Evidence snapshot reviewed Sep 10, 2026GitHub checked Aug 21, 2026
Evidence-verifiedPlugin BundleAutomation & AgentsWeb Profile

dsh-resume-turn

Resume eligible interrupted DSH model replies from their streamed partial output instead of restarting from zero.

At a glance

What it does

Resume eligible interrupted DSH model replies from their streamed partial output instead of restarting from zero.

Use cases
Automation & AgentsAutomationSession ManagementConfiguration
Works with
Deepseek HarnessDsh Llm Retry
Compatibility

Web Profile
Not declared in supplied evidence

Trust & status

Evidence-verified
Checked Sep 10, 2026, 2:28 PM UTC

Code-evidenced contributions

What it adds to DSH

Agent PresetsInterrupted-turn recovery

Retries eligible interrupted model replies by steering the next request with captured partial output.

Mechanism evidence

Before you choose it

This DSH bundle handles selected mid-stream failures such as TIMEOUT, TRANSPORT, SERVER, and RATE_LIMIT. When partial output exists, it adds a visible auto-resume steering message containing that output and asks the model to continue; otherwise it leaves recovery to the normal retry flow.

Best for

DSH users running slow or unreliable model endpoints who want long replies to continue after a disconnect.

Common tasks

  • Continue a long streamed answer after a transient endpoint failure.
  • Avoid repeating an entire reply when partial output was already generated.
  • Set a per-turn resume limit, eligible failure codes, delay, or quoted-output limit.

Permissions and data

The plugin reads current-attempt session event chunks and places captured partial output into a visible steering message for the next retry.

Permissions
  • Access to DSH request-error and session event flow.
  • Ability to steer a retrying agent turn.
Data handling
  • Captures visible text and reasoning chunks from the interrupted attempt.
  • Quotes up to the configured partial-output limit into the resumed request context.
External services
  • No external service or credential requirement is declared in the supplied evidence.
Credentials
  • None declared.

Limitations

  • It does not resume user-cancelled requests, non-transient failures, failures without partial output, or mid-tool-call interruptions.
  • A continued reply can rephrase text at the interruption boundary.
  • The default budget is three resumes per turn; later recovery falls back to normal retry.
  • A host restart resets in-memory resume budgets and boundaries.

What DSHub checked

  • Pinned Git source and DSH bundle structure were verified.
  • The manifest declares Node.js >=22 and optional DSH peer dependencies.
  • The README documents GitHub installation and configurable recovery behavior.

What DSHub did not check

  • Installation and runtime behavior were not executed.
  • No npm registry package version was found in the supplied evidence.
  • A compatible DSH Harness version range is not declared.

Pinned install

Install dsh-resume-turn

This plugin bundle does not have a DSH Plugin install action. Use its source documentation for the delivery method.

Visit the source project

Maintainer source

Project README

View at commit c31eae7
Maintainer-authored contentCaptured from README.md on Sep 10, 2026. The text and repository-relative media are fixed to commit c31eae726fe7 with content hash f574a198a65d; provider-hosted badges may update independently. README commands are upstream documentation; the DSHub copy action above is the verified, version-pinned install.

dsh-resume-turn

DSH plugin: resume an interrupted reply from its partial output instead of restarting from scratch.

简体中文 · Repository · Issues · MIT

When a model request fails mid-stream on a slow / flaky endpoint (e.g. the AMD DeepSeek endpoint — slow inference, frequent disconnects, TIMEOUT / TRANSPORT / SERVER / RATE_LIMIT), the default dsh-llm-retry rebuilds the same request and re-runs it from zero: everything that had already streamed (including a long thinking chain) is thrown away, and a multi-minute attempt can be repeated several times before giving up.

dsh-resume-turn changes that: at the failure point it collects the partial output that already streamed (visible text + reasoning chunks) from the session event log, injects a visible "auto-resumed" steering message that quotes that partial output and instructs the model to continue from where it stopped, and takes over recovery with { kind: 'retry' } — so the next request starts from the interruption point, not from zero.

