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-mongodb@1.4.0 ### Minor Changes - [#1928](https://github.com/langchain-ai/langgraphjs/pull/1928) [`3d7fcea`](https://github.com/langchain-ai/langgraphjs/commit/3d7fcea7d7ea7f1203d24be9df607d5a8e8717bc) Thanks [@Mihailoff](https://github.com/Mihailoff)! - Add TTL support for automatic checkpoint expiration - Add optional `ttl` parameter to MongoDBSaver (value in seconds) - Add `setup()` method to create TTL indexes on collections - Add `upserted_at` timestamp to documents when TTL is enabled - Each write refreshes TTL (expires after inactivity, not creation) ### Patch Changes - [#2556](https://github.com/langchain-ai/langgraphjs/pull/2556) [`bee3c91`](https://github.com/langchain-ai/langgraphjs/commit/bee3c91d0adc315ebde0622d8c4b1fff041c1bfd) Thanks [@mohamedkhaled4053](https://github.com/mohamedkhaled4053)! - Fix `MongoDBSaver.putWrites` throwing `MongoServerError: Invalid BulkOperation, Batch cannot be empty` when called with an empty `writes` array. This is reached by human-in-the-loop / `interrupt()` flows, where a task can complete producing zero channel writes and LangGraph calls `putWrites(config, [], taskId)`. `putWrites` now no-ops on empty writes, matching the behavior of the postgres and sqlite savers (which iterate and naturally skip empty batches). - [#2550](https://github.com/langchain-ai/langgraphjs/pull/2550) [`2b8cc2f`](https://github.com/langchain-ai/langgraphjs/commit/2b8cc2f3fd5c9d3c33b56e013292daf5d936428e) Thanks [@lazydiv](https://github.com/lazydiv)! - feat(checkpoint-mongodb): add setup() to create required indexes ## @langchain/langgraph-api@1.4.0 ### Minor Changes - [#2559](https://github.com/langchain-ai/langgraphjs/pull/2559) [`48cbdd2`](https://github.com/langchain-ai/langgraphjs/commit/48cbdd23fdf29277530f6aa05c397c9902e81206) Thanks [@christian-bromann](https://github.com/christian-bromann)! - feat(langgraph-cli): add `deploy` command for LangSmith Deployment Port the Python CLI's `langgraph deploy` workflow to `@langchain/langgraph-cli`, including local and remote build paths, deployment lifecycle subcommands (`list`, `revisions list`, `delete`, `logs`), and host-backend client utilities with tests. ### Patch Changes - [#2557](https://github.com/langchain-ai/langgraphjs/pull/2557) [`b1e856d`](https://github.com/langchain-ai/langgraphjs/commit/b1e856d987ac16148dc0872d1fecf70e659ef28e) Thanks [@christian-bromann](https://github.com/christian-bromann)! - fix(langgraph-api): preserve non-empty response_metadata on protocol-v2 state messages The protocol-v2 state normalizer stripped `response_metadata` from messages, dropping data that HITL flows rely on — an interrupt's card is carried on `AIMessage.response_metadata` (e.g. `{ cards: ... }`). Non-empty `response_metadata` is now retained so the card reaches the client. - [#2557](https://github.com/langchain-ai/langgraphjs/pull/2557) [`b1e856d`](https://github.com/langchain-ai/langgraphjs/commit/b1e856d987ac16148dc0872d1fecf70e659ef28e) Thanks [@christian-bromann](https://github.com/christian-bromann)! - fix(sdk): apply state update and goto alongside interrupt resume `respond(decision, { update, goto })` now maps to LangGraph's `Command(resume, update, goto)`, so a human-in-the-loop UI can commit a state update (e.g. push the interrupt card into state) in the **same superstep** as the resume — one checkpoint, no separate `updateState` write, no flicker. `@langchain/langgraph-api` forwards `update`/`goto` through `input.respond`, and `@langchain/core` message instances in `update` are serialized to dicts before transport, exactly like `submit()`. Bumps `@langchain/protocol` to `^0.0.18` for the `Goto` type. `respond`/`respondAll` also apply `update` **optimistically** (mirroring `submit()`): the pushed messages paint immediately, with stable ids minted so the resumed run's echo reconciles them in place. Without this the interrupt is cleared the instant `respond()` dispatches while the pushed card only reappears a server round-trip later — so the card would flicker in that gap. The optimistic state settles