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\n \n \n \n\n",[19,86],"22a313ae-a4e0-42d6-ba4e-128ae672019c","favicon.svg","019f5787-9e56-744c-a7c0-efd159402223",12,["D",1783891090793],"\n\n",[19,93],"f9b77a82-fdfb-4b04-9d38-2ab5b1b6dfe3","components","019f5787-9e56-744c-a7c0-e8da824a838c",["D",1783879933383],0,"directory",[19,100],"cd2f3e6a-3d8f-41a1-be95-898eeb8449f8",["D",1783879933383],[19],{"_36":106,"_13":19,"_66":69,"_68":-5,"_70":71,"_72":77,"_74":75,"_38":166,"_17":103,"_78":104,"_80":-5,"_82":51,"_83":-5,"_122":167,"_18":168},{"_36":150,"_13":151,"_66":152,"_68":-5,"_70":71,"_72":153,"_74":75,"_38":154,"_17":103,"_78":104,"_80":-5,"_82":51,"_83":-5,"_122":155,"_18":156},{"_36":142,"_13":143,"_66":144,"_68":-5,"_70":71,"_72":145,"_74":75,"_38":146,"_17":103,"_78":24,"_80":147,"_82":51,"_83":-5,"_122":148,"_18":149},{"_36":134,"_13":135,"_66":136,"_68":-5,"_70":71,"_72":137,"_74":75,"_38":138,"_17":34,"_78":24,"_80":139,"_82":51,"_83":-5,"_122":140,"_18":141},{"_36":125,"_13":126,"_66":127,"_68":-5,"_70":71,"_72":128,"_74":75,"_38":129,"_17":34,"_78":130,"_80":131,"_82":51,"_83":-5,"_122":132,"_18":133},{"_36":115,"_13":116,"_66":117,"_68":-5,"_70":71,"_72":118,"_74":75,"_38":119,"_17":77,"_78":120,"_80":121,"_82":51,"_83":-5,"_122":123,"_18":124},"63da0a9b-5186-455a-aac1-237d96141c49","worker.ts","72ade53e-7e1d-11f1-a961-1607ee4eb77e",13,["D",1783891091086],"interval","import { runWorker } from \"./lib/batch.ts\";\n\ntype IntervalEvent = {\n lastRunAt?: Date;\n};\n\nexport default async function (_interval: IntervalEvent) {\n const result = await runWorker();\n console.log(result);\n return result;\n}\n","children",[],[116],"380b5781-a420-4a52-8f8a-a8a3223fa180","index.ts","019f5787-9e56-744c-a7c1-0231b454a6bb",14,["D",1783891091117],"http","import { parseVal, serveFile } from \"https://esm.town/v/std/utils/index.ts\";\nimport {\n getOAuthUserData,\n oauthMiddleware,\n} from \"https://esm.town/v/std/oauth/middleware.ts\";\nimport { Hono } from \"npm:hono\";\nimport {\n cancelJob,\n fileResponse,\n listJobs,\n queueJob,\n refreshJob,\n} from \"./lib/batch.ts\";\n\nconst app = new Hono();\nconst OWNER = \"khxu\";\n\nasync function requireOwner(request: Request) {\n const session = await getOAuthUserData(request);\n if (!session?.user) return { error: \"login\" as const };\n if (session.user.username !== OWNER) return { error: \"forbidden\" as const };\n return { session };\n}\n\napp.get(\"/\", async (c) => {\n const auth = await requireOwner(c.req.raw);\n if (\"error\" in auth) {\n return auth.error === \"login\"\n ? c.redirect(\"/auth/login\")\n : c.text(\"Forbidden\", 403);\n }\n return serveFile(\"/frontend/index.html\");\n});\n\napp.get(\"/frontend/**/*\", (c) => serveFile(c.req.path));\napp.get(\"/source\", (c) => c.redirect(parseVal().links.self.val));\n\napp.use(\"/api/*\", async (c, next) => {\n const auth = await requireOwner(c.req.raw);\n if (\"error\" in auth) {\n return c.json(\n {\n error: auth.error === \"login\" ? \"Authentication required\" : \"Forbidden\",\n },\n auth.error === \"login\" ? 401 : 403,\n );\n }\n await next();\n});\n\napp.get(\"/api/session\", async (c) => {\n const session = await getOAuthUserData(c.req.raw);\n return c.json({\n username: session?.user.username,\n storage: {\n free: \"10 MB\",\n pro: \"1 GB\",\n strategy:\n \"Inputs are deleted after submission; results stream from OpenAI.