ai-agent-book 精选快照（<2MB 代码与文档，来自 github.com/bojieli/ai-agent-book）

chapter2/prompt-engineering/tau_bench/model_utils/api/exception.py

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+import json
+import os
+import time
+from concurrent.futures import ThreadPoolExecutor
+from typing import Any, Callable, TypeVar
+
+from tau_bench.model_utils.model.exception import ModelError, Result
+
+T = TypeVar("T")
+
+_REPORT_DIR = os.path.expanduser("~/.llm-primitives/log")
+
+
+def set_report_dir(path: str) -> None:
+    global _REPORT_DIR
+    _REPORT_DIR = path
+
+
+def get_report_dir() -> str:
+    return _REPORT_DIR
+
+
+def log_report_to_disk(report: dict[str, Any], path: str) -> None:
+    with open(path, "w") as f:
+        json.dump(report, f, indent=4)
+
+
+def generate_report_location() -> str:
+    if not os.path.exists(_REPORT_DIR):
+        os.makedirs(_REPORT_DIR)
+    return os.path.join(_REPORT_DIR, f"report-{time.time_ns()}.json")
+
+
+class APIError(Exception):
+    def __init__(self, short_message: str, report: dict[str, Any] | None = None) -> None:
+        self.report_path = generate_report_location()
+        self.short_message = short_message
+        self.report = report
+        if self.report is not None:
+            log_report_to_disk(
+                report={"error_type": "APIError", "report": report}, path=self.report_path
+            )
+        super().__init__(f"{short_message}\n\nSee the full report at {self.report_path}")
+
+
+def execute_and_filter_model_errors(
+    funcs: list[Callable[[], T]],
+    max_concurrency: int | None = None,
+) -> list[T] | list[ModelError]:
+    def _invoke_w_o_llm_error(invocable: Callable[[], T]) -> Result:
+        try:
+            return Result(value=invocable(), error=None)
+        except ModelError as e:
+            return Result(value=None, error=e)
+
+    with ThreadPoolExecutor(max_workers=max_concurrency) as executor:
+        results = list(executor.map(_invoke_w_o_llm_error, funcs))
+
+    errors: list[ModelError] = []
+    values = []
+    for res in results:
+        if res.error is not None:
+            errors.append(res.error)
+        else:
+            values.append(res.value)
+    if len(values) == 0:
+        assert len(errors) > 0
+        raise errors[0]
+    return values