on the resumed run's terminal (pending → sent, or rolled back on a failure before any echo). User-initiated optimistic writes (`submit()` / `respond()` / `respondAll()`) now commit to the store **synchronously**, in the same tick as the triggering event, instead of being coalesced onto the next macrotask. This lets a framework render the pushed message in the **same commit** as any local UI state the caller flips alongside it (e.g. a HITL form swapping its inputs for the resolved card), so the card no longer blinks out for the one-macrotask window before the flush lands. High-frequency streaming writes keep their macrotask coalescing. - Updated dependencies \[[`48cbdd2`](https://github.com/langchain-ai/langgraphjs/commit/48cbdd23fdf29277530f6aa05c397c9902e81206)]: - @langchain/langgraph-ui@1.4.0 ## @langchain/langgraph-cli@1.4.0 ### Minor Changes - [#2559](https://github.com/langchain-ai/langgraphjs/pull/2559) [`48cbdd2`](https://github.com/langchain-ai/langgraphjs/commit/48cbdd23fdf29277530f6aa05c397c9902e81206) Thanks [@christian-bromann](https://github.com/christian-bromann)! - feat(langgraph-cli): add `deploy` command for LangSmith Deployment Port the Python CLI's `langgraph deploy` workflow to `@langchain/langgraph-cli`, including local and remote build paths, deployment lifecycle subcommands (`list`, `revisions list`, `delete`, `logs`), and host-backend client utilities with tests. ### Patch Changes - Updated dependencies \[[`48cbdd2`](https://github.com/langchain-ai/langgraphjs/commit/48cbdd23fdf29277530f6aa05c397c9902e81206), [`b1e856d`](https://github.com/langchain-ai/langgraphjs/commit/b1e856d987ac16148dc0872d1fecf70e659ef28e), [`b1e856d`](https://github.com/langchain-ai/langgraphjs/commit/b1e856d987ac16148dc0872d1fecf70e659ef28e)]: - @langchain/langgraph-api@1.4.0 ## @langchain/langgraph-ui@1.4.0 ### Minor Changes - [#2559](https://github.com/langchain-ai/langgraphjs/pull/2559) [`48cbdd2`](https://github.com/langchain-ai/langgraphjs/commit/48cbdd23fdf29277530f6aa05c397c9902e81206) Thanks [@christian-bromann](https://github.com/christian-bromann)! - feat(langgraph-cli): add `deploy` command for LangSmith Deployment Port the Python CLI's `langgraph deploy` workflow to `@langchain/langgraph-cli`, including local and remote build paths, deployment lifecycle subcommands (`list`, `revisions list`, `delete`, `logs`), and host-backend client utilities with tests. ## @langchain/langgraph@1.4.5 ### Patch Changes - [#2557](https://github.com/langchain-ai/langgraphjs/pull/2557) [`b1e856d`](https://github.com/langchain-ai/langgraphjs/commit/b1e856d987ac16148dc0872d1fecf70e659ef28e) Thanks [@christian-bromann](https://github.com/christian-bromann)! - fix(sdk): apply state update and goto alongside interrupt resume `respond(decision, { update, goto })` now maps to LangGraph's `Command(resume, update, goto)`, so a human-in-the-loop UI can commit a state update (e.g. push the interrupt card into state) in the **same superstep** as the resume — one checkpoint, no separate `updateState` write, no flicker. `@langchain/langgraph-api` forwards `update`/`goto` through `input.respond`, and `@langchain/core` message instances in `update` are serialized to dicts before transport, exactly like `submit()`. Bumps `@langchain/protocol` to `^0.0.18` for the `Goto` type. `respond`/`respondAll` also apply `update` **optimistically** (mirroring `submit()`): the pushed messages paint immediately, with stable ids minted so the resumed run's echo reconciles them in place. Without this the interrupt is cleared the instant `respond()` dispatches while the pushed card only reappears a server round-trip later — so the card would flicker in that gap. The optimistic state settles on the resumed run's terminal (pending → sent, or rolled back on a failure before any echo). User-initiated optimistic writes (`submit()` / `respond()` / `respondAll()`) now commit to the store **synchronously**, in the same tick as the triggering event, instead of being coalesced onto the next macrotask. This lets a framework render the pushed message in the **same commit** as any local UI