\",\n },\n });\n});\n\napp.get(\"/api/jobs\", async (c) => c.json({ jobs: await listJobs() }));\n\napp.post(\"/api/jobs\", async (c) => {\n const body = await c.req.json<{\n name?: string;\n endpoint?: string;\n jsonl?: string;\n }>();\n if (\n typeof body.endpoint !== \"string\" ||\n typeof body.jsonl !== \"string\"\n ) {\n return c.json({ error: \"endpoint and jsonl are required\" }, 400);\n }\n try {\n const id = await queueJob(body.name ?? \"\", body.endpoint, body.jsonl);\n return c.json({ id }, 201);\n } catch (error) {\n return c.json(\n { error: error instanceof Error ? error.message : String(error) },\n 400,\n );\n }\n});\n\napp.post(\"/api/jobs/:id/refresh\", async (c) => {\n try {\n return c.json({ job: await refreshJob(c.req.param(\"id\")) });\n } catch (error) {\n return c.json(\n { error: error instanceof Error ? error.message : String(error) },\n 400,\n );\n }\n});\n\napp.post(\"/api/jobs/:id/cancel\", async (c) => {\n try {\n await cancelJob(c.req.param(\"id\"));\n return c.json({ ok: true });\n } catch (error) {\n return c.json(\n { error: error instanceof Error ? error.message : String(error) },\n 400,\n );\n }\n});\n\napp.get(\"/api/jobs/:id/:kind\", async (c) => {\n const kind = c.req.param(\"kind\");\n if (kind !== \"output\" && kind !== \"error\") {\n return c.json({ error: \"Unknown file kind\" }, 404);\n }\n try {\n const response = await fileResponse(c.req.param(\"id\"), kind);\n return new Response(response.body, {\n headers: {\n \"Content-Type\": \"application/jsonl\",\n \"Content-Disposition\": `attachment; filename=\"batch-${\n c.req.param(\"id\")\n }-${kind}.jsonl\"`,\n },\n });\n } catch (error) {\n return c.json(\n { error: error instanceof Error ? error.message : String(error) },\n 400,\n );\n }\n});\n\napp.onError((err) => Promise.reject(err));\nexport default oauthMiddleware(app.fetch);\n",[],[126],"6249b39a-e883-4c00-91fd-6d75e32a20fb","README.md","019f5787-9e56-744c-a7c0-ffd51944028f",9,["D",1783891090787],"# OpenAI Batch Console\n\nA Val Town dashboard for queueing OpenAI Batch API JSONL files, monitoring batch\nprogress, cancelling jobs, and downloading output/error files.\n\n- Val: https://www.val.town/x/khxu/openai-batch-dashboard\n- Live dashboard: https://khxu--019f57879e56744ca7c10231b454a6bb.web.val.run\n\n## Setup\n\n1. Create an OpenAI API key at https://platform.openai.com/api-keys.\n2. Add it to the val as `OPENAI_API_KEY`.\n3. Log in with Val Town at the HTTP endpoint. Access is restricted to `khxu`.\n4. Paste JSONL, or drag and drop/select one or more JSONL files, then queue the\n batch. Multiple files are combined in selection order.\n\nAdd the OpenAI key here:\n\nhttps://www.val.town/x/khxu/openai-batch-dashboard/environment-variables?key=OPENAI_API_KEY\n\nOptional val environment variables:\n\n- `MAX_BATCH_SUBMISSIONS_PER_RUN` - queued batches submitted per worker run\n (default `3`, maximum `20`).\n- `MAX_QUEUED_FILE_BYTES` - maximum transient JSONL size accepted by the val\n (default `8000000`).\n\n## GitHub and Val Town sync\n\nGitHub is the source of truth. `.github/workflows/deploy.yml` deploys pushes to\n`main` with the Val Town `vt` CLI. `.github/workflows/pull.yml` periodically\ncaptures edits made in the Val Town editor.\n\nCreate a Val Town API key with val read/write scope at:\n\nhttps://www.val.town/settings/api\n\nAdd it to this repository as the `VAL_TOWN_API_KEY` Actions secret:\n\nhttps://github.com/khxu/llm-batch-processor/settings/secrets/actions/new\n\nThe workflows intentionally fail with a clear message until that secret is\nconfigured.