, + "revision": self.revision, + "codegen_version": codegen_version, + "action": action_name, + "language": self.language, + "delta_time": delta_time, + "cumulative_time": cumulative_time, + "cpu_time": current_cpu, # CPU usage at this point. + "memory_usage": current_mem, + "memory_delta": memory_delta, + "error": None, + } + self.write_output(measurement) + + # Update last measurement time and memory for the next delta. + self.last_measure_time = current_time + self.last_measure_mem = current_mem + + def finish(self, error: str | None = None): + """ + Called automatically when the profiling context is exited. + This method records a final measurement (for the total duration) and + writes all collected metrics to the CSV file. + """ + finish_time = time.perf_counter() + finish_cpu = float(time.process_time()) + finish_mem = int(psutil.Process(os.getpid()).memory_info().rss / (1024 * 1024)) + + total_duration = finish_time - self.start_time + + # Calculate final memory delta. + memory_delta = finish_mem - self.last_measure_mem + + # Record the overall profile measurement. + self.write_output({ + "repo": self.name, + "revision": self.revision, + "codegen_version": codegen_version, + "language": self.language, + "action": "total_parse", + "delta_time": total_duration, + "cumulative_time": total_duration, + "cpu_time": finish_cpu, + "memory_usage": finish_mem, + "memory_delta": memory_delta, + "error": error, + }) + + def write_output(self, measurement: dict[str, Any]): + """ + Writes all measurements to the CSV file using CSVOutput. + """ + self.logger.info(json.dumps(measurement, indent=4)) + self.output.write_output(measurement) diff --git a/codegen-on-oss/codegen_on_oss/outputs/__init__.py b/codegen-on-oss/codegen_on_oss/outputs/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/codegen-on-oss/codegen_on_oss/outputs/base.py b/codegen-on-oss/codegen_on_oss/outputs/base.py new file mode 100644 index 000000000..d984fe45e --- /dev/null +++ b/codegen-on-oss/codegen_on_oss/outputs/base.py @@ -0,0 +1,16 @@ +import json +from typing import Any + +from loguru import logger + + +class BaseOutput: + """ + BaseOutput is a class that defines the interface for all output classes. + """ + + def __init__(self, fields: list[str]): + self.fields = fields + + def write_output(self, value: dict[str, Any]): + logger.info(json.dumps(value, indent=4)) diff --git a/codegen-on-oss/codegen_on_oss/outputs/csv_output.py b/codegen-on-oss/codegen_on_oss/outputs/csv_output.py new file mode 100644 index 000000000..09bcce82f --- /dev/null +++ b/codegen-on-oss/codegen_on_oss/outputs/csv_output.py @@ -0,0 +1,30 @@ +import csv +import os +from pathlib import Path +from typing import Any + +from codegen_on_oss.outputs.base import BaseOutput + + +class CSVOutput(BaseOutput): + """ + CSVOutput is a class that writes output to a CSV file. + """ + + def __init__(self, fields: list[str], output_path: str): + super().__init__(fields) + self.output_path = output_path + + def write_output(self, value: dict[str, Any]): + """ + Writes a dictionary to a CSV file. If the file does not exist, it creates it and writes headers; otherwise, it appends. + """ + file_exists = os.path.isfile(self.output_path) + if not file_exists: + Path(self.output_path).parent.mkdir(parents=True, exist_ok=True) + + with open(self.output_path, mode="a", newline="") as csv_file: + writer = csv.DictWriter(csv_file, fieldnames=self.fields) + if not file_exists: + writer.writeheader() + writer.writerow(value) diff --git a/codegen-on-oss/codegen_on_oss/outputs/sql_output.py b/codegen-on-oss/codegen_on_oss/outputs/sql_output.py new file mode 100644 index 000000000..545ce12ad --- /dev/null +++ b/codegen-on-oss/codegen_on_oss/outputs/sql_output.py @@ -0,0 +1,113 @@ +from typing import Any + +from pydantic import computed_field +from pydantic_settings import BaseSettings, SettingsConfigDict +from sqlalchemy import Column, Float, Integer, String, UniqueConstraint +from sqlalchemy.dialects.postgresql import insert +from sqlalchemy.engine import create_engine +from sqlalchemy.orm import DeclarativeBase, sessionmaker + +from .base import BaseOutput + + +class Base(DeclarativeBase): + pass + + +class SQLSettings(BaseSettings): + model_config = SettingsConfigDict(env_prefix="POSTGRESQL_") + host: str = "localhost" + port: int = 5432 + user: str = "postgres" + password: str = "postgres" # noqa: S105 + database: str = "postgres" + dialect: str = "postgresql" + + @computed_field + def url(self) -> str: + return f"{self.dialect}://{self.user}:{self.password}@{self.host}:{self.port}/{self.database}" + + +def get_session_maker(settings: SQLSettings): + engine = create_engine(settings.url) + return sessionmaker(bind=engine) + + +class ParseMetrics(Base): + __tablename__ = "parse_metrics" + + id = Column(Integer, primary_key=True) + repo = Column(String, index=True) + revision = Column(String, index=True) + language = Column(String, index=True) + action = Column(String, index=True) + codegen_version = Column(String, index=True) + delta_time = Column(Float, index=True) + cumulative_time = Column(Float, index=True) + cpu_time = Column(Float, index=True) + memory_usage = Column(Integer, index=True) + memory_delta = Column(Integer, index=True) + error = Column(String, index=True) + modal_function_call_id = Column(String) + + __table_args__ = ( + UniqueConstraint( + "repo", + "revision", + "action", + "codegen_version", + name="uq_repo_revision_action_codegen_version", + ), + ) + + +class PostgresSQLOutput(BaseOutput): + extras: dict[str, Any] + + def __init__(self, modal_function_call_id: str): + super().__init__( + fields=[ + "repo", + "revision", + "action", + "codegen_version", + "delta_time", + "cumulative_time", + "cpu_time", + "memory_usage", + "memory_delta", + "error", + "modal_function_call_id", + ] + ) + self.modal_function_call_id = modal_function_call_id + settings = SQLSettings() + self.session_maker = get_session_maker(settings) + + def write_output(self, value: dict[str, Any]): + with self.session_maker() as session: + stmt = insert(ParseMetrics).values( + **value, modal_function_call_id=self.modal_function_call_id + ) + stmt = stmt.on_conflict_do_update( + index_elements=[ + ParseMetrics.repo, + ParseMetrics.revision, + ParseMetrics.action, + ParseMetrics.codegen_version, + ], + set_={ + k: v + for k, v in value.items() + if k + not in ( + "repo", + "revision", + "action", + "codegen_version", + "id", + ) + }, + ) + session.execute(stmt) + session.commit() diff --git a/codegen-on-oss/codegen_on_oss/parser.py b/codegen-on-oss/codegen_on_oss/parser.py new file mode 100644 index 000000000..46ee45277 --- /dev/null +++ b/codegen-on-oss/codegen_on_oss/parser.py @@ -0,0 +1,86 @@ +import gc +import sys +from pathlib import Path +from typing import TYPE_CHECKING +from urllib.parse import urlparse + +from codegen import Codebase +from codegen.sdk.codebase.validation import ( + PostInitValidationStatus, + post_init_validation, +) +from codegen.sdk.extensions.utils import uncache_all +from loguru import logger + +from codegen_on_oss.errors import PostValidationError +from codegen_on_oss.metrics import MetricsProfiler + +if TYPE_CHECKING: + from codegen.sdk.codebase.config import ProjectConfig + + +class CodegenParser: + if TYPE_CHECKING: + repo_dir: Path + metrics_profiler: MetricsProfiler + + def __init__(self, repo_dir: Path, metrics_profiler: MetricsProfiler): + self.repo_dir = repo_dir + self.repo_dir.mkdir(parents=True, exist_ok=True) + self.metrics_profiler = metrics_profiler + sys.setrecursionlimit(10000000) + + def parse( + self, url: str, language: str | None = None, commit_hash: str | None = None + ): + """ + Parse the repository at the given URL. MetricsProfiler is used to profile the parse and + post_init_validation. + + Args: + url (str): The URL of the repository to parse. + commit_hash (str | None): The commit hash to parse. If None, the head commit will be used. + + """ + repo_name = urlparse(url).path.removeprefix("/").removesuffix(".git") + repo_dest_path = Path(*repo_name.split("/")) + repo_dest_path = self.repo_dir / repo_dest_path + repo_logger = logger.bind(repo_name=repo_name) + + self.gc() + + with self.metrics_profiler.start_profiler( + name=repo_name, revision=commit_hash, language=language, logger=repo_logger + ) as profile: + # Awkward design here is due to adapting to using Codebase.from_repo() and parsing done in __init__. + # May want to consider __init__ with parsed state from a separate input handling / parser class. + class ProfiledCodebase(Codebase): + def __init__(self, *args, projects: "list[ProjectConfig]", **kwargs): + # Since Codebase is performing git ops, we need to extract commit if it wasn't explicitly provided. + profile.revision = ( + profile.revision + or projects[ + 0 + ].repo_operator.head_commit # assume projects is not empty + ) + # from_repo would have performed any repo initialization necessary + # It could pull or use cached + profile.reset_checkpoint() + super().__init__(*args, projects=projects, **kwargs) + profile.language = profile.language or str(self.language).lower() + profile.measure("codebase_parse") + validation_status = post_init_validation(self) + + profile.measure("post_init_validation") + if validation_status is PostInitValidationStatus.SUCCESS: + return + else: + raise PostValidationError(validation_status) + + ProfiledCodebase.from_repo( + repo_name, tmp_dir=str(self.repo_dir.absolute()), commit=commit_hash + ) + + def gc(self): + uncache_all() + gc.collect() diff --git a/codegen-on-oss/codegen_on_oss/sources/__init__.py b/codegen-on-oss/codegen_on_oss/sources/__init__.py new file mode 100644 index 000000000..3b5cbffd6 --- /dev/null +++ b/codegen-on-oss/codegen_on_oss/sources/__init__.py @@ -0,0 +1,16 @@ +from .base import RepoSource, SourceSettings, all_sources +from .csv_source import CSVInputSettings, CSVInputSource +from .github_source import GithubSettings, GithubSource +from .single_source import SingleSettings, SingleSource + +__all__ = [ + "CSVInputSettings", + "CSVInputSource", + "GithubSettings", + "GithubSource", + "RepoSource", + "SingleSettings", + "SingleSource", + "SourceSettings", + "all_sources", +] diff --git a/codegen-on-oss/codegen_on_oss/sources/base.py b/codegen-on-oss/codegen_on_oss/sources/base.py new file mode 100644 index 000000000..48c6e89fd --- /dev/null +++ b/codegen-on-oss/codegen_on_oss/sources/base.py @@ -0,0 +1,65 @@ +from collections.abc import Iterator +from typing import TYPE_CHECKING, ClassVar, Generic, TypeVar + +from pydantic_settings import BaseSettings, SettingsConfigDict + + +class SourceSettings(BaseSettings): + """ + SourceSettings is a class that contains the settings for a source. + """ + + model_config = SettingsConfigDict(env_prefix="SOURCE_") + num_repos: int = 50 + + +SettingsType = TypeVar("SettingsType", bound=SourceSettings) + +all_sources: dict[str, type["RepoSource"]] = {} + + +class DuplicateSource(ValueError): + """ + DuplicateSource is an error that occurs when a source type is defined twice. + """ + + def __init__(self, source_type: str) -> None: + super().__init__(f"Source type {source_type} already exists") + + +class RepoSource(Generic[SettingsType]): + """ + RepoSource is a class that contains the configuration for a source. + """ + + source_type: ClassVar[str] + settings_cls: ClassVar[type[SourceSettings]] + + if TYPE_CHECKING: + settings: SourceSettings + + def __init_subclass__(cls) -> None: + if not hasattr(cls, "source_type"): + raise NotImplementedError("source_type must be defined") + + if not hasattr(cls, "settings_cls"): + raise NotImplementedError("settings_cls must be defined") + + if cls.source_type in all_sources: + raise DuplicateSource(cls.source_type) + all_sources[cls.source_type] = cls + + def __init__(self, settings: SourceSettings | None = None) -> None: + self.settings = settings or self.settings_cls() + + @classmethod + def from_source_type( + cls, source_type: str, settings: SourceSettings | None = None + ) -> "RepoSource": + return all_sources[source_type](settings) + + def __iter__(self) -> Iterator[tuple[str, str | None]]: + """ + Yields URL and optional commit hash of repositories. + """ + raise NotImplementedError diff --git a/codegen-on-oss/codegen_on_oss/sources/csv_source.py b/codegen-on-oss/codegen_on_oss/sources/csv_source.py new file mode 100644 index 000000000..14c003ac3 --- /dev/null +++ b/codegen-on-oss/codegen_on_oss/sources/csv_source.py @@ -0,0 +1,39 @@ +import csv +from collections.abc import Iterator +from pathlib import Path + +from pydantic import field_validator + +from .base import RepoSource, SourceSettings + + +class CSVInputSettings(SourceSettings, env_prefix="CSV_"): + """ + CSVInputSettings is a class that contains the settings for a CSVInputSource. + """ + + file_path: Path = Path("input.csv") + + @field_validator("file_path", mode="after") + def validate_file_path(cls, v): + if not v.exists(): + msg = f"File {v} does not exist" + raise ValueError(msg) + return v + + +class CSVInputSource(RepoSource): + """ + CSVInputSource is a source that reads URLs from a CSV file. + """ + + source_type = "csv" + settings_cls = CSVInputSettings + + def __iter__(self) -> Iterator[tuple[str, str | None]]: + with open(self.settings.file_path) as f: + reader = csv.DictReader(f, fieldnames=["url", "commit_hash"]) + next(reader) + + for row in reader: + yield row["url"], row.get("commit_hash") or None diff --git a/codegen-on-oss/codegen_on_oss/sources/github_source.py b/codegen-on-oss/codegen_on_oss/sources/github_source.py new file mode 100644 index 000000000..7c9f3b3a6 --- /dev/null +++ b/codegen-on-oss/codegen_on_oss/sources/github_source.py @@ -0,0 +1,59 @@ +from collections.abc import Iterator +from typing import TYPE_CHECKING, ClassVar, Literal + +from github import Auth, Github # nosemgrep + +from .base import RepoSource, SourceSettings + + +class GithubSettings(SourceSettings, env_prefix="GITHUB_"): + """ + Settings for the Github source. + """ + + language: Literal["python", "typescript"] = "python" + heuristic: Literal[ + "stars", + "forks", + "updated", + # "watchers", + # "contributors", + # "commit_activity", + # "issues", + # "dependency", + ] = "stars" + token: str | None = None + num_repos: int = 50 + + +class GithubSource(RepoSource[GithubSettings]): + """ + Source for Github repositories via Github Search API + """ + + if TYPE_CHECKING: + github_client: Github + settings: GithubSettings + + source_type: ClassVar[str] = "github" + settings_cls: ClassVar[type[GithubSettings]] = GithubSettings + + def __init__(self, *args, **kwargs) -> None: + super().__init__(*args, **kwargs) + if self.settings.token is None: + self.github_client = Github() + else: + self.github_client = Github(auth=Auth.Token(self.settings.token)) + + def __iter__(self) -> Iterator[tuple[str, str | None]]: + repositories = self.github_client.search_repositories( + query=f"language:{self.settings.language}", + sort=self.settings.heuristic, + order="desc", + ) + + for idx, repository in enumerate(repositories): + if idx >= self.settings.num_repos: + break + commit = repository.get_commits()[0] + yield repository.clone_url, commit.sha diff --git a/codegen-on-oss/codegen_on_oss/sources/single_source.py b/codegen-on-oss/codegen_on_oss/sources/single_source.py new file mode 100644 index 000000000..f017b51fe --- /dev/null +++ b/codegen-on-oss/codegen_on_oss/sources/single_source.py @@ -0,0 +1,31 @@ +from collections.abc import Iterator +from typing import TYPE_CHECKING, ClassVar + +from github import Github # nosemgrep + +from .base import RepoSource, SourceSettings + + +class SingleSettings(SourceSettings, env_prefix="SINGLE_"): + """ + Settings for the Single source. + """ + + url: str + commit: str | None = None + + +class SingleSource(RepoSource[SingleSettings]): + """ + Source for a single repository. + """ + + if TYPE_CHECKING: + github_client: Github + settings: SingleSettings + + source_type: ClassVar[str] = "single" + settings_cls: ClassVar[type[SingleSettings]] = SingleSettings + + def __iter__(self) -> Iterator[tuple[str, str | None]]: + yield self.settings.url, self.settings.commit diff --git a/codegen-on-oss/docker-compose.yaml b/codegen-on-oss/docker-compose.yaml new file mode 100644 index 000000000..6abf28f70 --- /dev/null +++ b/codegen-on-oss/docker-compose.yaml @@ -0,0 +1,9 @@ +services: + codegen-benchmark: + image: codegen-benchmark + build: . + env_file: + - .env + command: ["tail", "-f", "/dev/null"] + volumes: + - .:/app diff --git a/codegen-on-oss/input.csv b/codegen-on-oss/input.csv new file mode 100644 index 000000000..f1c4e9719 --- /dev/null +++ b/codegen-on-oss/input.csv @@ -0,0 +1,2 @@ +repo_url, commit_hash +https://github.com/JohnSnowLabs/spark-nlp.git,7d2bed7647bec3878362a4b7ebbe43befeabe2ba diff --git a/codegen-on-oss/modal_run.py b/codegen-on-oss/modal_run.py new file mode 100644 index 000000000..26c87f8f1 --- /dev/null +++ b/codegen-on-oss/modal_run.py @@ -0,0 +1,151 @@ +import os +import sys +from pathlib import Path + +import modal +from loguru import logger + +from codegen_on_oss.bucket_store import BucketStore +from codegen_on_oss.cache import cachedir +from codegen_on_oss.metrics import MetricsProfiler +from codegen_on_oss.parser import CodegenParser +from codegen_on_oss.sources import RepoSource + +parse_app = modal.App("codegen-oss-parse") + + +codegen_repo_volume = modal.Volume.from_name( + os.getenv("CODEGEN_MODAL_REPO_VOLUME", "codegen-oss-repo-volume"), + create_if_missing=True, +) + + +codegen_input_volume = modal.Volume.from_name( + os.getenv("CODEGEN_MODAL_INPUT_VOLUME", "codegen-oss-input-volume"), + create_if_missing=True, +) + +try: + aws_secrets = modal.Secret.from_name( + os.getenv("CODEGEN_MODAL_SECRET_NAME", "codegen-oss-bucket-credentials") + ) +except modal.exception.NotFoundError: + if Path(".env").exists(): + aws_secrets = modal.Secret.from_dotenv() + else: + aws_secrets = modal.Secret.from_dict({ + "AWS_ACCESS_KEY_ID": os.getenv("AWS_ACCESS_KEY_ID"), + "AWS_SECRET_ACCESS_KEY": os.getenv("AWS_SECRET_ACCESS_KEY"), + "BUCKET_NAME": os.getenv("BUCKET_NAME"), + "GITHUB_TOKEN": os.getenv("GITHUB_TOKEN"), + }) + + +@parse_app.function( + cpu=4, + memory=16384, + timeout=3600 * 8, + secrets=[aws_secrets], + volumes={ + str(cachedir.absolute()): codegen_repo_volume, + "/app/inputs": codegen_input_volume, + }, + image=modal.Image.debian_slim(python_version="3.13") + .pip_install("uv") + .apt_install("git") # required by codegen sdk + .workdir("/app") + .add_local_file("uv.lock", remote_path="/app/uv.lock", copy=True) + .add_local_file("pyproject.toml", remote_path="/app/pyproject.toml", copy=True) + .run_commands("uv sync --frozen --no-install-project") + .env({"PATH": "/app/.venv/bin:$PATH"}) + .add_local_python_source("codegen_on_oss") + .add_local_dir("codegen_on_oss", remote_path="/app/codegen_on_oss"), +) +def parse_repo_on_modal( + source: str, + env: dict[str, str], + log_output_path: str = "output.logs", + metrics_output_path: str = "metrics.csv", +): + """ + Parse repositories on Modal. + + Args: + source: The source of the repositories to parse. + env: The environment variables to use. + log_output_path: The path to the log file. + metrics_output_path: The path to the metrics file. + """ + os.environ.update(env) + + logger.add( + log_output_path, + format="{time: HH:mm:ss} {level} {message}", + level="INFO", + ) + logger.add(sys.stdout, format="{time: HH:mm:ss} {level} {message}", level="DEBUG") + + repo_source = RepoSource.from_source_type(source) + metrics_profiler = MetricsProfiler(metrics_output_path) + + parser = CodegenParser(Path(cachedir) / "repositories", metrics_profiler) + for repo_url, commit_hash in repo_source: + # Refresh any updating repo data from other instances + codegen_repo_volume.reload() + try: + parser.parse(repo_url, commit_hash) + except Exception as e: + logger.exception(f"Error parsing repository {repo_url}: {e}") + finally: + # Commit any cache changes to the repo volume + codegen_repo_volume.commit() + + store = BucketStore(bucket_name=os.getenv("BUCKET_NAME", "codegen-oss-parse")) + log_key = store.upload_file(log_output_path, "output.logs") + metrics_key = store.upload_file(metrics_output_path, "metrics.csv") + + logger.info(f"Uploaded logs to {log_key} in bucket {store.bucket_name}") + logger.info(f"Uploaded metrics to {metrics_key} in bucket {store.bucket_name}") + + +@parse_app.local_entrypoint() +def main( + source: str = "csv", + csv_file: str = "input.csv", + single_url: str = "https://github.com/codegen-sh/codegen-sdk.git", + single_commit: str | None = None, + github_language: str = "python", + github_heuristic: str = "stars", + github_num_repos: int = 50, +): + """ + Main entrypoint for the parse app. + """ + + match source: + case "csv": + input_path = Path(csv_file).relative_to(".") + with codegen_input_volume.batch_upload(force=True) as b: + b.put_file(csv_file, input_path) + + env = { + "CSV_FILE_PATH": f"/app/inputs/{input_path}", + } + case "single": + env = {"SINGLE_URL": single_url} + if single_commit: + env["SINGLE_COMMIT"] = single_commit + case "github": + env = { + "GITHUB_LANGUAGE": github_language, + "GITHUB_HEURISTIC": github_heuristic, + "GITHUB_NUM_REPOS": str(github_num_repos), + } + case _: + msg = f"Invalid source: {source}" + raise ValueError(msg) + + return parse_repo_on_modal.remote( + source=source, + env=env, + ) diff --git a/codegen-on-oss/pyproject.toml b/codegen-on-oss/pyproject.toml new file mode 100644 index 000000000..b4227c454 --- /dev/null +++ b/codegen-on-oss/pyproject.toml @@ -0,0 +1,125 @@ +[project] +name = "codegen-on-oss" +version = "0.0.1" +description = "Testing codegen parsing on popular OSS repositories" +authors = [{ name = "Chris Lee", email = "clee@codegen.com" }] +readme = "README.md" +keywords = ['python'] +requires-python = ">=3.12,<4.0" +classifiers = [ + "Intended Audience :: Developers", + "Programming Language :: Python", + "Programming Language :: Python :: 3", + "Programming Language :: Python :: 3.12", + "Programming Language :: Python :: 3.13", + "Topic :: Software Development :: Libraries :: Python Modules", +] +dependencies = [ + "boto3>=1.36.21", + "click>=8.1.8", + "codegen>=0.6.2", + "loguru>=0.7.3", + "modal>=0.73.51", + "pydantic-settings>=2.7.1", + "pygithub>=2.5.0", +] + +[project.urls] +Repository = "https://github.com/codegen-sh/codegen-on-oss" + +[dependency-groups] +dev = [ + "pytest>=7.2.0", + "pre-commit>=2.20.0", + "tox-uv>=1.11.3", + "deptry>=0.22.0", + "mypy>=0.991", + "pytest-cov>=4.0.0", + "ruff>=0.9.2", + "types-boto3[s3]>=1.36.21", +] + +[project.scripts] +cgparse = "codegen_on_oss.cli:cli" + +[project.optional-dependencies] +sql = ["alembic>=1.14.1", "psycopg2-binary>=2.9.10", "sqlalchemy>=2.0.38"] + +[build-system] +requires = ["hatchling"] +build-backend = "hatchling.build" + +[tool.setuptools] +py-modules = ["codegen_on_oss"] + +[tool.mypy] +files = ["codegen_on_oss"] +disallow_untyped_defs = true +disallow_any_unimported = true +no_implicit_optional = true +check_untyped_defs = true +warn_return_any = true +warn_unused_ignores = true +show_error_codes = true + +[tool.pytest.ini_options] +testpaths = ["tests"] + +[tool.ruff] +target-version = "py312" +line-length = 88 +fix = true + +[tool.ruff.lint] +select = [ + # flake8-2020 + "YTT", + # flake8-bandit + "S", + # flake8-bugbear + "B", + # flake8-builtins + "A", + # flake8-comprehensions + "C4", + # flake8-debugger + "T10", + # flake8-simplify + "SIM", + # isort + "I", + # mccabe + "C90", + # pycodestyle + "E", + "W", + # pyflakes + "F", + # pygrep-hooks + "PGH", + # pyupgrade + "UP", + # ruff + "RUF", + # tryceratops + "TRY", +] +ignore = [ + # LineTooLong + "E501", + # DoNotAssignLambda + "E731", +] + +[tool.ruff.lint.per-file-ignores] +"tests/*" = ["S101"] + +[tool.ruff.format] +preview = true + +[tool.coverage.report] +skip_empty = true + +[tool.coverage.run] +branch = true +source = ["codegen_on_oss"] diff --git a/codegen-on-oss/scripts/create_db.py b/codegen-on-oss/scripts/create_db.py new file mode 100644 index 000000000..7b6179f06 --- /dev/null +++ b/codegen-on-oss/scripts/create_db.py @@ -0,0 +1,18 @@ +from pydantic_settings import SettingsConfigDict + +from codegen_on_oss.outputs.sql_output import Base, SQLSettings, get_session_maker + + +class DotEnvSQLSettings(SQLSettings): + model_config = SettingsConfigDict( + env_file=".env", + env_prefix="POSTGRESQL_", + extra="ignore", + ) + + +settings = DotEnvSQLSettings() +session_maker = get_session_maker(settings) + +with session_maker() as session: + Base.metadata.create_all(bind=session.bind) diff --git a/codegen-on-oss/scripts/db b/codegen-on-oss/scripts/db new file mode 100755 index 000000000..2adf25c4f --- /dev/null +++ b/codegen-on-oss/scripts/db @@ -0,0 +1,7 @@ +#! 