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fal.ai integration

AI & Machine Learning · 4 actions · API key auth

Queue-based AI model inference via the fal.ai platform

Put fal.ai to workView fal.ai integration docs

The ModuleX fal.ai integration lets a ModuleX agent operate fal.ai on your behalf, running cancel actions across request to queues, requests and request responses, directly from a plain-English request, using your organization's own fal.ai credentials. No pre-built workflow is required: the agent picks the right fal.ai action for the task.

fal.ai is an ai & machine learning platform. ModuleX adds the agent layer: ask for an outcome and it selects and runs the right fal.ai action. Or, when you want a repeatable process, the composer assembles a fal.ai workflow for you, streaming the nodes onto the canvas as it builds.

Drive fal.ai in plain English

Type what you want. A ModuleX agent picks the right fal.ai action, or chains several, and runs it. No workflow to build.

  • “Adds a request to the queue for asynchronous processing, including specifying a webhook URL for receiving updates”
    resolves toadd_request_to_queue
  • “Cancels a request in the queue to stop a long-running task that is no longer needed”
    resolves tocancel_request
  • “Show me the request responses that match what I describe”
    resolves toget_request_response

What you can automate with fal.ai

  • Add a request to queue on the flyadd_request_to_queue
  • Cancel a request on requestcancel_request
  • Look up a request response on demandget_request_response

fal.ai integration at a glance

Vendorfal.ai
CategoryAI & Machine Learning
Actions available4
AuthenticationAPI key
Uses your own credentialsYes
Works with the assistantYes
Works in the composerYes
Multi-step / tool-chainingYes
Technical referenceView docs
Integration version1.0.0
Last updatedJul 2026

All 4 fal.ai actions

Request to Queues1
add_request_to_queue
Adds a request to the queue for asynchronous processing, including specifying a webhook URL for receiving updates
Requests1
cancel_request
Cancels a request in the queue to stop a long-running task that is no longer needed
Request Responses1
get_request_response
Gets the response of a completed request in the queue to retrieve results of an asynchronous task
Request Status1
get_request_status
Gets the status of a request in the queue to monitor the progress of an asynchronous task

See full parameters and response schemas in the fal.ai integration docs

Two ways to use fal.ai in ModuleX

Ask the assistantType what you want done and a ModuleX agent picks the right fal.ai action and runs it. No workflow to build.
Compose a workflowNeed it to happen every time? Describe the process and the composer wires fal.ai into a repeatable workflow you can run on a schedule, from chat, or as an API.

Connecting fal.ai

API keyfal.ai uses API-key authentication. You provide your own fal.ai secret key; ModuleX encrypts it and scopes it to your organization, so your whole team can use fal.ai without re-authenticating.

Step-by-step setup in the fal.ai docs

Works with fal.ai

Agents often chain fal.ai with these. Connect them once and one agent can use all of them in a single task.

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fal.ai + ModuleX FAQ

  • A ModuleX agent can run any of fal.ai's 4 actions, across request to queues, requests, request responses and request status, from a plain-English request, using your organization's own fal.ai credentials.

Put fal.ai to work in ModuleX.

Put fal.ai to workView technical docs

Connect fal.ai once with your own credentials and let your agent run all 4 actions on demand.

Last updated: Jul 2026Browse all 179 integrations