From 721fde3d602f527fa1944e8c9ef006c4555c9f24 Mon Sep 17 00:00:00 2001 From: Rita Aleksziev Date: Fri, 15 Nov 2024 17:14:43 +0100 Subject: [PATCH] generating testspecs for data --- evals/eval_swe_bench.py | 57 +++++++++++++++++++++++++++++++++++++---- 1 file changed, 52 insertions(+), 5 deletions(-) diff --git a/evals/eval_swe_bench.py b/evals/eval_swe_bench.py index 8e8327fd5..3aabfcba3 100644 --- a/evals/eval_swe_bench.py +++ b/evals/eval_swe_bench.py @@ -1,14 +1,17 @@ from swebench.harness.utils import load_swebench_dataset +from swebench.harness.run_evaluation import get_dataset_from_preds +from swebench.harness.run_evaluation import run_instances +from swebench.harness.test_spec import make_test_spec, TestSpec + +import subprocess from swebench.inference.make_datasets.create_instance import PATCH_EXAMPLE from evals.eval_utils import download_instances import cognee from cognee.api.v1.cognify.code_graph_pipeline import code_graph_pipeline from cognee.api.v1.search import SearchType -import os from pathlib import Path from cognee.infrastructure.databases.graph import get_graph_engine from cognee.infrastructure.llm.get_llm_client import get_llm_client -from cognee.shared.data_models import Answer async def cognee_and_llm(dataset, search_type = SearchType.CHUNKS): await cognee.prune.prune_data() @@ -47,7 +50,8 @@ async def cognee_and_llm(dataset, search_type = SearchType.CHUNKS): ) return answer_prediction -def llm_on_preprocessed_data(dataset): + +async def llm_on_preprocessed_data(dataset): problem_statement = dataset[0]['problem_statement'] prompt = dataset[0]["text"] @@ -59,6 +63,47 @@ def llm_on_preprocessed_data(dataset): ) return answer_prediction +async def get_preds(dataset, with_cognee): + if with_cognee: + text_output = await cognee_and_llm(dataset) + model_name = "with_cognee" + else: + text_output = await llm_on_preprocessed_data(dataset) + model_name = "without_cognee" + + preds = {dataset[0]["instance_id"]: + {"instance_id": dataset[0]["instance_id"], + "model_patch": text_output, + "model_name_or_path": model_name}} + + dataset_name = 'princeton-nlp/SWE-bench' if with_cognee else 'princeton-nlp/SWE-bench_bm25_13K' + preds_dataset = get_dataset_from_preds(dataset_name, + "test", + [dataset[0]["instance_id"]], + preds, + model_name) + + return preds, preds_dataset + +async def evaluate(test_specs: list[TestSpec], + preds: dict, + ): + for test_spec in test_specs: + pred = preds[test_spec.instance_id] + log_dir = Path("logs") + log_dir.mkdir(parents=True, exist_ok=True) + + patch_file = Path(log_dir / "patch.diff") + patch_file.write_text(pred["model_patch"] or "") + for command in test_spec.repo_script_list: + if "/testbed" in command: + command = command.replace("/testbed", "./testbed") + result = subprocess.run(command, shell=True, check=True, capture_output=True, text=True) + print(result) + + subprocess.run("git apply --allow-empty -v logs/patch.diff", shell=True, capture_output=True, text=True) + + async def main(): swe_dataset = load_swebench_dataset('princeton-nlp/SWE-bench', split='test') @@ -73,8 +118,10 @@ async def main(): else: dataset = download_instances(test_data, filepath) - llm_output_with_cognee = await cognee_and_llm(dataset) - llm_output_without_cognee = llm_on_preprocessed_data(test_data_preprocessed) + cognee_preds, cognee_preds_dataset = await get_preds(dataset, with_cognee=True) + # nocognee_preds = await get_preds(dataset, with_cognee=False) + test_specs = list(map(make_test_spec, test_data)) + results = await evaluate(test_specs, cognee_preds) if __name__ == "__main__": import asyncio