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StructuredOutputValidationError — a LangChain agent could not parse its own structured output

langchain.agents.structured_output.StructuredOutputValidationError: Failed to parse structured output for tool '<name>': <the error from parsing>.

(The shape of the error, assembled by us from the message template quoted below, with our placeholders in angle brackets. The class is in langchain/agents/structured_output.py, so from langchain.agents.structured_output import StructuredOutputValidationError is the import path, the same module factory.py imports it from, line 60.)

An agent built with create_agent(…, response_format=…) raises this when the model’s structured answer fails to parse into your schema. With a provider strategy (the provider’s native structured output) it is raised every time a reply with no tool calls fails to parse; there is no retry in that branch. With a tool strategy (the answer arrives as a call to an artificial tool) a parse failure is first handed to handle_errors, which defaults to True, under which the error text goes back to the model as a ToolMessage and the model is asked again; this error is raised only when handle_errors says not to retry. Every claim about the library below is read off the Python source of langchain-ai/langchain at tag langchain==1.4.4, fetched on 10 October 2026, with the line of each quote given; where we draw a conclusion from those lines rather than quote them, we say so.

The class

In langchain/agents/structured_output.py, lines 60–63:

class StructuredOutputValidationError(StructuredOutputError): """Raised when structured output tool call arguments fail to parse according to the schema.""" def __init__(self, tool_name: str, source: Exception, ai_message: AIMessage) -> None:

and the constructor body, lines 71–74:

self.tool_name = tool_name self.source = source self.ai_message = ai_message super().__init__(f"Failed to parse structured output for tool '{tool_name}': {source}.")

The parent, class StructuredOutputError(Exception): (line 35), is a plain Exception subclass. The docstring documents source as source: The exception that occurred. (line 68) and ai_message as ai_message: The AI message that contained the invalid structured output. (line 69). Because {source} is formatted into the message, the text after the colon is the str() of whatever parsing raised, followed by a full stop (our reading).

Where it is raised

We searched both fetched files for StructuredOutputValidationError(: it is constructed at line 1268 and line 1330 of factory.py, both inside _handle_model_output, which is called at lines 1511 and 1570. We did not fetch LangChain’s other files, so this list covers these two files only.

Provider strategy. Lines 1257–1272:

if isinstance(effective_response_format, ProviderStrategy): if not output.tool_calls: provider_strategy_binding = ProviderStrategyBinding.from_schema_spec( effective_response_format.schema_spec ) try: structured_response = provider_strategy_binding.parse(output) except Exception as exc: schema_name = getattr( effective_response_format.schema_spec.schema, "__name__", "response_format" ) validation_error = StructuredOutputValidationError(schema_name, exc, output) raise validation_error from exc else: return {"messages": [output], "structured_response": structured_response} return {"messages": [output]}

So a reply that carries tool calls is not parsed here at all, and a reply without tool calls that fails to parse raises; nothing in this branch calls _handle_structured_output_error or asks the model again. The name passed as tool_name is the schema’s __name__ — for a Pydantic model, dataclass or TypedDict, the class name — or "response_format" when the schema has no __name__, such as a JSON schema dict (our reading). The parse itself, in structured_output.py, raises a ValueError starting f"Native structured output expected valid JSON for {schema_name}, " (line 424) when the text is not JSON, and schema validation goes through _parse_with_schema, which raises msg = f"Failed to parse data to {schema_name}: {e}" (line 102); that string is the source you see after the colon (our reading).

Tool strategy. When the reply has tool calls and exactly one of them is a structured-output tool, the arguments are parsed with structured_response = structured_tool_binding.parse(tool_call["args"]) (line 1311) inside a try; then, lines 1329–1346:

except Exception as exc: exception = StructuredOutputValidationError(tool_call["name"], exc, output) should_retry, error_message = _handle_structured_output_error( exception, effective_response_format ) if not should_retry: raise exception from exc return { "messages": [ output, ToolMessage( content=error_message, tool_call_id=tool_call["id"], name=tool_call["name"], ), ], }

(More than one structured-output call in a reply is a different error, MultipleStructuredOutputsError, line 1289.)

When the tool strategy says no retry. _handle_structured_output_error, lines 654–673 of factory.py:

if not isinstance(response_format, ToolStrategy): return False, "" handle_errors = response_format.handle_errors if handle_errors is False: return False, "" if handle_errors is True: return True, STRUCTURED_OUTPUT_ERROR_TEMPLATE.format(error=str(exception)) if isinstance(handle_errors, str): return True, handle_errors if isinstance(handle_errors, type): if issubclass(handle_errors, Exception) and isinstance(exception, handle_errors): return True, STRUCTURED_OUTPUT_ERROR_TEMPLATE.format(error=str(exception)) return False, "" if isinstance(handle_errors, tuple): if any(isinstance(exception, exc_type) for exc_type in handle_errors): return True, STRUCTURED_OUTPUT_ERROR_TEMPLATE.format(error=str(exception)) return False, "" return True, handle_errors(exception)

The retry text is STRUCTURED_OUTPUT_ERROR_TEMPLATE = "Error: {error}\n Please fix your mistakes." (line 125). So should_retry is False — and this error is raised — only for handle_errors=False, or for an exception type or tuple of types that the StructuredOutputValidationError itself is not an instance of; True, a string and a callable always retry (our reading). The exception tested is the wrapper, not source, so handle_errors=ValueError does not match a schema failure even though _parse_with_schema raised a ValueError; it raises instead (our reading of lines 1330–1331 and 665–668). The default, in ToolStrategy.__init__, is | Callable[[Exception], str] = True, (line 242); the docstring describes False as - `False`: No retry, let exceptions propagate (line 221), and warns that for a raw JSON schema dict As a result, `handle_errors` is effectively inert for dict schemas. To get (line 228).

