apunkt/MetaGPT
1
0
Fork 0
mirror of https://github.com/FoundationAgents/MetaGPT.git synced 2026-06-17 15:35:21 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

Merge branch 'swebench_di' of github.com:stellaHSR/MetaGPT into swebench_di

Browse source
This commit is contained in:
stellahsr 2024-03-22 13:30:23 +08:00
commit 1e6d145d7e
2 changed files with 0 additions and 16 deletions
Download patch file Download diff file Expand all files Collapse all files

14
data/inference/const.py
View file

@ -45,20 +45,6 @@ def read_sub_set_instance(path=SUBSET_DATASET, tag="scikit-learn"):
fail_filters = df["instance_id_fail"].tolist()
pass_filters = [s for s in pass_filters if tag in s]
fail_filters = [s for s in fail_filters if tag in s]
print(pass_filters)
print(fail_filters)
# Filter for instances containing the tag in either column
# pass_filter = df["instance_id_pass"].str.contains(tag, na=False)
# fail_filter = df["instance_id_fail"].str.contains(tag, na=False)
# Combine the filters using | (OR operator) for efficiency
# combined_filter = pass_filters | fail_filters
# print(df[combined_filter])
# Apply combined filter and select the specific columns
# filtered_df = df[combined_filter][["instance_id_pass", "instance_id_fail"]]
# Flatten the DataFrame into a list and remove NaN values
subset_instance = pass_filters + fail_filters
return subset_instance

2
swe_bench/inference/run_api.py
View file

@ -56,7 +56,6 @@ async def openai_inference(
logger.info(f"{repo_prefix}_{version}")
data.append(f"{repo_prefix}_{version}")
# import pdb;pdb.set_trace()
response = await run_instance(instance=datum)
if response is None:
continue
@ -65,7 +64,6 @@ async def openai_inference(
output_dict["full_output"] = response
output_dict["model_patch"] = extract_diff(response)
print(json.dumps(output_dict), file=f, flush=True)
# print(data)
async def main(