[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-tanstack-ai-persistencebuild-prisma-adapter":3,"mdc-2y871u-key":54,"related-org-tanstack-ai-persistencebuild-prisma-adapter":9128,"related-repo-tanstack-ai-persistencebuild-prisma-adapter":9271},{"slug":4,"name":5,"fn":6,"description":7,"org":8,"tags":12,"stars":24,"repoUrl":25,"updatedAt":26,"license":27,"forks":28,"topics":29,"repo":49,"sourceUrl":52,"mdContent":53},"ai-persistencebuild-prisma-adapter","ai-persistence\u002Fbuild-prisma-adapter","build Prisma adapters for TanStack AI persistence","Use when an app already runs Prisma and needs TanStack AI chat persistence — writes a chat-persistence.ts into the app against its existing PrismaClient and schema.prisma. Covers the four models, BigInt timestamps, JSON-as-string columns, upsert-with-empty-update idempotency, and model renaming.",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},"tanstack","TanStack","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Ftanstack.png",[13,17,20,23],{"name":14,"slug":15,"type":16},"Database","database","tag",{"name":18,"slug":19,"type":16},"Prisma","prisma",{"name":21,"slug":22,"type":16},"Persistence","persistence",{"name":10,"slug":9,"type":16},2884,"https:\u002F\u002Fgithub.com\u002FTanStack\u002Fai","2026-07-30T05:53:30.493586",null,269,[30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,9,45,46,47,48],"ai","ai-agents","ai-sdk","anthropic","chatbot","function-calling","gemini","generative-ai","llm","multimodal","openai","react","solidjs","streaming","svelte","tool-calling","typescript","typescript-sdk","vue",{"repoUrl":25,"stars":24,"forks":28,"topics":50,"description":51},[30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,9,45,46,47,48],"🤖 Type-safe, provider-agnostic TypeScript AI SDK for streaming chat, tool calling, agents, and multimodal apps across OpenAI, Anthropic, Gemini, React, Vue, Svelte, and Solid.","https:\u002F\u002Fgithub.com\u002FTanStack\u002Fai\u002Ftree\u002FHEAD\u002Fpackages\u002Fai-persistence\u002Fskills\u002Fai-persistence\u002Fbuild-prisma-adapter","---\nname: ai-persistence\u002Fbuild-prisma-adapter\ndescription: Use when an app already runs Prisma and needs TanStack AI chat persistence — writes a chat-persistence.ts into the app against its existing PrismaClient and schema.prisma. Covers the four models, BigInt timestamps, JSON-as-string columns, upsert-with-empty-update idempotency, and model renaming.\n---\n\n# Prisma Chat Persistence\n\nThe deliverable is **one file in the app** — `src\u002Flib\u002Fchat-persistence.ts` —\nexporting a `ChatPersistence` built from the app's existing `PrismaClient`. Plus\nfour models added to the app's existing `schema.prisma` and a migration created\nwith the app's own `prisma migrate`.\n\nDo not create a package, a second client, a datasource block, a generator, or a\nhand-written SQL migration. The app has those.\n\nRead the **Build Your Own Adapter** guide\n(`docs\u002Fpersistence\u002Fbuild-your-own-adapter.md`) for the store contracts and\ninvariants, and **ai-persistence\u002Fstores** for the shape rules. Every\nstore below mirrors the reference in-memory backend in\n`@tanstack\u002Fai-persistence` (`memory.ts`); the shared conformance testkit is the\nproof.\n\n## 1. Read the app before writing anything\n\n| Find                 | Where to look                                                                  | What it decides                                                 |\n| -------------------- | ------------------------------------------------------------------------------ | --------------------------------------------------------------- |\n| Schema location      | `prisma\u002Fschema.prisma`, or a multi-file `prisma\u002Fschema\u002F` dir                   | Append to the existing file, or add one new `.prisma` file      |\n| Provider             | the `datasource` block                                                         | Whether `Json` is available; nothing else changes               |\n| Client singleton     | `src\u002Flib\u002Fprisma.ts`, `src\u002Fdb.ts`, `globalThis` dev cache                       | What `chat-persistence.ts` imports — never `new PrismaClient()` |\n| Generated client     | the `generator client` block (`output`, `prisma-client-js` vs `prisma-client`) | Where `ChatRun`\u002F`ChatInterrupt` row types come from             |\n| Existing model names | the schema                                                                     | Whether `Message`\u002F`Run` are taken — prefix if so                |\n| Migration flow       | `prisma\u002Fmigrations\u002F`, or `db push` in scripts                                  | `prisma migrate dev` vs `prisma db push`                        |\n\nPrisma 6 and 7 both work: the delegate query API (`findUnique`, `upsert`,\n`update`, `findMany`, `delete`) is unchanged, so it does not matter which\nclient the app generated.