\n\n## Storage and rate limits\n\nSQLite stores only job metadata. Blob storage holds input JSONL only while a job\nis queued and deletes it after OpenAI accepts the batch. Output and error files\nare streamed directly from OpenAI, so they do not consume Val Town blob storage.\n\nVal Town blob storage is account-wide: 10 MB on Free and 1 GB on Pro. The\ndefault 8 MB input cap is intentionally conservative. Separate object storage is\nunnecessary for ordinary small/medium batches with a short queue. Use S3/R2 if\nyou need multiple large queued inputs or retained archives.\n\nThe worker runs every 15 minutes. It polls active batches and submits a bounded\nnumber of queued jobs. OpenAI Batch API limits are separate from synchronous API\nlimits; account-specific enqueued-token limits still apply.\n\n## Security\n\nThe UI and APIs use Val Town OAuth and reject users other than `khxu`. The\nOpenAI key remains server-side in Val Town environment variables.\n",[],[135],"6e3ba639-5ff8-42c8-9d6d-4b0fc3f0db40",".vtignore","302d70fc-7e37-11f1-97c2-1607ee4eb77e",16,["D",1783891090825],".github/\n.git/\n",[],[143],"4634d912-1b8b-4830-97a4-f426ebf3c480","lib","c180e23a-f911-407e-b733-64191141d7d4",7,["D",1783880036835],[157],[151],{"_36":158,"_13":159,"_66":160,"_68":152,"_70":71,"_72":161,"_74":75,"_38":162,"_17":34,"_78":79,"_80":163,"_82":51,"_83":-5,"_122":164,"_18":165},"1e65b23d-46b7-4e92-a55a-d890a255a9fe","batch.ts","72bf847e-7e1d-11f1-b856-1607ee4eb77e",11,["D",1783891090914],"import { blob } from \"https://esm.town/v/std/blob/main.ts\";\nimport { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\n\nconst API_BASE = \"https://api.openai.com/v1\";\nconst TERMINAL = new Set([\n \"completed\",\n \"failed\",\n \"expired\",\n \"cancelled\",\n \"failed_local\",\n]);\n\nexport type Job = {\n id: string;\n name: string;\n endpoint: string;\n state: string;\n openai_batch_id: string | null;\n input_file_id: string | null;\n output_file_id: string | null;\n error_file_id: string | null;\n request_total: number;\n request_completed: number;\n request_failed: number;\n input_bytes: number;\n attempts: number;\n last_error: string | null;\n created_at: number;\n updated_at: number;\n};\n\nclass OpenAIError extends Error {\n constructor(public status: number, message: string) {\n super(message);\n }\n}\n\nexport async function ensureSchema() {\n await sqlite.batch([\n `CREATE TABLE IF NOT EXISTS batch_jobs (\n id TEXT PRIMARY KEY,\n name TEXT NOT NULL,\n endpoint TEXT NOT NULL,\n state TEXT NOT NULL,\n openai_batch_id TEXT,\n input_file_id TEXT,\n output_file_id TEXT,\n error_file_id TEXT,\n request_total INTEGER NOT NULL DEFAULT 0,\n request_completed INTEGER NOT NULL DEFAULT 0,\n request_failed INTEGER NOT NULL DEFAULT 0,\n input_bytes INTEGER NOT NULL,\n blob_key TEXT,\n attempts INTEGER NOT NULL DEFAULT 0,\n last_error TEXT,\n created_at INTEGER NOT NULL,\n updated_at INTEGER NOT NULL\n )`,\n `CREATE INDEX IF NOT EXISTS batch_jobs_state_idx\n ON batch_jobs(state, updated_at)`,\n `CREATE TABLE IF NOT EXISTS worker_locks (\n name TEXT PRIMARY KEY,\n locked_until INTEGER NOT NULL\n )`,\n ]);\n}\n\nfunction apiKey() {\n const key = Deno.env.get(\"OPENAI_API_KEY\");\n if (!key) throw new Error(\"OPENAI_API_KEY is not configured\");\n return key;\n}\n\nasync function openai(path: string, init: RequestInit = {}) {\n const headers = new Headers(init.headers);\n headers.set(\"Authorization\", `Bearer ${apiKey()}`);\n if (\n !