run-models

## Docs - Reference: <https://replicate.com/docs/llms.txt> - OpenAPI schema: <https://api.replicate.com/openapi.json> - MCP server: <https://mcp.replicate.com> - Per-model docs: `https://replicate.com/{owner}/{model}/llms.txt` - Set `Accept: text/markdown` when requesting docs pages for Markdown responses. ## Workflow 1. **Choose the right model** - Search with the API or ask the user. 2. **Get model metadata** - Fetch 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. ## Three ways to get 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. Max 60 seconds. 3. Set an HTTPS webhook URL when creating a prediction, and Replicate will POST to that URL when the prediction completes. ## Guidelines - 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. ## Predictions - A prediction goes through these states: `starting` -> `processing` -> `succeeded` / `failed` / `canceled`. - Official models use `owner/name` format. Community models require `owner/name:version_id`. - The `POST /v1/predictions` endpoint handles both. ## Webhooks - Set `webhook` to an HTTPS URL when creating a prediction. Replicate POSTs the full prediction object when it completes. - Filter events with `webhook_events_filter`: `start`, `output`, `logs`, `completed`. - Validate webhook signatures using the `Webhook-ID`, `Webhook-Timestamp`, and `Webhook-Signature` headers. Get the signing secret from `GET /v1/webhooks/default/secret`. ## Prediction lifetime - Set `lifetime` to auto-cancel predictions that run too long (e.g. `30s`, `5m`, `1h`). Measured from creation time. ## Streaming - Language models that support streaming include a `stream` URL in the response. Use SSE to receive incremental output. ## File handling - Prefer HTTPS URLs for file inputs. Output URLs from one prediction can be passed directly as file inputs to the next model. - Output file URLs expire after 1 hour. Download and store them immediately if you need to keep them. ## Multi-model workflows - Chain models by passing output URLs as file inputs to the next model. - Start all independent predictions in parallel, then collect results. - Output URLs are valid for 1 hour, which is enough for pipeline steps.