test: cover mid-stream litellm failures on buffered messages paths

routstr/upstream/messages_dispatch.py

@@ -492,10 +492,7 @@ def collapse_litellm_message(message: str) -> str:
     """Keep the innermost provider message and cap its length."""
     tail = message.rsplit("Original exception:", 1)[-1].strip()
     while True:
-        stripped = tail
-        for prefix in ("litellm.",):
-            if stripped.startswith(prefix):
-                stripped = stripped[len(prefix) :]
+        stripped = tail.removeprefix("litellm.")
         head, _, rest = stripped.partition(": ")
         if rest and head.endswith(("Error", "Exception")):
             stripped = rest.strip()

tests/unit/test_messages_upstream_errors.py

@@ -1,20 +1,152 @@
-import pytest
+import os
+from typing import Any, AsyncIterator
+from unittest.mock import AsyncMock, patch
 
-from routstr.upstream.messages_dispatch import collapse_litellm_message
+import litellm
+import pytest
+from litellm.exceptions import MidStreamFallbackError
+
+os.environ.setdefault("UPSTREAM_BASE_URL", "http://test")
+os.environ.setdefault("UPSTREAM_API_KEY", "test")
+
+from routstr.core.exceptions import UpstreamError  # noqa: E402
+from routstr.payment.models import Architecture, Model, Pricing  # noqa: E402
+from routstr.upstream.base import BaseUpstreamProvider  # noqa: E402
+from routstr.upstream.messages_dispatch import (  # noqa: E402
+    collapse_litellm_message,
+)
+
+_MIDSTREAM_FAILURE = MidStreamFallbackError(
+    message="No credits.",
+    model="x",
+    llm_provider="openai",
+    original_exception=litellm.APIError(
+        status_code=500, message="No credits.", llm_provider="openai", model="x"
+    ),
+)
 
 
 @pytest.mark.parametrize(
     ("message", "expected"),
     [
         ("You have no credits remaining.", "You have no credits remaining."),
-        (
-            "litellm.MidStreamFallbackError: litellm.APIError: No credits. "
-            "Original exception: MidStreamFallbackError: No credits. "
-            "Original exception: APIError: litellm.APIError: No credits.",
-            "No credits.",
-        ),
+        # upstream_error_from_exception reads `.message`, which omits the
+        # "Original exception:" chain that only `str()` appends.
+        (_MIDSTREAM_FAILURE.message, "No credits."),
+        (str(_MIDSTREAM_FAILURE), "No credits."),
         ("x" * 301, "x" * 299 + "…"),
     ],
 )
 def test_collapse_litellm_message(message: str, expected: str) -> None:
     assert collapse_litellm_message(message) == expected
+
+
+_RATE_LIMIT = litellm.RateLimitError(
+    message=(
+        "Rate limit reached for gpt-4o on tokens per min (TPM): Limit 30000, "
+        "Used 29000, Requested 2000. Please try again in 1.2s."
+    ),
+    llm_provider="openai",
+    model="gpt-4o",
+)
+_BAD_REQUEST = litellm.BadRequestError(
+    message="context length exceeded", model="gpt-4o", llm_provider="openai"
+)
+
+_MID_STREAM_CASES = [
+    pytest.param(_RATE_LIMIT, 429, "UPSTREAM_RATE_LIMIT", id="rate-limit"),
+    pytest.param(_BAD_REQUEST, 400, None, id="bad-request"),
+    pytest.param(_MIDSTREAM_FAILURE, 500, None, id="midstream-fallback"),
+]
+
+
+def _make_model() -> Model:
+    return Model(
+        id="gpt-4o",
+        name="gpt-4o",
+        created=0,
+        description="",
+        context_length=8192,
+        architecture=Architecture(
+            modality="text",
+            input_modalities=["text"],
+            output_modalities=["text"],
+            tokenizer="x",
+            instruct_type=None,
+        ),
+        pricing=Pricing(
+            prompt=0.0,
+            completion=0.0,
+            request=0.0,
+            image=0.0,
+            web_search=0.0,
+            internal_reasoning=0.0,
+            max_cost=0.0,
+        ),
+    )
+
+
+def _failing_stream(exc: Exception) -> AsyncIterator[dict]:
+    async def gen() -> AsyncIterator[dict]:
+        yield {
+            "type": "message_start",
+            "message": {"id": "msg_1", "model": "gpt-4o", "usage": {}},
+        }
+        raise exc
+
+    return gen()
+
+
+def _assert_upstream_error(
+    err: UpstreamError, status_code: int, code: str | None
+) -> None:
+    assert err.status_code == status_code
+    assert err.code == code
+    assert err.from_upstream_response is True
+    assert "litellm." not in str(err)
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(("exc", "status_code", "code"), _MID_STREAM_CASES)
+async def test_non_streaming_aggregation_surfaces_mid_stream_failure(
+    exc: Exception, status_code: int, code: str | None
+) -> None:
+    async def fake_acreate(**kwargs: Any) -> AsyncIterator[dict]:
+        return _failing_stream(exc)
+
+    with (
+        patch(
+            "litellm.anthropic.messages.acreate",
+            new=AsyncMock(side_effect=fake_acreate),
+        ),
+        pytest.raises(UpstreamError) as exc_info,
+    ):
+        await BaseUpstreamProvider(
+            base_url="http://test", api_key="k"
+        )._dispatch_anthropic_messages(
+            request_body=b'{"messages": [], "max_tokens": 8, "stream": false}',
+            model_obj=_make_model(),
+        )
+
+    _assert_upstream_error(exc_info.value, status_code, code)
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(("exc", "status_code", "code"), _MID_STREAM_CASES)
+async def test_x_cashu_buffered_stream_surfaces_mid_stream_failure(
+    exc: Exception, status_code: int, code: str | None
+) -> None:
+    provider = BaseUpstreamProvider(base_url="http://test", api_key="k")
+
+    with pytest.raises(UpstreamError) as exc_info:
+        await provider._stream_x_cashu_litellm_messages(
+            _failing_stream(exc),
+            amount=5_000,
+            unit="sat",
+            max_cost_for_model=10_000,
+            requested_model="gpt-4o",
+            mint=None,
+            request_id="req-test",
+        )
+
+    _assert_upstream_error(exc_info.value, status_code, code)