Custom bindings

# Vectorize
[[vectorize]]
binding = "VEC"
index_name = "auto"
dimensions = 768
metric = "cosine"

# R2
[[r2_buckets]]
binding = "FILES"
bucket_name = "auto"

# KV
[[kv_namespaces]]
binding = "CACHE"
id = "auto"
title = "my-cache"

# D1
[[d1_databases]]
binding = "MY_DB"
database_id = "auto"
database_name = "my-app-db"

# Queue producer
[[queues.producers]]
binding = "MAILER"
queue = "auto"

# Workers AI (no provisioning needed)
[ai]
binding = "AI"

# Browser Rendering
[browser]
binding = "BROWSER"

# Hyperdrive (cannot use "auto" - provision in CF dashboard first)
[[hyperdrive]]
binding = "PG"
id = "<your-hyperdrive-config-id>"

# Analytics Engine (rare; USAGE_EVENTS is auto-attached)
[[analytics_engine_datasets]]
binding = "EVENTS"
dataset = "my_events"

ASSETS, PLATFORM_WORKER, API_WORKER, APP_NAME, OWNER_USER_ID,
AUTH_JWT_PUBLIC_KEY, AUTH_JWT_ISSUER, AUTH_WORKER_URL,
APP_IDENTITY_TOKEN, APP_OWNER_JWT, INTERNAL_STORAGE_HMAC_SECRET,
USAGE_EVENTS

import { runMigrations } from 'deepspace/worker'

// Inside fetch handler or at module init:
await runMigrations(env.MY_DB, [
  `CREATE TABLE notes (
     id TEXT PRIMARY KEY,
     body TEXT NOT NULL,
     created_at TEXT NOT NULL DEFAULT CURRENT_TIMESTAMP
   );
   CREATE INDEX idx_notes_created ON notes(created_at);`,

  `ALTER TABLE notes ADD COLUMN tags TEXT;`,
])

import { meterAi, meterVectorize, meterUsage } from 'deepspace/worker'

// Workers AI usage
meterAi(env, '@cf/meta/llama-3.1-8b', { inputChars, outputChars })

// Vectorize usage
meterVectorize(env, 'docs', 'query', { vectors: 1, dims: 768, storedCount })

// Generic fallback (Browser Rendering, Hyperdrive, custom kinds)
meterUsage(env, 'browser', { id: 'render', units: 1, count: 1 })