ai-infrastructure-replicatelisted

# Replicate SDK Patterns > **Quick Guide:** Use the `replicate` npm package to run open-source ML models on serverless GPUs. Use `replicate.run()` for synchronous execution that returns output directly, `replicate.stream()` for SSE-based streaming, or `replicate.predictions.create()` for async background jobs with webhook notifications. Models are referenced as `owner/model` (uses latest version) or `owner/model:version` (pinned). File outputs are `FileOutput` objects implementing `ReadableStream`. Cold starts are expected for infrequently-used models -- use deployments with `min_instances` to keep models warm. --- <critical_requirements> ## CRITICAL: Before Using This Skill > **All code must follow project conventions in CLAUDE.md** (kebab-case, named exports, import ordering, `import type`, named constants) **(You MUST never hardcode API tokens -- always use environment variables via `process.env.REPLICATE_API_TOKEN`)** **(You MUST handle `FileOutput` objects for models that return files -- do not assume outputs are plain strings or URLs)** **(You MUST validate webhooks using `validateWebhook()` from the `replicate` package -- never trust unverified webhook payloads)** **(You MUST account for cold starts when running infrequently-used models -- use deployments for latency-sensitive applications)** **(You MUST specify model versions (`owner/model:version`) in production to ensure reproducible results -- unversioned references use the latest, which can change)** </