chore: Support tool runtime injection when custom args schema is prov… #33999
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CodSpeed Performance ReportMerging #33999 will improve performances by 23.04%Comparing
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| Mode | Benchmark | BASE |
HEAD |
Change | |
|---|---|---|---|---|---|
| ⚡ | WallTime | test_async_callbacks_in_sync |
24 ms | 19.5 ms | +23.04% |
| ⚡ | WallTime | test_import_time[BaseChatModel] |
527.7 ms | 479.4 ms | +10.07% |
| ⚡ | WallTime | test_import_time[ChatPromptTemplate] |
594 ms | 539.4 ms | +10.12% |
| ⚡ | WallTime | test_import_time[InMemoryVectorStore] |
614.5 ms | 556.4 ms | +10.44% |
| ⚡ | WallTime | test_import_time[tool] |
514 ms | 462.3 ms | +11.17% |
Footnotes
-
21 benchmarks were skipped, so the baseline results were used instead. If they were deleted from the codebase, click here and archive them to remove them from the performance reports. ↩
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Have a few questions about impl here, but generally I think this is the right track for a fix (basically, inspect signature, inject anyways).
Happy to pick this up and finish, just wanted to get some clarification first :).
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| @functools.cached_property | ||
| def _injected_args_keys(self) -> frozenset[str]: | ||
| fn = self.func or self.coroutine | ||
| if fn is None: | ||
| return _EMPTY_SET | ||
| return frozenset( | ||
| k | ||
| for k, v in signature(fn).parameters.items() | ||
| if _is_injected_arg_type(v.annotation) | ||
| ) | ||
|
|
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it's clear to me that this solves the problem bc we're inspecting the signature
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Also I think we build these from the tool decorator so I understand it solves our specific use case 👍
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eyurtsev
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Nov 18, 2025
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Nov 20, 2025
## overview
The main purpose of this is to respect tool signatures that request
injected args (like `ToolRuntime`) even when the explicitly specified
`args_schema` does not.
Ex in the following example, we should still inject `runtime` despite
its absence in `ArgsSchema`
```py
class ArgsSchema(BaseModel):
some_arg: int = Field(...)
@tool(args_schema=ArgsSchema)
def my_tool(some_arg: int, runtime: ToolRuntime): ...
```
This is accompanied by
langchain-ai/langchain#34051 which has tests
that pass w/ this change. This tests injection w/ `create_agent` (more
end to end than tests added in
langchain-ai/langchain#33999.
This unblocks the injection of `ToolRuntime` into MCP tools which is
exciting bc that exposes tool call id and state, which we previously
were unable to do.
## other benefits
* Cleaner code structure w/ more helpful docs about injected args.
* Nice perf boost, we're no longer inspecting the annotations of a
tool's schema 3 different times to detect store, state, and runtime
injections.
## additional notes
1. I could see a world where we want more of this logic to reside on the
tools themselves, but tools don't now about LG specific injection types
(like `ToolRuntime`, hence having this logic here for now).
2. We could separately add validation for the case where something is
specified in `args_schema` and not in the function signature (probably
at the tool level though).
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Support injection of injected args (like
InjectedToolCallId,ToolRuntime) when anargs_schemais specified that doesn't contain said args.This allows for pydantic validation of other args while retaining the ability to inject langchain specific arguments.
fixes #33646
fixes #31688
Taking a deep dive here reminded me that we definitely need to revisit our internal tooling logic, but I don't think we should do that in this PR.