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01:15:59 -0800 Subject: [PATCH 06/16] add: integrate with postgresql output --- .../run_swebench_modal_harness.py | 40 +++++++++---------- codegen-on-oss/codegen_modal_deploy.py | 6 ++- .../codegen_on_oss/outputs/sql_output.py | 39 +++++++++++++++++- 3 files changed, 59 insertions(+), 26 deletions(-) diff --git a/codegen-examples/examples/swebench_agent_run/run_swebench_modal_harness.py b/codegen-examples/examples/swebench_agent_run/run_swebench_modal_harness.py index 8bd6a8699..8a4b01d94 100644 --- a/codegen-examples/examples/swebench_agent_run/run_swebench_modal_harness.py +++ b/codegen-examples/examples/swebench_agent_run/run_swebench_modal_harness.py @@ -12,6 +12,7 @@ from typing import cast import modal +from codegen_on_oss.outputs.sql_output import SWEBenchSQLOutput from swebench.harness.constants import ( APPLY_PATCH_FAIL, APPLY_PATCH_PASS, @@ -73,7 +74,8 @@ def _get_sandbox(self, timeout: int | None = None): LOCAL_SANDBOX_ENTRYPOINT_PATH, REMOTE_SANDBOX_ENTRYPOINT_PATH, ), - timeout=120 * 60, # Much larger than default timeout to account for image build time + timeout=120 + * 60, # Much larger than default timeout to account for image build time ) def run_instance_modal( test_spec: TestSpec, @@ -186,7 +188,9 @@ def run_instance_modal( test_log_path=test_output_path, include_tests_status=True, ) - logger.info(f"report: {report}\nResult for {instance_id}: resolved: {report[instance_id]['resolved']}") + logger.info( + f"report: {report}\nResult for {instance_id}: resolved: {report[instance_id]['resolved']}" + ) return TestOutput( instance_id=instance_id, @@ -253,7 +257,9 @@ def run_instances_modal( # Check for instances that have already been run for test_spec in test_specs: - log_dir = get_log_dir(predictions[test_spec.instance_id], run_id, test_spec.instance_id) + log_dir = get_log_dir( + predictions[test_spec.instance_id], run_id, test_spec.instance_id + ) if log_dir.exists(): continue run_test_specs.append(test_spec) @@ -272,24 +278,14 @@ def run_instances_modal( ], ) + swebench_sql_output = SWEBenchSQLOutput(modal_function_call_id=run_id) for result in results: result = cast(TestOutput, result) - - # log_dir = result.log_dir - # log_dir.mkdir(parents=True, exist_ok=True) - # with open(log_dir / "run_instance.log", "w") as f: - # f.write(result.run_instance_log) - # with open(log_dir / "test_output.txt", "w") as f: - # f.write(result.test_output) - # with open(log_dir / "patch.diff", "w") as f: - # f.write(result.patch_diff) - # with open(log_dir / "report.json", "w") as f: - # try: - # report_json = json.loads(result.report_json_str) - # json.dump(report_json, f, indent=4) - # except Exception: - # # This happens if the test fails with any exception - # print(f"{result.instance_id}: no report.json") - - # TODO: DO SOMETHING WITH OUTPUTS AND LOGS. - # TODO: SAVE THINGS TO POSTGRESQL FOR DASHBOARD + swebench_sql_output.write_output( + { + "instance_id": result.instance_id, + "output": result.test_output, + "errored": result.errored, + "report": json.loads(result.report_json_str), + } + ) diff --git a/codegen-on-oss/codegen_modal_deploy.py b/codegen-on-oss/codegen_modal_deploy.py index 6aa3b3253..a0fa03539 100644 --- a/codegen-on-oss/codegen_modal_deploy.py +++ b/codegen-on-oss/codegen_modal_deploy.py @@ -6,7 +6,7 @@ from codegen_on_oss.cache import cachedir from codegen_on_oss.metrics import MetricsProfiler -from codegen_on_oss.outputs.sql_output import PostgresSQLOutput +from codegen_on_oss.outputs.sql_output import ParseMetricsSQLOutput from codegen_on_oss.parser import CodegenParser app = modal.App("codegen-oss-parse") @@ -60,7 +60,9 @@ def parse_repo( """ logger.add(sys.stdout, format="{time: HH:mm:ss} {level} {message}", level="DEBUG") - output = PostgresSQLOutput(modal_function_call_id=modal.current_function_call_id()) + output = ParseMetricsSQLOutput( + modal_function_call_id=modal.current_function_call_id() + ) metrics_profiler = MetricsProfiler(output) parser = CodegenParser(Path(cachedir) / "repositories", metrics_profiler) # Refresh any updating repo data from other instances diff --git a/codegen-on-oss/codegen_on_oss/outputs/sql_output.py b/codegen-on-oss/codegen_on_oss/outputs/sql_output.py index 545ce12ad..183d43445 100644 --- a/codegen-on-oss/codegen_on_oss/outputs/sql_output.py +++ b/codegen-on-oss/codegen_on_oss/outputs/sql_output.py @@ -2,7 +2,7 @@ from pydantic import computed_field from pydantic_settings import BaseSettings, SettingsConfigDict -from sqlalchemy import Column, Float, Integer, String, UniqueConstraint +from sqlalchemy import JSONB, Boolean, Column, Float, Integer, String, UniqueConstraint from sqlalchemy.dialects.postgresql import insert from sqlalchemy.engine import create_engine from sqlalchemy.orm import DeclarativeBase, sessionmaker @@ -61,7 +61,18 @@ class ParseMetrics(Base): ) -class PostgresSQLOutput(BaseOutput): +class SWEBenchResult(Base): + __tablename__ = "swebench_output" + + id = Column(Integer, primary_key=True) + instance_id = Column(String, index=True) + modal_function_call_id = Column(String) + errored = Column(Boolean, index=True) + output = Column(String) + report = Column(JSONB) + + +class ParseMetricsSQLOutput(BaseOutput): extras: dict[str, Any] def __init__(self, modal_function_call_id: str): @@ -111,3 +122,27 @@ def write_output(self, value: dict[str, Any]): ) session.execute(stmt) session.commit() + + +class SWEBenchSQLOutput(BaseOutput): + def __init__(self, modal_function_call_id: str): + self.modal_function_call_id = modal_function_call_id + settings = SQLSettings() + self.session_maker = get_session_maker(settings) + super().__init__( + fields=[ + "instance_id", + "modal_function_call_id", + "errored", + "output", + "report", + ] + ) + + def write_output(self, value: dict[str, Any]): + with self.session_maker() as session: + stmt = insert(SWEBenchResult).values( + **value, modal_function_call_id=self.modal_function_call_id + ) + session.execute(stmt) + session.commit() From 74a019cedbf059f6dd763b82a16d84e5cb9dc66d Mon Sep 17 00:00:00 2001 From: clee-codegen <185840274+clee-codegen@users.noreply.github.com> Date: Mon, 3 Mar 2025 09:17:13 +0000 Subject: [PATCH 07/16] Automated pre-commit update --- .../swebench_agent_run/run_swebench_modal_harness.py | 11 +++-------- 1 file changed, 3 insertions(+), 8 deletions(-) diff --git a/codegen-examples/examples/swebench_agent_run/run_swebench_modal_harness.py b/codegen-examples/examples/swebench_agent_run/run_swebench_modal_harness.py index 8a4b01d94..b5bd12fe6 100644 --- a/codegen-examples/examples/swebench_agent_run/run_swebench_modal_harness.py +++ b/codegen-examples/examples/swebench_agent_run/run_swebench_modal_harness.py @@ -74,8 +74,7 @@ def _get_sandbox(self, timeout: int | None = None): LOCAL_SANDBOX_ENTRYPOINT_PATH, REMOTE_SANDBOX_ENTRYPOINT_PATH, ), - timeout=120 - * 60, # Much larger than default timeout to account for image build time + timeout=120 * 60, # Much larger than default timeout to account for image build time ) def run_instance_modal( test_spec: TestSpec, @@ -188,9 +187,7 @@ def run_instance_modal( test_log_path=test_output_path, include_tests_status=True, ) - logger.info( - f"report: {report}\nResult for {instance_id}: resolved: {report[instance_id]['resolved']}" - ) + logger.info(f"report: {report}\nResult for {instance_id}: resolved: {report[instance_id]['resolved']}") return TestOutput( instance_id=instance_id, @@ -257,9 +254,7 @@ def run_instances_modal( # Check for instances that have already been run for test_spec in test_specs: - log_dir = get_log_dir( - predictions[test_spec.instance_id], run_id, test_spec.instance_id - ) + log_dir = get_log_dir(predictions[test_spec.instance_id], run_id, test_spec.instance_id) if log_dir.exists(): continue run_test_specs.append(test_spec) From 46171bf928a6ae729dacfa1d53912033ee75b746 Mon Sep 17 00:00:00 2001 From: Chris Lee Date: Mon, 3 Mar 2025 23:19:33 -0800 Subject: [PATCH 08/16] wip: integration --- .../swebench_agent_run/pyproject.toml | 2 +- .../examples/swebench_agent_run/run_eval.py | 184 +++++--- .../run_swebench_modal_harness.py | 286 ------------ .../swebench_agent_run/snapshot_manager.py | 57 --- codegen-examples/uv.lock | 38 +- .../codegen_on_oss/outputs/sql_output.py | 44 +- .../extensions/swebench/modal_harness.py | 438 ++++++++++++++++++ src/codegen/extensions/swebench/report.py | 39 +- 8 files changed, 640 insertions(+), 448 deletions(-) delete mode 100644 codegen-examples/examples/swebench_agent_run/run_swebench_modal_harness.py delete mode 100644 codegen-examples/examples/swebench_agent_run/snapshot_manager.py create mode 100644 src/codegen/extensions/swebench/modal_harness.py diff --git a/codegen-examples/examples/swebench_agent_run/pyproject.toml b/codegen-examples/examples/swebench_agent_run/pyproject.toml index fc612d4b1..05df11885 100644 --- a/codegen-examples/examples/swebench_agent_run/pyproject.toml +++ b/codegen-examples/examples/swebench_agent_run/pyproject.toml @@ -4,7 +4,7 @@ version = "0.1.0" description = "Add your description here" readme = "README.md" requires-python = ">=3.12, <3.14" -dependencies = ["modal>=0.73.25"] +dependencies = ["modal>=0.73.25", "psycopg2-binary"] [tool.setuptools] py-modules = ["entry_point", "run_eval"] diff --git a/codegen-examples/examples/swebench_agent_run/run_eval.py b/codegen-examples/examples/swebench_agent_run/run_eval.py index b39cede6f..87138004e 100644 --- a/codegen-examples/examples/swebench_agent_run/run_eval.py +++ b/codegen-examples/examples/swebench_agent_run/run_eval.py @@ -1,91 +1,99 @@ -import asyncio import json import traceback -from pathlib import Path import uuid -import modal -import click from datetime import datetime +from pathlib import Path + +import click +import modal from codegen.extensions.swebench.harness import run_agent_on_entry -from codegen.extensions.swebench.utils import SWEBenchDataset, SweBenchExample, get_swe_bench_examples from codegen.extensions.swebench.report import generate_report +from codegen.extensions.swebench.utils import ( + SWEBenchDataset, + SweBenchExample, + get_swe_bench_examples, +) from codegen.sdk.core.codebase import Codebase PREDS_DNAME = Path(__file__).parent / "predictions" LOG_DIR = Path(__file__).parent / "logs" -run_agent_modal = modal.Function.from_name(app_name="swebench-agent-run", name="run_agent_modal") +run_agent_modal = modal.Function.from_name( + app_name="swebench-agent-run", + name="run_agent_modal", +) -async def process_batch_modal(examples: list[SweBenchExample], batch_size=10): - """Process a batch of examples concurrently. +def process_modal(examples: list[SweBenchExample]): + """Process all examples using Modal's map function. Args: examples: List of SweBenchExample objects to process - batch_size: Number of examples to process concurrently. - Default is 50 which provides good parallelization - while staying well within Modal's limits. """ results = [] - # Process examples in batches - for i in range(0, len(examples), batch_size): - batch = examples[i : i + batch_size] - - # Create tasks for this batch - batch_tasks = [run_agent_modal.remote.aio(example) for example in batch] + try: + batch_results = run_agent_modal.map(examples) - # Wait for all tasks in this batch to complete - print(f"Processing batch {i // batch_size + 1}/{len(examples) // batch_size + 1} (examples {i + 1}-{min(i + batch_size, len(examples))})") + for example, result in zip(examples, batch_results): + if isinstance(result, Exception): + error_info = { + "error_type": type(result).__name__, + "error_message": str(result), + "traceback": traceback.format_exception(type(result), result, result.__traceback__), + } - try: - batch_results = await asyncio.gather(*batch_tasks, return_exceptions=True) + if isinstance(result, modal.exception.Error): + error_info["modal_error_code"] = getattr(result, "code", None) + error_info["modal_error_details"] = getattr(result, "details", None) - # Store results - for example, result in zip(batch, batch_results): - error_info = None + print(f"Error processing {example.instance_id}:") + print(f"Type: {error_info['error_type']}") + print(f"Message: {error_info['error_message']}") + print("Traceback:") + print("".join(error_info["traceback"])) - if isinstance(result, Exception): - error_type = type(result).__name__ - error_info = { - "error_type": error_type, - "error_message": str(result), - "traceback": traceback.format_exception(type(result), result, result.__traceback__), + results.append( + { + "instance_id": example.instance_id, + "status": "error", + "error_info": error_info, } - - if isinstance(result, modal.exception.Error): - error_info["modal_error_code"] = getattr(result, "code", None) - error_info["modal_error_details"] = getattr(result, "details", None) - - print(f"Error processing {example.instance_id}:") - print(f"Type: {error_type}") - print(f"Message: {str(result)}") - print("Traceback:") - print("".join(error_info["traceback"])) - - results.append({"instance_id": example.instance_id, "status": "error", "error_info": error_info}) - else: - if result is None: - print(f"Warning: Null result for {example.instance_id}") - results.append({"instance_id": example.instance_id, "status": "error", "error_info": {"error_type": "NullResult", "error_message": "Process returned None"}}) - else: - results.append(result) - - except Exception as e: - print("Batch processing error:") - print(f"Type: {type(e).__name__}") - print(f"Message: {str(e)}") - traceback.print_exc() - - # Mark all examples in the batch as failed - for example in batch: + ) + elif result is None: + print(f"Warning: Null result for {example.instance_id}") results.append( { "instance_id": example.instance_id, "status": "error", - "error_info": {"error_type": type(e).__name__, "error_message": str(e), "traceback": traceback.format_exc(), "batch_failure": True}, + "error_info": { + "error_type": "NullResult", + "error_message": "Process returned None", + }, } ) + else: + results.append(result) + + except Exception as e: + print("Processing error:") + print(f"Type: {type(e).__name__}") + print(f"Message: {str(e)}") + traceback.print_exc() + + # Mark all examples as failed + for example in examples: + results.append( + { + "instance_id": example.instance_id, + "status": "error", + "error_info": { + "error_type": type(e).__name__, + "error_message": str(e), + "traceback": traceback.format_exc(), + }, + } + ) return results @@ -129,12 +137,26 @@ def process_batch_local(examples: list[SweBenchExample], batch_size=10, codebase print("Traceback:") print(error_info["traceback"]) - results.append({"instance_id": example.instance_id, "status": "error", "error_info": error_info}) + results.append( + { + "instance_id": example.instance_id, + "status": "error", + "error_info": error_info, + } + ) return results -async def run_eval(use_existing_preds: str | None, dataset: str, length: int, instance_id: str | None = None, local: bool = False, codebases: dict[str, Codebase] = {}, repo: str | None = None): +def run_eval( + use_existing_preds: str | None, + dataset: str, + length: int, + instance_id: str | None = None, + local: bool = False, + codebases: dict[str, Codebase] = {}, + repo: str | None = None, +): run_id = use_existing_preds or str(uuid.uuid4()) print(f"Run ID: {run_id}") predictions_dir = PREDS_DNAME / f"results_{run_id}" @@ -162,7 +184,7 @@ async def run_eval(use_existing_preds: str | None, dataset: str, length: int, in if local: results = process_batch_local(examples, codebases=codebases) else: - results = await process_batch_modal(examples) + results = process_modal(examples) # Save individual results for result in results: @@ -212,16 +234,48 @@ async def run_eval(use_existing_preds: str | None, dataset: str, length: int, in @click.command() -@click.option("--use-existing-preds", help="The run ID of the existing predictions to use.", type=str, default=None) -@click.option("--dataset", help="The dataset to use.", type=click.Choice(["lite", "full", "verified"]), default="lite") +@click.option( + "--use-existing-preds", + help="The run ID of the existing predictions to use.", + type=str, + default=None, +) +@click.option( + "--dataset", + help="The dataset to use.", + type=click.Choice(["lite", "full", "verified"]), + default="lite", +) @click.option("--length", help="The number of examples to process.", type=int, default=10) -@click.option("--instance-id", help="The instance ID of the example to process.", type=str, default=None) +@click.option( + "--instance-id", + help="The instance ID of the example to process.", + type=str, + default=None, +) @click.option("--local", help="Run the evaluation locally.", is_flag=True, default=False) @click.option("--repo", help="The repo to use.", type=str, default=None) def run_eval_command(use_existing_preds, dataset, length, instance_id, local, repo): print(f"Repo: {repo}") - asyncio.run(run_eval(use_existing_preds=use_existing_preds, dataset=dataset, length=length, instance_id=instance_id, codebases=None, local=local, repo=repo)) + run_eval( + use_existing_preds=use_existing_preds, + dataset=dataset, + length=length, + instance_id=instance_id, + codebases=None, + local=local, + repo=repo, + ) if __name__ == "__main__": + # Generate Report on Modal + # generate_report( + # Path( + # "/home/chris/codegen/codegen/codegen-examples/examples/swebench_agent_run/predictions/results_5761ef09-2bd7-4d90-8346-0a8adefb4439/" + # ), + # LOG_DIR, + # SWEBenchDataset.LITE, + # "5761ef09-2bd7-4d90-8346-0a8adefb4439", + # ) run_eval_command() diff --git a/codegen-examples/examples/swebench_agent_run/run_swebench_modal_harness.py b/codegen-examples/examples/swebench_agent_run/run_swebench_modal_harness.py deleted file mode 100644 index b5bd12fe6..000000000 --- a/codegen-examples/examples/swebench_agent_run/run_swebench_modal_harness.py +++ /dev/null @@ -1,286 +0,0 @@ -""" -Largely copied from swebench/harness/modal_eval/run_evaluation_modal.py - -Points of difference: - - We added CGModalSandboxRuntime class that is used to populate the sandbox with the snapshot. - - We are adding custom post-processing of the TestOutput in run_instances_modal -""" - -import json -import time -import traceback -from typing import cast - -import modal -from codegen_on_oss.outputs.sql_output import SWEBenchSQLOutput -from swebench.harness.constants import ( - APPLY_PATCH_FAIL, - APPLY_PATCH_PASS, - SWEbenchInstance, -) -from swebench.harness.docker_build import setup_logger -from swebench.harness.grading import get_eval_report -from swebench.harness.modal_eval.run_evaluation_modal import ( - LOCAL_SANDBOX_ENTRYPOINT_PATH, - REMOTE_SANDBOX_ENTRYPOINT_PATH, - ModalSandboxRuntime, - TestOutput, - get_log_dir, -) -from swebench.harness.test_spec.test_spec import TestSpec, make_test_spec -from swebench.harness.utils import EvaluationError - -from .snapshot_manager import ModalDictSnapshotManager - -app = modal.App.from_name("swebench-agent-run", create_if_missing=True) - - -class CGModalSandboxRuntime(ModalSandboxRuntime): - def __init__( - self, - example: SWEbenchInstance, - timeout: int | None = None, - verbose: bool = True, - ): - self.example = example - self.snapshot_manager = ModalDictSnapshotManager() - self.test_spec = make_test_spec(example) - self.sandbox = self._get_sandbox(timeout) - self.verbose = verbose - self._stream_tasks = [] - - # Hack for pylint - self.write_file("/sys/fs/cgroup/cpu/cpu.shares", "2048") - - @property - def image(self) -> modal.Image: - return ModalSandboxRuntime.get_instance_image(self.test_spec) - - def _get_sandbox(self, timeout: int | None = None): - """ - Populate sandbox ourselves - """ - uid = self.snapshot_manager.get_snapshot_uid(self.example) - if uid is None: - sandbox = super()._get_sandbox(timeout) - snapshot = sandbox._experimental_snapshot() - self.snapshot_manager.save_snapshot_uid(self.example, snapshot.object_id) - else: - return modal.Sandbox._experimental_from_snapshot(uid) - - -@app.function( - image=modal.Image.debian_slim(python_version="3.13").add_local_file( - LOCAL_SANDBOX_ENTRYPOINT_PATH, - REMOTE_SANDBOX_ENTRYPOINT_PATH, - ), - timeout=120 * 60, # Much larger than default timeout to account for image build time -) -def run_instance_modal( - test_spec: TestSpec, - pred: dict, - run_id: str, - timeout: int | None = None, -) -> TestOutput: - """ - Run a single instance with the given prediction. - - Args: - test_spec (TestSpec): TestSpec instance - pred (dict): Prediction w/ model_name_or_path, model_patch, instance_id - run_id (str): Run ID - timeout (int): Timeout for running tests - """ - instance_id = test_spec.instance_id - log_dir = get_log_dir(pred, run_id, instance_id) - log_dir.mkdir(parents=True, exist_ok=True) - - log_file = log_dir / "run_instance.log" - - logger = setup_logger(instance_id, log_file, add_stdout=True) - - try: - runner = CGModalSandboxRuntime(test_spec, timeout) - except Exception as e: - print(f"Error creating sandbox: {e}") - raise EvaluationError( - instance_id, - f"Error creating sandbox: {e}", - logger, - ) from e - - patch_diff = pred.get("model_patch", "") - - try: - patch_file = "/tmp/patch.diff" - runner.write_file(patch_file, patch_diff) - - apply_patch_output, returncode = runner.exec( - "cd /testbed && git apply -v /tmp/patch.diff", - ) - - if returncode != 0: - logger.info("Failed to apply patch to container, trying again...") - - apply_patch_output, returncode = runner.exec( - "cd /testbed && patch --batch --fuzz=5 -p1 -i /tmp/patch.diff", - ) - - if returncode != 0: - logger.info(f"{APPLY_PATCH_FAIL}:\n{apply_patch_output}") - raise EvaluationError( - instance_id, - f"{APPLY_PATCH_FAIL}:\n{apply_patch_output}", - logger, - ) - else: - logger.info(f"{APPLY_PATCH_PASS}:\n{apply_patch_output}") - else: - logger.info(f"{APPLY_PATCH_PASS}:\n{apply_patch_output}") - - # Get git diff before running eval script - git_diff_output_before, returncode = runner.exec( - "cd /testbed && git diff", - ) - logger.info(f"Git diff before:\n{git_diff_output_before}") - - eval_file = "/root/eval.sh" - eval_script = test_spec.eval_script - # django hack - eval_script = eval_script.replace("locale-gen", "locale-gen en_US.UTF-8") - runner.write_file(eval_file, eval_script) - - start_time = time.time() - - run_command = "cd /testbed" - # pylint hack - if "pylint" in test_spec.instance_id: - run_command += " && PYTHONPATH=" - # increase recursion limit for testing - run_command += " && python3 -c 'import sys; sys.setrecursionlimit(10000)'" - # run eval script - run_command += " && /bin/bash /root/eval.sh" - test_output, returncode = runner.exec(run_command) - - total_runtime = time.time() - start_time - - test_output_path = log_dir / "test_output.txt" - logger.info(f"Test runtime: {total_runtime:_.2f} seconds") - with open(test_output_path, "w") as f: - f.write(test_output) - logger.info(f"Test output for {instance_id} written to {test_output_path}") - print(f"Test output for {instance_id} written to {test_output_path}") - - # Get git diff after running eval script - git_diff_output_after, returncode = runner.exec("cd /testbed && git diff") - - # Check if git diff changed after running eval script - logger.info(f"Git diff after:\n{git_diff_output_after}") - if git_diff_output_after != git_diff_output_before: - logger.info("Git diff changed after running eval script") - - # Get report from test output - logger.info(f"Grading answer for {instance_id}...") - report = get_eval_report( - test_spec=test_spec, - prediction=pred, - test_log_path=test_output_path, - include_tests_status=True, - ) - logger.info(f"report: {report}\nResult for {instance_id}: resolved: {report[instance_id]['resolved']}") - - return TestOutput( - instance_id=instance_id, - test_output=test_output, - report_json_str=json.dumps(report, indent=4), - run_instance_log=log_file.read_text(), - patch_diff=patch_diff, - log_dir=log_dir, - errored=False, - ) - except modal.exception.SandboxTimeoutError as e: - raise EvaluationError( - instance_id, - f"Test timed out after {timeout} seconds.", - logger, - ) from e - except EvaluationError: - error_msg = traceback.format_exc() - logger.info(error_msg) - return TestOutput( - instance_id=instance_id, - test_output="", - report_json_str="", - run_instance_log=log_file.read_text(), - patch_diff=patch_diff, - log_dir=log_dir, - errored=True, - ) - except Exception as e: - error_msg = f"Error in evaluating model for {instance_id}: {e}\n{traceback.format_exc()}\nCheck ({logger.log_file}) for more information." - logger.error(error_msg) - return TestOutput( - instance_id=instance_id, - test_output="", - report_json_str="", - run_instance_log=log_file.read_text(), - patch_diff=patch_diff, - log_dir=log_dir, - errored=True, - ) - - -def run_instances_modal( - predictions: dict, - instances: list, - full_dataset: list, - run_id: str, - timeout: int, -): - """ - Run all instances for the given predictions on Modal. - - Args: - predictions (dict): Predictions dict generated by the model - instances (list): List of instances - run_id (str): Run ID - timeout (int): Timeout for running tests - """ - test_specs = list(map(make_test_spec, instances)) - - with modal.enable_output(): - with app.run(): - run_test_specs = [] - - # Check for instances that have already been run - for test_spec in test_specs: - log_dir = get_log_dir(predictions[test_spec.instance_id], run_id, test_spec.instance_id) - if log_dir.exists(): - continue - run_test_specs.append(test_spec) - - if run_test_specs: - # Run instances that haven't been run yet - results = run_instance_modal.starmap( - [ - ( - test_spec, - predictions[test_spec.instance_id], - run_id, - timeout, - ) - for test_spec in run_test_specs - ], - ) - - swebench_sql_output = SWEBenchSQLOutput(modal_function_call_id=run_id) - for result in results: - result = cast(TestOutput, result) - swebench_sql_output.write_output( - { - "instance_id": result.instance_id, - "output": result.test_output, - "errored": result.errored, - "report": json.loads(result.report_json_str), - } - ) diff --git a/codegen-examples/examples/swebench_agent_run/snapshot_manager.py b/codegen-examples/examples/swebench_agent_run/snapshot_manager.py deleted file mode 100644 index 50fb96a59..000000000 --- a/codegen-examples/examples/swebench_agent_run/snapshot_manager.py +++ /dev/null @@ -1,57 +0,0 @@ -import io -import json -from collections import defaultdict - -import modal -from swebench.harness.constants import SWEbenchInstance - - -class SnapshotManager: - def get_snapshot_uid(self, example: SWEbenchInstance) -> str: - raise NotImplementedError("Not implemented") - - def save_snapshot_uid(self, example: SWEbenchInstance, snapshot_uid: str) -> None: - raise NotImplementedError("Not implemented") - - -class VolumeSnapshotManager(SnapshotManager): - def __init__(self, volume_name: str = "swebench-agent-snapshot-volume"): - self.snapshot_volume = modal.Volume.from_name(volume_name, create_if_missing=True) - self.snapshot_meta_file_path: str = "/root/snapshot_meta.json" - - def get_snapshot_uid(self, example: SWEbenchInstance) -> str: - snapshot_meta = self.read_snapshot_meta() - return snapshot_meta[example.repo][example.environment_setup_commit] - - def save_snapshot_uid(self, example: SWEbenchInstance, snapshot_uid: str) -> None: - snapshot_meta = self.read_snapshot_meta() - snapshot_meta[example.repo][example.environment_setup_commit] = snapshot_uid - with self.snapshot_volume.batch_upload() as upload: - upload.put_file( - io.BytesIO(json.dumps(snapshot_meta).encode("utf-8")), - self.snapshot_meta_file_path, - ) - self.snapshot_volume.commit() - - def read_snapshot_meta(self) -> dict[str, dict[str, str]]: - bytes_io = io.BytesIO() - try: - self.snapshot_volume.read_file_into_fileobj(self.snapshot_meta_file_path, bytes_io) - snapshot_meta = json.loads(bytes_io.getvalue().decode("utf-8")) - except FileNotFoundError: - snapshot_meta = {} - return defaultdict(lambda: defaultdict(lambda: None), snapshot_meta) - - -class ModalDictSnapshotManager(SnapshotManager): - def __init__(self, name: str = "swebench-agent-snapshot-dict"): - self.snapshot_dict = modal.Dict.from_name(name, create_if_missing=True) - - def get_snapshot_uid(self, example: SWEbenchInstance) -> str | None: - try: - return self.snapshot_dict[(example.repo, example.environment_setup_commit)] - except KeyError: - return None - - def save_snapshot_uid(self, example: SWEbenchInstance, snapshot_uid: str) -> None: - self.snapshot_dict[(example.repo, example.environment_setup_commit)] = snapshot_uid diff --git a/codegen-examples/uv.lock b/codegen-examples/uv.lock index d34fae7ac..8e0cfa182 100644 --- a/codegen-examples/uv.lock +++ b/codegen-examples/uv.lock @@ -1,5 +1,4 @@ version = 1 -revision = 1 requires-python = ">=3.12, <3.14" resolution-markers = [ 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"modal" }, + { name = "psycopg2-binary" }, ] [package.metadata] -requires-dist = [{ name = "modal", specifier = ">=0.73.25" }] +requires-dist = [ + { name = "modal", specifier = ">=0.73.25" }, + { name = "psycopg2-binary" }, +] [[package]] name = "synchronicity" diff --git a/codegen-on-oss/codegen_on_oss/outputs/sql_output.py b/codegen-on-oss/codegen_on_oss/outputs/sql_output.py index 183d43445..e3fae129b 100644 --- a/codegen-on-oss/codegen_on_oss/outputs/sql_output.py +++ b/codegen-on-oss/codegen_on_oss/outputs/sql_output.py @@ -2,10 +2,10 @@ from pydantic import computed_field from pydantic_settings import BaseSettings, SettingsConfigDict -from sqlalchemy import JSONB, Boolean, Column, Float, Integer, String, UniqueConstraint +from sqlalchemy import Float, Integer, String, UniqueConstraint from sqlalchemy.dialects.postgresql import insert from sqlalchemy.engine import create_engine -from sqlalchemy.orm import DeclarativeBase, sessionmaker +from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column, sessionmaker from .base import BaseOutput @@ -36,19 +36,19 @@ def get_session_maker(settings: SQLSettings): class ParseMetrics(Base): __tablename__ = "parse_metrics" - id = Column(Integer, primary_key=True) - repo = Column(String, index=True) - revision = Column(String, index=True) - language = Column(String, index=True) - action = Column(String, index=True) - codegen_version = Column(String, index=True) - delta_time = Column(Float, index=True) - cumulative_time = Column(Float, index=True) - cpu_time = Column(Float, index=True) - memory_usage = Column(Integer, index=True) - memory_delta = Column(Integer, index=True) - error = Column(String, index=True) - modal_function_call_id = Column(String) + id: Mapped[int] = mapped_column(Integer, primary_key=True) + repo: Mapped[str] = mapped_column(String, index=True) + revision: Mapped[str] = mapped_column(String, index=True) + language: Mapped[str] = mapped_column(String, index=True) + action: Mapped[str] = mapped_column(String, index=True) + codegen_version: Mapped[str] = mapped_column(String, index=True) + delta_time: Mapped[float] = mapped_column(Float, index=True) + cumulative_time: Mapped[float] = mapped_column(Float, index=True) + cpu_time: Mapped[float] = mapped_column(Float, index=True) + memory_usage: Mapped[int] = mapped_column(Integer, index=True) + memory_delta: Mapped[int] = mapped_column(Integer, index=True) + error: Mapped[str] = mapped_column(String, index=True) + modal_function_call_id: Mapped[str] = mapped_column(String) __table_args__ = ( UniqueConstraint( @@ -64,12 +64,14 @@ class ParseMetrics(Base): class SWEBenchResult(Base): __tablename__ = "swebench_output" - id = Column(Integer, primary_key=True) - instance_id = Column(String, index=True) - modal_function_call_id = Column(String) - errored = Column(Boolean, index=True) - output = Column(String) - report = Column(JSONB) + id: Mapped[int] = mapped_column(primary_key=True) + codegen_version: Mapped[str] = mapped_column(index=True) + submitted: Mapped[int] + completed_instances: Mapped[int] + resolved_instances: Mapped[int] + unresolved_instances: Mapped[int] + empty_patches: Mapped[int] + error_instances: Mapped[int] class ParseMetricsSQLOutput(BaseOutput): diff --git a/src/codegen/extensions/swebench/modal_harness.py b/src/codegen/extensions/swebench/modal_harness.py new file mode 100644 index 000000000..525fee4d7 --- /dev/null +++ b/src/codegen/extensions/swebench/modal_harness.py @@ -0,0 +1,438 @@ +"""Largely copied from swebench/harness/modal_eval/run_evaluation_modal.py + +Points of difference: + - We added CGModalSandboxRuntime class that is used to populate the sandbox with the snapshot. + - We are adding custom post-processing of the TestOutput in run_instances_modal +""" + +import io +import json +import time +import traceback +from collections import defaultdict +from importlib.metadata import version +from unittest.mock import patch + +import modal +from swebench.harness.constants import ( + APPLY_PATCH_FAIL, + APPLY_PATCH_PASS, + SWEbenchInstance, +) +from swebench.harness.docker_build import setup_logger +from swebench.harness.grading import get_eval_report +from swebench.harness.modal_eval.run_evaluation_modal import ( + LOCAL_SANDBOX_ENTRYPOINT_PATH, + REMOTE_SANDBOX_ENTRYPOINT_PATH, + ModalSandboxRuntime, + TestOutput, + get_log_dir, +) +from swebench.harness.run_evaluation import main +from swebench.harness.test_spec.test_spec import TestSpec, make_test_spec +from swebench.harness.utils import EvaluationError + + +class SnapshotManager: + def get_snapshot_uid(self, example: SWEbenchInstance) -> str: + msg = "Not implemented" + raise NotImplementedError(msg) + + def save_snapshot_uid(self, example: SWEbenchInstance, snapshot_uid: str) -> None: + msg = "Not implemented" + raise NotImplementedError(msg) + + +class VolumeSnapshotManager(SnapshotManager): + def __init__(self, volume_name: str = "swebench-agent-snapshot-volume"): + self.snapshot_volume = modal.Volume.from_name(volume_name, create_if_missing=True) + self.snapshot_meta_file_path: str = "/root/snapshot_meta.json" + + def get_snapshot_uid(self, example: SWEbenchInstance) -> str: + snapshot_meta = self.read_snapshot_meta() + return snapshot_meta[example.repo][example.environment_setup_commit] + + def save_snapshot_uid(self, example: SWEbenchInstance, snapshot_uid: str) -> None: + snapshot_meta = self.read_snapshot_meta() + snapshot_meta[example.repo][example.environment_setup_commit] = snapshot_uid + with self.snapshot_volume.batch_upload() as upload: + upload.put_file( + io.BytesIO(json.dumps(snapshot_meta).encode("utf-8")), + self.snapshot_meta_file_path, + ) + self.snapshot_volume.commit() + + def read_snapshot_meta(self) -> dict[str, dict[str, str]]: + bytes_io = io.BytesIO() + try: + self.snapshot_volume.read_file_into_fileobj(self.snapshot_meta_file_path, bytes_io) + snapshot_meta = json.loads(bytes_io.getvalue().decode("utf-8")) + except FileNotFoundError: + snapshot_meta = {} + return defaultdict(lambda: defaultdict(lambda: None), snapshot_meta) + + +class ModalDictSnapshotManager(SnapshotManager): + def __init__(self, name: str = "swebench-agent-snapshot-dict"): + self.snapshot_dict = modal.Dict.from_name(name, create_if_missing=True) + + def get_snapshot_uid(self, example: SWEbenchInstance) -> str | None: + try: + return self.snapshot_dict[(example.repo, example.environment_setup_commit)] + except KeyError: + return None + + def save_snapshot_uid(self, example: SWEbenchInstance, snapshot_uid: str) -> None: + self.snapshot_dict[(example.repo, example.environment_setup_commit)] = snapshot_uid + + +class CGModalSandboxRuntime(ModalSandboxRuntime): + def __init__( + self, + example: SWEbenchInstance, + timeout: int | None = None, + verbose: bool = True, + ): + self.example = example + self.snapshot_manager = ModalDictSnapshotManager() + self.test_spec = make_test_spec(example) + self.sandbox = self._get_sandbox(timeout) + self.verbose = verbose + self._stream_tasks = [] + + # Hack for pylint + self.write_file("/sys/fs/cgroup/cpu/cpu.shares", "2048") + + @property + def image(self) -> modal.Image: + return ModalSandboxRuntime.get_instance_image(self.test_spec) + + def _get_sandbox(self, timeout: int | None = None): + """Populate sandbox ourselves""" + uid = self.snapshot_manager.get_snapshot_uid(self.example) + if uid is None: + sandbox = super()._get_sandbox(timeout) + snapshot = sandbox._experimental_snapshot() + self.snapshot_manager.save_snapshot_uid(self.example, snapshot.object_id) + else: + return modal.Sandbox._experimental_from_snapshot(uid) + + +app = modal.App.lookup("swebench-agent-run", create_if_missing=True) + + +@app.function( + image=modal.Image.debian_slim().add_local_file( + LOCAL_SANDBOX_ENTRYPOINT_PATH, + REMOTE_SANDBOX_ENTRYPOINT_PATH, + ), + timeout=120 * 60, # Much larger than default timeout to account for image build time +) +def run_instance_modal( + test_spec: TestSpec, + pred: dict, + run_id: str, + timeout: int | None = None, +) -> TestOutput: + """Run a single instance with the given prediction. + + Args: + test_spec (TestSpec): TestSpec instance + pred (dict): Prediction w/ model_name_or_path, model_patch, instance_id + run_id (str): Run ID + timeout (int): Timeout for running tests + """ + instance_id = test_spec.instance_id + log_dir = get_log_dir(pred, run_id, instance_id) + log_dir.mkdir(parents=True, exist_ok=True) + + log_file = log_dir / "run_instance.log" + + logger = setup_logger(instance_id, log_file, add_stdout=True) + + try: + runner = ModalSandboxRuntime(test_spec, timeout) + except Exception as e: + print(f"Error creating sandbox: {e}") + raise EvaluationError( + instance_id, + f"Error creating sandbox: {e}", + logger, + ) from e + + patch_diff = pred.get("model_patch", "") + + try: + patch_file = "/tmp/patch.diff" + runner.write_file(patch_file, patch_diff) + + apply_patch_output, returncode = runner.exec( + "cd /testbed && git apply -v /tmp/patch.diff", + ) + + if returncode != 0: + logger.info("Failed to apply patch to container, trying again...") + + apply_patch_output, returncode = runner.exec( + "cd /testbed && patch --batch --fuzz=5 -p1 -i /tmp/patch.diff", + ) + + if returncode != 0: + logger.info(f"{APPLY_PATCH_FAIL}:\n{apply_patch_output}") + raise EvaluationError( + instance_id, + f"{APPLY_PATCH_FAIL}:\n{apply_patch_output}", + logger, + ) + else: + logger.info(f"{APPLY_PATCH_PASS}:\n{apply_patch_output}") + else: + logger.info(f"{APPLY_PATCH_PASS}:\n{apply_patch_output}") + + # Get git diff before running eval script + git_diff_output_before, returncode = runner.exec( + "cd /testbed && git diff", + ) + logger.info(f"Git diff before:\n{git_diff_output_before}") + + eval_file = "/root/eval.sh" + eval_script = test_spec.eval_script + # django hack + eval_script = eval_script.replace("locale-gen", "locale-gen en_US.UTF-8") + runner.write_file(eval_file, eval_script) + + start_time = time.time() + + run_command = "cd /testbed" + # pylint hack + if "pylint" in test_spec.instance_id: + run_command += " && PYTHONPATH=" + # increase recursion limit for testing + run_command += " && python3 -c 'import sys; sys.setrecursionlimit(10000)'" + # run eval script + run_command += " && /bin/bash /root/eval.sh" + test_output, returncode = runner.exec(run_command) + + total_runtime = time.time() - start_time + + test_output_path = log_dir / "test_output.txt" + logger.info(f"Test runtime: {total_runtime:_.2f} seconds") + with open(test_output_path, "w") as f: + f.write(test_output) + logger.info(f"Test output for {instance_id} written to {test_output_path}") + print(f"Test output for {instance_id} written to {test_output_path}") + + # Get git diff after running eval script + git_diff_output_after, returncode = runner.exec("cd /testbed && git diff") + + # Check if git diff changed after running eval script + logger.info(f"Git diff after:\n{git_diff_output_after}") + if git_diff_output_after != git_diff_output_before: + logger.info("Git diff changed after running eval script") + + # Get report from test output + logger.info(f"Grading answer for {instance_id}...") + report = get_eval_report( + test_spec=test_spec, + prediction=pred, + test_log_path=test_output_path, + include_tests_status=True, + ) + logger.info(f"report: {report}\nResult for {instance_id}: resolved: {report[instance_id]['resolved']}") + + return TestOutput( + instance_id=instance_id, + test_output=test_output, + report_json_str=json.dumps(report, indent=4), + run_instance_log=log_file.read_text(), + patch_diff=patch_diff, + log_dir=log_dir, + errored=False, + ) + except modal.exception.SandboxTimeoutError as e: + raise EvaluationError( + instance_id, + f"Test timed out after {timeout} seconds.", + logger, + ) from e + except EvaluationError: + error_msg = traceback.format_exc() + logger.info(error_msg) + return TestOutput( + instance_id=instance_id, + test_output="", + report_json_str="", + run_instance_log=log_file.read_text(), + patch_diff=patch_diff, + log_dir=log_dir, + errored=True, + ) + except Exception as e: + error_msg = f"Error in evaluating model for {instance_id}: {e}\n{traceback.format_exc()}\nCheck ({logger.log_file}) for more information." + logger.exception(error_msg) + return TestOutput( + instance_id=instance_id, + test_output="", + report_json_str="", + run_instance_log=log_file.read_text(), + patch_diff=patch_diff, + log_dir=log_dir, + errored=True, + ) + + +def patched_swebench_eval( # Defaults from swebench harness + predictions_path, # Required argument + run_id, # Required argument + dataset_name="princeton-nlp/SWE-bench_Lite", + split="test", + instance_ids=None, # Default None since it's optional + max_workers=4, + open_file_limit=4096, + timeout=1800, + force_rebuild=False, + cache_level="env", + clean=False, + namespace="swebench", + instance_image_tag="latest", + rewrite_reports=False, + report_dir=".", + modal=False, + **kwargs, +): + with patch( + "swebench.harness.modal_eval.run_evaluation_modal.run_instance_modal", + run_instance_modal, + ): + return main( + dataset_name=dataset_name, + split=split, + instance_ids=instance_ids, + predictions_path=predictions_path, + max_workers=max_workers, + force_rebuild=force_rebuild, + cache_level=cache_level, + clean=clean, + open_file_limit=open_file_limit, + run_id=run_id, + timeout=timeout, + namespace=namespace, + rewrite_reports=rewrite_reports, + modal=modal, + instance_image_tag=instance_image_tag, + report_dir=report_dir, + **kwargs, + ) + + +# def run_instances_modal( +# predictions: dict, +# instances: list, +# full_dataset: list, +# run_id: str, +# timeout: int, +# ): +# """Run all instances for the given predictions on Modal. + +# Args: +# predictions (dict): Predictions dict generated by the model +# instances (list): List of instances +# run_id (str): Run ID +# timeout (int): Timeout for running tests +# """ +# test_specs = list(map(make_test_spec, instances)) + +# with modal.enable_output(): +# with app.run(): +# run_test_specs = [] + +# # Check for instances that have already been run +# for test_spec in test_specs: +# log_dir = get_log_dir( +# predictions[test_spec.instance_id], run_id, test_spec.instance_id +# ) +# if log_dir.exists(): +# continue +# run_test_specs.append(test_spec) + +# if run_test_specs: +# # Run instances that haven't been run yet +# results = run_instance_modal.starmap( +# [ +# ( +# test_spec, +# predictions[test_spec.instance_id], +# run_id, +# timeout, +# ) +# for test_spec in run_test_specs +# ], +# ) + +# for result in results: +# result = cast(TestOutput, result) + +# # Save logs locally +# log_dir = result.log_dir +# log_dir.mkdir(parents=True, exist_ok=True) +# with open(log_dir / "run_instance.log", "w") as f: +# f.write(result.run_instance_log) +# with open(log_dir / "test_output.txt", "w") as f: +# f.write(result.test_output) +# with open(log_dir / "patch.diff", "w") as f: +# f.write(result.patch_diff) +# with open(log_dir / "report.json", "w") as f: +# try: +# report_json = json.loads(result.report_json_str) +# json.dump(report_json, f, indent=4) +# except Exception: +# # This happens if the test fails with any exception +# print(f"{result.instance_id}: no report.json") + +# make_run_report(predictions, full_dataset, run_id) + + +def write_report_to_db(report_file: str): + import psycopg2 + + try: + codegen_version = version("codegen") + except Exception: + codegen_version = "dev" + + with open(report_file) as f: + report = json.load(f) + + # Establish connection + conn = psycopg2.connect(host="localhost", database="swebench", user="swebench", password="swebench") + + # Create a cursor + cur = conn.cursor() + + try: + # Single row insert + cur.execute( + "INSERT INTO table_name (codegen_version, submitted, completed_instances, resolved_instances, unresolved_instances, empty_patches, error_instances) VALUES (%s, %s, %s, %s, %s, %s, %s)", + ( + codegen_version, + report["submitted_instances"], + report["completed_instances"], + report["resolved_instances"], + report["unresolved_instances"], + report["empty_patch_instances"], + report["error_instances"], + ), + ) + + # Commit the transaction + conn.commit() + + except Exception as e: + # Rollback in case of error + conn.rollback() + print(f"Error: {e}") + + finally: + # Close cursor and connection + cur.close() + conn.close() diff --git a/src/codegen/extensions/swebench/report.py b/src/codegen/extensions/swebench/report.py index a2b624bb5..f42c8a9b5 100755 --- a/src/codegen/extensions/swebench/report.py +++ b/src/codegen/extensions/swebench/report.py @@ -1,31 +1,38 @@ #!