Tool runs in `_TracerCore._create_tool_run` were discarding the
structured `inputs` dict that `BaseTool.run` passes to `on_tool_start`,
replacing it with `{"input": str(filtered_tool_input)}`. Consequently,
every multi-arg tool (e.g. ones in `deepagents` like `execute`,
`edit_file`, `write_file`, `grep`, ...) appeared in LangSmith with a
stringified, escaped dump of its arguments — multi-line bash commands
rendered with `\n` and were effectively unreadable. Chain runs already
preserved dicts via `_get_chain_inputs`; tool runs are now symmetric.
## Changes
- Preserve `inputs` when it is already a `dict` in the `original` /
`original+chat` branch of `_TracerCore._create_tool_run`, falling back
to `{"input": input_str}` only when no structured payload was provided
- Add regression tests in the sync and async base-tracer suites that
pass a structured `inputs` to `on_tool_start` and assert the dict
survives onto the resulting `Run`
## Breaking change
Custom `BaseTracer` subclasses that parsed `Run.inputs["input"]` as a
stringified dict for tool runs will need to read the structured fields
directly. The shape now matches what `on_tool_start(inputs=...)` has
always received — introduced alongside `_schema_format` in the
`astream_events` work — and what `streaming_events` consumers already
see.
Drop the `NotImplementedError` branch in `warn_deprecated` so callers
can pass `pending=False` without specifying a `removal` version. The
previous behavior contradicted the docstring (which claimed an empty
default would auto-compute a removal version) — no such computation
existed; the function just raised a placeholder "Need to determine which
default deprecation schedule to use" error.
When a langsmith `@traceable` function invokes a LangChain Runnable or
LangGraph subgraph, the callback manager's `_configure` function injects
the `@traceable` RunTree into the `LangChainTracer`'s `run_map` so that
child runs can resolve their parent for trace nesting. However, since
the RunTree was created outside the tracer's callback lifecycle,
`_end_trace` never removes it. The entry persists in `run_map`
indefinitely, retaining the full RunTree and its entire child tree.
In applications with nested subgraph invocations (e.g. an outer
investigation graph delegating to skill agent subgraphs, each compiled
as their own `StateGraph`), this causes RunTree objects to accumulate
linearly with every call.
**Fix:** Track which `run_map` entries were injected externally via a
shared `_external_run_ids` refcount dict on `_TracerCore`. When
`_start_trace` adds a child under an external parent, it increments the
count. When `_end_trace` finishes a child, it decrements — and evicts
the external parent from `run_map` once the last child completes.
The refcount (rather than a simple set) is necessary because a single
external parent may have multiple sibling children in the callback chain
(e.g. a `prompt | llm` `RunnableSequence`). Only truly external runs are
tracked — the `_configure` guard `if run_id_str not in handler.run_map`
prevents tracer-managed runs from being misclassified.
Resolve symlinks before validating file extensions in the deprecated
`save()` method on prompt classes.
Credit to Jeff Ponte (@JDP-Security) for reporting the symlink
resolution issue.
Adds serialization mappings for `ChatBedrockConverse` and `BedrockLLM`
to unblock standard tests on `langchain-core>=1.2.5` (context:
[langchain-aws#821](https://github.com/langchain-ai/langchain-aws/pull/821)).
Also introduces a class-specific validator system in
`langchain_core.load` that blocks deserialization of AWS Bedrock models
when `endpoint_url` or `base_url` parameters are present, preventing
SSRF attacks via crafted serialized payloads.