state the caller flips alongside it (e.g. a HITL form swapping its inputs for the resolved card), so the card no longer blinks out for the one-macrotask window before the flush lands. High-frequency streaming writes keep their macrotask coalescing. - Updated dependencies \[[`b1e856d`](https://github.com/langchain-ai/langgraphjs/commit/b1e856d987ac16148dc0872d1fecf70e659ef28e)]: - @langchain/langgraph-sdk@1.9.24 ## @langchain/langgraph-sdk@1.9.24 ### Patch Changes - [#2557](https://github.com/langchain-ai/langgraphjs/pull/2557) [`b1e856d`](https://github.com/langchain-ai/langgraphjs/commit/b1e856d987ac16148dc0872d1fecf70e659ef28e) Thanks [@christian-bromann](https://github.com/christian-bromann)! - fix(sdk): apply state update and goto alongside interrupt resume `respond(decision, { update, goto })` now maps to LangGraph's `Command(resume, update, goto)`, so a human-in-the-loop UI can commit a state update (e.g. push the interrupt card into state) in the **same superstep** as the resume — one checkpoint, no separate `updateState` write, no flicker. `@langchain/langgraph-api` forwards `update`/`goto` through `input.respond`, and `@langchain/core` message instances in `update` are serialized to dicts before transport, exactly like `submit()`. Bumps `@langchain/protocol` to `^0.0.18` for the `Goto` type. `respond`/`respondAll` also apply `update` **optimistically** (mirroring `submit()`): the pushed messages paint immediately, with stable ids minted so the resumed run's echo reconciles them in place. Without this the interrupt is cleared the instant `respond()` dispatches while the pushed card only reappears a server round-trip later — so the card would flicker in that gap. The optimistic state settles on the resumed run's terminal (pending → sent, or rolled back on a failure before any echo). User-initiated optimistic writes (`submit()` / `respond()` / `respondAll()`) now commit to the store **synchronously**, in the same tick as the triggering event, instead of being coalesced onto the next macrotask. This lets a framework render the pushed message in the **same commit** as any local UI state the caller flips alongside it (e.g. a HITL form swapping its inputs for the resolved card), so the card no longer blinks out for the one-macrotask window before the flush lands. High-frequency streaming writes keep their macrotask coalescing. ## @langchain/angular@1.0.25 ### Patch Changes - [#2557](https://github.com/langchain-ai/langgraphjs/pull/2557) [`b1e856d`](https://github.com/langchain-ai/langgraphjs/commit/b1e856d987ac16148dc0872d1fecf70e659ef28e) Thanks [@christian-bromann](https://github.com/christian-bromann)! - fix(sdk): apply state update and goto alongside interrupt resume `respond(decision, { update, goto })` now maps to LangGraph's `Command(resume, update, goto)`, so a human-in-the-loop UI can commit a state update (e.g. push the interrupt card into state) in the **same superstep** as the resume — one checkpoint, no separate `updateState` write, no flicker. `@langchain/langgraph-api` forwards `update`/`goto` through `input.respond`, and `@langchain/core` message instances in `update` are serialized to dicts before transport, exactly like `submit()`. Bumps `@langchain/protocol` to `^0.0.18` for the `Goto` type. `respond`/`respondAll` also apply `update` **optimistically** (mirroring `submit()`): the pushed messages paint immediately, with stable ids minted so the resumed run's echo reconciles them in place. Without this the interrupt is cleared the instant `respond()` dispatches while the pushed card only reappears a server round-trip later — so the card would flicker in that gap. The optimistic state settles on the resumed run's terminal (pending → sent, or rolled back on a failure before any echo). User-initiated optimistic writes (`submit()` / `respond()` / `respondAll()`) now commit to the store **synchronously**, in the same tick as the triggering event, instead of being coalesced onto the next macrotask. This lets a framework render the pushed message in the **same commit** as any local UI state the caller flips alongside it (e.g. a