/usr/bin/env python import json -import subprocess +import traceback from collections import defaultdict from pathlib import Path +from codegen.extensions.swebench.modal_harness import ( + patched_swebench_eval, + write_report_to_db, +) from codegen.extensions.swebench.tests import remove_patches_to_tests from codegen.extensions.swebench.utils import SWEBenchDataset NUM_EVAL_PROCS = 5 -def run_evals(predictions_jsonl, logs_dir: Path, dataset: SWEBenchDataset, run_id: str): - """Run the evaluations on the predictions on modal.""" - run_evals_cmd = f""" -python -m swebench.harness.run_evaluation - --predictions_path {predictions_jsonl} - --run_id {run_id} - --dataset_name {dataset.value} - --cache_level instance - --report_dir {logs_dir} - --modal true -""" - run_evals_cmd = " ".join([line.strip() for line in run_evals_cmd.split() if line.strip()]) - print("Running evaluation command:", run_evals_cmd) - - subprocess.run(run_evals_cmd.split(), check=True) +def run_evals(predictions_jsonl, logs_dir: Path, dataset: SWEBenchDataset, run_id: str) -> str: + """Returns report path""" + report_path = patched_swebench_eval( + predictions_jsonl, + run_id, + dataset_name=dataset.value, + cache_level="instance", + report_dir=logs_dir, + modal=True, + ) + + if report_path is not None: + try: + write_report_to_db(report_path) + except Exception: + print("Error writing report to db") + traceback.print_exc() + return report_path def get_report(predictions_jsonl, logs_dir: Path): From 45eb835eef426aec9e958c6ae77121d544d9096c Mon Sep 17 00:00:00 2001 From: Chris Lee Date: Tue, 4 Mar 2025 10:33:53 -0800 Subject: [PATCH 09/16] fix: integration with modal deployments --- .../examples/swebench_agent_run/run_eval.py | 8 ---- .../extensions/swebench/modal_harness.py | 37 +++++++++++++------ 2 files changed, 25 insertions(+), 20 deletions(-) diff --git a/codegen-examples/examples/swebench_agent_run/run_eval.py b/codegen-examples/examples/swebench_agent_run/run_eval.py index 87138004e..1dcf1f84c 100644 --- a/codegen-examples/examples/swebench_agent_run/run_eval.py +++ b/codegen-examples/examples/swebench_agent_run/run_eval.py @@ -270,12 +270,4 @@ def run_eval_command(use_existing_preds, dataset, length, instance_id, local, re if __name__ == "__main__": # Generate Report on Modal - # generate_report( - # Path( - # "/home/chris/codegen/codegen/codegen-examples/examples/swebench_agent_run/predictions/results_5761ef09-2bd7-4d90-8346-0a8adefb4439/" - # ), - # LOG_DIR, - # SWEBenchDataset.LITE, - # "5761ef09-2bd7-4d90-8346-0a8adefb4439", - # ) run_eval_command() diff --git a/src/codegen/extensions/swebench/modal_harness.py b/src/codegen/extensions/swebench/modal_harness.py index 525fee4d7..8c89166df 100644 --- a/src/codegen/extensions/swebench/modal_harness.py +++ b/src/codegen/extensions/swebench/modal_harness.py @@ -10,10 +10,11 @@ import time import traceback from collections import defaultdict +from contextlib import nullcontext from importlib.metadata import version from unittest.mock import patch -import modal +import modal as modal_lib from swebench.harness.constants import ( APPLY_PATCH_FAIL, APPLY_PATCH_PASS, @@ -27,6 +28,7 @@ ModalSandboxRuntime, TestOutput, get_log_dir, + swebench_image, ) from swebench.harness.run_evaluation import main from swebench.harness.test_spec.test_spec import TestSpec, make_test_spec @@ -45,7 +47,7 @@ def save_snapshot_uid(self, example: SWEbenchInstance, snapshot_uid: str) -> Non class VolumeSnapshotManager(SnapshotManager): def __init__(self, volume_name: str = "swebench-agent-snapshot-volume"): - self.snapshot_volume = modal.Volume.from_name(volume_name, create_if_missing=True) + self.snapshot_volume = modal_lib.Volume.from_name(volume_name, create_if_missing=True) self.snapshot_meta_file_path: str = "/root/snapshot_meta.json" def get_snapshot_uid(self, example: SWEbenchInstance) -> str: @@ -74,7 +76,7 @@ def read_snapshot_meta(self) -> dict[str, dict[str, str]]: class ModalDictSnapshotManager(SnapshotManager): def __init__(self, name: str = "swebench-agent-snapshot-dict"): - self.snapshot_dict = modal.Dict.from_name(name, create_if_missing=True) + self.snapshot_dict = modal_lib.Dict.from_name(name, create_if_missing=True) def get_snapshot_uid(self, example: SWEbenchInstance) -> str | None: try: @@ -104,7 +106,7 @@ def __init__( self.write_file("/sys/fs/cgroup/cpu/cpu.shares", "2048") @property - def image(self) -> modal.Image: + def image(self) -> modal_lib.Image: return ModalSandboxRuntime.get_instance_image(self.test_spec) def _get_sandbox(self, timeout: int | None = None): @@ -115,17 +117,17 @@ def _get_sandbox(self, timeout: int | None = None): snapshot = sandbox._experimental_snapshot() self.snapshot_manager.save_snapshot_uid(self.example, snapshot.object_id) else: - return modal.Sandbox._experimental_from_snapshot(uid) + return modal_lib.Sandbox._experimental_from_snapshot(uid) -app = modal.App.lookup("swebench-agent-run", create_if_missing=True) +app = modal_lib.App.lookup("swebench-agent-run", create_if_missing=True) @app.function( - image=modal.Image.debian_slim().add_local_file( + image=swebench_image.add_local_file( LOCAL_SANDBOX_ENTRYPOINT_PATH, REMOTE_SANDBOX_ENTRYPOINT_PATH, - ), + ).add_local_python_source("modal_harness"), timeout=120 * 60, # Much larger than default timeout to account for image build time ) def run_instance_modal( @@ -249,7 +251,7 @@ def run_instance_modal( log_dir=log_dir, errored=False, ) - except modal.exception.SandboxTimeoutError as e: + except modal_lib.exception.SandboxTimeoutError as e: raise EvaluationError( instance_id, f"Test timed out after {timeout} seconds.", @@ -300,10 +302,21 @@ def patched_swebench_eval( # Defaults from swebench harness modal=False, **kwargs, ): - with patch( - "swebench.harness.modal_eval.run_evaluation_modal.run_instance_modal", - run_instance_modal, + with ( + patch( + "swebench.harness.modal_eval.run_evaluation_modal.run_instance_modal", + modal_lib.Function.from_name( + app_name="swebench-agent-run", + name="run_instance_modal", + ), + ), + patch( + "swebench.harness.modal_eval.run_evaluation_modal.app", + app, + ), ): + # Don't want swebench to run app.run() again + app.run = nullcontext return main( dataset_name=dataset_name, split=split, From 7a3b415bcc08590d4e6a5c9e92206642eea92025 Mon Sep 17 00:00:00 2001 From: Chris Lee Date: Tue, 4 Mar 2025 17:35:15 -0800 Subject: [PATCH 10/16] wip: initial refactor --- .../swebench_agent_run/entry_point.py | 19 -- .../examples/swebench_agent_run/metrics.py | 50 ++++ .../modal_harness/__init__.py | 3 + .../modal_harness/entry_point.py | 227 ++---------------- .../modal_harness/sandbox.py | 103 ++++++++ .../examples/swebench_agent_run}/report.py | 51 ++-- .../examples/swebench_agent_run/run_eval.py | 86 +++++-- 7 files changed, 262 insertions(+), 277 deletions(-) delete mode 100644 codegen-examples/examples/swebench_agent_run/entry_point.py create mode 100644 codegen-examples/examples/swebench_agent_run/metrics.py create mode 100644 codegen-examples/examples/swebench_agent_run/modal_harness/__init__.py rename src/codegen/extensions/swebench/modal_harness.py => codegen-examples/examples/swebench_agent_run/modal_harness/entry_point.py (50%) create mode 100644 codegen-examples/examples/swebench_agent_run/modal_harness/sandbox.py rename {src/codegen/extensions/swebench => codegen-examples/examples/swebench_agent_run}/report.py (82%) diff --git a/codegen-examples/examples/swebench_agent_run/entry_point.py b/codegen-examples/examples/swebench_agent_run/entry_point.py deleted file mode 100644 index 411b09d3b..000000000 --- a/codegen-examples/examples/swebench_agent_run/entry_point.py +++ /dev/null @@ -1,19 +0,0 @@ -from codegen.extensions.swebench.utils import SweBenchExample -from codegen.extensions.swebench.harness import run_agent_on_entry -import modal - -image = ( - modal.Image.debian_slim(python_version="3.13") - .apt_install(["git", "ripgrep"]) - .pip_install("fastapi[standard]") - .copy_local_dir("../../../", "/root/codegen", ignore=[".venv", "**/.venv", "tests", "**/tests"]) - .run_commands("pip install -e /root/codegen") -) - -app = modal.App(name="swebench-agent-run", image=image, secrets=[modal.Secret.from_dotenv()]) - - -@app.function(timeout=10 * 60) -async def run_agent_modal(entry: SweBenchExample): - """Modal function to process a single example from the SWE-bench dataset.""" - return run_agent_on_entry(entry) diff --git a/codegen-examples/examples/swebench_agent_run/metrics.py b/codegen-examples/examples/swebench_agent_run/metrics.py new file mode 100644 index 000000000..681338309 --- /dev/null +++ b/codegen-examples/examples/swebench_agent_run/metrics.py @@ -0,0 +1,50 @@ +import json +from importlib.metadata import version + + +def write_report_to_db(report_file: str): + import psycopg2 + + try: + codegen_version = version("codegen") + except Exception: + codegen_version = "dev" + + with open(report_file) as f: + report = json.load(f) + + # Establish connection + conn = psycopg2.connect( + host="localhost", database="swebench", user="swebench", password="swebench" + ) + + # Create a cursor + cur = conn.cursor() + + try: + # Single row insert + cur.execute( + "INSERT INTO table_name (codegen_version, submitted, completed_instances, resolved_instances, unresolved_instances, empty_patches, error_instances) VALUES (%s, %s, %s, %s, %s, %s, %s)", + ( + codegen_version, + report["submitted_instances"], + report["completed_instances"], + report["resolved_instances"], + report["unresolved_instances"], + report["empty_patch_instances"], + report["error_instances"], + ), + ) + + # Commit the transaction + conn.commit() + + except Exception as e: + # Rollback in case of error + conn.rollback() + print(f"Error: {e}") + + finally: + # Close cursor and connection + cur.close() + conn.close() diff --git a/codegen-examples/examples/swebench_agent_run/modal_harness/__init__.py b/codegen-examples/examples/swebench_agent_run/modal_harness/__init__.py new file mode 100644 index 000000000..e26435103 --- /dev/null +++ b/codegen-examples/examples/swebench_agent_run/modal_harness/__init__.py @@ -0,0 +1,3 @@ +from .entry_point import patched_swebench_eval + +__all__ = ["patched_swebench_eval"] diff --git a/src/codegen/extensions/swebench/modal_harness.py b/codegen-examples/examples/swebench_agent_run/modal_harness/entry_point.py similarity index 50% rename from src/codegen/extensions/swebench/modal_harness.py rename to codegen-examples/examples/swebench_agent_run/modal_harness/entry_point.py index 8c89166df..76bc56341 100644 --- a/src/codegen/extensions/swebench/modal_harness.py +++ b/codegen-examples/examples/swebench_agent_run/modal_harness/entry_point.py @@ -5,20 +5,18 @@ - We are adding custom post-processing of the TestOutput in run_instances_modal """ -import io import json import time import traceback -from collections import defaultdict from contextlib import nullcontext -from importlib.metadata import version from unittest.mock import patch import modal as modal_lib +from codegen.extensions.swebench.harness import run_agent_on_entry +from codegen.extensions.swebench.utils import SweBenchExample from swebench.harness.constants import ( APPLY_PATCH_FAIL, APPLY_PATCH_PASS, - SWEbenchInstance, ) from swebench.harness.docker_build import setup_logger from swebench.harness.grading import get_eval_report @@ -31,96 +29,27 @@ swebench_image, ) from swebench.harness.run_evaluation import main -from swebench.harness.test_spec.test_spec import TestSpec, make_test_spec +from swebench.harness.test_spec.test_spec import TestSpec from swebench.harness.utils import EvaluationError +image = ( + modal_lib.Image.debian_slim(python_version="3.13") + .apt_install(["git", "ripgrep"]) + .copy_local_dir( + "../../../", "/root/codegen", ignore=[".venv", "**/.venv", "tests", "**/tests"] + ) + .run_commands("pip install -e /root/codegen") +) -class SnapshotManager: - def get_snapshot_uid(self, example: SWEbenchInstance) -> str: - msg = "Not implemented" - raise NotImplementedError(msg) - - def save_snapshot_uid(self, example: SWEbenchInstance, snapshot_uid: str) -> None: - msg = "Not implemented" - raise NotImplementedError(msg) - - -class VolumeSnapshotManager(SnapshotManager): - def __init__(self, volume_name: str = "swebench-agent-snapshot-volume"): - self.snapshot_volume = modal_lib.Volume.from_name(volume_name, create_if_missing=True) - self.snapshot_meta_file_path: str = "/root/snapshot_meta.json" - - def get_snapshot_uid(self, example: SWEbenchInstance) -> str: - snapshot_meta = self.read_snapshot_meta() - return snapshot_meta[example.repo][example.environment_setup_commit] - - def save_snapshot_uid(self, example: SWEbenchInstance, snapshot_uid: str) -> None: - snapshot_meta = self.read_snapshot_meta() - snapshot_meta[example.repo][example.environment_setup_commit] = snapshot_uid - with self.snapshot_volume.batch_upload() as upload: - upload.put_file( - io.BytesIO(json.dumps(snapshot_meta).encode("utf-8")), - self.snapshot_meta_file_path, - ) - self.snapshot_volume.commit() - - def read_snapshot_meta(self) -> dict[str, dict[str, str]]: - bytes_io = io.BytesIO() - try: - self.snapshot_volume.read_file_into_fileobj(self.snapshot_meta_file_path, bytes_io) - snapshot_meta = json.loads(bytes_io.getvalue().decode("utf-8")) - except FileNotFoundError: - snapshot_meta = {} - return defaultdict(lambda: defaultdict(lambda: None), snapshot_meta) - - -class ModalDictSnapshotManager(SnapshotManager): - def __init__(self, name: str = "swebench-agent-snapshot-dict"): - self.snapshot_dict = modal_lib.Dict.from_name(name, create_if_missing=True) - - def get_snapshot_uid(self, example: SWEbenchInstance) -> str | None: - try: - return self.snapshot_dict[(example.repo, example.environment_setup_commit)] - except KeyError: - return None - - def save_snapshot_uid(self, example: SWEbenchInstance, snapshot_uid: str) -> None: - self.snapshot_dict[(example.repo, example.environment_setup_commit)] = snapshot_uid - - -class CGModalSandboxRuntime(ModalSandboxRuntime): - def __init__( - self, - example: SWEbenchInstance, - timeout: int | None = None, - verbose: bool = True, - ): - self.example = example - self.snapshot_manager = ModalDictSnapshotManager() - self.test_spec = make_test_spec(example) - self.sandbox = self._get_sandbox(timeout) - self.verbose = verbose - self._stream_tasks = [] - - # Hack for pylint - self.write_file("/sys/fs/cgroup/cpu/cpu.shares", "2048") - - @property - def image(self) -> modal_lib.Image: - return ModalSandboxRuntime.get_instance_image(self.test_spec) - - def _get_sandbox(self, timeout: int | None = None): - """Populate sandbox ourselves""" - uid = self.snapshot_manager.get_snapshot_uid(self.example) - if uid is None: - sandbox = super()._get_sandbox(timeout) - snapshot = sandbox._experimental_snapshot() - self.snapshot_manager.save_snapshot_uid(self.example, snapshot.object_id) - else: - return modal_lib.Sandbox._experimental_from_snapshot(uid) +app = modal_lib.App( + name="swebench-agent-run", image=image, secrets=[modal_lib.Secret.from_dotenv()] +) -app = modal_lib.App.lookup("swebench-agent-run", create_if_missing=True) +@app.function(timeout=10 * 60) +async def run_agent_modal(entry: SweBenchExample): + """Modal function to process a single example from the SWE-bench dataset.""" + return run_agent_on_entry(entry) @app.function( @@ -128,7 +57,8 @@ def _get_sandbox(self, timeout: int | None = None): LOCAL_SANDBOX_ENTRYPOINT_PATH, REMOTE_SANDBOX_ENTRYPOINT_PATH, ).add_local_python_source("modal_harness"), - timeout=120 * 60, # Much larger than default timeout to account for image build time + timeout=120 + * 60, # Much larger than default timeout to account for image build time ) def run_instance_modal( test_spec: TestSpec, @@ -240,7 +170,9 @@ def run_instance_modal( test_log_path=test_output_path, include_tests_status=True, ) - logger.info(f"report: {report}\nResult for {instance_id}: resolved: {report[instance_id]['resolved']}") + logger.info( + f"report: {report}\nResult for {instance_id}: resolved: {report[instance_id]['resolved']}" + ) return TestOutput( instance_id=instance_id, @@ -336,116 +268,3 @@ def patched_swebench_eval( # Defaults from swebench harness report_dir=report_dir, **kwargs, ) - - -# def run_instances_modal( -# predictions: dict, -# instances: list, -# full_dataset: list, -# run_id: str, -# timeout: int, -# ): -# """Run all instances for the given predictions on Modal. - -# Args: -# predictions (dict): Predictions dict generated by the model -# instances (list): List of instances -# run_id (str): Run ID -# timeout (int): Timeout for running tests -# """ -# test_specs = list(map(make_test_spec, instances)) - -# with modal.enable_output(): -# with app.run(): -# run_test_specs = [] - -# # Check for instances that have already been run -# for test_spec in test_specs: -# log_dir = get_log_dir( -# predictions[test_spec.instance_id], run_id, test_spec.instance_id -# ) -# if log_dir.exists(): -# continue -# run_test_specs.append(test_spec) - -# if run_test_specs: -# # Run instances that haven't been run yet -# results = run_instance_modal.starmap( -# [ -# ( -# test_spec, -# predictions[test_spec.instance_id], -# run_id, -# timeout, -# ) -# for test_spec in run_test_specs -# ], -# ) - -# for result in results: -# result = cast(TestOutput, result) - -# # Save logs locally -# log_dir = result.log_dir -# log_dir.mkdir(parents=True, exist_ok=True) -# with open(log_dir / "run_instance.log", "w") as f: -# f.write(result.run_instance_log) -# with open(log_dir / "test_output.txt", "w") as f: -# f.write(result.test_output) -# with open(log_dir / "patch.diff", "w") as f: -# f.write(result.patch_diff) -# with open(log_dir / "report.json", "w") as f: -# try: -# report_json = json.loads(result.report_json_str) -# json.dump(report_json, f, indent=4) -# except Exception: -# # This happens if the test fails with any exception -# print(f"{result.instance_id}: no report.json") - -# make_run_report(predictions, full_dataset, run_id) - - -def write_report_to_db(report_file: str): - import psycopg2 - - try: - codegen_version = version("codegen") - except Exception: - codegen_version = "dev" - - with open(report_file) as f: - report = json.load(f) - - # Establish connection - conn = psycopg2.connect(host="localhost", database="swebench", user="swebench", password="swebench") - - # Create a cursor - cur = conn.cursor() - - try: - # Single row insert - cur.execute( - "INSERT INTO table_name (codegen_version, submitted, completed_instances, resolved_instances, unresolved_instances, empty_patches, error_instances) VALUES (%s, %s, %s, %s, %s, %s, %s)", - ( - codegen_version, - report["submitted_instances"], - report["completed_instances"], - report["resolved_instances"], - report["unresolved_instances"], - report["empty_patch_instances"], - report["error_instances"], - ), - ) - - # Commit the transaction - conn.commit() - - except Exception as e: - # Rollback in case of error - conn.rollback() - print(f"Error: {e}") - - finally: - # Close cursor and connection - cur.close() - conn.close() diff --git a/codegen-examples/examples/swebench_agent_run/modal_harness/sandbox.py b/codegen-examples/examples/swebench_agent_run/modal_harness/sandbox.py new file mode 100644 index 000000000..33e3149f7 --- /dev/null +++ b/codegen-examples/examples/swebench_agent_run/modal_harness/sandbox.py @@ -0,0 +1,103 @@ +import io +import json +from collections import defaultdict + +import modal as modal_lib +from swebench.harness.constants import ( + SWEbenchInstance, +) +from swebench.harness.modal_eval.run_evaluation_modal import ( + ModalSandboxRuntime, +) +from swebench.harness.test_spec.test_spec import make_test_spec + + +class SnapshotManager: + def get_snapshot_uid(self, example: SWEbenchInstance) -> str: + msg = "Not implemented" + raise NotImplementedError(msg) + + def save_snapshot_uid(self, example: SWEbenchInstance, snapshot_uid: str) -> None: + msg = "Not implemented" + raise NotImplementedError(msg) + + +class VolumeSnapshotManager(SnapshotManager): + def __init__(self, volume_name: str = "swebench-agent-snapshot-volume"): + self.snapshot_volume = modal_lib.Volume.from_name( + volume_name, create_if_missing=True + ) + self.snapshot_meta_file_path: str = "/root/snapshot_meta.json" + + def get_snapshot_uid(self, example: SWEbenchInstance) -> str: + snapshot_meta = self.read_snapshot_meta() + return snapshot_meta[example.repo][example.environment_setup_commit] + + def save_snapshot_uid(self, example: SWEbenchInstance, snapshot_uid: str) -> None: + snapshot_meta = self.read_snapshot_meta() + snapshot_meta[example.repo][example.environment_setup_commit] = snapshot_uid + with self.snapshot_volume.batch_upload() as upload: + upload.put_file( + io.BytesIO(json.dumps(snapshot_meta).encode("utf-8")), + self.snapshot_meta_file_path, + ) + self.snapshot_volume.commit() + + def read_snapshot_meta(self) -> dict[str, dict[str, str]]: + bytes_io = io.BytesIO() + try: + self.snapshot_volume.read_file_into_fileobj( + self.snapshot_meta_file_path, bytes_io + ) + snapshot_meta = json.loads(bytes_io.getvalue().decode("utf-8")) + except FileNotFoundError: + snapshot_meta = {} + return defaultdict(lambda: defaultdict(lambda: None), snapshot_meta) + + +class ModalDictSnapshotManager(SnapshotManager): + def __init__(self, name: str = "swebench-agent-snapshot-dict"): + self.snapshot_dict = modal_lib.Dict.from_name(name, create_if_missing=True) + + def get_snapshot_uid(self, example: SWEbenchInstance) -> str | None: + try: + return self.snapshot_dict[(example.repo, example.environment_setup_commit)] + except KeyError: + return None + + def save_snapshot_uid(self, example: SWEbenchInstance, snapshot_uid: str) -> None: + self.snapshot_dict[(example.repo, example.environment_setup_commit)] = ( + snapshot_uid + ) + + +class CGModalSandboxRuntime(ModalSandboxRuntime): + def __init__( + self, + example: SWEbenchInstance, + timeout: int | None = None, + verbose: bool = True, + ): + self.example = example + self.snapshot_manager = ModalDictSnapshotManager() + self.test_spec = make_test_spec(example) + self.sandbox = self._get_sandbox(timeout) + self.verbose = verbose + self._stream_tasks = [] + + # Hack for pylint + self.write_file("/sys/fs/cgroup/cpu/cpu.shares", "2048") + + @property + def image(self) -> modal_lib.Image: + return ModalSandboxRuntime.get_instance_image(self.test_spec) + + def _get_sandbox(self, timeout: int | None = None): + """Populate sandbox ourselves""" + uid = self.snapshot_manager.get_snapshot_uid(self.example) + if uid is None: + sandbox = super()._get_sandbox(timeout) + snapshot = sandbox._experimental_snapshot() + self.snapshot_manager.save_snapshot_uid(self.example, snapshot.object_id) + else: + return modal_lib.Sandbox._experimental_from_snapshot(uid) diff --git a/src/codegen/extensions/swebench/report.py b/codegen-examples/examples/swebench_agent_run/report.py similarity index 82% rename from src/codegen/extensions/swebench/report.py rename to codegen-examples/examples/swebench_agent_run/report.py index f42c8a9b5..cf916b121 100755 --- a/src/codegen/extensions/swebench/report.py +++ b/codegen-examples/examples/swebench_agent_run/report.py @@ -1,38 +1,15 @@ #!