(init.body instanceof FormData) &&\n init.body &&\n !headers.has(\"Content-Type\")\n ) {\n headers.set(\"Content-Type\", \"application/json\");\n }\n const response = await fetch(`${API_BASE}${path}`, { ...init, headers });\n if (!response.ok) {\n const text = await response.text();\n throw new OpenAIError(\n response.status,\n `OpenAI ${response.status}: ${text.slice(0, 1000)}`,\n );\n }\n return response;\n}\n\nfunction validateJsonl(jsonl: string, endpoint: string) {\n const bytes = new TextEncoder().encode(jsonl).byteLength;\n const maxBytes = Number(\n Deno.env.get(\"MAX_QUEUED_FILE_BYTES\") ?? 8_000_000,\n );\n if (!jsonl.trim()) throw new Error(\"JSONL input is empty\");\n if (bytes > maxBytes) {\n throw new Error(\n `Input exceeds this val's ${maxBytes.toLocaleString()} byte queue limit`,\n );\n }\n\n const ids = new Set();\n let requests = 0;\n let model: string | undefined;\n for (const [index, line] of jsonl.split(/\\r?\\n/).entries()) {\n if (!line.trim()) continue;\n let item: Record;\n try {\n item = JSON.parse(line);\n } catch {\n throw new Error(`Line ${index + 1} is not valid JSON`);\n }\n if (item.method !== \"POST\") {\n throw new Error(`Line ${index + 1}: method must be POST`);\n }\n if (item.url !== endpoint) {\n throw new Error(`Line ${index + 1}: url must equal ${endpoint}`);\n }\n if (typeof item.custom_id !== \"string\" || !item.custom_id) {\n throw new Error(`Line ${index + 1}: custom_id is required`);\n }\n if (ids.has(item.custom_id)) {\n throw new Error(\n `Line ${index + 1}: duplicate custom_id ${item.custom_id}`,\n );\n }\n ids.add(item.custom_id);\n const itemModel = item.body?.model;\n if (typeof itemModel === \"string\") {\n model ??= itemModel;\n if (model !== itemModel) {\n throw new Error(\n \"All requests in a batch file must use the same model\",\n );\n }\n }\n requests++;\n }\n if (!requests) throw new Error(\"JSONL contains no requests\");\n if (requests > 50_000) {\n throw new Error(\"OpenAI allows at most 50,000 requests per batch\");\n }\n return { bytes, requests };\n}\n\nexport async function queueJob(\n name: string,\n endpoint: string,\n jsonl: string,\n) {\n await ensureSchema();\n if (!endpoint.startsWith(\"/v1/\")) {\n throw new Error(\"Endpoint must start with /v1/\");\n }\n const { bytes, requests } = validateJsonl(jsonl, endpoint);\n const id = crypto.randomUUID();\n const blobKey = `batch-input:${id}`;\n const now = Date.now();\n await blob.set(blobKey, jsonl);\n try {\n await sqlite.execute({\n sql: `INSERT INTO batch_jobs\n (id, name, endpoint, state, request_total, input_bytes, blob_key,\n created_at, updated_at)\n VALUES (?, ?, ?, 'queued', ?, ?, ?, ?, ?)`,\n args: [\n id,\n name.trim() || `Batch ${new Date(now).toLocaleString()}`,\n endpoint,\n requests,\n bytes,\n blobKey,\n now,\n now,\n ],\n });\n } catch (error) {\n await blob.delete(blobKey);\n throw error;\n }\n return id;\n}\n\nexport async function listJobs(): Promise {\n await ensureSchema();\n const result = await sqlite.execute(\n `SELECT id, name, endpoint, state, openai_batch_id, input_file_id,\n output_file_id, error_file_id, request_total, request_completed,\n request_failed, input_bytes, attempts, last_error, created_at, updated_at\n FROM batch_jobs ORDER BY created_at DESC LIMIT 100`,\n );\n return result.rows as unknown as Job[];\n}\n\nexport async function getJob(id: string) {\n await ensureSchema();\n const result = await sqlite.execute({\n sql: \"SELECT * FROM batch_jobs WHERE id = ?