# AI use cases for Loom Flow (banmu123/LoomFlow)

Repo: [banmu123/LoomFlow](https://github.com/banmu123/LoomFlow) | Use cases: 4 | Page: https://dedupedai.com/use-cases/banmu123-loomflow/

LoomFlow is a self-hosted, lightweight AI workflow builder that turns a plain-language description into a runnable workflow on a visual canvas and can publish it as an HTTP API.

This file holds every use case of this repo. Each one starts with a "## " heading and ends with its URL.

- Turn a plain-language idea into a runnable AI workflow: https://dedupedai.com/use-cases/banmu123-loomflow/build-workflow-from-plain-language/
- Publish a finished workflow as an authenticated HTTP API: https://dedupedai.com/use-cases/banmu123-loomflow/publish-workflow-as-api-endpoint/
- Share a runnable workflow page with a client without sign-in: https://dedupedai.com/use-cases/banmu123-loomflow/share-workflow-demo-with-client/
- Find why a workflow run failed and fix it from the trace: https://dedupedai.com/use-cases/banmu123-loomflow/debug-failing-workflow-with-trace/

## How to turn a plain-language idea into a runnable AI workflow with Loom Flow

Repo: [banmu123/LoomFlow](https://github.com/banmu123/LoomFlow) | Difficulty: Intermediate | Time: 45 minutes | Basis: From the README

Describe a multi-step AI process in one sentence and get a workflow on the canvas you can run.

**Who it is for:** An indie developer or content creator who has a recurring AI task in mind but does not want to hand-build nodes first.

**The problem:** Setting up an AI pipeline usually means learning a visual tool, placing nodes, and wiring them before anything runs.

**The outcome:** A generated workflow on the canvas, tuned by hand and executed once with a visible result.

### Steps

1. Run `git clone https://github.com/banmu123/LoomFlow.git && cd LoomFlow && bash scripts/init-env.sh && docker compose up -d` in a terminal
2. Open http://localhost:5000, sign in as admin with the default password, and change the password right away
3. Go to Admin, then Model Settings, then Add Model, and enter your model ID, base URL, and API key
4. In the chat, describe your process in plain language, for example: input a product name, generate selling-point copy, then generate a promo video script
5. Review the generated nodes on the visual canvas, adjust parameters, and run the workflow

### Prompt to paste into your agent

```text
Set up LoomFlow from https://github.com/banmu123/LoomFlow using `bash scripts/init-env.sh` and `docker compose up -d`, then describe the process <process description> in the chat so it generates a workflow. Expected output: a workflow on the canvas with Start and End nodes and the steps from the description. Verify that http://localhost:5000 loads and that the generated workflow appears on the canvas before you report success.
```

### Caveat

The README says the model is added in the admin UI and not through environment keys, so you need your own provider API key before the generated workflow can run.

Risk, credentials: The default admin login is admin with password 123456, so change it on first sign-in and before exposing the server.

Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/

URL: https://dedupedai.com/use-cases/banmu123-loomflow/build-workflow-from-plain-language/

## How to publish a finished workflow as an authenticated HTTP API with Loom Flow

Repo: [banmu123/LoomFlow](https://github.com/banmu123/LoomFlow) | Difficulty: Intermediate | Time: 30 minutes | Basis: From the README

Expose a tested workflow as a POST endpoint that your app or script can call with one API key.

**Who it is for:** A developer who wants to add an AI feature to an existing product and needs a stable endpoint instead of running the canvas by hand.

**The problem:** A workflow that only runs inside a canvas cannot be called from other systems.

**The outcome:** A published workflow endpoint that returns results when called with a Bearer key from curl or another client.

### Steps

1. Build and test the workflow on the canvas until one run succeeds
2. Publish the workflow from the app, which auto-generates your global API key on first publish
3. Copy the API key immediately, because it is shown only once
4. Call the endpoint with `curl -X POST https://your-host/api/publish/{workflowId}/execute -H "Authorization: Bearer ffk_xxxxx" -H "Content-Type: application/json" -d '{"inputs": {"query": "..."}}'` (inferred, check the README)
5. If the key expires, regenerate it on the API Keys page

### Prompt to paste into your agent

```text
Using the LoomFlow repo at https://github.com/banmu123/LoomFlow, publish the workflow <workflowId> and call its execute endpoint with the input <sample input>. Expected output: a JSON response from POST /api/publish/<workflowId>/execute. Verify that the call returns HTTP 200 with the workflow result and that the Authorization header uses your current API key.
```

### Caveat

The README gives the endpoint pattern but not a full list of request fields, so check the inputs your workflow expects before you send the request.

Risk, credentials: One global API key calls every published workflow, so store it in a secret manager and never commit it to code.

Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/

URL: https://dedupedai.com/use-cases/banmu123-loomflow/publish-workflow-as-api-endpoint/

## How to share a runnable workflow page with a client without sign-in with Loom Flow

Repo: [banmu123/LoomFlow](https://github.com/banmu123/LoomFlow) | Difficulty: Intermediate | Time: 30 minutes | Basis: From the README

Send a public link so a client can see the nodes, enter inputs, and run the workflow themselves.

**Who it is for:** A small studio that needs to demo an AI automation to a client or stakeholder who has no account.

**The problem:** Demos stall when the viewer must create an account or install anything before seeing the workflow work.

**The outcome:** A public link where the recipient views the workflow, fills in inputs, and runs it in the browser.

### Steps

1. Open a finished workflow in the app and generate its public share link
2. Test the link in a private browser window to confirm it loads without signing in
3. Send the link to the client along with a short note on which inputs to try
4. Watch the run result and the node-level trace together if the client asks how it works

### Prompt to paste into your agent

```text
In LoomFlow at https://github.com/banmu123/LoomFlow, generate a public share link for the workflow <workflowName>. Expected output: a URL that opens the workflow page without login. Verify by opening the link in a logged-out browser session and running the workflow once with the sample input <sample input>.
```

### Caveat

The README says recipients can run the workflow without signing in, so anything the workflow calls will use your configured models and the cost falls on your account.

Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/

URL: https://dedupedai.com/use-cases/banmu123-loomflow/share-workflow-demo-with-client/

## How to find why a workflow run failed and fix it from the trace with Loom Flow

Repo: [banmu123/LoomFlow](https://github.com/banmu123/LoomFlow) | Difficulty: Intermediate | Time: 30 minutes | Basis: From the README

Use the per-node execution trace and the canvas assistant to locate the failing step and its likely fix.

**Who it is for:** A builder whose workflow returns an error or stalls and who needs to know which node caused it.

**The problem:** A failed multi-step run is hard to diagnose when you only see a final error message.

**The outcome:** A named failing node with its status, duration, and error, plus a root-cause explanation and a suggested fix.

### Steps

1. Run the workflow that is failing and open its execution trace after the run ends
2. Read the timeline to find the node with the error, its duration, and token usage
3. Ask the canvas AI assistant why the run failed and request root cause and fix suggestions
4. Apply the suggested change to the canvas, then run the workflow again

### Prompt to paste into your agent

```text
Using LoomFlow at https://github.com/banmu123/LoomFlow, open the execution trace for the failed run <runId> of workflow <workflowName> and ask the canvas assistant for the root cause. Expected output: the failing node name, its error, and a proposed fix. Verify by re-running the workflow after applying the fix and confirming the trace shows all nodes completed.
```

### Caveat

The assistant's root-cause answer depends on the model you configured, so confirm any suggested fix against the trace before applying it.

Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/

URL: https://dedupedai.com/use-cases/banmu123-loomflow/debug-failing-workflow-with-trace/