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What you can do with Auto Swarm Shadow Adapter

A Python adapter that lets AutoSwarm agentic DAG tasks pause for a human reviewer or a remote worker without blocking parallel branches, with state kept in SQLite.

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AhmadHassan-BTed/AutoSwarm-Shadow-Adapter on GitHub

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What do you want to do?

4 use cases

  • Pause a legal review step for human sign-off

    Park a legal_counsel task for a human reviewer while other DAG branches keep running.

    View prompt
    Use the repo AhmadHassan-BTed/AutoSwarm-Shadow-Adapter with the AutoSwarm session for <target project>. Park the legal_counsel task, then list the pending items in the shadow queue. Expected output: a list of parked tasks with their status and brief. Verify that each parked task shows AWAITING_HUMAN and that no other DAG branch is blocked.

  • Serve a developer seat from a local GPU model

    Connect a local Ollama model to the senior_developer role using shadow-worker.

    View prompt
    Use the repo AhmadHassan-BTed/AutoSwarm-Shadow-Adapter to connect a shadow-worker for the senior_developer role at <server URL> using the Ollama provider with model llama3.3:70b. Expected output: a running worker that reports the tasks it claims and the deliverables it submits. Verify that the worker logged in with the account <username> and that a claimed task reached the submitted state.

  • Fill a QA seat with a remote OpenAI key

    Run a shadow-worker on a separate machine that uses its own OpenAI key for qa_tester tasks.

    View prompt
    Use the repo AhmadHassan-BTed/AutoSwarm-Shadow-Adapter to start a shadow-worker for the qa_tester role on <remote machine> with the openai provider and model gpt-4o. Expected output: the worker's log showing each claimed task and each submitted deliverable. Verify that the key is read from the LOCAL_OPENAI_API_KEY variable and not printed to the log.

  • Plug a private agent into the shadow queue

    Use the ShadowWorker Python class to run your own handler against parked tasks.

    View prompt
    Use the repo AhmadHassan-BTed/AutoSwarm-Shadow-Adapter to build a ShadowWorker with a custom_handler that calls <private model or database> for the <role> role. Expected output: a Python script that runs forever and returns one string per task. Verify that the handler's returned text appears as the deliverable for a parked task.

How to use Auto Swarm Shadow Adapter

  1. Check you have what it needs: A working AutoSwarm install (the README links to HKUDS/AutoSwarm); Python; A SHADOW_JWT_SECRET of at least 32 characters.
  2. Open AhmadHassan-BTed/AutoSwarm-Shadow-Adapter on GitHub and read the README and license.
  3. Set SHADOW_JWT_SECRET to a secret of at least 32 characters, and optionally SHADOW_API_PORT (default 8800), before starting the adapter.
  4. Start an AutoSwarm company session with opc chat --mode company "Build feature X"; the Manager AI assigns work to role seats such as legal_counsel.
  5. Open the React portal on the adapter port, find the parked task in the pending queue, and read the brief.
  6. Attach up to 5 deliverable files (10MB each, 50MB total by default) and submit through the REST API, or send rework_requested if the work needs changes.

These steps come from our top use case, Pause a legal review step for human sign-off, which also has a copy-paste agent prompt.

Auto Swarm Shadow Adapter alternatives · Best AI repos for Work and operations

About this repo

Requirements

  • A working AutoSwarm install (the README links to HKUDS/AutoSwarm)
  • Python
  • A SHADOW_JWT_SECRET of at least 32 characters
  • Access to a local model server (Ollama) or an API key for Anthropic or OpenAI, depending on the use case
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Questions about Auto Swarm Shadow Adapter

What is Auto Swarm Shadow Adapter?

A Python adapter that lets AutoSwarm agentic DAG tasks pause for a human reviewer or a remote worker without blocking parallel branches, with state kept in SQLite. It is an open-source project on GitHub: https://github.com/AhmadHassan-BTed/AutoSwarm-Shadow-Adapter.

Who is Auto Swarm Shadow Adapter for?

Teams running AutoSwarm company workflows who need human sign-off or remote workers in the loop.

What can I do with Auto Swarm Shadow Adapter?

4 use cases so far, for example: Pause a legal review step for human sign-off; Serve a developer seat from a local GPU model; Fill a QA seat with a remote OpenAI key. Each has steps and a copy-paste agent prompt.

What do I need to run Auto Swarm Shadow Adapter?

A working AutoSwarm install (the README links to HKUDS/AutoSwarm); Python; A SHADOW_JWT_SECRET of at least 32 characters; Access to a local model server (Ollama) or an API key for Anthropic or OpenAI, depending on the use case.

What are alternatives to Auto Swarm Shadow Adapter?

Other hot AI repos in Work and operations: AI Job Search, Solidcraft, Fastbrowse, Awesome AI Agent Platforms, Nautilo.

Is Auto Swarm Shadow Adapter safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.