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FEATURE REQ: Interrupt structured response format #1080

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opened 2026-02-20 17:42:59 -05:00 by yindo · 7 comments
yindo commented 2026-02-20 17:42:59 -05:00
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Originally created by @casparb on GitHub (Dec 2, 2025).

Privileged issue

  • I am a LangGraph maintainer, or was asked directly by a LangGraph maintainer to create an issue here.

Issue Content

When interrupting with interrupt(value: str), users should be able to specify an InputSchema that enforces the format the interrupt can be resumed with.

Expected behaviors:

  • If a resume map is provided and the response format does not match InputSchema, re-raise the interrupt
  • If a null resume is provided and there is one pending interrupt, and the response format does not match, re-raise the interrupt
  • If the response format does match InputSchema, resume the interrupt
Originally created by @casparb on GitHub (Dec 2, 2025). ### Privileged issue - [x] I am a LangGraph maintainer, or was asked directly by a LangGraph maintainer to create an issue here. ### Issue Content When interrupting with `interrupt(value: str)`, users should be able to specify an InputSchema that enforces the format the interrupt can be resumed with. Expected behaviors: - If a resume map is provided and the response format does not match InputSchema, re-raise the interrupt - If a null resume is provided and there is one pending interrupt, and the response format does not match, re-raise the interrupt - If the response format does match InputSchema, resume the interrupt
yindo added the enhancement label 2026-02-20 17:42:59 -05:00
yindo closed this issue 2026-02-20 17:42:59 -05:00
yindo commented 2026-02-20 17:42:59 -05:00
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@kushalgarg101 commented on GitHub (Dec 3, 2025):

Hello there, I am looking to complete this! Could you provide an example, like what input and output should look like! that would be great and really helpful for me.

@kushalgarg101 commented on GitHub (Dec 3, 2025): Hello there, I am looking to complete this! Could you provide an example, like what input and output should look like! that would be great and really helpful for me.
yindo commented 2026-02-20 17:43:00 -05:00
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@casparb commented on GitHub (Dec 3, 2025):

Hi @kushalgarg101, take a look at how structured output is handled in create_agent. Specifically look at the implementation for StructuredResponseT - users should be able to provide a schema in the format of: dict, Pydantic BaseModel, dataclass

@casparb commented on GitHub (Dec 3, 2025): Hi @kushalgarg101, take a look at how structured output is handled in `create_agent`. Specifically look at the implementation for `StructuredResponseT` - users should be able to provide a schema in the format of: dict, Pydantic BaseModel, dataclass
yindo commented 2026-02-20 17:43:00 -05:00
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@vector-one commented on GitHub (Dec 3, 2025):

Hi @casparb, I have worked on similar issues in this repo before. I can create a reliable, working PR for this ASAP. Could I take this issue?

@vector-one commented on GitHub (Dec 3, 2025): Hi @casparb, I have worked on similar issues in this repo before. I can create a reliable, working PR for this ASAP. Could I take this issue?
yindo commented 2026-02-20 17:43:00 -05:00
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@kushalgarg101 commented on GitHub (Dec 3, 2025):

hello aaryan 👋 , I am really looking to work on this, just struggling because i am pretty new to open source contri. So is there a possibility if you could help me please .

@kushalgarg101 commented on GitHub (Dec 3, 2025): hello aaryan 👋 , I am really looking to work on this, just struggling because i am pretty new to open source contri. So is there a possibility if you could help me please .
yindo commented 2026-02-20 17:43:00 -05:00
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@vector-one commented on GitHub (Dec 3, 2025):

Hey @kushalgarg101, welcome to open source! Since this involves some specific schema validation logic within create_agent, I can go ahead and put up the PR to get it fixed quickly.

However, I'll make sure to tag you in the PR and add detailed comments explaining the changes. That way, you can review the code to see exactly how the implementation works for your future contributions. Does that sound good?

@vector-one commented on GitHub (Dec 3, 2025): Hey @kushalgarg101, welcome to open source! Since this involves some specific schema validation logic within create_agent, I can go ahead and put up the PR to get it fixed quickly. However, I'll make sure to tag you in the PR and add detailed comments explaining the changes. That way, you can review the code to see exactly how the implementation works for your future contributions. Does that sound good?
yindo commented 2026-02-20 17:43:00 -05:00
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@kushalgarg101 commented on GitHub (Dec 3, 2025):

@Aaryan-549 alright that sounds good and it would definitely help me to learn, thank you!

@kushalgarg101 commented on GitHub (Dec 3, 2025): @Aaryan-549 alright that sounds good and it would definitely help me to learn, thank you!
yindo commented 2026-02-20 17:43:00 -05:00
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@sydney-runkle commented on GitHub (Jan 9, 2026):

Closing as a dupe of https://github.com/langchain-ai/langgraph/issues/5027

@sydney-runkle commented on GitHub (Jan 9, 2026): Closing as a dupe of https://github.com/langchain-ai/langgraph/issues/5027
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Reference: langchain-ai/langgraph#1080
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