Maton

fal.ai

Access the fal.ai queue API with managed API key authentication. Run 1000+ AI models including image generation (Flux, SDXL), video generation (Minimax), image upscaling, text-to-speech, and more.

Reference

Submit Request

Submit a request to run a model. Returns immediately with a request ID.

POST /fal-ai/fal-ai/{model-id}
Content-Type: application/json

{
  "prompt": "model-specific parameters",
  ...
}

Response:

{
  "status": "IN_QUEUE",
  "request_id": "3229f185-a99a-48c0-a292-e25bf9baaeba",
  "response_url": "https://queue.fal.run/fal-ai/flux/requests/3229f185-a99a-48c0-a292-e25bf9baaeba",
  "status_url": "https://queue.fal.run/fal-ai/flux/requests/3229f185-a99a-48c0-a292-e25bf9baaeba/status",
  "cancel_url": "https://queue.fal.run/fal-ai/flux/requests/3229f185-a99a-48c0-a292-e25bf9baaeba/cancel",
  "queue_position": 0
}

Check Status

Poll for request status until completion.

GET /fal-ai/fal-ai/{model-id}/requests/{request_id}/status

Response (IN_PROGRESS):

{
  "status": "IN_PROGRESS",
  "request_id": "3229f185-a99a-48c0-a292-e25bf9baaeba"
}

Response (COMPLETED):

{
  "status": "COMPLETED",
  "request_id": "3229f185-a99a-48c0-a292-e25bf9baaeba",
  "metrics": {
    "inference_time": 0.3334658145904541
  }
}

Get Result

Retrieve the completed result.

GET /fal-ai/fal-ai/{model-id}/requests/{request_id}

Response (image generation):

{
  "images": [
    {
      "url": "https://v3b.fal.media/files/...",
      "width": 1024,
      "height": 1024,
      "content_type": "image/jpeg"
    }
  ],
  "timings": {
    "inference": 0.1587670766748488
  },
  "seed": 761506470,
  "prompt": "a tiny cute cat"
}

Cancel Request

Cancel a queued or in-progress request.

PUT /fal-ai/fal-ai/{model-id}/requests/{request_id}/cancel

Flux Schnell (Fast Image Generation)

python <<'EOF'
import urllib.request, os, json

data = json.dumps({
    "prompt": "a serene mountain landscape at sunset",
    "image_size": "landscape_16_9",
    "num_images": 1,
    "num_inference_steps": 4
}).encode()

req = urllib.request.Request('https://api.maton.ai/fal-ai/fal-ai/flux/schnell', data=data, method='POST')
req.add_header('Authorization', f'Bearer {os.environ["MATON_API_KEY"]}')
req.add_header('Content-Type', 'application/json')
print(json.dumps(json.load(urllib.request.urlopen(req)), indent=2))
EOF

Parameters:

  • prompt (required): Text description of the image
  • image_size: square_hd, square, portrait_4_3, portrait_16_9, landscape_4_3, landscape_16_9
  • num_images: Number of images to generate (default: 1)
  • num_inference_steps: Number of steps (default: 4)
  • seed: Random seed for reproducibility

Fast SDXL (Stable Diffusion XL)

python <<'EOF'
import urllib.request, os, json

data = json.dumps({
    "prompt": "a futuristic city skyline at night",
    "negative_prompt": "blurry, low quality",
    "image_size": "landscape_16_9",
    "num_images": 1
}).encode()

req = urllib.request.Request('https://api.maton.ai/fal-ai/fal-ai/fast-sdxl', data=data, method='POST')
req.add_header('Authorization', f'Bearer {os.environ["MATON_API_KEY"]}')
req.add_header('Content-Type', 'application/json')
print(json.dumps(json.load(urllib.request.urlopen(req)), indent=2))
EOF

Parameters:

  • prompt (required): Text description
  • negative_prompt: What to avoid in the image
  • image_size: Output dimensions
  • num_images: Number of images
  • guidance_scale: CFG scale (default: 7.5)
  • num_inference_steps: Number of steps

Clarity Upscaler (Image Upscaling)

python <<'EOF'
import urllib.request, os, json

data = json.dumps({
    "image_url": "https://example.com/image.jpg",
    "scale": 2
}).encode()

req = urllib.request.Request('https://api.maton.ai/fal-ai/fal-ai/clarity-upscaler', data=data, method='POST')
req.add_header('Authorization', f'Bearer {os.environ["MATON_API_KEY"]}')
req.add_header('Content-Type', 'application/json')
print(json.dumps(json.load(urllib.request.urlopen(req)), indent=2))
EOF

Parameters:

  • image_url (required): URL of the image to upscale
  • scale: Upscale factor (2, 4)

Minimax Video Generation

python <<'EOF'
import urllib.request, os, json

data = json.dumps({
    "prompt": "A cat playing with a ball in slow motion"
}).encode()

req = urllib.request.Request('https://api.maton.ai/fal-ai/fal-ai/minimax/video-01', data=data, method='POST')
req.add_header('Authorization', f'Bearer {os.environ["MATON_API_KEY"]}')
req.add_header('Content-Type', 'application/json')
print(json.dumps(json.load(urllib.request.urlopen(req)), indent=2))
EOF

F5-TTS (Text-to-Speech)

python <<'EOF'
import urllib.request, os, json

data = json.dumps({
    "gen_text": "Hello world, this is a test of fal ai text to speech."
}).encode()

req = urllib.request.Request('https://api.maton.ai/fal-ai/fal-ai/f5-tts', data=data, method='POST')
req.add_header('Authorization', f'Bearer {os.environ["MATON_API_KEY"]}')
req.add_header('Content-Type', 'application/json')
print(json.dumps(json.load(urllib.request.urlopen(req)), indent=2))
EOF

Request Status Values

StatusDescription
IN_QUEUERequest received, waiting for runner
IN_PROGRESSModel is processing the request
COMPLETEDProcessing finished, result available
FAILEDProcessing failed (check error details)

Request Headers

HeaderDescription
X-Fal-Request-TimeoutServer-side deadline in seconds
X-Fal-Runner-HintSession affinity for routing
X-Fal-Queue-Prioritynormal (default) or low
X-Fal-No-RetryDisable automatic retries

Resources

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