Files
langchain/libs/core
Nick Hollon 922a000f21 fix(core): preserve reasoning block extras across stream deltas
Anthropic's thinking stream emits a `signature_delta` after the
reasoning text finishes. The adapter surfaces this as a reasoning
delta carrying `extras.signature` (and no new text). Two places
were dropping those fields while assembling the accumulated block:

- `_compat_bridge._accumulate` only concatenated the `reasoning`
  text, silently discarding any other keys (including `extras`) on
  later deltas.
- `chat_model_stream._push_content_block_finish` rebuilt the
  finalized reasoning block as `{"type": "reasoning", "reasoning": ...}`,
  dropping everything the finish event carried.

Together, these stripped Claude's `extras.signature` from the
assembled `AIMessage`, and the next turn in a `create_agent` loop
failed with `messages.<n>.content.<k>.thinking.signature: Field
required`.

The bridge now merges `extras` (so earlier keys survive later
deltas) and replaces other non-text fields; `ChatModelStream`
spreads the incoming finish block before overwriting the two
fields it owns.

Covered by the new
`test_lifecycle_validator_anthropic_reasoning_preserves_signature`
case.
2026-04-21 14:20:59 -04:00
..

🦜🍎 LangChain Core

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Quick Install

pip install langchain-core

🤔 What is this?

LangChain Core contains the base abstractions that power the LangChain ecosystem.

These abstractions are designed to be as modular and simple as possible.

The benefit of having these abstractions is that any provider can implement the required interface and then easily be used in the rest of the LangChain ecosystem.

⛰️ Why build on top of LangChain Core?

The LangChain ecosystem is built on top of langchain-core. Some of the benefits:

  • Modularity: We've designed Core around abstractions that are independent of each other, and not tied to any specific model provider.
  • Stability: We are committed to a stable versioning scheme, and will communicate any breaking changes with advance notice and version bumps.
  • Battle-tested: Core components have the largest install base in the LLM ecosystem, and are used in production by many companies.

📖 Documentation

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