How it works

agent/request-error (waterfall)
  ├─ user cancelled?        → delegate (never auto-resume over a user stop)
  ├─ code not transient?    → delegate
  ├─ no partial output?     → delegate (nothing to resume; default retry is right)
  ├─ mid tool-call?         → delegate (restart is safer for tool arguments)
  ├─ resume budget spent (default 3 / turn)? → delegate
  └─ otherwise
       ├─ collect current-attempt chunks (assistant/chunk events after the
       │  last attempt boundary) → partial text + reasoning
       ├─ cancellable backoff (2s, doubling, cap 30s)
       ├─ agent.steer(resume message)   # visible "auto-resumed" row; carries
       │                                 # the partial output + "continue" instruction
       └─ return { kind: 'retry' }      # retry rebuilds the request from the
                                         # surface, which now includes the resume message

Install (one command)

# from GitHub
npx @deepseek-ai/dsh plugin --profile web add github:Harris-Logic/dsh-resume-turn

# or from a local checkout
npx @deepseek-ai/dsh plugin --profile web add /absolute/path/to/dsh-resume-turn

Restart the profile (or the web host) to activate. The package declares dsh.bundle.patch, so the installer appends it to dsh.profile.bundles and its cordis.patch.yml plugin row is applied automatically — no manual file edits. @deepseek-ai/* modules come from the host (the very schemastery / dsh-llm instances DSH itself runs on): they are declared as optional peers and are never installed separately.

Config

The plugin has no required config. Optional keys (in the profile's cordis.patch.yml row config, or as bundle config):

key default meaning
maxResumesPerTurn 3 max auto-resumes per turn; beyond that, default retry takes over
resumeCodes ["TIMEOUT","TRANSPORT","SERVER","RATE_LIMIT"] failure codes eligible for resume
initialDelayMs 2000 backoff before the first resume (doubles per attempt, cap 30s)
maxPartialChars 12000 max characters of partial output quoted into the resume message

Interaction with dsh-llm-retry

  • On providers whose retryPolicy is mode: always (recommended for flaky endpoints; see the A1 config notes), llm-retry consults downstream recovery first — this plugin gets the first refusal. Returning { kind: 'retry' } short-circuits the chain; returning undefined lets llm-retry schedule its own backoff.
  • On mode: normal providers this plugin is only consulted if it is ordered before llm-retry in the waterfall; otherwise the default restart-based retry applies unchanged.

Limitations

  • Resume quotes the partial output into context; the continued answer may rephrase a boundary sentence (mitigated by the "don't repeat" instruction).
  • If the endpoint fails again right after a resume, attempts count against the per-turn budget; after the budget is spent the default retry takes over.
  • A host restart resets in-memory resume budgets/boundaries (no custom session events are appended, so stored logs stay fully readable).

License

MIT

Operate deliberately

Install and manage

Prerequisites and target Profile

Target Web Profile

Delivery Dsh Bundle Git — Harris-Logic/dsh-resume-turn#c31eae726fe744871d97605a890c41b86d0dbcfc

Verify, update, and remove

Show lifecycle commands
Verify
dsh plugin --profile web list

Compatibility and access

Requires Node.js >=22 and DSH host peer modules. Not declared in supplied evidence

Review compatibility evidence

Risk facts

Data Handling

Partial visible text and reasoning chunks are quoted into a new steering message after eligible failures.

Evidence
License

MIT licensed; provided without warranty.

Evidence
Evidence and editorial reviewManifest, Bundle patch, distribution and freshness

Immutable evidence

Review status and source activity

AI reviewed

Use the pinned GitHub bundle path; assess context sensitivity before enabling it because partial model output is inserted into subsequent request context.

AI reviewed Sep 10, 2026, 2:29 PM UTCGitHub facts last checked Sep 10, 2026, 2:29 PM UTC

No material source change has been recorded since this evidence baseline.

Next step

Follow the Plugin installation workflow

Subscribe to material changes for dsh-resume-turn