Core serialization tests now opt into the object allowlists they rely on
instead of assuming default deserialization permits core objects.
Compatibility tests that intentionally exercise deprecated runnable
streaming and history APIs also suppress the expected deprecation
warnings so they can keep covering those legacy paths cleanly.
## Changes
- Updated serialization and prompt round-trip tests to pass
`allowed_objects="core"` or targeted allowlists when loading
`AIMessage`, prompt templates, structured prompts, runnable maps, and
related core objects.
- Adjusted secret-injection regression coverage to keep testing
`secrets_from_env=True` behavior while explicitly allowing core
deserialization paths.
- Tightened prompt deserialization rejection tests so attribute-access
payloads are loaded only through the specific prompt-template allowlist
needed to reach validation.
- Added module-level warning filters around legacy runnable
compatibility coverage for `astream_log`,
`astream_events(version="v1")`, and `RunnableWithMessageHistory`.
- Bumped the `langchain` package's minimum `langgraph` dependency from
`1.2.4` to `1.2.5`.
## Testing
- Updated unit tests across core serialization, prompt, fake chat model,
runnable history, and runnable event coverage.
Provider-native structured output fallback detection now uses bounded
model-name patterns instead of broad substring checks, reducing false
positives for unrelated model IDs. The model examples and test fixtures
across OpenAI/OpenRouter-facing code were refreshed around current
OpenAI model families while preserving shipped defaults.
## Changes
- Tightened `FALLBACK_MODELS_WITH_STRUCTURED_OUTPUT` from loose string
fragments to regex patterns, with `_supports_provider_strategy` matching
full model-name segments instead of arbitrary substrings.
- Expanded structured-output fallback coverage for newer OpenAI,
Anthropic, and xAI/Grok model families, including `gpt-5.x`, newer
Claude 4/5-style names, and `grok-build`.
- Reused `_attempt_infer_model_provider` in provider tool search routing
so `_provider_from_model_name` follows the same provider inference
behavior as `init_chat_model`.
- Suppressed irrelevant provider-inference deprecation warnings during
provider tool search registry lookup.
- Refreshed OpenAI, Azure OpenAI, OpenRouter, core metadata, and example
model references from older fixtures like `gpt-4`, `gpt-4o`, `o1`, and
`o4-mini` to current test/profile models such as `gpt-5.5`,
`gpt-5-nano`, and `gpt-4.1-mini`.
- Removed outdated OpenAI test assumptions around legacy `o1` behavior
and narrowed legacy structured-output checks to explicitly legacy model
names.
Removes the built-in Bedrock class init validator from `load` so Bedrock
kwargs such as `base_url` and `endpoint_url` are no longer specially
rejected during deserialization.
This keeps provider-specific SSRF policy out of core; callers should
continue to avoid untrusted manifests or use restrictive
`allowed_objects`.
Verified with `make format`, `make lint`, and the focused serialization
load unit tests.
AI-assisted contribution by Open SWE.
Made by [Open SWE](https://openswe.vercel.app)
---------
Co-authored-by: open-swe[bot] <215916821+open-swe[bot]@users.noreply.github.com>
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>
Replaces #33618
**Description:** Fixes the bug in the `load()` function where secret
placeholders in plain dicts were not replaced, even if they match a key
in `secrets_map`, and adds a test case.
Example:
```py
obj = {"api_key": "__SECRET_API_KEY__"}
secret_key = "secret_key_1234"
secrets_map = {"__SECRET_API_KEY__": secret_key}
result = load(obj, secrets_map=secrets_map)
```
Before this change, printing `api_key` in `result` would output
`"__SECRET_API_KEY__"`. Now, it will properly output
`"secret_key_1234"`.
**Issue:** Fixes#31804
**Dependencies:** None
`make format`, `make lint`, and `make test` have all passed on my
machine.
---------
Co-authored-by: Mason Daugherty <mason@langchain.dev>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
## Description
Currently when deserializing objects that contain non-deserializable
values, we throw an error. However, there are cases (e.g. proxies that
return response fields containing extra fields like Python datetimes),
where these values are not important and we just want to drop them.
Twitter handle: @hacubu
---------
Co-authored-by: Mason Daugherty <github@mdrxy.com>
Resolves https://github.com/langchain-ai/langchain/issues/29003,
https://github.com/langchain-ai/langchain/issues/27264
Related: https://github.com/langchain-ai/langchain-redis/issues/52
```python
from langchain.chat_models import init_chat_model
from langchain.globals import set_llm_cache
from langchain_community.cache import SQLiteCache
from pydantic import BaseModel
cache = SQLiteCache()
set_llm_cache(cache)
class Temperature(BaseModel):
value: int
city: str
llm = init_chat_model("openai:gpt-4o-mini")
structured_llm = llm.with_structured_output(Temperature)
```
```python
# 681 ms
response = structured_llm.invoke("What is the average temperature of Rome in May?")
```
```python
# 6.98 ms
response = structured_llm.invoke("What is the average temperature of Rome in May?")
```
Ruff doesn't know about the python version in
`[tool.poetry.dependencies]`. It can get it from
`project.requires-python`.
Notes:
* poetry seems to have issues getting the python constraints from
`requires-python` and using `python` in per dependency constraints. So I
had to duplicate the info. I will open an issue on poetry.
* `inspect.isclass()` doesn't work correctly with `GenericAlias`
(`list[...]`, `dict[..., ...]`) on Python <3.11 so I added some `not
isinstance(type, GenericAlias)` checks:
Python 3.11
```pycon
>>> import inspect
>>> inspect.isclass(list)
True
>>> inspect.isclass(list[str])
False
```
Python 3.9
```pycon
>>> import inspect
>>> inspect.isclass(list)
True
>>> inspect.isclass(list[str])
True
```
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Support using additional import mapping. This allows users to override
old mappings/add new imports to the loads function.
- [x ] **Add tests and docs**: If you're adding a new integration,
please include
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in
`docs/docs/integrations` directory.
- [ x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Fix some circular deps:
- move PromptValue into top level module bc both PromptTemplates and
OutputParsers import
- move tracer context vars to `tracers.context` and import them in
functions in `callbacks.manager`
- add core import tests