On a retry, no structured_response is returned, and the edge after the model node routes back to it, line 2039: # the injection of artificial tool messages. Jump to the model node (our reading of which edge applies).

Which strategy you are on

If you pass a bare schema as response_format, it becomes an AutoStrategy, and for each model call line 1413 picks effective_response_format = ProviderStrategy(schema=response_format.schema) when _supports_provider_strategy says the model supports it, else a ToolStrategy (lines 1414–1419; the one reused at line 1417 is built at line 1080 the same way) — so handle_errors is at its default (our reading). A message whose source begins “Native structured output expected valid JSON” came from the provider path, since that text is only in ProviderStrategyBinding.parse (our reading).

What it looks like in the field

In langchain-ai/langchain#40753, ToolStrategy retries structured-output validation failures without any cap (open when we fetched it), the reporter, on langchain 1.3.15, builds an agent with response_format=ToolStrategy(GraderResponse), # handle_errors=True by default and a model that repeats an invalid tool call. Their output shows the model called again and again — model call #10, conversation is now 19 messages — until a traceback whose frames are repro.py line 71, .../langgraph/pregel/main.py line 3913 in invoke and line 3011 in stream, ending langgraph.errors.GraphRecursionError: Recursion limit of 10 reached without hitting a stop condition. — so under the default the run ended at the recursion limit, not with this error. They propose an attempt cap: Suggested fix: an attempt budget on `ToolStrategy` (e.g. `max_retries`), so the original … (their report; we read 1.4.4 only, and quote no cap there).

langchain-ai/langchain#40751, `ToolStrategy` structured-output retries (`handle_errors=True`) have no attempt cap — loops until the transcript blows the model's context window, describes the same path on langchain==1.3.15; it was closed, with an automated comment that says “We do not allow automated issue submission at this time.”

What the caller sees and can read

• e.tool_name — the structured-output tool call’s name (tool strategy), or the schema’s __name__ or "response_format" (provider strategy).
• e.source — the exception parsing raised; both sites also chain it, raise … from exc, so it is e.__cause__ too.
• e.ai_message — the AIMessage that held the bad output: its text content on the provider path, its tool_calls on the tool path (our reading).
• Not this error — under the default handle_errors=True, a tool-strategy failure is never raised as this class; it becomes a ToolMessage beginning “Error:” and the model is asked again (our reading of lines 661–662 and 1337–1346).

What to do

• Read e.source first. “Native structured output expected valid JSON” means the provider path got text that is not JSON; “Failed to parse data to” means the JSON (provider path) or the tool-call arguments (tool path) did not validate against your schema; the part after it is the validator’s own message (our reading of lines 424 and 102).
• On the provider path, there is no retry in that branch: catch the error around invoke, or pass ToolStrategy(YourSchema) explicitly so a failure is sent back to the model instead (our inference).
• On the tool path, you see this only with handle_errors=False or an exception type or tuple that did not match. To retry on schema failures by type, name StructuredOutputValidationError (or StructuredOutputError), not ValueError (our reading of lines 665–672).
• If a run never ends under the default, the retries go on until something else stops them; set recursion_limit in the run config as #40753 does, and expect a GraphRecursionError rather than this one (their report; our inference for 1.4.4).

from langchain_core.language_models.chat_models import BaseChatModel from pydantic import BaseModel from langchain.agents import create_agent from langchain.agents.structured_output import ( StructuredOutputValidationError, ToolStrategy, ) class Weather(BaseModel): city: str temp_c: float def ask(model: BaseChatModel, question: str) -> Weather | None: # Our sketch: handle_errors=False so a bad answer raises at once. agent = create_agent( model, [], response_format=ToolStrategy(Weather, handle_errors=False), ) try: result = agent.invoke({"messages": [("user", question)]}) except StructuredOutputValidationError as e: print(e.tool_name) print(repr(e.source)) print(e.ai_message.tool_calls or e.ai_message.content) return None return result["structured_response"]

(Our sketch, not library code, and not run against your version. The imports of create_agent, ToolStrategy and BaseChatModel, the positional tools list and the invoke input are as in the reproduction in #40753; that the error reaches invoke’s caller unchanged, and the "structured_response" key in the result, are our inference from the state the node returns, not something we ran.)

What is behind this site

The short version: StructuredOutputValidationError means a LangChain v1 agent could not parse the model’s structured answer into your schema. On the provider strategy it is raised whenever a reply with no tool calls fails to parse, with your schema’s name in the message; on the tool strategy it is raised only when handle_errors is False or names exception types the error does not match — by default the error goes back to the model and it is asked again. Read e.source for why, and e.ai_message for what the model wrote.

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