/usr/bin/env python import json -import traceback from collections import defaultdict from pathlib import Path -from codegen.extensions.swebench.modal_harness import ( - patched_swebench_eval, - write_report_to_db, -) from codegen.extensions.swebench.tests import remove_patches_to_tests from codegen.extensions.swebench.utils import SWEBenchDataset -NUM_EVAL_PROCS = 5 - - -def run_evals(predictions_jsonl, logs_dir: Path, dataset: SWEBenchDataset, run_id: str) -> str: - """Returns report path""" - report_path = patched_swebench_eval( - predictions_jsonl, - run_id, - dataset_name=dataset.value, - cache_level="instance", - report_dir=logs_dir, - modal=True, - ) +from .modal_harness import patched_swebench_eval - if report_path is not None: - try: - write_report_to_db(report_path) - except Exception: - print("Error writing report to db") - traceback.print_exc() - return report_path +NUM_EVAL_PROCS = 5 def get_report(predictions_jsonl, logs_dir: Path): @@ -107,18 +84,22 @@ def preds_to_jsonl(predictions, predictions_dir: Path): for inst, pred in predictions.items(): minimal_pred = { "model_name_or_path": model_name, # Use default model name - "model_patch": remove_patches_to_tests(pred["model_patch"]) if "model_patch" in pred else pred.get("patch", ""), + "model_patch": remove_patches_to_tests(pred["model_patch"]) + if "model_patch" in pred + else pred.get("patch", ""), "instance_id": pred["instance_id"], } fh.write(json.dumps(minimal_pred) + "\n") return predictions_jsonl -def generate_report(predictions_dir: Path, logs_dir: Path, dataset: SWEBenchDataset, run_id: str): +def generate_report( + predictions_dir: Path, logs_dir: Path, dataset: SWEBenchDataset, run_id: str +) -> str | None: # Automatically find all JSON files in predictions/results if not predictions_dir.exists(): print(f"Directory does not exist: {predictions_dir}") - return 1 + return None prediction_files = list(predictions_dir.glob("*.json")) print(f"Found {len(prediction_files)} prediction files") @@ -147,8 +128,14 @@ def generate_report(predictions_dir: Path, logs_dir: Path, dataset: SWEBenchData print(f"Using log directory: {log_dir}") # Run evaluations - run_evals(predictions_jsonl, logs_dir, dataset, run_id) - + evaluation_result_file = patched_swebench_eval( + predictions_jsonl, + run_id, + dataset_name=dataset.value, + cache_level="instance", + report_dir=logs_dir, + modal=True, + ) # Get and display report report = get_report(predictions_jsonl, logs_dir) @@ -156,6 +143,6 @@ def generate_report(predictions_dir: Path, logs_dir: Path, dataset: SWEBenchData predictions = update_pred_json(predictions, report, predictions_dir) else: print("No valid predictions found") - return 1 + return None - return 0 + return evaluation_result_file diff --git a/codegen-examples/examples/swebench_agent_run/run_eval.py b/codegen-examples/examples/swebench_agent_run/run_eval.py index 1dcf1f84c..52e876117 100644 --- a/codegen-examples/examples/swebench_agent_run/run_eval.py +++ b/codegen-examples/examples/swebench_agent_run/run_eval.py @@ -15,6 +15,8 @@ ) from codegen.sdk.core.codebase import Codebase +from metrics import write_report_to_db + PREDS_DNAME = Path(__file__).parent / "predictions" LOG_DIR = Path(__file__).parent / "logs" @@ -40,7 +42,9 @@ def process_modal(examples: list[SweBenchExample]): error_info = { "error_type": type(result).__name__, "error_message": str(result), - "traceback": traceback.format_exception(type(result), result, result.__traceback__), + "traceback": traceback.format_exception( + type(result), result, result.__traceback__ + ), } if isinstance(result, modal.exception.Error): @@ -98,7 +102,9 @@ def process_modal(examples: list[SweBenchExample]): return results -def process_batch_local(examples: list[SweBenchExample], batch_size=10, codebases: dict[str, Codebase] = {}): +def process_batch_local( + examples: list[SweBenchExample], batch_size=10, codebases: dict[str, Codebase] = {} +): """Process a batch of examples synchronously. Args: @@ -111,14 +117,18 @@ def process_batch_local(examples: list[SweBenchExample], batch_size=10, codebase # Process examples in batches for i in range(0, len(examples), batch_size): batch = examples[i : i + batch_size] - print(f"Processing batch {i // batch_size + 1}/{len(examples) // batch_size + 1} (examples {i + 1}-{min(i + batch_size, len(examples))})") + print( + f"Processing batch {i // batch_size + 1}/{len(examples) // batch_size + 1} (examples {i + 1}-{min(i + batch_size, len(examples))})" + ) # Process each example in the batch for example in batch: try: # Run the agent locally instead of using modal if codebases and example.instance_id in codebases: - result = run_agent_on_entry(example, codebase=codebases[example.instance_id]) + result = run_agent_on_entry( + example, codebase=codebases[example.instance_id] + ) else: result = run_agent_on_entry(example) results.append(result) @@ -166,9 +176,12 @@ def run_eval( "verified": SWEBenchDataset.VERIFIED, } dataset_enum = dataset_dict[dataset] - print(repo) - examples = get_swe_bench_examples(dataset=dataset_enum, length=length, instance_id=instance_id, repo=repo) - print(f"Examples:\n{'\n'.join([f'{e.instance_id} - {e.repo} - {e.base_commit}' for e in examples])}") + examples = get_swe_bench_examples( + dataset=dataset_enum, length=length, instance_id=instance_id, repo=repo + ) + print( + f"Examples:\n{'\n'.join([f'{e.instance_id} - {e.repo} - {e.base_commit}' for e in examples])}" + ) try: if use_existing_preds is None: @@ -201,7 +214,13 @@ def run_eval( "timestamp": timestamp, "total_examples": len(examples), "successful": len([r for r in results if r and "status" not in r]), - "failed": len([r for r in results if r and "status" in r and r["status"] == "error"]), + "failed": len( + [ + r + for r in results + if r and "status" in r and r["status"] == "error" + ] + ), "error_types": {}, "results": results, } @@ -209,8 +228,12 @@ def run_eval( # Collect error statistics for result in results: if result and "status" in result and result["status"] == "error": - error_type = result.get("error_info", {}).get("error_type", "Unknown") - summary["error_types"][error_type] = summary["error_types"].get(error_type, 0) + 1 + error_type = result.get("error_info", {}).get( + "error_type", "Unknown" + ) + summary["error_types"][error_type] = ( + summary["error_types"].get(error_type, 0) + 1 + ) with open(summary_file, "w") as f: json.dump(summary, f, indent=4) @@ -226,7 +249,7 @@ def run_eval( print(f" {error_type}: {count}") # Generate Report on Modal - generate_report(predictions_dir, LOG_DIR, dataset_enum, run_id) + return predictions_dir, LOG_DIR, dataset_enum, run_id except Exception: print("Fatal error in run_eval:") traceback.print_exc() @@ -246,27 +269,46 @@ def run_eval( type=click.Choice(["lite", "full", "verified"]), default="lite", ) -@click.option("--length", help="The number of examples to process.", type=int, default=10) +@click.option( + "--length", help="The number of examples to process.", type=int, default=10 +) @click.option( "--instance-id", help="The instance ID of the example to process.", type=str, default=None, ) -@click.option("--local", help="Run the evaluation locally.", is_flag=True, default=False) +@click.option( + "--local", help="Run the evaluation locally.", is_flag=True, default=False +) +@click.option( + "--push-metrics", help="Push metrics to the database.", is_flag=True, default=False +) @click.option("--repo", help="The repo to use.", type=str, default=None) -def run_eval_command(use_existing_preds, dataset, length, instance_id, local, repo): +def run_eval_command( + use_existing_preds, dataset, length, instance_id, local, repo, push_metrics +): print(f"Repo: {repo}") - run_eval( - use_existing_preds=use_existing_preds, - dataset=dataset, - length=length, - instance_id=instance_id, - codebases=None, - local=local, - repo=repo, + + evaluation_result_file = generate_report( + run_eval( + use_existing_preds=use_existing_preds, + dataset=dataset, + length=length, + instance_id=instance_id, + codebases=None, + local=local, + repo=repo, + ) ) + if evaluation_result_file is not None and push_metrics: + try: + write_report_to_db(evaluation_result_file) + except Exception: + print("Error writing report to db") + traceback.print_exc() + if __name__ == "__main__": # Generate Report on Modal From 01236e5cfd40af3ccb6924dca340a9af5e581f29 Mon Sep 17 00:00:00 2001 From: Chris Lee Date: Tue, 4 Mar 2025 19:40:26 -0800 Subject: [PATCH 11/16] fix: refactor run to complete --- .../swebench_agent_run/.env.db.template | 5 + .../examples/swebench_agent_run/.gitignore | 1 + .../examples/swebench_agent_run/README.md | 107 +- .../examples/swebench_agent_run/agent_cli.py | 55 + .../examples/swebench_agent_run/deploy.sh | 3 + .../examples/swebench_agent_run/eval_cli.py | 314 ++ .../swebench_agent_run/pyproject.toml | 42 +- .../examples/swebench_agent_run/run_eval.py | 315 -- .../swebench_agent_run/__init__.py | 0 .../{ => swebench_agent_run}/metrics.py | 19 +- .../modal_harness/__init__.py | 0 .../modal_harness/entry_point.py | 59 +- .../modal_harness/sandbox.py | 12 +- .../{ => swebench_agent_run}/report.py | 0 .../swebench_agent_run/utils.py | 28 + .../examples/swebench_agent_run/test.py | 14 - .../examples/swebench_agent_run/uv.lock | 3637 +++++++++++++++++ codegen-examples/pyproject.toml | 2 - codegen-examples/uv.lock | 208 +- 19 files changed, 4428 insertions(+), 393 deletions(-) create mode 100644 codegen-examples/examples/swebench_agent_run/.env.db.template create mode 100644 codegen-examples/examples/swebench_agent_run/.gitignore create mode 100644 codegen-examples/examples/swebench_agent_run/agent_cli.py create mode 100755 codegen-examples/examples/swebench_agent_run/deploy.sh create mode 100644 codegen-examples/examples/swebench_agent_run/eval_cli.py delete mode 100644 codegen-examples/examples/swebench_agent_run/run_eval.py create mode 100644 codegen-examples/examples/swebench_agent_run/swebench_agent_run/__init__.py rename codegen-examples/examples/swebench_agent_run/{ => swebench_agent_run}/metrics.py (68%) rename codegen-examples/examples/swebench_agent_run/{ => swebench_agent_run}/modal_harness/__init__.py (100%) rename codegen-examples/examples/swebench_agent_run/{ => swebench_agent_run}/modal_harness/entry_point.py (86%) rename codegen-examples/examples/swebench_agent_run/{ => swebench_agent_run}/modal_harness/sandbox.py (92%) rename codegen-examples/examples/swebench_agent_run/{ => swebench_agent_run}/report.py (100%) create mode 100644 codegen-examples/examples/swebench_agent_run/swebench_agent_run/utils.py delete mode 100644 codegen-examples/examples/swebench_agent_run/test.py create mode 100644 codegen-examples/examples/swebench_agent_run/uv.lock diff --git a/codegen-examples/examples/swebench_agent_run/.env.db.template b/codegen-examples/examples/swebench_agent_run/.env.db.template new file mode 100644 index 000000000..e29dbd721 --- /dev/null +++ b/codegen-examples/examples/swebench_agent_run/.env.db.template @@ -0,0 +1,5 @@ +POSTGRES_HOST="localhost" +POSTGRES_DATABASE="swebench" +POSTGRES_USER="swebench" +POSTGRES_PASSWORD="swebench" +POSTGRES_PORT="5432" diff --git a/codegen-examples/examples/swebench_agent_run/.gitignore b/codegen-examples/examples/swebench_agent_run/.gitignore new file mode 100644 index 000000000..2737aca5c --- /dev/null +++ b/codegen-examples/examples/swebench_agent_run/.gitignore @@ -0,0 +1 @@ +.env.db diff --git a/codegen-examples/examples/swebench_agent_run/README.md b/codegen-examples/examples/swebench_agent_run/README.md index c6dc48676..d74cbdcf9 100644 --- a/codegen-examples/examples/swebench_agent_run/README.md +++ b/codegen-examples/examples/swebench_agent_run/README.md @@ -1,35 +1,96 @@ -# INSTRUCTIONS +# SWE-bench Agent Runner -1. Create a `.env` file in the `swebench_agent_run` directory (codegen-examples/examples/swebench_agent_run) and add your API keys. +Tool for running and evaluating model fixes using SWE-bench. -1. cd into the `codegen-examples/examples/swebench_agent_run` directory +## Setup -1. Create a `.venv` with `uv venv` and activate it with `source .venv/bin/activate` +1. Using the `.env.template` reference, create a `.env` file in the project root and add your API keys: -1. Install the dependencies with `uv pip install .` + ```env + OPENAI_API_KEY=your_key_here + MODAL_TOKEN_ID=your_token_id + MODAL_TOKEN_SECRET=your_token_secret + ``` -1. Install the codegen dependencies with `uv add codegen` +1. Create and activate a virtual environment: -- Note: If you'd like to install the dependencies using the global environment, use `uv pip install -e ../../../` instead of `uv pip install .`. This will allow you to test modifications to the codegen codebase. You will need to run `uv pip install -e ../../../` each time you make changes to the codebase. + ```bash + uv venv + source .venv/bin/activate + ``` -6. Ensure that you have a modal account and profile set up. If you don't have one, you can create one at https://modal.com/ +1. Install the package: -1. Activate the appropriate modal profile `python -m modal profile activate ` + ```bash + # Basic installation + uv pip install -e . -1. Launch the modal app with `python -m modal deploy --env= entry_point.py` + # With metrics support + uv pip install -e ".[metrics]" -1. Run the evaluation with `python -m run_eval` with the desired options: + # With development tools + uv pip install -e ".[dev]" -- ```bash - $ python run_eval.py --help - Usage: run_eval.py [OPTIONS] + # Install everything + uv pip install -e ".[all]" + ``` - Options: - --use-existing-preds TEXT The run ID of the existing predictions to - use. - --dataset [lite|full|verified] The dataset to use. - --length INTEGER The number of examples to process. - --instance-id TEXT The instance ID of the example to process. - --repo TEXT The repo to use. - --help Show this message and exit. - ``` +1. Set up Modal: + + - Create an account at https://modal.com/ if you don't have one + - Activate your Modal profile: + ```bash + python -m modal profile activate + ``` + - Deploy the Modal app: + ```bash + python -m modal deploy entry_point.py + ``` + +## Usage + +The package provides two main command-line tools: + +### Testing SWE CodeAgent + +Run the agent on a specific repository: + +```bash +# Using the installed command +swe-agent --repo pallets/flask --prompt "Analyze the URL routing system" + +# Options +swe-agent --help +Options: + --agent-class [DefaultAgent|CustomAgent] Agent class to use + --repo TEXT Repository to analyze (owner/repo) + --prompt TEXT Prompt for the agent + --help Show this message and exit +``` + +### Running SWE-Bench Eval + +Deploy modal app + +```bash +./deploy.sh +``` + +Run evaluations on model fixes: + +```bash +# Using the installed command +swe-eval --dataset lite --length 10 + +# Options +swe-eval --help +Options: + --use-existing-preds TEXT Run ID of existing predictions + --dataset [lite|full|verified] Dataset to use + --length INTEGER Number of examples to process + --instance-id TEXT Specific instance ID to process + --repo TEXT Specific repo to evaluate + --local Run evaluation locally + --push-metrics Push results to metrics database (Requires additional database environment variables) + --help Show this message and exit +``` diff --git a/codegen-examples/examples/swebench_agent_run/agent_cli.py b/codegen-examples/examples/swebench_agent_run/agent_cli.py new file mode 100644 index 000000000..223cea4cb --- /dev/null +++ b/codegen-examples/examples/swebench_agent_run/agent_cli.py @@ -0,0 +1,55 @@ +import click +import modal +from codegen import CodeAgent, Codebase + +image = modal.Image.debian_slim(python_version="3.13").apt_install("git").pip_install("codegen") + +app = modal.App( + name="codegen-examples", + image=image, + secrets=[modal.Secret.from_dotenv()], +) + + +@app.function() +def run_agent(repo_name: str, prompt: str) -> bool: + codebase = Codebase.from_repo(repo_full_name=repo_name) + agent = CodeAgent(codebase) + return agent.run(prompt=prompt) + + +@click.command() +@click.option( + "--repo", + type=str, + default="pallets/flask", + help="The repository to analyze (format: owner/repo)", +) +@click.option( + "--prompt", + type=str, + default="Tell me about the codebase and the files in it.", + help="The prompt to send to the agent", +) +def main(repo: str, prompt: str): + """Run a codegen agent on a GitHub repository.""" + # Import agent class dynamically based on name + + click.echo(f"Running on {repo}") + click.echo(f"Prompt: {prompt}") + + try: + with app.run(): + result = run_agent.remote(repo, prompt) + if result: + click.echo("✅ Analysis completed successfully:") + click.echo(result) + else: + click.echo("❌ Analysis failed") + except Exception as e: + click.echo(f"❌ Error: {str(e)}", err=True) + raise click.Abort() + + +if __name__ == "__main__": + main() diff --git a/codegen-examples/examples/swebench_agent_run/deploy.sh b/codegen-examples/examples/swebench_agent_run/deploy.sh new file mode 100755 index 000000000..a1a681fb3 --- /dev/null +++ b/codegen-examples/examples/swebench_agent_run/deploy.sh @@ -0,0 +1,3 @@ +#! /bin/bash + +uv run modal deploy swebench_agent_run/modal_harness/entry_point.py diff --git a/codegen-examples/examples/swebench_agent_run/eval_cli.py b/codegen-examples/examples/swebench_agent_run/eval_cli.py new file mode 100644 index 000000000..22d5aa969 --- /dev/null +++ b/codegen-examples/examples/swebench_agent_run/eval_cli.py @@ -0,0 +1,314 @@ +import json +import traceback +import uuid +from dataclasses import asdict, dataclass +from datetime import datetime +from pathlib import Path +from typing import Any, ClassVar, Dict, List, Optional, Tuple + +import click +import modal +from codegen.extensions.swebench.harness import run_agent_on_entry +from codegen.extensions.swebench.utils import ( + SWEBenchDataset, + SweBenchExample, + get_swe_bench_examples, +) +from codegen.sdk.core.codebase import Codebase + +from swebench_agent_run.report import generate_report +from swebench_agent_run.utils import track_batches + +# Constants +PREDS_DNAME = Path(__file__).parent / "predictions" +LOG_DIR = Path(__file__).parent / "logs" + +# Modal function setup +run_agent_modal = modal.Function.from_name( + app_name="swebench-agent-run", + name="run_agent_modal", +) + + +# Type aliases +@dataclass +class ErrorInfo: + error_type: str + error_message: str + traceback: str + modal_error_code: Optional[str] = None + modal_error_details: Optional[dict] = None + + def format_error(self, example_id: str = "") -> Dict[str, Any]: + """Format error information into a structured dictionary.""" + error_dict = { + "error_context": "Processing error" + if not example_id + else f"Error processing {example_id}", + "error_details": { + "type": self.error_type, + "message": self.error_message, + "traceback": self.traceback.split("\n"), # Split for better JSON formatting + }, + } + + if self.modal_error_code or self.modal_error_details: + error_dict["error_details"]["modal_specific"] = { + "error_code": self.modal_error_code, + "error_details": self.modal_error_details, + } + + return error_dict + + +@dataclass +class ProcessingResult: + instance_id: str + status: Optional[str] = None + error_info: Optional[ErrorInfo] = None + result: Optional[dict] = None + + ERROR_STATUS: ClassVar[str] = "error" # Class constant for error status + + @classmethod + def create_error(cls, instance_id: str, error_info: ErrorInfo) -> "ProcessingResult": + """Create a ProcessingResult instance for an error case.""" + return cls(instance_id=instance_id, status=cls.ERROR_STATUS, error_info=error_info) + + +def create_error_info(error: Exception, example_id: str = "") -> ErrorInfo: + """Create standardized error information.""" + traceback_str = ( + "".join(traceback.format_exception(type(error), error, error.__traceback__)) + if hasattr(error, "__traceback__") + else traceback.format_exc() + ) + + error_info = ErrorInfo( + error_type=type(error).