\n\n**Never invent a migration path.** Add the models, then have the user run their\nown `npx prisma migrate dev --name chat-persistence` (or `db push`) and\n`prisma generate`.\n\n## 2. Add the models to their schema\n\nIDs are `String`, timestamps are `BigInt` (portable epoch ms — `Int` overflows\nin 2038, `DateTime` forces a conversion at every boundary), JSON payloads are\n`String`. Use `@map`\u002F`@@map` to match the app's database naming.\n\n```prisma\nmodel ChatThread {\n  threadId     String @id @map(\"thread_id\")\n  messagesJson String @map(\"messages_json\")\n  updatedAt    BigInt @map(\"updated_at\")\n\n  @@map(\"chat_threads\")\n}\n\nmodel ChatRun {\n  runId      String  @id @map(\"run_id\")\n  threadId   String  @map(\"thread_id\")\n  status     String\n  startedAt  BigInt  @map(\"started_at\")\n  finishedAt BigInt? @map(\"finished_at\")\n  error      String?\n  usageJson  String? @map(\"usage_json\")\n\n  @@index([threadId, status])\n  @@map(\"chat_runs\")\n}\n\nmodel ChatInterrupt {\n  interruptId  String  @id @map(\"interrupt_id\")\n  runId        String  @map(\"run_id\")\n  threadId     String  @map(\"thread_id\")\n  status       String\n  requestedAt  BigInt  @map(\"requested_at\")\n  resolvedAt   BigInt? @map(\"resolved_at\")\n  payloadJson  String  @map(\"payload_json\")\n  responseJson String? @map(\"response_json\")\n\n  @@index([threadId, requestedAt])\n  @@map(\"chat_interrupts\")\n}\n\nmodel ChatMetadata {\n  namespace String\n  key       String\n  valueJson String @map(\"value_json\")\n\n  @@id([namespace, key])\n  @@map(\"chat_metadata\")\n}\n```\n\nRename models freely to fit the app — the store code below is the only thing\nthat references them. Extra app-owned fields (a `userId`, audit columns) are\nfine as long as they are optional or defaulted, so the stores' creates still\nsucceed. `namespace` is the `MetadataStore` first argument; the stock SQL in\nthe guide calls the same column `scope`.\n\nOn **Postgres or MySQL** you can switch the `*Json` fields to Prisma's `Json`\ntype and drop the `JSON.stringify`\u002F`parse` in the mappers below. Keep `String`\nif the app targets SQLite or if it is multi-provider.\n\n## 3. Write `src\u002Flib\u002Fchat-persistence.ts`\n\nTwo conversions the SQL backends do not need: `BigInt` timestamps in and out,\nand JSON as strings. Everything else is the shared invariant set.\n\n```ts ignore\nimport { defineAIPersistence } from '@tanstack\u002Fai-persistence'\nimport type {\n  ChatInterrupt,\n  ChatRun,\n  Prisma,\n  PrismaClient,\n} from '@prisma\u002Fclient'\nimport type { ModelMessage, TokenUsage } from '@tanstack\u002Fai'\nimport type {\n  ChatPersistence,\n  InterruptRecord,\n  InterruptStatus,\n  InterruptStore,\n  MessageStore,\n  MetadataStore,\n  RunRecord,\n  RunStatus,\n  RunStore,\n} from '@tanstack\u002Fai-persistence'\n\nimport { prisma } from '@\u002Flib\u002Fprisma'\n\n\u002F\u002F Trusts the shape the stores themselves wrote — nothing else writes these\n\u002F\u002F columns.\nfunction parseJson\u003CT>(raw: string): T {\n  return JSON.parse(raw)\n}\n\nconst RUN_STATUSES: ReadonlyArray\u003CRunStatus> = [\n  'running',\n  'completed',\n  'failed',\n  'interrupted',\n]\nconst INTERRUPT_STATUSES: ReadonlyArray\u003CInterruptStatus> = [\n  'pending',\n  'resolved',\n  'cancelled',\n]\n\n\u002F\u002F The column is a plain String, so narrow instead of trusting it.\nfunction toRunStatus(value: string): RunStatus {\n  const status = RUN_STATUSES.find((candidate) => candidate === value)\n  if (!status) throw new Error(`Unknown run status: ${value}`)\n  return status\n}\n\nfunction toInterruptStatus(value: string): InterruptStatus {\n  const status = INTERRUPT_STATUSES.find((candidate) => candidate === value)\n  if (!status) throw new Error(`Unknown interrupt status: ${value}`)\n  return status\n}\n\n\u002F\u002F Records omit absent optionals so they compare cleanly against the reference\n\u002F\u002F in-memory backend.\nfunction mapRun(row: ChatRun): RunRecord {\n  return {\n    runId: row.runId,\n    threadId: row.threadId,\n    status: toRunStatus(row.status),\n    startedAt: Number(row.startedAt),\n    ...