Fal ai skill

fal.ai — Image, Video & Audio Generation

Generate images, videos, and audio using fal.ai's model library (600+ models). Covers Python and JavaScript SDKs, model selection, prompt engineering, and production patterns.

Setup

Python:

pip install fal-client

import fal_client
# Requires FAL_KEY environment variable

JavaScript/TypeScript:

npm install @fal-ai/client

import * as fal from "@fal-ai/client";
// Requires FAL_KEY environment variable

Models — Quick Reference

Image Generation

Model	ID	Speed	Best For
Flux Pro v1.1	fal-ai/flux-pro/v1.1	~3-6s	Production images
Flux Pro Ultra	fal-ai/flux-pro/v1.1-ultra	~8-12s	Maximum detail
Flux Schnell	fal-ai/flux/schnell	~1-4s	Fast prototyping
Flux Dev	fal-ai/flux/dev	~3-5s	Balanced quality/speed

Video Generation

Model	ID	Best For
Kling 1.6 T2V	fal-ai/kling-video/v1.6/standard/text-to-video	Text to video
Kling 1.6 I2V	fal-ai/kling-video/v1.6/standard/image-to-video	Animate a still image
Kling 2.6 Pro	fal-ai/kling-video/v2.6/pro/image-to-video	Professional quality

Audio

Model	ID	Best For
ElevenLabs TTS	fal-ai/elevenlabs/tts/multilingual-v2	Text to speech

Image Generation

Python

result = fal_client.subscribe(
    "fal-ai/flux-pro/v1.1",
    arguments={
        "prompt": "dark figure dissolving into void, motion blur, crushed blacks, cinematic B&W",
        "image_size": "square_hd",
        "num_images": 1,
        "num_inference_steps": 28,
        "guidance_scale": 3.5,
        "enable_safety_checker": False,
    },
)
image_url = result["images"][0]["url"]

JavaScript

const result = await fal.run("fal-ai/flux-pro/v1.1", {
  input: {
    prompt: "dark figure dissolving into void, motion blur, crushed blacks, cinematic B&W",
    image_size: "square_hd",
    num_images: 1,
    num_inference_steps: 28,
    guidance_scale: 3.5,
    enable_safety_checker: false,
  },
});
const imageUrl = result.images[0].url;

Image Size Options

• Presets: square_hd, square, portrait_4_3, portrait_16_9, landscape_4_3, landscape_16_9
• Custom: { "width": 1080, "height": 1350 } (must be multiples of 8)

Parameters

Param	Default	Range	Effect
num_inference_steps	28	10-50	Quality (higher = slower + better)
guidance_scale	3.5	1-10	Prompt adherence (lower = creative)
num_images	1	1-4	Batch size
seed	random	any int	Reproducibility

Video Generation

Image-to-Video (recommended — better quality)

result = fal_client.subscribe(
    "fal-ai/kling-video/v1.6/standard/image-to-video",
    arguments={
        "prompt": "slow camera drift, subtle motion blur, atmospheric",
        "image_url": "https://v3.fal.media/files/...",
        "duration": "5",
        "aspect_ratio": "9:16",
    },
)
video_url = result["video"]["url"]

Text-to-Video

result = fal_client.subscribe(
    "fal-ai/kling-video/v1.6/standard/text-to-video",
    arguments={
        "prompt": "dark figure walking through fog, cinematic slow motion",
        "duration": "5",
        "aspect_ratio": "16:9",
    },
)

Duration & Aspect

• Duration: "5" or "10" seconds (5s produces more focused results)
• Aspect: "16:9", "9:16", "1:1"

File Upload

Upload local files to fal CDN for use in image-to-video or image-to-image:

cdn_url = fal_client.upload_file("path/to/image.png")
# Returns: https://v3.fal.media/files/{prefix}/{id}.{ext}

const cdnUrl = await fal.storage.upload(file);

Async / Queue Pattern

For long-running tasks (video generation), use the queue:

Python

# Submit to queue
handle = fal_client.submit(
    "fal-ai/kling-video/v1.6/standard/image-to-video",
    arguments={...},
)

# Check status
status = fal_client.status("fal-ai/kling-video/v1.6/standard/image-to-video", handle.request_id)

# Get result when done
result = fal_client.result("fal-ai/kling-video/v1.6/standard/image-to-video", handle.request_id)

JavaScript

const handle = await fal.queue.submit("fal-ai/kling-video/v1.6/standard/image-to-video", {
  input: {...},
});

// Stream status updates
for await (const status of fal.queue.streamStatus(handle.request_id)) {
  console.log(status);
}

const result = await fal.queue.result(handle.request_id);

Webhook Pattern

fal_client.subscribe(
    "fal-ai/flux-pro/v1.1",
    arguments={...},
    webhook_url="https://your-server.com/webhook/fal",
)
# Server receives POST with:
# Header: X-Fal-Webhook-Signature (verify for security)
# Body: { "request_id": "...", "status": "OK", "result": {...} }

Timeout & Error Handling

Python — Timeout Wrapper

import concurrent.futures

def fal_with_timeout(model, arguments, timeout=300):
    with concurrent.futures.ThreadPoolExecutor(max_workers=1) as executor:
        future = executor.submit(fal_client.subscribe, model, arguments=arguments)
        try:
            return future.result(timeout=timeout)
        except concurrent.futures.TimeoutError:
            raise TimeoutError(f"fal.ai {model} timed out after {timeout}s")

Error Types

try:
    result = fal_client.subscribe(model, arguments=args)
except fal_client.ValidationError:
    # Content policy violation or bad params — don't retry
    pass
except fal_client.RateLimitError:
    # Too many requests — exponential backoff
    import time, random
    time.sleep((2 ** attempt) + random.uniform(0, 1))
except fal_client.FalClientTimeoutError:
    # Timeout — may be transient, retry
    pass

The platform auto-retries up to 10 times on 503/504/connection errors.

Rate Limits

• New accounts: 2 concurrent requests
• Scales up to 40 as you purchase credits
• Requests exceeding the limit are queued automatically

Prompt Engineering

Structure

[Subject] + [Environment/Mood] + [Style] + [Technical/Camera]

Example

dark figure dissolving into void, motion blur and ghosting,
crushed blacks and high contrast | moody electronic aesthetic |
wide frame from waist up | 28mm lens, cinematic, B&W editorial

Tips

• Keep under 100 words — every word should serve a purpose
• Be specific about lighting: "golden hour", "dramatic side lighting", "soft diffused"
• Style modifiers: "cinematic", "photorealistic", "editorial", "minimalist"
• Camera language: "28mm lens", "macro", "aerial view", "shallow depth of field"
• Flux models don't support negative_prompt — describe what you want, not what to avoid

Response Structure

Image

{
  "images": [{ "url": "https://v3.fal.media/...", "width": 1024, "height": 1024 }],
  "seed": 12345
}

Video

{
  "video": { "url": "https://v3.fal.media/...", "content_type": "video/mp4" }
}

CDN URLs persist and are reusable across requests.