tweak exception messages; error_log->help_message

src/paperqa/core.py

@@ -126,7 +126,7 @@ def fraction_replacer(match: re.Match) -> str:
 
 class LLMContextError(ValueError):
     retryable: ClassVar[bool]
-    error_log: ClassVar[str]
+    help_message: ClassVar[str]  # Eventually passed to logger.exception
 
     def __init__(self, message: str, llm_results: list[LLMResult]) -> None:
         super().__init__(message)
@@ -138,7 +138,7 @@ class LLMBadContextJSONError(LLMContextError):
 
     retryable = True
     error_log = (
-        "Abandoning this context."
+        "Abandoning this context creation."
         " Your model may not be capable of supporting JSON output"
         " or our parsing technique could use some work. Try"
         " a different model or specify `Settings(prompts={'use_json': False})`."
@@ -270,7 +270,7 @@ async def _map_fxn_summary(  # noqa: PLR0912
                 used_text_only_fallback = True
         except litellm.Timeout as exc:
             raise LLMContextTimeoutError(
-                f"LLM call to create a context timed out on text named {text.name!r}: {exc}",
+                f"LLM call to create a context timed out on text named {text.name!r}.",
                 llm_results=llm_results,
             ) from exc
 
@@ -362,11 +362,11 @@ async def map_fxn_summary(**kwargs) -> tuple[Context | None, list[LLMResult]]:
     except LLMContextError as exc:
         if not exc.retryable:
             logger.exception(
-                "Non-retryable failure creating a context. %s", exc.error_log
+                "Non-retryable failure creating a context. %s", exc.help_message
             )
             return None, exc.llm_results
         try:
             return await _map_fxn_summary(**kwargs, _prior_attempt=exc)
         except LLMContextError as exc2:
-            logger.exception("Failed twice to create a context. %s", exc2.error_log)
+            logger.exception("Failed twice to create a context. %s", exc2.help_message)
             return None, exc2.llm_results

tests/test_paperqa.py

@@ -110,7 +110,10 @@ def test_multiple_authors() -> None:
 
 
 def test_multiple_citations() -> None:
-    text = "As discussed by several authors (Smith et al. 1999; Johnson 2001; Lee et al. 2003)."
+    text = (
+        "As discussed by several authors (Smith et al. 1999; Johnson 2001; Lee et al."
+        " 2003)."
+    )
     assert strip_citations(text) == "As discussed by several authors ."
 
 
@@ -623,6 +626,7 @@ async def test_query(docs_fixture) -> None:
 
 @pytest.mark.asyncio
 async def test_custom_context_str_fn(docs_fixture) -> None:
+
     async def custom_context_str_fn(  # noqa: RUF029
         settings: Settings,  # noqa: ARG001
         contexts: list[Context],  # noqa: ARG001
@@ -648,6 +652,7 @@ async def custom_context_str_fn(  # noqa: RUF029
 
 @pytest.mark.asyncio
 async def test_aquery_groups_contexts_by_question(docs_fixture) -> None:
+
     session = PQASession(question="What is the relationship between chemistry and AI?")
 
     doc = Doc(docname="test_doc", citation="Test Doc, 2025", dockey="key1")
@@ -734,14 +739,12 @@ async def test_query_with_iteration(docs_fixture) -> None:
     prior_session = PQASession(question=question, answer=prior_answer)
     await docs_fixture.aquery(prior_session, llm_model=llm, settings=settings)
     assert prior_answer in cast(
-        "str",
-        my_results[-1].prompt[1].content,  # type: ignore[union-attr, index]
+        "str", my_results[-1].prompt[1].content  # type: ignore[union-attr, index]
     ), "prior answer not in prompt"
     # run without a prior session to check that the flow works correctly
     await docs_fixture.aquery(question, llm_model=llm, settings=settings)
     assert settings.prompts.answer_iteration_prompt[:10] not in cast(  # type: ignore[index]
-        "str",
-        my_results[-1].prompt[1].content,  # type: ignore[union-attr, index]
+        "str", my_results[-1].prompt[1].content  # type: ignore[union-attr, index]
     ), "prior answer prompt should not be inserted"
 
 
@@ -965,9 +968,7 @@ class StubLLMModel(LLMModel):
         name: str = "custom/myllm"
 
         async def acompletion(
-            self,
-            messages: list[Message],
-            **kwargs,  # noqa: ARG002
+            self, messages: list[Message], **kwargs  # noqa: ARG002
         ) -> list[LLMResult]:
             return [
                 LLMResult(
@@ -981,9 +982,7 @@ async def acompletion(
 
         @rate_limited
         async def acompletion_iter(
-            self,
-            messages: list[Message],
-            **kwargs,  # noqa: ARG002
+            self, messages: list[Message], **kwargs  # noqa: ARG002
         ) -> AsyncIterable[LLMResult]:
             yield LLMResult(
                 model=self.name,
@@ -1715,7 +1714,10 @@ async def test_custom_prompts(stub_data_dir: Path) -> None:
 
 @pytest.mark.asyncio
 async def test_pre_prompt(stub_data_dir: Path) -> None:
-    pre = "What is water's boiling point in Fahrenheit? Please respond with a complete sentence."
+    pre = (
+        "What is water's boiling point in Fahrenheit? Please respond with a complete"
+        " sentence."
+    )
 
     settings = Settings.from_name("fast")
     settings.prompts.pre = pre
@@ -2443,7 +2445,8 @@ def test_llm_parse_json_with_escaped_characters(self, input_text, expected_outpu
     def test_llm_subquotes_and_newlines(self, input_text: str) -> None:
         output = {
             "summary": (
-                'An excerpt with "quoted stuff" or "maybe more." More stuff (with parenthesis).'
+                'An excerpt with "quoted stuff" or "maybe more." More stuff (with'
+                " parenthesis)."
             ),
             "relevance_score": 8,
         }