SKILL.md
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- Use the search and collections APIs to find and compare the best models. Do not list all the models via API, as it's basically a firehose.
- Collections are curated by Replicate staff, so they're vetted.
- Official models are in the "official" collection.
- Use official models because they:
- are always running
- have stable API interfaces
- have predictable output pricing
- are maintained by Replicate staff
- If you must use a community model, be aware that it can take a long time to boot.
- You can create always-on deployments of community models, but you pay for model uptime.
Running models
Models take time to run. There are three ways to run a model via API and get its output:
- Create a prediction, store its id from the response, and poll until completion.
- Set a
Prefer: waitheader when creating a prediction for a blocking synchronous response. Only recommended for very fast models.
- Set an HTTPS webhook URL when creating a prediction, and Replicate will POST to that URL when the prediction completes.
Follow these guideliness when running models:
- Use the "POST /v1/predictions" endpoint, as it supports both official and community models.
- Every model has its own OpenAPI schema. Always fetch and check model schemas to make sure you're setting valid inputs. Even popular models change their schemas.
- Validate input parameters against schema constraints (minimum, maximum, enum values). Don't generate values that violate them.
- When unsure about a parameter value, use the model's default example or omit the optional parameter.
- Don't set optional inputs unless you have a reason to. Stick to the required inputs and let the model's defaults do the work.
- Use HTTPS URLs for file inputs whenever possible. You can also send base64-encoded files, but they should be avoided.
- Fire off multiple predictions concurrently. Don't wait for one to finish before starting the next.
- Output file URLs expire after 1 hour, so back them up if you need to keep them, using a service like Cloudflare R2.
- Webhooks are a good mechanism for receiving and storing prediction output.