This PR was opened by the [Changesets release](https://github.com/changesets/action) GitHub action. When you're ready to do a release, you can merge this and the packages will be published to npm automatically. If you're not ready to do a release yet, that's fine, whenever you add more changesets to main, this PR will be updated. # Releases ## @langchain/langgraph-checkpoint@1.1.2 ### Patch Changes - [#2544](https://github.com/langchain-ai/langgraphjs/pull/2544) [`4487214`](https://github.com/langchain-ai/langgraphjs/commit/448721449f0801009ba76b03dd2e9c16f900bbba) Thanks [@christian-bromann](https://github.com/christian-bromann)! - fix(langgraph): make concurrent DeltaChannel writes deterministic on replay Concurrent same-superstep writes to a `DeltaChannel` could reconstruct from a checkpoint differently than they were applied live, because live execution ordered them by task path while savers replayed them by task id. This fixes that divergence in two complementary ways: - Plain concurrent writes are now applied in the canonical `(task_id, idx)` order on both paths: `_applyWrites` orders them that way live, and the `getDeltaChannelHistory` walk enforces the same order so reconstruction matches live for every saver (Postgres, SQLite, MongoDB, Redis, and custom). - An `Overwrite` now wins its entire super-step: every sibling write in the same step — before AND after the `Overwrite` — is discarded, matching `BinaryOperatorAggregate`. This makes the result independent of the (unstable) ordering of concurrent fan-in writes; previously a plain write that landed after an `Overwrite` in the same step was still folded in. To keep reconstruction in sync with this `Overwrite` rule, any `DeltaChannel` that sees an `Overwrite` in a super-step is now force-snapshotted at the next checkpoint (and, under `"exit"` durability, in the final checkpoint). The post-overwrite value is materialized into `channel_values`, so a cold read seeds from that snapshot and never has to replay across the reset — making live and reconstructed state identical without changing the sparse-replay history shape. These delta-channel APIs remain Beta. - [#2531](https://github.com/langchain-ai/langgraphjs/pull/2531) [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b) Thanks [@christian-bromann](https://github.com/christian-bromann)! - fix(langgraph): forward task metadata and name subagents via lc_agent_name `mapDebugTasks` now forwards filtered user-meaningful task config metadata (including `lc_agent_name`) onto `tasks` stream payloads. The lifecycle transformer uses that metadata to set subagent `graph_name` from `lc_agent_name` and recover `cause: { type: "toolCall", tool_call_id }` from parent tool-dispatch tasks. Adds the shared `EXCLUDED_METADATA_KEYS` constant to `@langchain/langgraph-checkpoint`. Ports langgraph#7928. ## @langchain/langgraph-checkpoint-redis@1.0.10 ### Patch Changes - [#2336](https://github.com/langchain-ai/langgraphjs/pull/2336) [`25907eb`](https://github.com/langchain-ai/langgraphjs/commit/25907eb0be25258c26327c6c68c72bc828ee1cff) Thanks [@MohMaherId](https://github.com/MohMaherId)! - fix(langgraph-checkpoint-redis): persist and reconstruct full `channel_values` across multi-node graphs. `RedisSaver.put()` delta-filters `channel_values` to only the channels written by the current node, but `getTuple()` had no reconstruction logic — unlike `PostgresSaver` — so any multi-node graph whose last node wrote a subset of channels silently lost the others. Each changed channel is now persisted as a version-keyed `checkpoint_blob:*` entry in `put()` and missing channels are reconstructed from those blobs on read. `deleteThread()` now also deletes the `checkpoint_blob:*` keys. Without this the blobs introduced above would orphan forever (memory growth) and thread deletion would be incomplete, matching `PostgresSaver.deleteThread()` parity. When `ttlConfig.refreshOnRead` is enabled, reads now refresh the TTL of the reconstructed `checkpoint_blob:*` keys alongside the checkpoint key. Otherwise a read would keep the checkpoint alive while the blobs it depends on expired, silently dropping reconstructed channels. On write, `put()` now refreshes the TTL of every blob the checkpoint references (the full `channel_versions` set), not just the channels changed by the current