\",\n args: [id],\n });\n return result.rows[0] as Record | undefined;\n}\n\nasync function acquireLock() {\n const now = Date.now();\n const result = await sqlite.execute({\n sql: `INSERT INTO worker_locks(name, locked_until)\n VALUES ('batch-worker', ?)\n ON CONFLICT(name) DO UPDATE SET locked_until = excluded.locked_until\n WHERE worker_locks.locked_until < ?`,\n args: [now + 4 * 60_000, now],\n });\n return result.rowsAffected > 0;\n}\n\nasync function updateFromBatch(id: string, batch: any) {\n await sqlite.execute({\n sql: `UPDATE batch_jobs SET state = ?, openai_batch_id = ?,\n input_file_id = ?, output_file_id = ?, error_file_id = ?,\n request_total = ?, request_completed = ?, request_failed = ?,\n last_error = ?, updated_at = ? WHERE id = ?`,\n args: [\n batch.status,\n batch.id,\n batch.input_file_id,\n batch.output_file_id ?? null,\n batch.error_file_id ?? null,\n batch.request_counts?.total ?? 0,\n batch.request_counts?.completed ?? 0,\n batch.request_counts?.failed ?? 0,\n batch.errors ? JSON.stringify(batch.errors).slice(0, 4000) : null,\n Date.now(),\n id,\n ],\n });\n}\n\nasync function submitJob(job: Record) {\n await sqlite.execute({\n sql: `UPDATE batch_jobs SET state = 'submitting',\n attempts = attempts + 1, updated_at = ? WHERE id = ?`,\n args: [Date.now(), job.id],\n });\n try {\n let inputFileId = job.input_file_id as string | null;\n if (!inputFileId) {\n const response = await blob.get(job.blob_key);\n const jsonl = await response.text();\n const form = new FormData();\n form.set(\"purpose\", \"batch\");\n form.set(\n \"file\",\n new File([jsonl], `${job.id}.jsonl`, {\n type: \"application/jsonl\",\n }),\n );\n const uploaded = await openai(\"/files\", {\n method: \"POST\",\n body: form,\n }).then((r) => r.json());\n inputFileId = uploaded.id;\n await sqlite.execute({\n sql: `UPDATE batch_jobs SET input_file_id = ?, updated_at = ?\n WHERE id = ?`,\n args: [inputFileId, Date.now(), job.id],\n });\n }\n const batch = await openai(\"/batches\", {\n method: \"POST\",\n body: JSON.stringify({\n input_file_id: inputFileId,\n endpoint: job.endpoint,\n completion_window: \"24h\",\n metadata: {\n val_job_id: job.id,\n name: job.name.slice(0, 200),\n },\n }),\n }).then((r) => r.json());\n await updateFromBatch(job.id, batch);\n if (job.blob_key) await blob.delete(job.blob_key);\n await sqlite.execute({\n sql: \"UPDATE batch_jobs SET blob_key = NULL WHERE id = ?\",\n args: [job.id],\n });\n } catch (error) {\n const retryable = error instanceof OpenAIError &&\n (error.status === 429 || error.status >= 500);\n await sqlite.execute({\n sql: `UPDATE batch_jobs SET state = ?, last_error = ?, updated_at = ?\n WHERE id = ?`,\n args: [\n retryable ? \"queued\" : \"failed_local\",\n String(error).slice(0, 4000),\n Date.now(),\n job.id,\n ],\n });\n }\n}\n\nexport async function refreshJob(id: string) {\n const job = await getJob(id);\n if (!job) throw new Error(\"Job not found\");\n if (!job.openai_batch_id || TERMINAL.has(job.state)) return job;\n const batch = await openai(`/batches/${job.openai_batch_id}`).then((r) =>\n r.json()\n );\n await updateFromBatch(id, batch);\n return await getJob(id);\n}\n\nexport async function runWorker() {\n await ensureSchema();\n if (!(await acquireLock())) return { skipped: \"worker already running\" };\n\n const stale = Date.now() - 20 * 60_000;\n await sqlite.execute({\n sql: `UPDATE batch_jobs SET state = 'queued',\n last_error = 'Recovered a stale submission', updated_at = ?\n WHERE state = 'submitting' AND updated_at < ?