__name__, + error_message=str(error), + traceback=traceback_str, + ) + + if isinstance(error, modal.exception.Error): + error_info.modal_error_code = getattr(error, "code", None) + error_info.modal_error_details = getattr(error, "details", None) + + # Print formatted error as JSON + print(json.dumps(error_info.format_error(example_id), indent=2)) + + return error_info + + +def process_modal(examples: list[SweBenchExample]) -> List[ProcessingResult]: + """Process examples using Modal's parallel execution.""" + results: List[ProcessingResult] = [] + + try: + batch_results = run_agent_modal.map(examples) + + for example, result in zip(examples, batch_results): + if isinstance(result, Exception): + error_info = create_error_info(result, example.instance_id) + results.append(ProcessingResult.create_error(example.instance_id, error_info)) + elif result is None: + print(f"Warning: Null result for {example.instance_id}") + results.append( + ProcessingResult.create_error( + example.instance_id, + ErrorInfo( + error_type="NullResult", + error_message="Process returned None", + ), + ) + ) + else: + results.append(ProcessingResult(instance_id=example.instance_id, result=result)) + + except Exception as e: + error_info = create_error_info(e) + # Mark all examples as failed + results.extend( + [ProcessingResult.create_error(example.instance_id, error_info) for example in examples] + ) + + return results + + +def process_batch_local( + examples: list[SweBenchExample], + batch_size: int = 10, + codebases: dict[str, Codebase] = {}, +) -> List[ProcessingResult]: + """Process examples in local batches.""" + results: List[ProcessingResult] = [] + + for _, batch in track_batches(examples, batch_size, desc="Processing examples"): + for example in batch: + try: + result = run_agent_on_entry(example, codebase=codebases.get(example.instance_id)) + results.append(ProcessingResult(instance_id=example.instance_id, result=result)) + except Exception as e: + error_info = create_error_info(e, example.instance_id) + results.append(ProcessingResult.create_error(example.instance_id, error_info)) + + return results + + +def save_results( + results: List[ProcessingResult], predictions_dir: Path, timestamp: str +) -> Tuple[Path, dict]: + """Save individual results and create summary.""" + # Save individual results + for result in results: + output_file = predictions_dir / f"{result.instance_id}.json" + output_file.parent.mkdir(exist_ok=True, parents=True) + with open(output_file, "w") as f: + # Convert dataclass to dict for JSON serialization + json.dump(asdict(result), f, indent=4) + + # Create and save summary + summary = { + "timestamp": timestamp, + "total_examples": len(results), + "successful": len([r for r in results if not r.status]), # No status means success + "failed": len([r for r in results if r.status == ProcessingResult.ERROR_STATUS]), + "error_types": {}, + "results": [asdict(r) for r in results], # Convert all results to dict + } + + # Collect error statistics + for result in results: + if result.status == ProcessingResult.ERROR_STATUS and result.error_info: + error_type = result.error_info.error_type + summary["error_types"][error_type] = summary["error_types"].get(error_type, 0) + 1 + + summary_file = predictions_dir / f"summary_{timestamp}.json" + with open(summary_file, "w") as f: + json.dump(summary, f, indent=4) + + return summary_file, summary + + +def print_summary(summary: dict, predictions_dir: Path, summary_file: Path) -> None: + """Print processing summary information.""" + print("\nProcessing complete!") + print(f"Results saved to: {predictions_dir}") + print(f"Summary saved to: {summary_file}") + print(f"Successful: {summary['successful']}/{summary['total_examples']}") + print(f"Failed: {summary['failed']}/{summary['total_examples']}") + + if summary["error_types"]: + print("\nError type distribution:") + for error_type, count in summary["error_types"].items(): + print(f" {error_type}: {count}") + + +def run_eval( + use_existing_preds: Optional[str], + dataset: str, + length: int, + instance_id: Optional[str] = None, + local: bool = False, + codebases: Dict[str, Codebase] = {}, + repo: Optional[str] = None, +) -> Tuple[Path, Path, SWEBenchDataset, str]: + """Main evaluation function.""" + run_id = use_existing_preds or str(uuid.uuid4()) + print(f"Run ID: {run_id}") + + predictions_dir = PREDS_DNAME / f"results_{run_id}" + dataset_enum = { + "lite": SWEBenchDataset.LITE, + "full": SWEBenchDataset.FULL, + "verified": SWEBenchDataset.VERIFIED, + }[dataset] + + examples = get_swe_bench_examples( + dataset=dataset_enum, length=length, instance_id=instance_id, repo=repo + ) + print( + "Examples:\n" + "\n".join(f"{e.instance_id} - {e.repo} - {e.base_commit}" for e in examples) + ) + + try: + if use_existing_preds is None: + print(f"Processing {len(examples)} examples...") + predictions_dir.mkdir(exist_ok=True, parents=True) + timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") + + results = ( + process_batch_local(examples, codebases=codebases) + if local + else process_modal(examples) + ) + summary_file, summary = save_results(results, predictions_dir, timestamp) + print_summary(summary, predictions_dir, summary_file) + + return predictions_dir, LOG_DIR, dataset_enum, run_id + except Exception: + traceback.print_exc() + raise + + +@click.command() +@click.option( + "--use-existing-preds", + help="The run ID of the existing predictions to use.", + type=str, + default=None, +) +@click.option( + "--dataset", + help="The dataset to use.", + type=click.Choice(["lite", "full", "verified"]), + default="lite", +) +@click.option("--length", help="The number of examples to process.", type=int, default=10) +@click.option( + "--instance-id", + help="The instance ID of the example to process.", + type=str, + default=None, +) +@click.option("--local", help="Run the evaluation locally.", is_flag=True, default=False) +@click.option("--push-metrics", help="Push metrics to the database.", is_flag=True, default=False) +@click.option("--repo", help="The repo to use.", type=str, default=None) +def main( + use_existing_preds: Optional[str], + dataset: str, + length: int, + instance_id: Optional[str], + local: bool, + repo: Optional[str], + push_metrics: bool, +) -> None: + """Command-line interface for running evaluations.""" + print(f"Repo: {repo}") + + evaluation_result_file = generate_report( + *run_eval( + use_existing_preds=use_existing_preds, + dataset=dataset, + length=length, + instance_id=instance_id, + codebases=None, + local=local, + repo=repo, + ) + ) + + if evaluation_result_file is not None and push_metrics: + try: + from swebench_agent_run.metrics import ( + write_report_to_db, # delay import because of extras + ) + + write_report_to_db(evaluation_result_file) + except Exception: + print("Error writing report to db") + traceback.print_exc() + + +if __name__ == "__main__": + main() diff --git a/codegen-examples/examples/swebench_agent_run/pyproject.toml b/codegen-examples/examples/swebench_agent_run/pyproject.toml index 05df11885..c8774eb77 100644 --- a/codegen-examples/examples/swebench_agent_run/pyproject.toml +++ b/codegen-examples/examples/swebench_agent_run/pyproject.toml @@ -1,10 +1,44 @@ [project] name = "swebench-agent-run" version = "0.1.0" -description = "Add your description here" +description = "SWE-bench agent runner for evaluating model fixes" readme = "README.md" requires-python = ">=3.12, <3.14" -dependencies = ["modal>=0.73.25", "psycopg2-binary"] +dependencies = [ + "modal>=0.73.25", + "tqdm>=4.66.0", + "click>=8.1.0", + "codegen", + "swebench>=3.0.15", +] -[tool.setuptools] -py-modules = ["entry_point", "run_eval"] +[project.optional-dependencies] +metrics = ["psycopg2-binary"] +dev = ["ruff", "mypy"] +all = ["swebench-agent-run[metrics,dev]"] + +[project.scripts] +swe-agent = "agent_cli:main" +swe-eval = "eval_cli:main" +modal-deploy = "modal_harness:deploy" + +[tool.ruff] +line-length = 100 +target-version = "py312" + + +[tool.mypy] +python_version = "3.12" +strict = true +warn_return_any = true +warn_unused_configs = true + +[build-system] +requires = ["hatchling"] +build-backend = "hatchling.build" + +[tool.hatch.metadata] +allow-direct-references = true + +[tool.uv.sources] +codegen = { path = "../../../" } diff --git a/codegen-examples/examples/swebench_agent_run/run_eval.py b/codegen-examples/examples/swebench_agent_run/run_eval.py deleted file mode 100644 index 52e876117..000000000 --- a/codegen-examples/examples/swebench_agent_run/run_eval.py +++ /dev/null @@ -1,315 +0,0 @@ -import json -import traceback -import uuid -from datetime import datetime -from pathlib import Path - -import click -import modal -from codegen.extensions.swebench.harness import run_agent_on_entry -from codegen.extensions.swebench.report import generate_report -from codegen.extensions.swebench.utils import ( - SWEBenchDataset, - SweBenchExample, - get_swe_bench_examples, -) -from codegen.sdk.core.codebase import Codebase - -from metrics import write_report_to_db - -PREDS_DNAME = Path(__file__).parent / "predictions" -LOG_DIR = Path(__file__).parent / "logs" - -run_agent_modal = modal.Function.from_name( - app_name="swebench-agent-run", - name="run_agent_modal", -) - - -def process_modal(examples: list[SweBenchExample]): - """Process all examples using Modal's map function. - - Args: - examples: List of SweBenchExample objects to process - """ - results = [] - - try: - batch_results = run_agent_modal.map(examples) - - for example, result in zip(examples, batch_results): - if isinstance(result, Exception): - error_info = { - "error_type": type(result).__name__, - "error_message": str(result), - "traceback": traceback.format_exception( - type(result), result, result.__traceback__ - ), - } - - if isinstance(result, modal.exception.Error): - error_info["modal_error_code"] = getattr(result, "code", None) - error_info["modal_error_details"] = getattr(result, "details", None) - - print(f"Error processing {example.instance_id}:") - print(f"Type: {error_info['error_type']}") - print(f"Message: {error_info['error_message']}") - print("Traceback:") - print("".join(error_info["traceback"])) - - results.append( - { - "instance_id": example.instance_id, - "status": "error", - "error_info": error_info, - } - ) - elif result is None: - print(f"Warning: Null result for {example.instance_id}") - results.append( - { - "instance_id": example.instance_id, - "status": "error", - "error_info": { - "error_type": "NullResult", - "error_message": "Process returned None", - }, - } - ) - else: - results.append(result) - - except Exception as e: - print("Processing error:") - print(f"Type: {type(e).__name__}") - print(f"Message: {str(e)}") - traceback.print_exc() - - # Mark all examples as failed - for example in examples: - results.append( - { - "instance_id": example.instance_id, - "status": "error", - "error_info": { - "error_type": type(e).__name__, - "error_message": str(e), - "traceback": traceback.format_exc(), - }, - } - ) - - return results - - -def process_batch_local( - examples: list[SweBenchExample], batch_size=10, codebases: dict[str, Codebase] = {} -): - """Process a batch of examples synchronously. - - Args: - examples: List of SweBenchExample objects to process - batch_size: Number of examples to process in each batch. - Default is 10 to avoid overwhelming the system. - """ - results = [] - - # Process examples in batches - for i in range(0, len(examples), batch_size): - batch = examples[i : i + batch_size] - print( - f"Processing batch {i // batch_size + 1}/{len(examples) // batch_size + 1} (examples {i + 1}-{min(i + batch_size, len(examples))})" - ) - - # Process each example in the batch - for example in batch: - try: - # Run the agent locally instead of using modal - if codebases and example.instance_id in codebases: - result = run_agent_on_entry( - example, codebase=codebases[example.instance_id] - ) - else: - result = run_agent_on_entry(example) - results.append(result) - - except Exception as e: - error_type = type(e).__name__ - error_info = { - "error_type": error_type, - "error_message": str(e), - "traceback": traceback.format_exc(), - } - - print(f"Error processing {example.instance_id}:") - print(f"Type: {error_type}") - print(f"Message: {str(e)}") - print("Traceback:") - print(error_info["traceback"]) - - results.append( - { - "instance_id": example.instance_id, - "status": "error", - "error_info": error_info, - } - ) - - return results - - -def run_eval( - use_existing_preds: str | None, - dataset: str, - length: int, - instance_id: str | None = None, - local: bool = False, - codebases: dict[str, Codebase] = {}, - repo: str | None = None, -): - run_id = use_existing_preds or str(uuid.uuid4()) - print(f"Run ID: {run_id}") - predictions_dir = PREDS_DNAME / f"results_{run_id}" - dataset_dict = { - "lite": SWEBenchDataset.LITE, - "full": SWEBenchDataset.FULL, - "verified": SWEBenchDataset.VERIFIED, - } - dataset_enum = dataset_dict[dataset] - examples = get_swe_bench_examples( - dataset=dataset_enum, length=length, instance_id=instance_id, repo=repo - ) - print( - f"Examples:\n{'\n'.join([f'{e.instance_id} - {e.repo} - {e.base_commit}' for e in examples])}" - ) - - try: - if use_existing_preds is None: - print(f"Processing {len(examples)} examples...") - - # Create output directory if it doesn't exist - predictions_dir.mkdir(exist_ok=True, parents=True) - - # Create a timestamp for this run - timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") - - # Process all examples in parallel batches - if local: - results = process_batch_local(examples, codebases=codebases) - else: - results = process_modal(examples) - - # Save individual results - for result in results: - if result and "instance_id" in result: - instance_id = result["instance_id"] - output_file = predictions_dir / f"{instance_id}.json" - output_file.parent.mkdir(exist_ok=True, parents=True) - with open(output_file, "w") as f: - json.dump(result, f, indent=4) - - # Save summary file - summary_file = predictions_dir / f"summary_{timestamp}.json" - summary = { - "timestamp": timestamp, - "total_examples": len(examples), - "successful": len([r for r in results if r and "status" not in r]), - "failed": len( - [ - r - for r in results - if r and "status" in r and r["status"] == "error" - ] - ), - "error_types": {}, - "results": results, - } - - # Collect error statistics - for result in results: - if result and "status" in result and result["status"] == "error": - error_type = result.get("error_info", {}).get( - "error_type", "Unknown" - ) - summary["error_types"][error_type] = ( - summary["error_types"].get(error_type, 0) + 1 - ) - - with open(summary_file, "w") as f: - json.dump(summary, f, indent=4) - - print("\nProcessing complete!") - print(f"Results saved to: {predictions_dir}") - print(f"Summary saved to: {summary_file}") - print(f"Successful: {summary['successful']}/{summary['total_examples']}") - print(f"Failed: {summary['failed']}/{summary['total_examples']}") - if summary["error_types"]: - print("\nError type distribution:") - for error_type, count in summary["error_types"].items(): - print(f" {error_type}: {count}") - - # Generate Report on Modal - return predictions_dir, LOG_DIR, dataset_enum, run_id - except Exception: - print("Fatal error in run_eval:") - traceback.print_exc() - raise - - -@click.command() -@click.option( - "--use-existing-preds", - help="The run ID of the existing predictions to use.", - type=str, - default=None, -) -@click.option( - "--dataset", - help="The dataset to use.", - type=click.Choice(["lite", "full", "verified"]), - default="lite", -) -@click.option( - "--length", help="The number of examples to process.", type=int, default=10 -) -@click.option( - "--instance-id", - help="The instance ID of the example to process.", - type=str, - default=None, -) -@click.option( - "--local", help="Run the evaluation locally.", is_flag=True, default=False -) -@click.option( - "--push-metrics", help="Push metrics to the database.", is_flag=True, default=False -) -@click.option("--repo", help="The repo to use.", type=str, default=None) -def run_eval_command( - use_existing_preds, dataset, length, instance_id, local, repo, push_metrics -): - print(f"Repo: {repo}") - - evaluation_result_file = generate_report( - run_eval( - use_existing_preds=use_existing_preds, - dataset=dataset, - length=length, - instance_id=instance_id, - codebases=None, - local=local, - repo=repo, - ) - ) - - if evaluation_result_file is not None and push_metrics: - try: - write_report_to_db(evaluation_result_file) - except Exception: - print("Error writing report to db") - traceback.print_exc() - - -if __name__ == "__main__": - # Generate Report on Modal - run_eval_command() diff --git a/codegen-examples/examples/swebench_agent_run/swebench_agent_run/__init__.py b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/codegen-examples/examples/swebench_agent_run/metrics.py b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/metrics.py similarity index 68% rename from codegen-examples/examples/swebench_agent_run/metrics.py rename to codegen-examples/examples/swebench_agent_run/swebench_agent_run/metrics.py index 681338309..d9fd49521 100644 --- a/codegen-examples/examples/swebench_agent_run/metrics.py +++ b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/metrics.py @@ -1,9 +1,20 @@ import json +import os from importlib.metadata import version +from pathlib import Path + +import psycopg2 +from dotenv import load_dotenv def write_report_to_db(report_file: str): - import psycopg2 + load_dotenv(str((Path(__file__).parent.parent / ".env.db").resolve())) + + postgres_host = os.getenv("POSTGRES_HOST") + postgres_database = os.getenv("POSTGRES_DATABASE") + postgres_user = os.getenv("POSTGRES_USER") + postgres_password = os.getenv("POSTGRES_PASSWORD") + postgres_port = os.getenv("POSTGRES_PORT") try: codegen_version = version("codegen") @@ -15,7 +26,11 @@ def write_report_to_db(report_file: str): # Establish connection conn = psycopg2.connect( - host="localhost", database="swebench", user="swebench", password="swebench" + host=postgres_host, + database=postgres_database, + user=postgres_user, + password=postgres_password, + port=postgres_port, ) # Create a cursor diff --git a/codegen-examples/examples/swebench_agent_run/modal_harness/__init__.py b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/__init__.py similarity index 100% rename from codegen-examples/examples/swebench_agent_run/modal_harness/__init__.py rename to codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/__init__.py diff --git a/codegen-examples/examples/swebench_agent_run/modal_harness/entry_point.py b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/entry_point.py similarity index 86% rename from codegen-examples/examples/swebench_agent_run/modal_harness/entry_point.py rename to codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/entry_point.py index 76bc56341..3092b17c0 100644 --- a/codegen-examples/examples/swebench_agent_run/modal_harness/entry_point.py +++ b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/entry_point.py @@ -9,11 +9,10 @@ import time import traceback from contextlib import nullcontext +from typing import TYPE_CHECKING from unittest.mock import patch import modal as modal_lib -from codegen.extensions.swebench.harness import run_agent_on_entry -from codegen.extensions.swebench.utils import SweBenchExample from swebench.harness.constants import ( APPLY_PATCH_FAIL, APPLY_PATCH_PASS, @@ -32,13 +31,51 @@ from swebench.harness.test_spec.test_spec import TestSpec from swebench.harness.utils import EvaluationError +if TYPE_CHECKING: + from codegen.extensions.swebench.utils import SweBenchExample + image = ( modal_lib.Image.debian_slim(python_version="3.13") .apt_install(["git", "ripgrep"]) - .copy_local_dir( - "../../../", "/root/codegen", ignore=[".venv", "**/.venv", "tests", "**/tests"] + .add_local_dir( + "../../../", + "/root/codegen", + ignore=[ + "__pycache__", + "**/__pycache__", + ".venv", + "**/.venv", + "tests", + "**/tests", + "codegen-on-oss/", + "codegen-examples/", + "build/", + ".vscode/", + ".codegen/", + ".github/", + ".architecture/", + "docs/", + "*cache/", + ], + copy=True, + ) + .add_local_dir( + ".", + "/root/swebench_agent_run", + ignore=[ + "__pycache__", + "**/__pycache__", + ".venv", + "**/.venv", + ".env*", + ], + copy=True, + ) + .run_commands( + "pip install -e /root/codegen", + "rm -r /root/codegen/.git", + "pip install -e /root/swebench_agent_run", ) - .run_commands("pip install -e /root/codegen") ) app = modal_lib.App( @@ -47,18 +84,18 @@ @app.function(timeout=10 * 60) -async def run_agent_modal(entry: SweBenchExample): +async def run_agent_modal(entry: "SweBenchExample"): + from codegen.extensions.swebench.harness import run_agent_on_entry + """Modal function to process a single example from the SWE-bench dataset.""" return run_agent_on_entry(entry) @app.function( image=swebench_image.add_local_file( - LOCAL_SANDBOX_ENTRYPOINT_PATH, - REMOTE_SANDBOX_ENTRYPOINT_PATH, - ).add_local_python_source("modal_harness"), - timeout=120 - * 60, # Much larger than default timeout to account for image build time + LOCAL_SANDBOX_ENTRYPOINT_PATH, REMOTE_SANDBOX_ENTRYPOINT_PATH, copy=True + ).add_local_python_source("eval_cli", "swebench_agent_run", copy=True), + timeout=120 * 60, # Much larger than default timeout to account for image build time ) def run_instance_modal( test_spec: TestSpec, diff --git a/codegen-examples/examples/swebench_agent_run/modal_harness/sandbox.py b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/sandbox.py similarity index 92% rename from codegen-examples/examples/swebench_agent_run/modal_harness/sandbox.py rename to codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/sandbox.py index 33e3149f7..25664d1f5 100644 --- a/codegen-examples/examples/swebench_agent_run/modal_harness/sandbox.py +++ b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/sandbox.py @@ -24,9 +24,7 @@ def save_snapshot_uid(self, example: SWEbenchInstance, snapshot_uid: str) -> Non class VolumeSnapshotManager(SnapshotManager): def __init__(self, volume_name: str = "swebench-agent-snapshot-volume"): - self.snapshot_volume = modal_lib.Volume.from_name( - volume_name, create_if_missing=True - ) + self.snapshot_volume = modal_lib.Volume.from_name(volume_name, create_if_missing=True) self.snapshot_meta_file_path: str = "/root/snapshot_meta.json" def get_snapshot_uid(self, example: SWEbenchInstance) -> str: @@ -46,9 +44,7 @@ def save_snapshot_uid(self, example: SWEbenchInstance, snapshot_uid: str) -> Non def read_snapshot_meta(self) -> dict[str, dict[str, str]]: bytes_io = io.BytesIO() try: - self.snapshot_volume.read_file_into_fileobj( - self.snapshot_meta_file_path, bytes_io - ) + self.snapshot_volume.read_file_into_fileobj(self.snapshot_meta_file_path, bytes_io) snapshot_meta = json.loads(bytes_io.getvalue().decode("utf-8")) except FileNotFoundError: snapshot_meta = {} @@ -66,9 +62,7 @@ def get_snapshot_uid(self, example: SWEbenchInstance) -> str | None: return None def save_snapshot_uid(self, example: SWEbenchInstance, snapshot_uid: str) -> None: - self.snapshot_dict[(example.repo, example.environment_setup_commit)] = ( - snapshot_uid - ) + self.snapshot_dict[(example.repo, example.environment_setup_commit)] = snapshot_uid class CGModalSandboxRuntime(ModalSandboxRuntime): diff --git a/codegen-examples/examples/swebench_agent_run/report.py b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/report.py similarity index 100% rename from codegen-examples/examples/swebench_agent_run/report.py rename to codegen-examples/examples/swebench_agent_run/swebench_agent_run/report.py diff --git a/codegen-examples/examples/swebench_agent_run/swebench_agent_run/utils.py b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/utils.py new file mode 100644 index 000000000..64ed1609b --- /dev/null +++ b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/utils.py @@ -0,0 +1,28 @@ +from itertools import batched +from typing import Iterator, List, TypeVar + +from tqdm import tqdm + +T = TypeVar("T") + + +def track_batches( + items: List[T], batch_size: int, desc: str = "Processing" +) -> Iterator[tuple[int, List[T]]]: + """ + Track batch progress with tqdm. + Returns tuples of (batch_number, batch_items). + """ + total_items = len(items) + total_batches = (total_items + batch_size - 1) // batch_size + + with tqdm( + total=total_items, + desc=desc, + unit="examples", + bar_format="{l_bar}{bar}| {n_fmt}/{total_fmt} examples [{elapsed}<{remaining}, {rate_fmt}]", + ) as pbar: + for batch_num, batch in enumerate(batched(items, batch_size), 1): + pbar.set_postfix({"batch": f"{batch_num}/{total_batches}", "batch_size": len(batch)}) + yield batch_num, batch + pbar.update(len(batch)) diff --git a/codegen-examples/examples/swebench_agent_run/test.py b/codegen-examples/examples/swebench_agent_run/test.py deleted file mode 100644 index fb6e4eb5a..000000000 --- a/codegen-examples/examples/swebench_agent_run/test.py +++ /dev/null @@ -1,14 +0,0 @@ -from codegen import Codebase -import modal - -image = modal.Image.debian_slim(python_version="3.13").apt_install("git").pip_install("fastapi[standard]").run_commands("pip install codegen") - -app = modal.App(name="codegen-examples", 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Mon Sep 17 00:00:00 2001 From: Chris Lee Date: Mon, 10 Mar 2025 16:06:02 -0700 Subject: [PATCH 12/16] wip: merge changes from run_eval develop --- .../swebench_agent_run/entry_point.py | 19 ------- .../examples/swebench_agent_run/eval_cli.py | 55 +++++++++++++++---- .../examples/swebench_agent_run/run_eval.py | 37 ++++++++++--- .../{ => swebench_agent_run}/constants.py | 0 .../modal_harness/entry_point.py | 6 +- .../examples/swebench_agent_run/uv.lock | 25 +++++++-- 6 files changed, 95 insertions(+), 47 deletions(-) delete mode 100644 codegen-examples/examples/swebench_agent_run/entry_point.py rename codegen-examples/examples/swebench_agent_run/{ => swebench_agent_run}/constants.py (100%) diff --git a/codegen-examples/examples/swebench_agent_run/entry_point.py b/codegen-examples/examples/swebench_agent_run/entry_point.py deleted file mode 100644 index a364aaa19..000000000 --- a/codegen-examples/examples/swebench_agent_run/entry_point.py +++ /dev/null @@ -1,19 +0,0 @@ -from codegen.extensions.swebench.utils import SweBenchExample -from codegen.extensions.swebench.harness import run_agent_on_entry -import modal - -image = ( - modal.Image.debian_slim(python_version="3.13") - .apt_install(["git", "ripgrep"]) - .pip_install("fastapi[standard]") - .copy_local_dir("../../../", "/root/codegen", ignore=[".venv", "**/.venv", "tests", "**/tests"]) - .run_commands("pip install -e /root/codegen") -) - -app = modal.App(name="swebench-agent-run", image=image, secrets=[modal.Secret.from_dotenv()]) - - -@app.function(timeout=43200) -async def run_agent_modal(entry: SweBenchExample, run_id: str, model: str): - """Modal function to process a single example from the SWE-bench dataset.""" - return run_agent_on_entry(entry, run_id=run_id, model=model) diff --git a/codegen-examples/examples/swebench_agent_run/eval_cli.py b/codegen-examples/examples/swebench_agent_run/eval_cli.py index 22d5aa969..04da0e538 100644 --- a/codegen-examples/examples/swebench_agent_run/eval_cli.py +++ b/codegen-examples/examples/swebench_agent_run/eval_cli.py @@ -16,6 +16,7 @@ ) from codegen.sdk.core.codebase import Codebase +from swebench_agent_run.constants import DATASET_DICT from swebench_agent_run.report import generate_report from swebench_agent_run.utils import track_batches @@ -100,12 +101,18 @@ def create_error_info(error: Exception, example_id: str = "") -> ErrorInfo: return error_info -def process_modal(examples: list[SweBenchExample]) -> List[ProcessingResult]: +def process_modal( + examples: list[SweBenchExample], + model: str, + run_id: str, +) -> List[ProcessingResult]: """Process examples using Modal's parallel execution.""" results: List[ProcessingResult] = [] try: - batch_results = run_agent_modal.map(examples) + batch_results = run_agent_modal.starmap( + [(ex, run_id, model) for ex in examples], + ) for example, result in zip(examples, batch_results): if isinstance(result, Exception): @@ -139,6 +146,8 @@ def process_batch_local( examples: list[SweBenchExample], batch_size: int = 10, codebases: dict[str, Codebase] = {}, + model: str = "claude-3-7-sonnet-latest", + run_id: str | None = None, ) -> List[ProcessingResult]: """Process examples in local batches.""" results: List[ProcessingResult] = [] @@ -146,7 +155,12 @@ def process_batch_local( for _, batch in track_batches(examples, batch_size, desc="Processing examples"): for example in batch: try: - result = run_agent_on_entry(example, codebase=codebases.get(example.instance_id)) + result = run_agent_on_entry( + example, + model=model, + codebase=codebases.get(example.instance_id), + run_id=run_id, + ) results.append(ProcessingResult(instance_id=example.instance_id, result=result)) except Exception as e: error_info = create_error_info(e, example.instance_id) @@ -206,23 +220,19 @@ def print_summary(summary: dict, predictions_dir: Path, summary_file: Path) -> N def run_eval( use_existing_preds: Optional[str], - dataset: str, + dataset_enum: SWEBenchDataset, length: int, instance_id: Optional[str] = None, local: bool = False, codebases: Dict[str, Codebase] = {}, repo: Optional[str] = None, + model: str = "claude-3-7-sonnet-latest", ) -> Tuple[Path, Path, SWEBenchDataset, str]: """Main evaluation function.""" run_id = use_existing_preds or str(uuid.uuid4()) print(f"Run ID: {run_id}") predictions_dir = PREDS_DNAME / f"results_{run_id}" - dataset_enum = { - "lite": SWEBenchDataset.LITE, - "full": SWEBenchDataset.FULL, - "verified": SWEBenchDataset.VERIFIED, - }[dataset] examples = get_swe_bench_examples( dataset=dataset_enum, length=length, instance_id=instance_id, repo=repo @@ -233,14 +243,24 @@ def run_eval( try: if use_existing_preds is None: + print(f"Repo: {repo}") + print( + f"Examples:\n{'\n'.join([f'{e.instance_id} - {e.repo} - {e.base_commit}' for e in examples])}" + ) print(f"Processing {len(examples)} examples...") + predictions_dir.mkdir(exist_ok=True, parents=True) timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") results = ( - process_batch_local(examples, codebases=codebases) + process_batch_local( + examples, + codebases=codebases, + model=model, + run_id=run_id, + ) if local - else process_modal(examples) + else process_modal(examples, model=model, run_id=run_id) ) summary_file, summary = save_results(results, predictions_dir, timestamp) print_summary(summary, predictions_dir, summary_file) @@ -274,6 +294,13 @@ def run_eval( @click.option("--local", help="Run the evaluation locally.", is_flag=True, default=False) @click.option("--push-metrics", help="Push metrics to the database.", is_flag=True, default=False) @click.option("--repo", help="The repo to use.", type=str, default=None) +@click.option( + "--num-workers", + help="The number of workers to use. This is the number of examples that will be processed concurrently. A large number may lead to rate limiting issues.", + type=int, + default=5, +) +@click.option("--model", help="The model to use.", type=str, default="claude-3-7-sonnet-latest") def main( use_existing_preds: Optional[str], dataset: str, @@ -281,6 +308,8 @@ def main( instance_id: Optional[str], local: bool, repo: Optional[str], + num_workers: int, + model: str, push_metrics: bool, ) -> None: """Command-line interface for running evaluations.""" @@ -289,12 +318,14 @@ def main( evaluation_result_file = generate_report( *run_eval( use_existing_preds=use_existing_preds, - dataset=dataset, + dataset_enum=DATASET_DICT[dataset], length=length, instance_id=instance_id, codebases=None, local=local, repo=repo, + num_workers=num_workers, + model=model, ) ) diff --git a/codegen-examples/examples/swebench_agent_run/run_eval.py b/codegen-examples/examples/swebench_agent_run/run_eval.py index 4240b7036..79dd9def0 100644 --- a/codegen-examples/examples/swebench_agent_run/run_eval.py +++ b/codegen-examples/examples/swebench_agent_run/run_eval.py @@ -1,18 +1,24 @@ +""" +!!! REFACTORED INTO eval_cli.py !!! +""" + import asyncio import json +import time import traceback -from pathlib import Path import uuid -import modal +from pathlib import Path + import click -import time +import modal from codegen.extensions.swebench.enums import SWEBenchDataset, SWEBenchLiteSubset -from constants import DATASET_DICT from codegen.extensions.swebench.harness import run_agent_on_entry -from codegen.extensions.swebench.utils import SweBenchExample, get_swe_bench_examples from codegen.extensions.swebench.report import generate_report +from codegen.extensions.swebench.utils import SweBenchExample, get_swe_bench_examples from codegen.sdk.core.codebase import Codebase +from swebench_agent_run.constants import DATASET_DICT + PREDS_DNAME = Path(__file__).parent / "predictions" LOG_DIR = Path(__file__).parent / "logs" @@ -197,7 +203,11 @@ async def process_example(example, attempt, current_task): await queue.put((example, attempt + 1)) return None - return {"status": "error", "instance_id": example.instance_id, "error_info": error_info} + return { + "status": "error", + "instance_id": example.instance_id, + "error_info": error_info, + } async def worker(): # Store this task reference to allow targeted cancellation @@ -259,7 +269,10 @@ async def worker(): # Return results in the same order as input examples return [ - results.get(example.instance_id, {"instance_id": example.instance_id, "status": "missing"}) + results.get( + example.instance_id, + {"instance_id": example.instance_id, "status": "missing"}, + ) for example in examples ] @@ -293,7 +306,10 @@ def process_batch_local( # Run the agent locally instead of using modal if codebases and example.instance_id in codebases: result = run_agent_on_entry( - example, model=model, codebase=codebases[example.instance_id], run_id=run_id + example, + model=model, + codebase=codebases[example.instance_id], + run_id=run_id, ) else: result = run_agent_on_entry(example, model=model, run_id=run_id) @@ -435,7 +451,10 @@ async def run_eval( ) @click.option("--length", help="The number of examples to process.", type=int, default=None) @click.option( - "--instance-id", help="The instance ID of the example to process.", type=str, default=None + "--instance-id", + help="The instance ID of the example to process.", + type=str, + default=None, ) @click.option("--local", help="Run the evaluation locally.", is_flag=True, default=False) @click.option("--repo", help="The repo to use.", type=str, default=None) diff --git a/codegen-examples/examples/swebench_agent_run/constants.py b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/constants.py similarity index 100% rename from codegen-examples/examples/swebench_agent_run/constants.py rename to codegen-examples/examples/swebench_agent_run/swebench_agent_run/constants.py diff --git a/codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/entry_point.py b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/entry_point.py index 3092b17c0..f5d8b050e 100644 --- a/codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/entry_point.py +++ b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/entry_point.py @@ -83,12 +83,12 @@ ) -@app.function(timeout=10 * 60) -async def run_agent_modal(entry: "SweBenchExample"): +@app.function(timeout=43200) +async def run_agent_modal(entry: "SweBenchExample", run_id: str, model: str): from codegen.extensions.swebench.harness import run_agent_on_entry """Modal function to process a single example from the SWE-bench dataset.""" - return run_agent_on_entry(entry) + return run_agent_on_entry(entry, run_id=run_id, model=model) @app.function( diff --git a/codegen-examples/examples/swebench_agent_run/uv.lock b/codegen-examples/examples/swebench_agent_run/uv.lock index 09059a827..0267ea146 100644 --- a/codegen-examples/examples/swebench_agent_run/uv.lock +++ b/codegen-examples/examples/swebench_agent_run/uv.lock @@ -342,6 +342,7 @@ dependencies = [ { name = "langchain-anthropic" }, { name = "langchain-core" }, { name = "langchain-openai" }, + { name = "langchain-xai" }, { name = "langgraph" }, { name = "langgraph-prebuilt" }, { name = "langsmith" }, @@ -419,6 +420,7 @@ requires-dist = [ { name = "langchain-anthropic", specifier = ">=0.3.7" }, { name = "langchain-core" }, { name = "langchain-openai" }, + { name = "langchain-xai", specifier = ">=0.2.1" }, { name = "langgraph" }, { name = "langgraph-prebuilt" }, { name = "langsmith" }, @@ -431,7 +433,7 @@ requires-dist = [ { name = "neo4j" }, { name = "networkx", specifier = ">=3.4.1" }, { name = "numpy", specifier = ">=2.2.2" }, - { name = "openai", specifier = "==1.65.2" }, + { name = "openai", specifier = "==1.65.5" }, { name = "packaging", specifier = ">=24.2" }, { name = "pip", specifier = ">=24.3.1" }, { name = "plotly", specifier = ">=5.24.0,<7.0.0" }, @@ -1334,6 +1336,21 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/4c/f8/6b82af988e65af9697f6a2f25373fb173fd32d48b62772a8773c5184c870/langchain_text_splitters-0.3.6-py3-none-any.whl", hash = "sha256:e5d7b850f6c14259ea930be4a964a65fa95d9df7e1dbdd8bad8416db72292f4e", size = 31197 }, ] +[[package]] +name = "langchain-xai" +version = "0.2.1" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "aiohttp" }, + { name = "langchain-core" }, + { name = "langchain-openai" }, + { name = "requests" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/a3/94/a633bf1b4bbf66e4516f4188adc1174480c465ae12fb98f06c3e23c98519/langchain_xai-0.2.1.tar.gz", hash = "sha256:143a6f52be7617b5e5c68ab10c9b7df90914f54a6b3098566ce22b5d8fd89da5", size = 7788 } +wheels = [ + { url = "https://files.pythonhosted.org/packages/7b/88/d8050e610fadabf97c1745d24f0987b3e53b72fca63c8038ab1e0c103da9/langchain_xai-0.2.1-py3-none-any.whl", hash = "sha256:87228125cb15131663979d627210fca47dcd6b9a28462e8b5fee47f73bbed9f4", size = 6263 }, +] + [[package]] name = "langgraph" version = "0.3.5" @@ -1810,7 +1827,7 @@ wheels = [ [[package]] name = "openai" -version = "1.65.2" +version = "1.65.5" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "anyio" }, @@ -1822,9 +1839,9 @@ dependencies = [ { name = "tqdm" }, { name = "typing-extensions" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/f6/03/0bbf201a7e44920d892db0445874c8111be4255cb9495379df18d6d36ea1/openai-1.65.2.tar.gz", hash = "sha256:729623efc3fd91c956f35dd387fa5c718edd528c4bed9f00b40ef290200fb2ce", size = 359185 } +sdist = { url = "https://files.pythonhosted.org/packages/56/cf/e02fb2c5a834803e6f29f43fd3dfe010303282d1ea450a5b95e28608860a/openai-1.65.5.tar.gz", hash = "sha256:17d39096bbcaf6c86580244b493a59e16613460147f0ba5ab6e608cdb6628149", size = 359548 } wheels = [ - { url = "https://files.pythonhosted.org/packages/2c/3b/722ed868cb56f70264190ed479b38b3e46d14daa267d559a3fe3bd9061cf/openai-1.65.2-py3-none-any.whl", hash = "sha256:27d9fe8de876e31394c2553c4e6226378b6ed85e480f586ccfe25b7193fb1750", size = 473206 }, + { url = "https://files.pythonhosted.org/packages/fc/8f/a178d73277bf2d838617fa20ba4ae6952e26074664aacb53ae4532a69588/openai-1.65.5-py3-none-any.whl", hash = "sha256:5948a504e7b4003d921cfab81273813793a31c25b1d7b605797c01757e0141f1", size = 474468 }, ] [[package]] From 60fed54026b0109d8980985f357cccdeb76caa6a Mon Sep 17 00:00:00 2001 From: Chris Lee Date: Mon, 10 Mar 2025 16:28:26 -0700 Subject: [PATCH 13/16] add: coarse retries for agent run --- .../examples/swebench_agent_run/eval_cli.py | 8 ----- .../swebench_agent_run/pyproject.toml | 1 + .../modal_harness/entry_point.py | 29 ++++++++++++++++++- .../examples/swebench_agent_run/uv.lock | 2 ++ 4 files changed, 31 insertions(+), 9 deletions(-) diff --git a/codegen-examples/examples/swebench_agent_run/eval_cli.py b/codegen-examples/examples/swebench_agent_run/eval_cli.py index 04da0e538..4f70fe006 100644 --- a/codegen-examples/examples/swebench_agent_run/eval_cli.py +++ b/codegen-examples/examples/swebench_agent_run/eval_cli.py @@ -294,12 +294,6 @@ def run_eval( @click.option("--local", help="Run the evaluation locally.", is_flag=True, default=False) @click.option("--push-metrics", help="Push metrics to the database.", is_flag=True, default=False) @click.option("--repo", help="The repo to use.", type=str, default=None) -@click.option( - "--num-workers", - help="The number of workers to use. This is the number of examples that will be processed concurrently. A large number may lead to rate limiting issues.", - type=int, - default=5, -) @click.option("--model", help="The model to use.", type=str, default="claude-3-7-sonnet-latest") def main( use_existing_preds: Optional[str], @@ -308,7 +302,6 @@ def main( instance_id: Optional[str], local: bool, repo: Optional[str], - num_workers: int, model: str, push_metrics: bool, ) -> None: @@ -324,7 +317,6 @@ def main( codebases=None, local=local, repo=repo, - num_workers=num_workers, model=model, ) ) diff --git a/codegen-examples/examples/swebench_agent_run/pyproject.toml b/codegen-examples/examples/swebench_agent_run/pyproject.toml index c8774eb77..640e252b5 100644 --- a/codegen-examples/examples/swebench_agent_run/pyproject.toml +++ b/codegen-examples/examples/swebench_agent_run/pyproject.toml @@ -10,6 +10,7 @@ dependencies = [ "click>=8.1.0", "codegen", "swebench>=3.0.15", + "tenacity>=9.0.0", ] [project.optional-dependencies] diff --git a/codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/entry_point.py b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/entry_point.py index f5d8b050e..b72a2c113 100644 --- a/codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/entry_point.py +++ b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/entry_point.py @@ -13,6 +13,7 @@ from unittest.mock import patch import modal as modal_lib +import tenacity from swebench.harness.constants import ( APPLY_PATCH_FAIL, APPLY_PATCH_PASS, @@ -83,12 +84,38 @@ ) +class ShouldRetry(Exception): + pass + + @app.function(timeout=43200) async def run_agent_modal(entry: "SweBenchExample", run_id: str, model: str): from codegen.extensions.swebench.harness import run_agent_on_entry """Modal function to process a single example from the SWE-bench dataset.""" - return run_agent_on_entry(entry, run_id=run_id, model=model) + for attempt in tenacity.Retrying( + wait=tenacity.wait_exponential_jitter(max=600), + retry=tenacity.retry_if_exception_type(ShouldRetry), + ): + with attempt: + try: + return run_agent_on_entry(entry, run_id=run_id, model=model) + except Exception as e: + if any( + msg in str(e).lower() + for msg in ( + "rate limit", + "too many requests", + "429", + "throttle", + "quota exceeded", + "capacity", + "limit exceeded", + ) + ): + raise ShouldRetry() from e + else: + raise e @app.function( diff --git a/codegen-examples/examples/swebench_agent_run/uv.lock b/codegen-examples/examples/swebench_agent_run/uv.lock index 0267ea146..ad009ade6 100644 --- a/codegen-examples/examples/swebench_agent_run/uv.lock +++ b/codegen-examples/examples/swebench_agent_run/uv.lock @@ -3068,6 +3068,7 @@ dependencies = [ { name = "codegen" }, { name = "modal" }, { name = "swebench" }, + { name = "tenacity" }, { name = "tqdm" }, ] @@ -3095,6 +3096,7 @@ requires-dist = [ { name = "ruff", marker = "extra == 'dev'" }, { name = "swebench", specifier = ">=3.0.15" }, { name = "swebench-agent-run", extras = ["metrics", "dev"], marker = "extra == 'all'" }, + { name = "tenacity", specifier = ">=9.0.0" }, { name = "tqdm", specifier = ">=4.66.0" }, ] From 260d5bcbefed5e683f136ac87712ca7009b1d3b1 Mon Sep 17 00:00:00 2001 From: Chris Lee Date: Tue, 11 Mar 2025 16:40:08 -0700 Subject: [PATCH 14/16] fix: limit agent modal function concurrency --- .../swebench_agent_run/modal_harness/entry_point.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/entry_point.py b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/entry_point.py index b72a2c113..6002e6364 100644 --- a/codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/entry_point.py +++ b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/entry_point.py @@ -88,7 +88,7 @@ class ShouldRetry(Exception): pass -@app.function(timeout=43200) +@app.function(timeout=43200, max_containers=10) async def run_agent_modal(entry: "SweBenchExample", run_id: str, model: str): from codegen.extensions.swebench.harness import run_agent_on_entry From c8cbde9913175658ef41323aa68d6dd5f334187c Mon Sep 17 00:00:00 2001 From: Chris Lee Date: Tue, 11 Mar 2025 18:16:38 -0700 Subject: [PATCH 15/16] fix: post-merge bugs --- .../examples/swebench_agent_run/eval_cli.py | 9 +- .../examples/swebench_agent_run/run_eval.py | 488 ------------------ .../swebench_agent_run/metrics.py | 18 +- .../swebench_agent_run/report.py | 3 +- 4 files changed, 21 insertions(+), 497 deletions(-) delete mode 100644 codegen-examples/examples/swebench_agent_run/run_eval.py diff --git a/codegen-examples/examples/swebench_agent_run/eval_cli.py b/codegen-examples/examples/swebench_agent_run/eval_cli.py index 4f70fe006..faec4848c 100644 --- a/codegen-examples/examples/swebench_agent_run/eval_cli.py +++ b/codegen-examples/examples/swebench_agent_run/eval_cli.py @@ -321,7 +321,14 @@ def main( ) ) - if evaluation_result_file is not None and push_metrics: + if push_metrics: + if evaluation_result_file is None: + if use_existing_preds is None: + print("Evaluation was not run - no metrics were pushed") + return + else: + evaluation_result_file = f"results.