fal-ai_skill

Overview

This skill connects your app to fal.ai's serverless AI platform for generating images, video, and audio. It exposes fast, production-ready models (Flux, SDXL, Kling) and supports image editing, inpainting, background removal, upscaling, and real-time streaming. Use it to add serverless, low-latency generative features without managing GPUs.

How this skill works

It calls fal.ai model endpoints via the serverless client to subscribe, stream, queue, or proxy requests. You send a prompt and optional assets (images, masks, control images) and receive URLs or streamed events with generated results. It supports model selection, size presets, inference tuning (steps, guidance, scheduler), and webhook or queue workflows for long-running jobs.

When to use it

• Add real-time image generation or previews in interactive apps
• Build serverless image-to-image editing and inpainting pipelines
• Generate short procedural videos or convert images to video
• Integrate background removal, face-swap, or upscaling into media workflows
• Offload heavy model inference to a managed, low-latency backend

Best practices

• Keep API keys server-side; use the proxy route for browser clients
• Choose model based on latency/quality tradeoff (flux/schnell for speed, flux-pro for quality)
• Use streaming for interactive feedback and queue/webhooks for long tasks
• Provide negative_prompt and guidance_scale to reduce artifacts and control output
• Pass precise image_size presets or explicit width/height for consistent outputs

Example use cases

• User-upload portrait retouching: image-to-image with Flux inpainting and upscaler
• Live art app: realtime Flux Schnell streaming for instant previews
• Marketing asset pipeline: generate multiple 16:9 variations with queue submit and webhook callbacks
• Short text-to-video clips: Kling Video for social previews from a text prompt
• Interactive control workflows: use ControlNet conditioning to enforce pose or edges for generated characters