`,\n args: [Date.now(), stale],\n });\n\n const active = await sqlite.execute(\n `SELECT id FROM batch_jobs WHERE openai_batch_id IS NOT NULL\n AND state NOT IN ('completed', 'failed', 'expired', 'cancelled')\n ORDER BY updated_at ASC LIMIT 50`,\n );\n for (const row of active.rows) {\n try {\n await refreshJob(String(row.id));\n } catch (error) {\n await sqlite.execute({\n sql: `UPDATE batch_jobs SET last_error = ?, updated_at = ?\n WHERE id = ?`,\n args: [String(error).slice(0, 4000), Date.now(), row.id],\n });\n }\n }\n\n const limit = Math.max(\n 1,\n Math.min(\n 20,\n Number(Deno.env.get(\"MAX_BATCH_SUBMISSIONS_PER_RUN\") ?? 3),\n ),\n );\n const queued = await sqlite.execute({\n sql: `SELECT * FROM batch_jobs WHERE state = 'queued'\n ORDER BY created_at ASC LIMIT ?`,\n args: [limit],\n });\n for (const job of queued.rows) {\n await submitJob(job as Record);\n }\n await sqlite.execute({\n sql: `UPDATE worker_locks SET locked_until = 0\n WHERE name = 'batch-worker'`,\n });\n return {\n refreshed: active.rows.length,\n submitted: queued.rows.length,\n };\n}\n\nexport async function cancelJob(id: string) {\n const job = await getJob(id);\n if (!job) throw new Error(\"Job not found\");\n if (job.state === \"queued\") {\n if (job.blob_key) await blob.delete(job.blob_key);\n await sqlite.execute({\n sql: `UPDATE batch_jobs SET state = 'cancelled', blob_key = NULL,\n updated_at = ? WHERE id = ?`,\n args: [Date.now(), id],\n });\n return;\n }\n if (!job.openai_batch_id || TERMINAL.has(job.state)) {\n throw new Error(\"Job cannot be cancelled in its current state\");\n }\n const batch = await openai(`/batches/${job.openai_batch_id}/cancel`, {\n method: \"POST\",\n }).then((r) => r.json());\n await updateFromBatch(id, batch);\n}\n\nexport async function fileResponse(\n id: string,\n kind: \"output\" | \"error\",\n) {\n const job = await getJob(id);\n if (!job) throw new Error(\"Job not found\");\n const fileId = kind === \"output\" ? job.output_file_id : job.error_file_id;\n if (!fileId) throw new Error(`${kind} file is not available`);\n return await openai(`/files/${fileId}/content`);\n}\n",[],[151,159],["D",1783879933383],[169,170,171,172],[19],{"_36":99,"_13":100,"_66":101,"_68":69,"_70":71,"_72":77,"_74":75,"_38":182,"_17":103,"_78":104,"_80":-5,"_82":51,"_83":-5,"_122":183,"_18":184},{"_36":92,"_13":93,"_66":94,"_68":69,"_70":71,"_72":95,"_74":75,"_38":179,"_17":77,"_78":24,"_80":97,"_82":51,"_83":-5,"_122":180,"_18":181},{"_36":85,"_13":86,"_66":87,"_68":69,"_70":71,"_72":88,"_74":75,"_38":176,"_17":77,"_78":24,"_80":90,"_82":51,"_83":-5,"_122":177,"_18":178},{"_36":64,"_13":65,"_66":67,"_68":69,"_70":71,"_72":73,"_74":75,"_38":173,"_17":77,"_78":79,"_80":81,"_82":51,"_83":-5,"_122":174,"_18":175},["D",1783891090820],[],[19,65],["D",1783880036514],[],[19,86],["D",1783891090793],[],[19,93],["D",1783879933383],[185,186],[19,100],{"_36":194,"_13":195,"_66":196,"_68":101,"_70":71,"_72":32,"_74":75,"_38":197,"_17":34,"_78":79,"_80":198,"_82":51,"_83":-5,"_122":199,"_18":200},{"_36":187,"_13":188,"_66":189,"_68":101,"_70":71,"_72":77,"_74":75,"_38":190,"_17":103,"_78":79,"_80":191,"_82":51,"_83":-5,"_122":192,"_18":193},"ce3c17da-0999-4264-83a6-f685d25a1e88","Counter.tsx","019f5787-9e56-744c-a7c0-e45d18af04cf",["D",1783879933383],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport { useState } from \"https://esm.sh/react@18.2.0\";\n\nexport function Counter() {\n const [count, setCount] = useState(0);\n return (\n