HITL form swapping its inputs for the resolved card), so the card no longer blinks out for the one-macrotask window before the flush lands. High-frequency streaming writes keep their macrotask coalescing. - Updated dependencies \[[`b1e856d`](https://github.com/langchain-ai/langgraphjs/commit/b1e856d987ac16148dc0872d1fecf70e659ef28e)]: - @langchain/langgraph-sdk@1.9.24 ## @langchain/react@1.0.25 ### Patch Changes - [#2557](https://github.com/langchain-ai/langgraphjs/pull/2557) [`b1e856d`](https://github.com/langchain-ai/langgraphjs/commit/b1e856d987ac16148dc0872d1fecf70e659ef28e) Thanks [@christian-bromann](https://github.com/christian-bromann)! - fix(sdk): apply state update and goto alongside interrupt resume `respond(decision, { update, goto })` now maps to LangGraph's `Command(resume, update, goto)`, so a human-in-the-loop UI can commit a state update (e.g. push the interrupt card into state) in the **same superstep** as the resume — one checkpoint, no separate `updateState` write, no flicker. `@langchain/langgraph-api` forwards `update`/`goto` through `input.respond`, and `@langchain/core` message instances in `update` are serialized to dicts before transport, exactly like `submit()`. Bumps `@langchain/protocol` to `^0.0.18` for the `Goto` type. `respond`/`respondAll` also apply `update` **optimistically** (mirroring `submit()`): the pushed messages paint immediately, with stable ids minted so the resumed run's echo reconciles them in place. Without this the interrupt is cleared the instant `respond()` dispatches while the pushed card only reappears a server round-trip later — so the card would flicker in that gap. The optimistic state settles on the resumed run's terminal (pending → sent, or rolled back on a failure before any echo). User-initiated optimistic writes (`submit()` / `respond()` / `respondAll()`) now commit to the store **synchronously**, in the same tick as the triggering event, instead of being coalesced onto the next macrotask. This lets a framework render the pushed message in the **same commit** as any local UI state the caller flips alongside it (e.g. a HITL form swapping its inputs for the resolved card), so the card no longer blinks out for the one-macrotask window before the flush lands. High-frequency streaming writes keep their macrotask coalescing. - Updated dependencies \[[`b1e856d`](https://github.com/langchain-ai/langgraphjs/commit/b1e856d987ac16148dc0872d1fecf70e659ef28e)]: - @langchain/langgraph-sdk@1.9.24 ## @langchain/svelte@1.0.25 ### Patch Changes - [#2557](https://github.com/langchain-ai/langgraphjs/pull/2557) [`b1e856d`](https://github.com/langchain-ai/langgraphjs/commit/b1e856d987ac16148dc0872d1fecf70e659ef28e) Thanks [@christian-bromann](https://github.com/christian-bromann)! - fix(sdk): apply state update and goto alongside interrupt resume `respond(decision, { update, goto })` now maps to LangGraph's `Command(resume, update, goto)`, so a human-in-the-loop UI can commit a state update (e.g. push the interrupt card into state) in the **same superstep** as the resume — one checkpoint, no separate `updateState` write, no flicker. `@langchain/langgraph-api` forwards `update`/`goto` through `input.respond`, and `@langchain/core` message instances in `update` are serialized to dicts before transport, exactly like `submit()`. Bumps `@langchain/protocol` to `^0.0.18` for the `Goto` type. `respond`/`respondAll` also apply `update` **optimistically** (mirroring `submit()`): the pushed messages paint immediately, with stable ids minted so the resumed run's echo reconciles them in place. Without this the interrupt is cleared the instant `respond()` dispatches while the pushed card only reappears a server round-trip later — so the card would flicker in that gap. The optimistic state settles on the resumed run's terminal (pending → sent, or rolled back on a failure before any echo). User-initiated optimistic writes (`submit()` / `respond()` / `respondAll()`) now commit to the store **synchronously**, in the same tick as the triggering event, instead of being coalesced onto the next macrotask. This lets a