chore: import upstream snapshot with attribution

2026-07-13 13:36:15 +08:00
commit e64161ec32
892 changed files with 116950 additions and 0 deletions
@@ -0,0 +1,94 @@
+# tess successfully running.
+# (GPT) if it aligns with the spec & rationality of the spec.
+import json
+import re
+from pathlib import Path
+
+from rdagent.app.data_science.conf import DS_RD_SETTING
+from rdagent.components.coder.CoSTEER.evaluators import (
+    CoSTEEREvaluator,
+    CoSTEERSingleFeedback,
+)
+from rdagent.components.coder.CoSTEER.knowledge_management import (
+    CoSTEERQueriedKnowledgeV2,
+)
+from rdagent.components.coder.data_science.conf import get_ds_env
+from rdagent.components.coder.data_science.utils import remove_eda_part
+from rdagent.core.experiment import FBWorkspace, Task
+from rdagent.utils.agent.tpl import T
+from rdagent.utils.agent.workflow import build_cls_from_json_with_retry
+
+DIRNAME = Path(__file__).absolute().resolve().parent
+
+DataLoaderEvalFeedback = CoSTEERSingleFeedback
+
+
+class DataLoaderCoSTEEREvaluator(CoSTEEREvaluator):
+    def evaluate(
+        self,
+        target_task: Task,
+        implementation: FBWorkspace,
+        gt_implementation: FBWorkspace,
+        queried_knowledge: CoSTEERQueriedKnowledgeV2 = None,
+        **kwargs,
+    ) -> DataLoaderEvalFeedback:
+        target_task_information = target_task.get_task_information()
+        if (
+            queried_knowledge is not None
+            and target_task_information in queried_knowledge.success_task_to_knowledge_dict
+        ):
+            return queried_knowledge.success_task_to_knowledge_dict[target_task_information].feedback
+        elif queried_knowledge is not None and target_task_information in queried_knowledge.failed_task_info_set:
+            return DataLoaderEvalFeedback(
+                execution="This task has failed too many times, skip implementation.",
+                return_checking="This task has failed too many times, skip implementation.",
+                code="This task has failed too many times, skip implementation.",
+                final_decision=False,
+            )
+
+        env = get_ds_env(
+            extra_volumes={self.scen.debug_path: T("scenarios.data_science.share:scen.input_path").r()},
+            running_timeout_period=self.scen.real_debug_timeout(),
+        )
+
+        # TODO: do we need to clean the generated temporary content?
+        fname = "test/data_loader_test.py"
+        test_code = (DIRNAME / "eval_tests" / "data_loader_test.txt").read_text()
+        implementation.inject_files(**{fname: test_code})
+        result = implementation.run(env=env, entry=f"python {fname}")
+        stdout = result.stdout
+        ret_code = result.exit_code
+        match = re.search(r"(.*?)=== Start of EDA part ===(.*)=== End of EDA part ===(.*)", stdout, re.DOTALL)
+        stdout_part_1, eda_output, stdout_part_2 = match.groups() if match else (stdout, None, "")
+        stdout = stdout_part_1 + stdout_part_2
+        if eda_output is not None and len(eda_output.split(" ")) > 10000:
+            eda_output += "Length of EDA output is too long, truncated. Please reject this implementation and motivate it to reduce the length of EDA output."
+
+        if "main.py" in implementation.file_dict and ret_code == 0:
+            workflow_stdout = implementation.execute(env=env, entry="python main.py")
+            workflow_stdout = remove_eda_part(workflow_stdout)
+        else:
+            workflow_stdout = None
+
+        system_prompt = T(".prompts:data_loader_eval.system").r(
+            task_desc=target_task.get_task_information(),
+            test_code=test_code,
+            code=implementation.file_dict["load_data.py"],
+            workflow_stdout=workflow_stdout,
+            workflow_code=implementation.all_codes,
+        )
+        user_prompt = T(".prompts:data_loader_eval.user").r(
+            stdout=stdout,
+            eda_output=eda_output,
+            workflow_stdout=workflow_stdout,
+        )
+
+        fb = build_cls_from_json_with_retry(
+            DataLoaderEvalFeedback,
+            system_prompt=system_prompt,
+            user_prompt=user_prompt,
+            init_kwargs_update_func=DataLoaderEvalFeedback.val_and_update_init_dict,
+        )
+        fb.final_decision = fb.final_decision and ret_code == 0
+
+        return fb