\n Clicked\n setCount((c) => c + 1)}\n class=\"bg-blue-500 hover:bg-blue-600 text-white font-medium px-4 py-2 rounded-lg transition-colors cursor-pointer\"\n >\n {count}\n \n times\n

\n );\n}\n",[],[19,100,188],"60dc5e4e-4453-47d8-9613-dd830744670f","App.tsx","019f5787-9e56-744c-a7c0-e2f4ac3695ef",["D",1783891090828],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport {\n type ChangeEvent,\n type DragEvent,\n type FormEvent,\n useEffect,\n useMemo,\n useRef,\n useState,\n} from \"https://esm.sh/react@18.2.0\";\n\ntype Job = {\n id: string;\n name: string;\n endpoint: string;\n state: string;\n openai_batch_id: string | null;\n output_file_id: string | null;\n error_file_id: string | null;\n request_total: number;\n request_completed: number;\n request_failed: number;\n input_bytes: number;\n last_error: string | null;\n created_at: number;\n};\n\nconst sample =\n `{\"custom_id\":\"request-1\",\"method\":\"POST\",\"url\":\"/v1/responses\",\"body\":{\"model\":\"gpt-5-mini\",\"input\":\"Write a one-line greeting.\"}}`;\nconst terminal = new Set([\n \"completed\",\n \"failed\",\n \"expired\",\n \"cancelled\",\n \"failed_local\",\n]);\n\nasync function api(path: string, init?: RequestInit) {\n const response = await fetch(path, {\n ...init,\n headers: {\n \"Content-Type\": \"application/json\",\n ...init?.headers,\n },\n });\n const data = await response.json();\n if (!response.ok) {\n throw new Error(data.error ?? `Request failed (${response.status})`);\n }\n return data;\n}\n\nfunction badge(state: string) {\n if (state === \"completed\") {\n return \"bg-emerald-100 text-emerald-800\";\n }\n if ([\"failed\", \"expired\", \"failed_local\"].includes(state)) {\n return \"bg-red-100 text-red-800\";\n }\n if ([\"queued\", \"submitting\"].includes(state)) {\n return \"bg-amber-100 text-amber-800\";\n }\n return \"bg-blue-100 text-blue-800\";\n}\n\nexport function App() {\n const [jobs, setJobs] = useState([]);\n const [name, setName] = useState(\"\");\n const [endpoint, setEndpoint] = useState(\"/v1/responses\");\n const [jsonl, setJsonl] = useState(sample);\n const [fileNames, setFileNames] = useState([]);\n const [dragging, setDragging] = useState(false);\n const [busy, setBusy] = useState(false);\n const [message, setMessage] = useState(\"\");\n const fileInput = useRef(null);\n const dragDepth = useRef(0);\n\n const activeCount = useMemo(\n () => jobs.filter((job) => !terminal.has(job.state)).length,\n [jobs],\n );\n\n async function load() {\n try {\n setJobs((await api(\"/api/jobs\")).jobs);\n } catch (error) {\n setMessage(String(error));\n }\n }\n\n useEffect(() => {\n load();\n const timer = setInterval(load, 30_000);\n return () => clearInterval(timer);\n }, []);\n\n async function loadFiles(files: File[]) {\n if (files.length === 0) return;\n\n setMessage(\"\");\n try {\n const contents = await Promise.all(files.map((file) => file.text()));\n const combined = contents.reduce((result, content) => {\n if (result && !result.endsWith(\"\\n\") && !content.startsWith(\"\\n\")) {\n return `${result}\\n${content}`;\n }\n return result + content;\n }, \"\");\n setJsonl(combined);\n setFileNames(files.map((file) => file.name));\n if (!name && files.length === 1) {\n setName(files[0].name.replace(/\\.(jsonl|ndjson)$/i, \"\"));\n }\n } catch (error) {\n setMessage(\n `Could not read the selected files: ${\n error instanceof Error ? error.message : String(error)\n }`,\n );\n }\n }\n\n function selectFiles(event: ChangeEvent) {\n void loadFiles(Array.from(event.currentTarget.files ?? []));\n event.currentTarget.value = \"\";\n }\n\n function dropFiles(event: DragEvent) {\n event.preventDefault();\n dragDepth.current = 0;\n setDragging(false);\n void loadFiles(Array.from(event.dataTransfer.files));\n }\n\n async function submit(event: FormEvent) {\n event.preventDefault();\n setBusy(true);\n setMessage(\"\");\n try {\n await api(\"/api/jobs\", {\n method: \"POST\",\n body: JSON.stringify({ name, endpoint, jsonl }),\n });\n setName(\"\");\n setMessage(\n \"Queued. The worker submits up to three batches every 15 minutes.\",\n );\n await load();\n } catch (error) {\n setMessage(error instanceof Error ? error.message : String(error));\n } finally {\n setBusy(false);\n }\n }\n\n async function action(id: string, verb: \"refresh\" | \"cancel\") {\n setMessage(\"\");\n try {\n await api(`/api/jobs/${id}/${verb}`, { method: \"POST\" });\n await load();\n } catch (error) {\n setMessage(error instanceof Error ? error.message : String(error));\n }\n }\n\n return (\n

