add const for swe-bench

data/inference/const.py

@@ -0,0 +1,53 @@
+# -*- coding: utf-8 -*-
+# @Author  : stellahong (stellahong@fuzhi.ai)
+# @Desc    :
+import pandas as pd
+
+from metagpt.const import METAGPT_ROOT
+
+SUBSET_DATASET = METAGPT_ROOT / "sub_swebench_dataset" / "sub_swebench.csv"
+SUBSET_DATASET_SKLERARN = METAGPT_ROOT / "sub_swebench_dataset" / "scikit-learn-68.csv"
+
+# SCIKIT_LEARN_IDS: A list of instance identifiers from 'sub_swebench.csv' within SUBSET_DATASET.
+# This collection represents a subset specifically related to scikit-learn content.
+SCIKIT_LEARN_IDS = [
+    "scikit-learn__scikit-learn-11578",
+    "scikit-learn__scikit-learn-10297",
+    "scikit-learn__scikit-learn-25747",
+    "scikit-learn__scikit-learn-15512",
+    "scikit-learn__scikit-learn-15119",
+    "scikit-learn__scikit-learn-10870",
+    "scikit-learn__scikit-learn-15100",
+    "scikit-learn__scikit-learn-14496",
+    "scikit-learn__scikit-learn-14890",
+    "scikit-learn__scikit-learn-10428",
+    "scikit-learn__scikit-learn-25744",
+    "scikit-learn__scikit-learn-11542",
+    "scikit-learn__scikit-learn-10198",
+    "scikit-learn__scikit-learn-10459",
+]
+
+
+def read_sub_set_instance(path=SUBSET_DATASET, tag="scikit-learn"):
+    try:
+        df = pd.read_excel(path)
+        # 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_filter | fail_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 = filtered_df.stack().dropna().tolist()
+
+        return subset_instance
+    except FileNotFoundError:
+        print(f"File not found: {path}")
+        return []
+    except Exception as e:
+        print(f"An error occurred: {e}")
+        return []