Fal AI Model Search & Integration
Guide for searching and integrating Fal AI models from fal.ai platform.
Workflow
1. Search Models
When user wants to find a model, use WebFetch to search:
https://fal.ai/explore/search?q=<search-query>
Process:
- Parse search results - look for model IDs in format (e.g., , )
- Extract: model ID, category (text-to-image, image-to-image, etc.), description
- Present the found models to the user with:
- Model name and category
- Description
- Playground link:
https://fal.ai/models/<full-model-id>
https://fal.ai/models/xai/<model>
https://fal.ai/models/fal-ai/<model>
- Wait for user confirmation on which model to use
Important: The full Model ID format depends on the model namespace:
| Search Result | Full Model ID | API Endpoint |
|---|
| | https://fal.run/xai/grok-imagine-image
|
bytedance/seedream/v4.5/...
| fal-ai/bytedance/seedream/v4.5/...
| https://fal.run/fal-ai/bytedance/seedream/v4.5/...
|
| | https://fal.run/fal-ai/flux-1/schnell
|
Rule: models use their ID directly; all others need
prefix.
2. Get Model Details
Once user confirms a model, fetch its detailed information:
URL Pattern Rules:
| Model Prefix | llms.txt URL | Playground URL | Full Model ID |
|---|
| https://fal.ai/models/xai/<name>/llms.txt
| https://fal.ai/models/xai/<name>
| |
| Others | https://fal.ai/models/fal-ai/<id>/llms.txt
| https://fal.ai/models/fal-ai/<id>
| |
Rule: If model ID starts with
, do NOT prepend
. For all other models, prepend
.
Examples:
- → llms.txt:
.../models/xai/grok-imagine-image/llms.txt
.../models/xai/grok-imagine-image
bytedance/seedream/v4.5/text-to-image
.../models/fal-ai/bytedance/seedream/v4.5/text-to-image/llms.txt
.../models/fal-ai/bytedance/seedream/v4.5/text-to-image
When presenting model details to user, always include:
- Model ID
- Playground link: For interactive testing
- API endpoint:
https://fal.run/<full-model-id>
- Documentation links: llms.txt, API docs (
https://fal.ai/models/<full-model-id>/api
Process:
- Parse the llms.txt content for:
- Model capabilities and use cases
- API endpoint and parameters
- Code examples
- Pricing information
- Present the key details to the user
- Confirm integration approach with user
3. Integration Guidelines
When integrating a Fal AI model:
- Check existing Fal client setup in the project
- Use the model ID returned from search (format: )
- Follow the API patterns shown in the llms.txt examples
- Add proper error handling for API calls
4. User Confirmation Points
Always confirm with user at these stages:
- After search results: "Found these models: [list with links]. Which one would you like to use?"
- After model details: "Here are the details for [model] ([playground link]). Shall I proceed with integration?"
- Before code changes: "I'll integrate [model] by [changes]. Does this look correct?"
Link format for presentation:
- Use markdown format:
- Always include the model's playground link so users can test it interactively
Common Model Patterns
| Model Type | Example IDs | Use Case |
|---|
| Text to Image | , | Generate images from text |
| Image to Image | , xai/grok-imagine-image/edit
| Transform existing images |
| Video | , | Generate video content |
| Audio | , | Text-to-speech, audio generation |
Example Output Format
When presenting search results to the user, use this format:
Found 3 models matching "flux":
1. **fal-ai/flux-schnell** (Text to Image)
- Fastest Flux model for high-quality image generation
- [Playground](https://fal.ai/models/fal-ai/flux-schnell) | [API Docs](https://fal.ai/models/fal-ai/flux-schnell/api)
2. **fal-ai/flux-pro/v1.1** (Text to Image)
- Professional-grade image generation with superior quality
- [Playground](https://fal.ai/models/fal-ai/flux-pro/v1.1) | [API Docs](https://fal.ai/models/fal-ai/flux-pro/v1.1/api)
Which model would you like to use?
Error Handling
| Error | Cause | Solution |
|---|
| No search results | Query too specific or no matching models | Suggest broader search terms or alternative keywords |
| Model not found (404) | Wrong URL pattern | Check if model starts with → use URL; otherwise use |
| llms.txt returns empty | Model deprecated or unavailable | Inform user the model may be deprecated; suggest alternatives |
| API key error (401) | Missing or invalid | Check environment variable or prompt user to set |
| Rate limit (429) | Too many requests | Implement exponential backoff; suggest retry after delay |
| Timeout | Model inference taking too long | For async models, use pattern with polling |
Notes
- The endpoint returns machine-readable documentation optimized for LLMs
- Model IDs can have various prefixes: , , etc. - always use the full ID from search results
- Always present options to the user before making integration decisions