\n OpenAI Batch Console\n

\n Queue, monitor, and download JSONL results.\n

\n \n

\n\n

New batch

\n \n Name\n setName(e.currentTarget.value)}\n placeholder=\"Nightly classification\"\n className=\"mt-1 w-full rounded-lg border border-slate-700 bg-slate-950 px-3 py-2 outline-none focus:border-blue-500\"\n />\n \n \n Endpoint\n setEndpoint(e.currentTarget.value)}\n className=\"mt-1 w-full rounded-lg border border-slate-700 bg-slate-950 px-3 py-2 font-mono text-sm outline-none focus:border-blue-500\"\n />\n \n

\n Batch JSONL\n {\n event.preventDefault();\n dragDepth.current += 1;\n setDragging(true);\n }}\n onDragOver={(event) => event.preventDefault()}\n onDragLeave={() => {\n dragDepth.current = Math.max(0, dragDepth.current - 1);\n if (dragDepth.current === 0) {\n setDragging(false);\n }\n }}\n onDrop={dropFiles}\n className={`mt-1 rounded-lg border-2 border-dashed p-4 text-center transition ${\n dragging\n ? \"border-blue-400 bg-blue-950/40\"\n : \"border-slate-700 bg-slate-950\"\n }`}\n >\n \n

\n Drop one or more JSONL files here\n

\n fileInput.current?.click()}\n className=\"mt-2 rounded-lg border border-slate-600 px-3 py-1.5 text-sm hover:bg-slate-800\"\n >\n Choose files\n \n

\n Multiple files are combined in selection order.\n

\n {fileNames.length > 0 && (\n

\n Loaded {fileNames.length} file{fileNames.length === 1 ? \"\" : \"s\"}:\n {\" \"}\n {fileNames.join(\", \")}\n

\n )}\n {\n setJsonl(e.currentTarget.value);\n setFileNames([]);\n }}\n rows={13}\n spellCheck={false}\n aria-label=\"Batch JSONL content\"\n className=\"mt-3 w-full rounded-lg border border-slate-700 bg-slate-950 px-3 py-2 font-mono text-xs leading-5 outline-none focus:border-blue-500\"\n />\n

\n \n {busy ? \"Queuing...\" : \"Queue batch\"}\n \n \n

\n OpenAI allows up to 50,000 requests and 200 MB per batch. This val\n defaults to an 8 MB transient queue cap to protect Val Town storage.\n

\n \n\n

Jobs

\n {activeCount} active - auto-refreshes every 30 seconds\n

\n \n Reload\n \n

\n {message && (\n

\n {message}\n

\n )}\n

\n {jobs.length === 0 && (\n

\n No batch jobs yet.\n

\n )}\n {jobs.map((job) => (\n \n

{job.name}

\n {job.openai_batch_id ?? job.id}\n

\n \n {job.state}\n \n

\n \n

\n \n {job.request_completed}/{job.request_total} completed\n \n {job.request_failed} failed\n {(job.input_bytes / 1024).toFixed(1)} KB\n {job.endpoint}\n

\n {job.last_error && (\n

\n                    {job.last_error}\n

\n )}\n

\n {!terminal.has(job.state) && job.openai_batch_id && (\n action(job.id, \"refresh\")}\n className=\"rounded-lg border border-slate-700 px-3 py-1.5 hover:bg-slate-800\"\n >\n Refresh status\n \n )}\n {!terminal.has(job.state) && (\n action(job.id, \"cancel\")}\n className=\"rounded-lg border border-red-900 px-3 py-1.5 text-red-300 hover:bg-red-950\"\n >\n Cancel\n \n )}\n {job.output_file_id && (\n \n Download output\n \n )}\n {job.error_file_id && (\n \n Download errors\n \n )}\n

\n ))}\n \n

\n \n View source and remix\n \n

\n \n \n \n );\n}\n",[],[19,100,195],"36e7b776-fb7f-421a-a88c-653cbd1b03d8",["D",1783879933383],"legacyEnvVars","httpPrivacy","description","Submit and monitor OpenAI Batch API 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