Closes#34645
## Changes
- Add `ChatBedrockConverse` and `BedrockLLM` entries to
`SERIALIZABLE_MAPPING` in `mapping.py`, mapping legacy paths to their
`langchain_aws` import locations
- Add `validators.py` with `_bedrock_validator` — rejects
deserialization kwargs containing `endpoint_url` or `base_url` for all
Bedrock-related classes (`ChatBedrock`, `BedrockChat`,
`ChatBedrockConverse`, `ChatAnthropicBedrock`, `BedrockLLM`, `Bedrock`)
- `CLASS_INIT_VALIDATORS` registry covers both serialized (legacy) keys
and resolved import paths from `ALL_SERIALIZABLE_MAPPINGS`, preventing
bypass via direct-path payloads
- Move kwargs extraction and all validator checks
(`CLASS_INIT_VALIDATORS` + `init_validator`) in `Reviver.__call__` to
run **before** `importlib.import_module()` — fail fast on security
violations before executing third-party code
- Class-specific validators are independent of `init_validator` and
cannot be disabled by passing `init_validator=None`
## Testing
- `test_validator_registry_keys_in_serializable_mapping` — structural
invariant test ensuring every `CLASS_INIT_VALIDATORS` key exists in
`ALL_SERIALIZABLE_MAPPINGS`
- 10 end-to-end `load()` tests covering all Bedrock class paths (legacy
aliases, resolved import paths, `ChatAnthropicBedrock`,
`init_validator=None` bypass attempt)
- Unit tests for `_bedrock_validator` covering `endpoint_url`,
`base_url`, both params, and safe kwargs
---------
Co-authored-by: Mason Daugherty <mason@langchain.dev>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
Register `ChatBaseten` from `langchain_baseten` in the core
serialization mapping so it can round-trip through `loads`/`dumps`.
Without this entry, serialized `ChatBaseten` objects fail to
deserialize.
PR #35788 added 7 new fields to the `langchain-profiles` CLI output
(`name`, `status`, `release_date`, `last_updated`, `open_weights`,
`attachment`, `temperature`) but didn't update `ModelProfile` in
`langchain-core`. Partner packages like `langchain-aws` that set
`extra="forbid"` on their Pydantic models hit `extra_forbidden`
validation errors when Pydantic encountered undeclared TypedDict keys at
construction time. This adds the missing fields, makes `ModelProfile`
forward-compatible, provides a base-class hook so partners can stop
duplicating model-profile validator boilerplate, migrates all in-repo
partners to the new hook, and adds runtime + CI-time warnings for schema
drift.
## Changes
### `langchain-core`
- Add `__pydantic_config__ = ConfigDict(extra="allow")` to
`ModelProfile` so unknown profile keys pass Pydantic validation even on
models with `extra="forbid"` — forward-compatibility for when the CLI
schema evolves ahead of core
- Declare the 7 missing fields on `ModelProfile`: `name`, `status`,
`release_date`, `last_updated`, `open_weights` (metadata) and
`attachment`, `temperature` (capabilities)
- Add `_warn_unknown_profile_keys()` in `model_profile.py` — emits a
`UserWarning` when a profile dict contains keys not in `ModelProfile`,
suggesting a core upgrade. Wrapped in a bare `except` so introspection
failures never crash model construction
- Add `BaseChatModel._resolve_model_profile()` hook that returns `None`
by default. Partners can override this single method instead of
redefining the full `_set_model_profile` validator — the base validator
calls it automatically
- Add `BaseChatModel._check_profile_keys` as a separate
`model_validator` that calls `_warn_unknown_profile_keys`. Uses a
distinct method name so partner overrides of `_set_model_profile` don't
inadvertently suppress the check
### `langchain-profiles` CLI
- Add `_warn_undeclared_profile_keys()` to the CLI (`cli.py`), called
after merging augmentations in `refresh()` — warns at profile-generation
time (not just runtime) when emitted keys aren't declared in
`ModelProfile`. Gracefully skips if `langchain-core` isn't installed
- Add guard test
`test_model_data_to_profile_keys_subset_of_model_profile` in
model-profiles — feeds a fully-populated model dict to
`_model_data_to_profile()` and asserts every emitted key exists in
`ModelProfile.__annotations__`. CI fails before any release if someone
adds a CLI field without updating the TypedDict
### Partner packages
- Migrate all 10 in-repo partners to the `_resolve_model_profile()`
hook, replacing duplicated `@model_validator` / `_set_model_profile`
overrides: anthropic, deepseek, fireworks, groq, huggingface, mistralai,
openai (base + azure), openrouter, perplexity, xai
- Anthropic retains custom logic (context-1m beta → `max_input_tokens`
override); all others reduce to a one-liner
- Add `pr_lint.yml` scope for the new `model-profiles` package