node, so carried-over blobs from earlier nodes expire in lockstep with the checkpoint doc. This write-side refresh is independent of `refreshOnRead`. The per-channel blob writes also now run in parallel. Known limitation: with TTL enabled, a carried-over blob can still be lost if it expires during an idle gap longer than `defaultTTL` (no read or write refreshed it in time). When that happens the channel is left cleanly absent on read rather than erroring. Fully closing this gap (re-persisting expired blobs) is tracked as a follow-up. ## @langchain/langgraph@1.4.3 ### Patch Changes - [#2544](https://github.com/langchain-ai/langgraphjs/pull/2544) [`4487214`](https://github.com/langchain-ai/langgraphjs/commit/448721449f0801009ba76b03dd2e9c16f900bbba) Thanks [@christian-bromann](https://github.com/christian-bromann)! - fix(langgraph): make concurrent DeltaChannel writes deterministic on replay Concurrent same-superstep writes to a `DeltaChannel` could reconstruct from a checkpoint differently than they were applied live, because live execution ordered them by task path while savers replayed them by task id. This fixes that divergence in two complementary ways: - Plain concurrent writes are now applied in the canonical `(task_id, idx)` order on both paths: `_applyWrites` orders them that way live, and the `getDeltaChannelHistory` walk enforces the same order so reconstruction matches live for every saver (Postgres, SQLite, MongoDB, Redis, and custom). - An `Overwrite` now wins its entire super-step: every sibling write in the same step — before AND after the `Overwrite` — is discarded, matching `BinaryOperatorAggregate`. This makes the result independent of the (unstable) ordering of concurrent fan-in writes; previously a plain write that landed after an `Overwrite` in the same step was still folded in. To keep reconstruction in sync with this `Overwrite` rule, any `DeltaChannel` that sees an `Overwrite` in a super-step is now force-snapshotted at the next checkpoint (and, under `"exit"` durability, in the final checkpoint). The post-overwrite value is materialized into `channel_values`, so a cold read seeds from that snapshot and never has to replay across the reset — making live and reconstructed state identical without changing the sparse-replay history shape. These delta-channel APIs remain Beta. - [#2531](https://github.com/langchain-ai/langgraphjs/pull/2531) [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b) Thanks [@christian-bromann](https://github.com/christian-bromann)! - fix(langgraph): merge instead of overwrite in `ensureLangGraphConfig` `ensureLangGraphConfig` now per-key merges `callbacks`, `tags`, `metadata`, and `configurable` across configs instead of last-write-wins, so values bound via `.withConfig({...})` survive when a later (e.g. invoke-time) config supplies other keys. The merged dicts are fresh objects, fixing a by-reference mutation of shared base configs. Also drops the now-redundant `combineCallbacks` workaround in `streamEvents`, which double-registered and double-fired graph-bound callbacks. - [#2531](https://github.com/langchain-ai/langgraphjs/pull/2531) [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b) Thanks [@christian-bromann](https://github.com/christian-bromann)! - fix(langgraph): preserve namespace nesting for imperative graph invokes When a compiled graph is invoked from inside another graph's running task (e.g. a tool body calling `subAgent.invoke(...)`), the surrounding task context — including the langgraph-internal nesting keys (`__pregel_read`, `__pregel_stream`, `checkpoint_ns`, the checkpoint map) — is propagated implicitly via `AsyncLocalStorage`. The base `Runnable.stream` calls langchain-core's `ensureConfig`, which replaces the ambient `configurable` wholesale whenever the caller passes its own. Because `createAgent` always supplies a `configurable`, every tool-invoked sub-agent lost those keys, ran as a fresh root run, and had its streamed events flattened to the root namespace instead of nesting under the triggering task. `Pregel.stream` now merges the ambient `configurable` underneath the caller's (caller keys win per-key) when the ambient marks an active task (`__pregel_read` present) but the explicit `configurable` is missing it. Declared subgraph nodes (which already carry their own `__pregel_read`) and top-level runs are unaffected. - [#2537](https://github.com/langchain-ai/langgraphjs/pull/2537) [`be09666`](https://github.com/langchain-ai/langgraphjs/commit/be096663f42fe7ea9355d6c0def4854e657866d8) Thanks [@christian-bromann](https://github.com/christian-bromann)! - fix(langgraph): dispatch stream messages handler inline The v3 `messages` handler (`StreamProtocolMessagesHandler`, which powers `run.messages`) only performs a synchronous `push()` onto the run's stream, but its callbacks were dispatched on LangChain's background callback queue (the default `awaitHandlers === false`). A model or tool call inside a nested or parallel task could therefore flush its `messages` chunk _after_ the Pregel loop returned and sealed the stream, where `IterableReadableWritableStream.push` silently drops chunks once closed. This surfaced as empty per-message streams (`sub.messages`) for subagents dispatched in parallel from a single tools step. The handler now sets `awaitHandlers = true` so its callbacks run inline — every push happens during the originating model/chain call while the stream is still open. This avoids the global over-wait, fake-timer deadlock, and error-path unhandled rejections that a blanket `awaitAllCallbacks()` drain before close would have introduced. - [#2531](https://github.com/langchain-ai/langgraphjs/pull/2531) [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b) Thanks [@christian-bromann](https://github.com/christian-bromann)! - fix(langgraph): forward task metadata and name subagents via lc_agent_name `mapDebugTasks` now forwards filtered user-meaningful task config metadata (including `lc_agent_name`) onto `tasks` stream payloads. The lifecycle transformer uses that metadata to set subagent `graph_name` from `lc_agent_name` and recover `cause: { type: "toolCall", tool_call_id }` from parent tool-dispatch tasks. Adds the shared `EXCLUDED_METADATA_KEYS` constant to `@langchain/langgraph-checkpoint`. Ports langgraph#7928. - [#2549](https://github.com/langchain-ai/langgraphjs/pull/2549) [`bc667a9`](https://github.com/langchain-ai/langgraphjs/commit/bc667a998ae9909d15795387dad45048e8947219) Thanks [@christian-bromann](https://github.com/christian-bromann)! - fix(langgraph): support DeltaChannel fields in StateSchema Add a `DeltaValue` state field (and a `MessagesDeltaValue` prebuilt) so a `DeltaChannel` can be declared via `StateSchema`, not just `Annotation.Root` or a raw channel map. `StateSchema` now maps `DeltaValue` to a `DeltaChannel` (forwarding `snapshotFrequency` and the value-schema default) and validates its inputs/`Overwrite` updates like `ReducedValue`. - Updated dependencies \[[`4487214`](https://github.com/langchain-ai/langgraphjs/commit/448721449f0801009ba76b03dd2e9c16f900bbba), [`2134c8a`](https://github.com/langchain-ai/langgraphjs/commit/2134c8a2c0bc8dd2ebea33e1191c8dd0c4b83236), [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b)]: - @langchain/langgraph-checkpoint@1.1.2 - @langchain/langgraph-sdk@1.9.23 ## @langchain/langgraph-sdk@1.9.23 ### Patch Changes - [#2545](https://github.com/langchain-ai/langgraphjs/pull/2545) [`2134c8a`](https://github.com/langchain-ai/langgraphjs/commit/2134c8a2c0bc8dd2ebea33e1191c8dd0c4b83236) Thanks [@christian-bromann](https://github.com/christian-bromann)! - fix(sdk): avoid scoped stream resubscribe churn Defer final projection disposal by one microtask so framework bindings that release and immediately reacquire the same scoped projection during reactive updates keep the existing stream subscription instead of rotating through root-only and scoped SSE filters. ## @langchain/angular@1.0.24 ### Patch Changes - Updated dependencies \[[`2134c8a`](https://github.com/langchain-ai/langgraphjs/commit/2134c8a2c0bc8dd2ebea33e1191c8dd0c4b83236)]: - @langchain/langgraph-sdk@1.9.23 ## @langchain/react@1.0.24 ### Patch Changes - Updated dependencies \[[`2134c8a`](https://github.com/langchain-ai/langgraphjs/commit/2134c8a2c0bc8dd2ebea33e1191c8dd0c4b83236)]: - @langchain/langgraph-sdk@1.9.23 ## @langchain/svelte@1.0.24 ### Patch Changes - Updated dependencies \[[`2134c8a`](https://github.com/langchain-ai/langgraphjs/commit/2134c8a2c0bc8dd2ebea33e1191c8dd0c4b83236)]: - @langchain/langgraph-sdk@1.9.23 ## @langchain/vue@1.0.24 ### Patch Changes - Updated dependencies \[[`2134c8a`](https://github.com/langchain-ai/langgraphjs/commit/2134c8a2c0bc8dd2ebea33e1191c8dd0c4b83236)]: - @langchain/langgraph-sdk@1.9.23 ## @example/ai-elements@0.1.39 ### Patch Changes - Updated dependencies \[[`4487214`](https://github.com/langchain-ai/langgraphjs/commit/448721449f0801009ba76b03dd2e9c16f900bbba), [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b), [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b), [`be09666`](https://github.com/langchain-ai/langgraphjs/commit/be096663f42fe7ea9355d6c0def4854e657866d8), [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b), [`bc667a9`](https://github.com/langchain-ai/langgraphjs/commit/bc667a998ae9909d15795387dad45048e8947219)]: - @langchain/langgraph@1.4.3 - @langchain/react@1.0.24 ## @examples/assistant-ui-claude@0.1.39 ### Patch Changes - Updated dependencies \[[`4487214`](https://github.com/langchain-ai/langgraphjs/commit/448721449f0801009ba76b03dd2e9c16f900bbba), [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b), [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b), [`be09666`](https://github.com/langchain-ai/langgraphjs/commit/be096663f42fe7ea9355d6c0def4854e657866d8), [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b), [`bc667a9`](https://github.com/langchain-ai/langgraphjs/commit/bc667a998ae9909d15795387dad45048e8947219)]: - @langchain/langgraph@1.4.3 - @langchain/react@1.0.24 ## @examples/ui-angular@0.0.49 ### Patch Changes - Updated dependencies \[[`4487214`](https://github.com/langchain-ai/langgraphjs/commit/448721449f0801009ba76b03dd2e9c16f900bbba), [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b), [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b), [`2134c8a`](https://github.com/langchain-ai/langgraphjs/commit/2134c8a2c0bc8dd2ebea33e1191c8dd0c4b83236), [`be09666`](https://github.com/langchain-ai/langgraphjs/commit/be096663f42fe7ea9355d6c0def4854e657866d8), [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b), [`bc667a9`](https://github.com/langchain-ai/langgraphjs/commit/bc667a998ae9909d15795387dad45048e8947219)]: - @langchain/langgraph@1.4.3 - @langchain/langgraph-sdk@1.9.23 - @langchain/angular@1.0.24 ## @examples/ui-multimodal@0.0.25 ### Patch Changes - Updated dependencies \[[`4487214`](https://github.com/langchain-ai/langgraphjs/commit/448721449f0801009ba76b03dd2e9c16f900bbba), [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b), [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b), [`be09666`](https://github.com/langchain-ai/langgraphjs/commit/be096663f42fe7ea9355d6c0def4854e657866d8), [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b), [`bc667a9`](https://github.com/langchain-ai/langgraphjs/commit/bc667a998ae9909d15795387dad45048e8947219)]: - @langchain/langgraph@1.4.3 - @langchain/react@1.0.24 ## @examples/ui-react@0.0.25 ### Patch Changes - Updated dependencies \[[`4487214`](https://github.com/langchain-ai/langgraphjs/commit/448721449f0801009ba76b03dd2e9c16f900bbba), [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b), [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b), [`2134c8a`](https://github.com/langchain-ai/langgraphjs/commit/2134c8a2c0bc8dd2ebea33e1191c8dd0c4b83236), [`be09666`](https://github.com/langchain-ai/langgraphjs/commit/be096663f42fe7ea9355d6c0def4854e657866d8), [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b), [`bc667a9`](https://github.com/langchain-ai/langgraphjs/commit/bc667a998ae9909d15795387dad45048e8947219)]: - @langchain/langgraph@1.4.3 - @langchain/langgraph-sdk@1.9.23 - @langchain/react@1.0.24 ## langgraph@1.0.43 ### Patch Changes - Updated dependencies \[[`4487214`](https://github.com/langchain-ai/langgraphjs/commit/448721449f0801009ba76b03dd2e9c16f900bbba), [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b), [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b), [`be09666`](https://github.com/langchain-ai/langgraphjs/commit/be096663f42fe7ea9355d6c0def4854e657866d8), [`38cfe01`](https://github.com/langchain-ai/langgraphjs/commit/38cfe01ff02490ff6bcc86c66708ef671f2e0d4b), [`bc667a9`](https://github.com/langchain-ai/langgraphjs/commit/bc667a998ae9909d15795387dad45048e8947219)]: - @langchain/langgraph@1.4.3 Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
@langchain/angular
Angular SDK for building AI-powered applications with Deep Agents, LangChain and LangGraph.