framework render the pushed message in the **same commit** as any local UI state the caller flips alongside it (e.g. a HITL form swapping its inputs for the resolved card), so the card no longer blinks out for the one-macrotask window before the flush lands. High-frequency streaming writes keep their macrotask coalescing. - Updated dependencies \[[`b1e856d`](https://github.com/langchain-ai/langgraphjs/commit/b1e856d987ac16148dc0872d1fecf70e659ef28e)]: - @langchain/langgraph-sdk@1.9.24 ## @langchain/vue@1.0.25 ### Patch Changes - [#2557](https://github.com/langchain-ai/langgraphjs/pull/2557) [`b1e856d`](https://github.com/langchain-ai/langgraphjs/commit/b1e856d987ac16148dc0872d1fecf70e659ef28e) Thanks [@christian-bromann](https://github.com/christian-bromann)! - fix(sdk): apply state update and goto alongside interrupt resume `respond(decision, { update, goto })` now maps to LangGraph's `Command(resume, update, goto)`, so a human-in-the-loop UI can commit a state update (e.g. push the interrupt card into state) in the **same superstep** as the resume — one checkpoint, no separate `updateState` write, no flicker. `@langchain/langgraph-api` forwards `update`/`goto` through `input.respond`, and `@langchain/core` message instances in `update` are serialized to dicts before transport, exactly like `submit()`. Bumps `@langchain/protocol` to `^0.0.18` for the `Goto` type. `respond`/`respondAll` also apply `update` **optimistically** (mirroring `submit()`): the pushed messages paint immediately, with stable ids minted so the resumed run's echo reconciles them in place. Without this the interrupt is cleared the instant `respond()` dispatches while the pushed card only reappears a server round-trip later — so the card would flicker in that gap. The optimistic state settles on the resumed run's terminal (pending → sent, or rolled back on a failure before any echo). User-initiated optimistic writes (`submit()` / `respond()` / `respondAll()`) now commit to the store **synchronously**, in the same tick as the triggering event, instead of being coalesced onto the next macrotask. This lets a framework render the pushed message in the **same commit** as any local UI state the caller flips alongside it (e.g. a HITL form swapping its inputs for the resolved card), so the card no longer blinks out for the one-macrotask window before the flush lands. High-frequency streaming writes keep their macrotask coalescing. - Updated dependencies \[[`b1e856d`](https://github.com/langchain-ai/langgraphjs/commit/b1e856d987ac16148dc0872d1fecf70e659ef28e)]: - @langchain/langgraph-sdk@1.9.24 ## @example/ai-elements@0.1.41 ### Patch Changes - Updated dependencies \[[`b1e856d`](https://github.com/langchain-ai/langgraphjs/commit/b1e856d987ac16148dc0872d1fecf70e659ef28e)]: - @langchain/react@1.0.25 - @langchain/langgraph@1.4.5 ## @examples/assistant-ui-claude@0.1.41 ### Patch Changes - Updated dependencies \[[`b1e856d`](https://github.com/langchain-ai/langgraphjs/commit/b1e856d987ac16148dc0872d1fecf70e659ef28e)]: - @langchain/react@1.0.25 - @langchain/langgraph@1.4.5 ## @examples/ui-angular@0.0.51 ### Patch Changes - Updated dependencies \[[`b1e856d`](https://github.com/langchain-ai/langgraphjs/commit/b1e856d987ac16148dc0872d1fecf70e659ef28e)]: - @langchain/langgraph-sdk@1.9.24 - @langchain/angular@1.0.25 - @langchain/langgraph@1.4.5 ## @examples/ui-multimodal@0.0.27 ### Patch Changes - Updated dependencies \[[`b1e856d`](https://github.com/langchain-ai/langgraphjs/commit/b1e856d987ac16148dc0872d1fecf70e659ef28e)]: - @langchain/react@1.0.25 - @langchain/langgraph@1.4.5 ## @examples/ui-react@0.0.27 ### Patch Changes - Updated dependencies \[[`b1e856d`](https://github.com/langchain-ai/langgraphjs/commit/b1e856d987ac16148dc0872d1fecf70e659ef28e)]: - @langchain/langgraph-sdk@1.9.24 - @langchain/react@1.0.25 - @langchain/langgraph@1.4.5 ## langgraph@1.0.45 ### Patch Changes - Updated dependencies \[[`b1e856d`](https://github.com/langchain-ai/langgraphjs/commit/b1e856d987ac16148dc0872d1fecf70e659ef28e)]: - @langchain/langgraph@1.4.5 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