replicate

Docs

• •Reference docs: https://replicate.com/docs/llms.txt
• •HTTP API schema: https://api.replicate.com/openapi.json
• •MCP server: https://mcp.replicate.com
• •Set an Accept: text/markdown header when requesting docs pages to get a Markdown response.

Workflow

Here's a common workflow for using Replicate's API to run a model:

1. •Choose the right model - Search with the API or ask the user
2. •Get model metadata - Fetch model input and output schema via API
3. •Create prediction - POST to /v1/predictions
4. •Poll for results - GET prediction until status is "succeeded"
5. •Return output - Usually URLs to generated content

Choosing models

• •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:

1. •Create a prediction, store its id from the response, and poll until completion.
2. •Set a Prefer: wait header when creating a prediction for a blocking synchronous response. Only recommended for very fast models.
3. •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.
• •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.