The package ships a Signals-first API built on top of the v2 streaming
protocol. injectStream returns a small, always-on root handle
(values, messages, isLoading, error, …) and pushes anything
namespaced (subagents, subgraphs, media, submission queue, per-message
metadata) behind ref-counted inject* selectors so components
only pay for data they actually consume.
Upgrading from
0.x? Seedocs/v1-migration.mdfor the complete matrix of option, return-shape, and transport changes.
Installation
npm install @langchain/angular @langchain/core
Peer dependencies: @angular/core (^18.0.0 – ^21.0.0),
@langchain/core (^1.1.27).
Quick start
import { Component } from "@angular/core";
import { injectStream } from "@langchain/angular";
@Component({
standalone: true,
template: `
<div>
@for (msg of stream.messages(); track msg.id ?? $index) {
<div>{{ str(msg.content) }}</div>
}
<button
[disabled]="stream.isLoading()"
(click)="onSubmit()"
>
Send
</button>
</div>
`,
})
export class ChatComponent {
readonly stream = injectStream({
assistantId: "agent",
apiUrl: "http://localhost:2024",
});
str(v: unknown) {
return typeof v === "string" ? v : JSON.stringify(v);
}
onSubmit() {
void this.stream.submit({
messages: [{ type: "human", content: "Hello!" }],
});
}
}
injectStream must be called from an Angular injection context —
the host's DestroyRef owns the stream, so navigating away destroys
the controller automatically.
Features at a glance
- Signals everywhere. Messages, values, tool calls, interrupts,
loading/error state — all Angular
Signal<T>s you call as functions in templates. - One call, two transports. Same option bag targets either the
LangGraph Platform (SSE by default,
transport: "websocket"opt-in) or a custom backend through anAgentServerAdapter. - Ref-counted selectors.
injectMessages,injectValues,injectToolCalls, media selectors, submission queue — the first consumer opens a subscription, the last one'sDestroyRefcloses it. Components pay only for what they render. - Human-in-the-loop. Interrupts are first-class signals; resume or fork a specific pending interrupt with one call.
- Headless tools. Register browser-side tool implementations; the runtime dispatches matching interrupts and auto-resumes with the return value.
- Subagent & subgraph discovery. Lightweight snapshots at the root; scoped content (messages, tool calls, state) via the same selectors, targeted at a snapshot or namespace.
- Forking without history preload. Per-message metadata +
submit({ forkFrom })replaces the legacybranch/fetchStateHistorytrio. - DI-native.
provideStreamfor subtree sharing,provideStreamDefaultsfor app-wide config,StreamServicefor class-based wrappers. - Typed end-to-end. Pass
typeof agentas the first generic — state, tool args, and per-subagent state flow through to every selector.
Public stream types
Use StreamApi<T> when you need to name the return type of
injectStream, useStream, provideStream, or StreamService in
Angular code. It is the Angular-facing alias for the Signals-first
handle.
UseStreamResult<T> is also exported as a React-compatible alias for
the same shape. Prefer it only in shared utilities that are designed to
accept stream handles from multiple framework packages.
Documentation
In-depth guides live under docs/:
inject-stream.md— options + return-shape referencetransports.md— SSE, WebSocket, and customAgentServerAdaptercustom-transport.md— implementingAgentServerAdapteragainst your own backend, with a worked walkthrough ofexamples/ui-react-transportselectors.md— scoped reads (injectMessages,injectValues, media, channels, …)interrupts.md— handling and responding to interruptsbranching.md— forking viainjectMessageMetadata+submit({ forkFrom })submission-queue.md—injectSubmissionQueueandmultitaskStrategy: "enqueue"headless-tools.md— browser-side tool implementationssubagents-subgraphs.md— discovery snapshots and scoped contentdependency-injection.md—provideStream,provideStreamDefaults,StreamServicetype-safety.md— generics, agent inference, and public stream aliasestesting.md—STREAM_INSTANCEfakes and service overridesv1-migration.md— migrating from0.x
Playground
For complete end-to-end examples, visit the LangChain UI Playground.
License
MIT