{use_existing_preds}.json" + try: from swebench_agent_run.metrics import ( write_report_to_db, # delay import because of extras diff --git a/codegen-examples/examples/swebench_agent_run/run_eval.py b/codegen-examples/examples/swebench_agent_run/run_eval.py deleted file mode 100644 index 79dd9def0..000000000 --- a/codegen-examples/examples/swebench_agent_run/run_eval.py +++ /dev/null @@ -1,488 +0,0 @@ -""" -!!! REFACTORED INTO eval_cli.py !!! -""" - -import asyncio -import json -import time -import traceback -import uuid -from pathlib import Path - -import click -import modal -from codegen.extensions.swebench.enums import SWEBenchDataset, SWEBenchLiteSubset -from codegen.extensions.swebench.harness import run_agent_on_entry -from codegen.extensions.swebench.report import generate_report -from codegen.extensions.swebench.utils import SweBenchExample, get_swe_bench_examples -from codegen.sdk.core.codebase import Codebase - -from swebench_agent_run.constants import DATASET_DICT - -PREDS_DNAME = Path(__file__).parent / "predictions" -LOG_DIR = Path(__file__).parent / "logs" - -run_agent_modal = modal.Function.from_name(app_name="swebench-agent-run", name="run_agent_modal") - - -async def process_batch_modal( - examples: list[SweBenchExample], - run_id: str, - model: str, - num_workers=5, - min_workers=1, - max_retries=3, -): - """Process a batch of examples concurrently using a queue system with incremental worker scaling. - - Args: - examples: List of SweBenchExample objects to process - num_workers: Initial number of examples to process concurrently - min_workers: Minimum number of concurrent workers to maintain - max_retries: Maximum number of retries for failed requests - """ - results = {} - queue = asyncio.Queue() - - # Shared state for worker management - state = { - "active_workers": num_workers, - "success_streak": 0, - "last_scaling_time": time.time(), - "scaling_cooldown": 0, # seconds between scaling operations - "worker_tasks": [], - "running": True, - } - - # Use a lock to protect shared state during adjustments - state_lock = asyncio.Lock() - - # Initialize the queue with (example, attempt) tuples - for example in examples: - await queue.put((example, 0)) # 0 represents first attempt - - async def scale_down_worker(task_to_cancel=None): - """Remove a single worker when rate limiting is detected""" - async with state_lock: - # Only scale if cooldown period has passed and we're above min_workers - current_time = time.time() - if ( - current_time - state["last_scaling_time"] < state["scaling_cooldown"] - or state["active_workers"] <= min_workers - ): - return False - - # Reset success streak when scaling down - state["success_streak"] = 0 - state["last_scaling_time"] = current_time - - # If a specific task was provided, cancel it - if task_to_cancel and task_to_cancel in state["worker_tasks"]: - print( - f"Rate limiting detected! Removing 1 worker, going from {state['active_workers']} to {state['active_workers'] - 1}" - ) - state["worker_tasks"].remove(task_to_cancel) - task_to_cancel.cancel() - state["active_workers"] -= 1 - return True - - # Otherwise, cancel the most recently added worker - elif state["worker_tasks"]: - print( - f"Rate limiting detected! Removing 1 worker, going from {state['active_workers']} to {state['active_workers'] - 1}" - ) - task = state["worker_tasks"].pop() - task.cancel() - state["active_workers"] -= 1 - return True - - return False - - async def scale_up_worker(): - """Add a single worker when operations have been consistently successful""" - async with state_lock: - # Only scale if cooldown period has passed and we're below num_workers - current_time = time.time() - if ( - current_time - state["last_scaling_time"] < state["scaling_cooldown"] - or state["active_workers"] >= num_workers - ): - return False - - # Add a worker after a streak of successful operations - if state["success_streak"] >= 5: - print( - f"Operations succeeding! Adding 1 worker, going from {state['active_workers']} to {state['active_workers'] + 1}" - ) - - # Create new worker - if state["running"]: - new_task = asyncio.create_task(worker()) - state["worker_tasks"].append(new_task) - state["active_workers"] += 1 - state["success_streak"] = 0 - state["last_scaling_time"] = current_time - return True - - return False - - async def is_rate_limit_error(error): - """Determine if an error is due to rate limiting""" - # Check for common rate limit error patterns - if isinstance(error, modal.exception.Error): - error_msg = str(error).lower() - rate_limit_indicators = [ - "rate limit", - "too many requests", - "429", - "throttle", - "quota exceeded", - "capacity", - "limit exceeded", - ] - return any(indicator in error_msg for indicator in rate_limit_indicators) - return False - - async def process_example(example, attempt, current_task): - try: - result = await run_agent_modal.remote.aio(example, run_id=run_id, model=model) - - if result is None: - print(f"Warning: Null result for {example.instance_id}") - return { - "status": "error", - "instance_id": example.instance_id, - "error_info": { - "error_type": "NullResult", - "error_message": "Process returned None", - }, - } - - # Increment success streak and potentially scale up - async with state_lock: - state["success_streak"] += 1 - - if state["success_streak"] % 5 == 0: # Check after every 5 successes - await scale_up_worker() - - return result - - except Exception as e: - error_type = type(e).__name__ - error_info = { - "error_type": error_type, - "error_message": str(e), - "traceback": traceback.format_exception(type(e), e, e.__traceback__), - } - - if isinstance(e, modal.exception.Error): - error_info["modal_error_code"] = getattr(e, "code", None) - error_info["modal_error_details"] = getattr(e, "details", None) - - print(f"Error processing {example.instance_id} (attempt {attempt + 1}):") - print(f"Type: {error_type}") - print(f"Message: {str(e)}") - - # Check if this is a rate limit error - if await is_rate_limit_error(e): - print(f"Rate limit detected on task for {example.instance_id}") - - # Scale down by removing this specific worker - scaled_down = await scale_down_worker(current_task) - - # If we're removing this worker, we need to requeue the task for another worker - if scaled_down: - # Requeue this example with the same attempt count (not incrementing) - await queue.put((example, attempt)) - return None - - # Otherwise add a small delay before retrying - await asyncio.sleep(2 * (attempt + 1)) # Exponential backoff - - if attempt < max_retries: - await queue.put((example, attempt + 1)) - return None - - return { - "status": "error", - "instance_id": example.instance_id, - "error_info": error_info, - } - - async def worker(): - # Store this task reference to allow targeted cancellation - current_task = asyncio.current_task() - - while state["running"]: - try: - # Use a timeout to allow worker to check if it should exit - try: - example, attempt = await asyncio.wait_for(queue.get(), timeout=1.0) - except asyncio.TimeoutError: - continue - - if example.instance_id in results: - queue.task_done() - continue - print(f"Processing example {example.instance_id}") - process_result = await process_example(example, attempt, current_task) - - # If we're still processing this task (not requeued due to rate limiting) - if process_result is not None: - results[example.instance_id] = { - "instance_id": example.instance_id, - **process_result, - } - print(f"Processed example {example.instance_id}") - queue.task_done() - - # If None is returned, the task was requeued due to rate limiting - # and this worker is being shut down, so exit the loop - else: - print(f"Task for {example.instance_id} has been requeued") - queue.task_done() - if current_task not in state["worker_tasks"]: - break - - except asyncio.CancelledError: - # Handle graceful cancellation - print("Worker task cancelled") - break - except Exception as e: - print(f"Worker error: {str(e)}") - traceback.print_exc() - queue.task_done() - - # Start initial workers - state["worker_tasks"] = [asyncio.create_task(worker()) for _ in range(num_workers)] - - # Wait for queue to be fully processed - await queue.join() - - # Mark as not running and cancel remaining workers - state["running"] = False - for w in state["worker_tasks"]: - w.cancel() - - # Wait for all workers to be cancelled - await asyncio.gather(*state["worker_tasks"], return_exceptions=True) - - # Return results in the same order as input examples - return [ - results.get( - example.instance_id, - {"instance_id": example.instance_id, "status": "missing"}, - ) - for example in examples - ] - - -def process_batch_local( - examples: list[SweBenchExample], - model: str, - num_workers=5, - codebases: dict[str, Codebase] = {}, - run_id: str | None = None, -): - """Process a batch of examples synchronously. - - Args: - examples: List of SweBenchExample objects to process - num_workers: Number of examples to process in each batch. - Default is 10 to avoid overwhelming the system. - """ - results = [] - - # Process examples in batches - for i in range(0, len(examples), num_workers): - batch = examples[i : i + num_workers] - print( - f"Processing batch {i // num_workers + 1}/{len(examples) // num_workers + 1} (examples {i + 1}-{min(i + num_workers, len(examples))})" - ) - - # Process each example in the batch - for example in batch: - try: - # Run the agent locally instead of using modal - if codebases and example.instance_id in codebases: - result = run_agent_on_entry( - example, - model=model, - codebase=codebases[example.instance_id], - run_id=run_id, - ) - else: - result = run_agent_on_entry(example, model=model, run_id=run_id) - results.append(result) - - except Exception as e: - error_type = type(e).__name__ - error_info = { - "error_type": error_type, - "error_message": str(e), - "traceback": traceback.format_exc(), - } - - print(f"Error processing {example.instance_id}:") - print(f"Type: {error_type}") - print(f"Message: {str(e)}") - print("Traceback:") - print(error_info["traceback"]) - - results.append( - { - "instance_id": example.instance_id, - "status": "error", - "error_info": error_info, - } - ) - - return results - - -async def run_eval( - dataset: str, - use_existing_preds: str | None = None, - length: int | None = None, - instance_id: str | None = None, - local: bool = False, - codebases: dict[str, Codebase] = {}, - repo: str | None = None, - num_workers: int = 2, - model: str = "claude-3-7-sonnet-latest", -): - run_id = use_existing_preds or str(uuid.uuid4()) - print(f"Run ID: {run_id}") - predictions_dir = PREDS_DNAME / f"results_{run_id}" - - dataset_enum = DATASET_DICT[dataset] - examples = get_swe_bench_examples( - dataset=dataset_enum, length=length, instance_id=instance_id, repo=repo - ) - - try: - if use_existing_preds is None: - print(f"Repo: {repo}") - print( - f"Examples:\n{'\n'.join([f'{e.instance_id} - {e.repo} - {e.base_commit}' for e in examples])}" - ) - print(f"Processing {len(examples)} examples...") - # Create output directory if it doesn't exist - predictions_dir.mkdir(exist_ok=True, parents=True) - - # Create a timestamp for this run - timestamp = time.strftime("%Y-%m-%d %H:%M %Z", time.localtime(time.time())) - - # Process all examples in parallel batches - if local: - results = process_batch_local( - examples, model=model, codebases=codebases, run_id=run_id - ) - else: - results = await process_batch_modal( - examples, model=model, run_id=run_id, num_workers=num_workers - ) - - # Save individual results - for result in results: - if result and "instance_id" in result: - instance_id = result["instance_id"] - output_file = predictions_dir / f"{instance_id}.json" - output_file.parent.mkdir(exist_ok=True, parents=True) - with open(output_file, "w") as f: - json.dump(result, f, indent=4) - - # Save summary file - summary_file = predictions_dir / f"summary_{timestamp}.json" - summary = { - "timestamp": timestamp, - "total_examples": len(examples), - "successful": len([r for r in results if r and "status" not in r]), - "failed": len( - [r for r in results if r and "status" in r and r["status"] == "error"] - ), - "error_types": {}, - "results": results, - } - - # Collect error statistics - for result in results: - if result and "status" in result and result["status"] == "error": - error_type = result.get("error_info", {}).get("error_type", "Unknown") - summary["error_types"][error_type] = ( - summary["error_types"].get(error_type, 0) + 1 - ) - - with open(summary_file, "w") as f: - json.dump(summary, f, indent=4) - - print("\nProcessing complete!") - print(f"Results saved to: {predictions_dir}") - print(f"Summary saved to: {summary_file}") - print(f"Successful: {summary['successful']}/{summary['total_examples']}") - print(f"Failed: {summary['failed']}/{summary['total_examples']}") - if summary["error_types"]: - print("\nError type distribution:") - for error_type, count in summary["error_types"].items(): - print(f" {error_type}: {count}") - - if isinstance(dataset_enum, SWEBenchLiteSubset): - dataset_enum = SWEBenchDataset.LITE - # Generate Report on Modal - generate_report(predictions_dir, LOG_DIR, dataset_enum, run_id) - except Exception: - print("Fatal error in run_eval:") - traceback.print_exc() - raise - - -@click.command() -@click.option( - "--dataset", - help="The dataset to use.", - type=click.Choice(["lite", "full", "verified", "lite_small", "lite_medium", "lite_large"]), - default="lite", -) -@click.option( - "--use-existing-preds", - help="The run ID of the existing predictions to use.", - type=str, - default=None, -) -@click.option("--length", help="The number of examples to process.", type=int, default=None) -@click.option( - "--instance-id", - help="The instance ID of the example to process.", - type=str, - default=None, -) -@click.option("--local", help="Run the evaluation locally.", is_flag=True, default=False) -@click.option("--repo", help="The repo to use.", type=str, default=None) -@click.option( - "--num-workers", - help="The number of workers to use. This is the number of examples that will be processed concurrently. A large number may lead to rate limiting issues.", - type=int, - default=5, -) -@click.option("--model", help="The model to use.", type=str, default="claude-3-7-sonnet-latest") -def run_eval_command( - dataset, use_existing_preds, length, instance_id, local, repo, num_workers, model -): - print(f"Repo: {repo}") - print(f"Model: {model}") - asyncio.run( - run_eval( - dataset=dataset, - use_existing_preds=use_existing_preds, - length=length, - instance_id=instance_id, - local=local, - repo=repo, - num_workers=num_workers, - model=model, - ) - ) - - -if __name__ == "__main__": - run_eval_command() diff --git a/codegen-examples/examples/swebench_agent_run/swebench_agent_run/metrics.py b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/metrics.py index d9fd49521..4052604d7 100644 --- a/codegen-examples/examples/swebench_agent_run/swebench_agent_run/metrics.py +++ b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/metrics.py @@ -8,13 +8,16 @@ def write_report_to_db(report_file: str): - load_dotenv(str((Path(__file__).parent.parent / ".env.db").resolve())) + path = Path(__file__).parent.parent / ".env.db" + if not path.exists(): + raise FileNotFoundError(f"DB credentials not found: {path}") + load_dotenv(str(path.resolve())) - postgres_host = os.getenv("POSTGRES_HOST") - postgres_database = os.getenv("POSTGRES_DATABASE") - postgres_user = os.getenv("POSTGRES_USER") - postgres_password = os.getenv("POSTGRES_PASSWORD") - postgres_port = os.getenv("POSTGRES_PORT") + postgres_host = os.getenv("POSTGRESQL_HOST") + postgres_database = os.getenv("POSTGRESQL_DATABASE") + postgres_user = os.getenv("POSTGRESQL_USER") + postgres_password = os.getenv("POSTGRESQL_PASSWORD") + postgres_port = os.getenv("POSTGRESQL_PORT") try: codegen_version = version("codegen") @@ -25,6 +28,7 @@ def write_report_to_db(report_file: str): report = json.load(f) # Establish connection + conn = psycopg2.connect( host=postgres_host, database=postgres_database, @@ -39,7 +43,7 @@ def write_report_to_db(report_file: str): try: # Single row insert cur.execute( - "INSERT INTO table_name (codegen_version, submitted, completed_instances, resolved_instances, unresolved_instances, empty_patches, error_instances) VALUES (%s, %s, %s, %s, %s, %s, %s)", + "INSERT INTO swebench_output (codegen_version, submitted, completed_instances, resolved_instances, unresolved_instances, empty_patches, error_instances) VALUES (%s, %s, %s, %s, %s, %s, %s)", ( codegen_version, report["submitted_instances"], diff --git a/codegen-examples/examples/swebench_agent_run/swebench_agent_run/report.py b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/report.py index 19325e844..ae7946b12 100755 --- a/codegen-examples/examples/swebench_agent_run/swebench_agent_run/report.py +++ b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/report.py @@ -131,13 +131,14 @@ def generate_report( print(f"Using log directory: {log_dir}") evaluation_result_file = patched_swebench_eval( - predictions_jsonl, + str(predictions_jsonl), run_id, dataset_name=dataset.value, cache_level="instance", report_dir=logs_dir, modal=True, ) + # Get and display report report = get_report(predictions_jsonl, logs_dir) From 45993abd339dcd9588a703f3c5be88a979287e9a Mon Sep 17 00:00:00 2001 From: Chris Lee Date: Mon, 17 Mar 2025 18:47:26 -0700 Subject: [PATCH 16/16] fix: end-to-end to metrics --- .../examples/swebench_agent_run/eval_cli.py | 35 +++++++++---------- .../modal_harness/entry_point.py | 2 +- .../swebench_agent_run/report.py | 16 ++++----- .../examples/swebench_agent_run/uv.lock | 27 +++++++++++--- 4 files changed, 47 insertions(+), 33 deletions(-) diff --git a/codegen-examples/examples/swebench_agent_run/eval_cli.py b/codegen-examples/examples/swebench_agent_run/eval_cli.py index faec4848c..6c58c03a6 100644 --- a/codegen-examples/examples/swebench_agent_run/eval_cli.py +++ b/codegen-examples/examples/swebench_agent_run/eval_cli.py @@ -307,34 +307,31 @@ def main( ) -> None: """Command-line interface for running evaluations.""" print(f"Repo: {repo}") - - evaluation_result_file = generate_report( - *run_eval( - use_existing_preds=use_existing_preds, - dataset_enum=DATASET_DICT[dataset], - length=length, - instance_id=instance_id, - codebases=None, - local=local, - repo=repo, - model=model, - ) + result = run_eval( + use_existing_preds=use_existing_preds, + dataset_enum=DATASET_DICT[dataset], + length=length, + instance_id=instance_id, + local=local, + repo=repo, + model=model, ) + generate_report(*result) + + evaluation_result_file = Path(f"results.{result[3]}.json") + if push_metrics: - if evaluation_result_file is None: - if use_existing_preds is None: - print("Evaluation was not run - no metrics were pushed") - return - else: - evaluation_result_file = f"results.{use_existing_preds}.json" + if not evaluation_result_file.exists() and use_existing_preds is None: + print("Evaluation was not run - no metrics were pushed") + return try: from swebench_agent_run.metrics import ( write_report_to_db, # delay import because of extras ) - write_report_to_db(evaluation_result_file) + write_report_to_db(str(evaluation_result_file.resolve())) except Exception: print("Error writing report to db") traceback.print_exc() diff --git a/codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/entry_point.py b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/entry_point.py index 6002e6364..d044af28f 100644 --- a/codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/entry_point.py +++ b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/modal_harness/entry_point.py @@ -284,7 +284,7 @@ def patched_swebench_eval( # Defaults from swebench harness run_id, # Required argument dataset_name="princeton-nlp/SWE-bench_Lite", split="test", - instance_ids=None, # Default None since it's optional + instance_ids=None, max_workers=4, open_file_limit=4096, timeout=1800, diff --git a/codegen-examples/examples/swebench_agent_run/swebench_agent_run/report.py b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/report.py index ae7946b12..580bc805a 100755 --- a/codegen-examples/examples/swebench_agent_run/swebench_agent_run/report.py +++ b/codegen-examples/examples/swebench_agent_run/swebench_agent_run/report.py @@ -71,22 +71,19 @@ def update_pred_json(predictions, report, predictions_dir: Path): return predictions -def preds_to_jsonl(predictions, predictions_dir: Path): - dname = predictions_dir - - predictions_jsonl = str(dname / "all_preds.jsonl") +def preds_to_jsonl(predictions, predictions_jsonl: Path): print(f"Creating JSONL file: {predictions_jsonl}") # Use a default model name since it's not in the predictions model_name = "results" with open(predictions_jsonl, "w") as fh: - for inst, pred in predictions.items(): + for pred in predictions.values(): minimal_pred = { "model_name_or_path": model_name, # Use default model name - "model_patch": remove_patches_to_tests(pred["model_patch"]) - if "model_patch" in pred - else pred.get("patch", ""), + "model_patch": remove_patches_to_tests( + pred.get("result", {}).get("model_patch", "") + ), "instance_id": pred["instance_id"], } fh.write(json.dumps(minimal_pred) + "\n") @@ -116,6 +113,7 @@ def generate_report( except json.JSONDecodeError: print(f"Error reading JSON from {file_path}") continue + if not existing_preds: if not predictions: print("No valid predictions found") @@ -123,7 +121,7 @@ def generate_report( print(f"Successfully loaded {len(predictions)} predictions") - predictions_jsonl = preds_to_jsonl(predictions, predictions_dir) + predictions_jsonl = preds_to_jsonl(predictions, predictions_jsonl) # Setup log directory log_dir = logs_dir / "results" diff --git a/codegen-examples/examples/swebench_agent_run/uv.lock b/codegen-examples/examples/swebench_agent_run/uv.lock index ad009ade6..d383e93de 100644 --- a/codegen-examples/examples/swebench_agent_run/uv.lock +++ b/codegen-examples/examples/swebench_agent_run/uv.lock @@ -321,8 +321,10 @@ wheels = [ name = "codegen" source = { directory = "../../../" } dependencies = [ + { name = "anthropic" }, { name = "astor" }, { name = "click" }, + { name = "codegen-sdk-pink" }, { name = "codeowners" }, { name = "colorlog" }, { name = "dataclasses-json" }, @@ -398,9 +400,11 @@ dependencies = [ [package.metadata] requires-dist = [ + { name = "anthropic" }, { name = "astor", specifier = ">=0.8.1,<1.0.0" }, { name = "attrs", marker = "extra == 'lsp'", specifier = ">=25.1.0" }, { name = "click", specifier = ">=8.1.7" }, + { name = "codegen-sdk-pink", specifier = ">=0.1.0" }, { name = "codeowners", specifier = ">=0.6.0,<1.0.0" }, { name = "colorlog", specifier = ">=6.9.0" }, { name = "dataclasses-json", specifier = ">=0.6.4,<1.0.0" }, @@ -433,7 +437,7 @@ requires-dist = [ { name = "neo4j" }, { name = "networkx", specifier = ">=3.4.1" }, { name = "numpy", specifier = ">=2.2.2" }, - 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