(row.finishedAt != null ? { finishedAt: Number(row.finishedAt) } : {}),\n    ...(row.error != null ? { error: row.error } : {}),\n    ...(row.usageJson != null\n      ? { usage: parseJson\u003CTokenUsage>(row.usageJson) }\n      : {}),\n  }\n}\n\nfunction mapInterrupt(row: ChatInterrupt): InterruptRecord {\n  return {\n    interruptId: row.interruptId,\n    runId: row.runId,\n    threadId: row.threadId,\n    status: toInterruptStatus(row.status),\n    requestedAt: Number(row.requestedAt),\n    payload: parseJson\u003CRecord\u003Cstring, unknown>>(row.payloadJson),\n    ...(row.resolvedAt != null ? { resolvedAt: Number(row.resolvedAt) } : {}),\n    ...(row.responseJson != null\n      ? { response: parseJson\u003Cunknown>(row.responseJson) }\n      : {}),\n  }\n}\n\nfunction createMessageStore(db: PrismaClient): MessageStore {\n  return {\n    async loadThread(threadId) {\n      const row = await db.chatThread.findUnique({ where: { threadId } })\n      \u002F\u002F Unknown thread is [], never null.\n      return row ? parseJson\u003CArray\u003CModelMessage>>(row.messagesJson) : []\n    },\n    \u002F\u002F Full overwrite — `messages` is the complete authoritative transcript.\n    async saveThread(threadId, messages) {\n      const messagesJson = JSON.stringify(messages)\n      const updatedAt = BigInt(Date.now())\n      await db.chatThread.upsert({\n        where: { threadId },\n        create: { threadId, messagesJson, updatedAt },\n        update: { messagesJson, updatedAt },\n      })\n    },\n  }\n}\n\nfunction createRunStore(db: PrismaClient): RunStore {\n  return {\n    async get(runId) {\n      const row = await db.chatRun.findUnique({ where: { runId } })\n      return row ? mapRun(row) : null\n    },\n    \u002F\u002F An empty `update` is Prisma's ON CONFLICT DO NOTHING: an existing runId\n    \u002F\u002F comes back untouched, so resume and double-submit are safe.\n    async createOrResume({ runId, threadId, startedAt, status }) {\n      const row = await db.chatRun.upsert({\n        where: { runId },\n        create: {\n          runId,\n          threadId,\n          status: status ?? 'running',\n          startedAt: BigInt(startedAt),\n        },\n        update: {},\n      })\n      return mapRun(row)\n    },\n    \u002F\u002F Patching an unknown runId is a no-op: never throws, never inserts.\n    async update(runId, patch) {\n      const data: Prisma.ChatRunUpdateManyMutationInput = {}\n      if (patch.status !== undefined) data.status = patch.status\n      if (patch.finishedAt !== undefined) {\n        data.finishedAt = BigInt(patch.finishedAt)\n      }\n      if (patch.error !== undefined) data.error = patch.error\n      if (patch.usage !== undefined)\n        data.usageJson = JSON.stringify(patch.usage)\n      if (Object.keys(data).length === 0) return\n\n      await db.chatRun.updateMany({ where: { runId }, data })\n    },\n    \u002F\u002F Optional in the contract; enables reconnect without a client-held run id.\n    async findActiveRun(threadId) {\n      const row = await db.chatRun.findFirst({\n        where: { threadId, status: 'running' },\n        orderBy: { startedAt: 'desc' },\n      })\n      return row ? mapRun(row) : null\n    },\n  }\n}\n\nfunction createInterruptStore(db: PrismaClient): InterruptStore {\n  \u002F\u002F Every listing is ordered by requestedAt ascending.\n  const listWhere = async (where: Prisma.ChatInterruptWhereInput) => {\n    const rows = await db.chatInterrupt.findMany({\n      where,\n      orderBy: { requestedAt: 'asc' },\n    })\n    return rows.map(mapInterrupt)\n  }\n\n  return {\n    \u002F\u002F Insert-if-absent: a duplicate create must never clobber a resolved\n    \u002F\u002F interrupt back to pending.\n    async create(record) {\n      await db.chatInterrupt.upsert({\n        where: { interruptId: record.interruptId },\n        create: {\n          interruptId: record.interruptId,\n          runId: record.runId,\n          threadId: record.threadId,\n          status: 'pending',\n          requestedAt: BigInt(record.requestedAt),\n          payloadJson: JSON.stringify(record.payload),\n          ...(record.response !== undefined\n            ? { responseJson: JSON.stringify(record.response) }\n            : {}),\n        },\n        update: {},\n      })\n    },\n    async resolve(interruptId, response) {\n      await db.chatInterrupt.updateMany({\n        where: { interruptId },\n        data: {\n          status: 'resolved',\n          resolvedAt: BigInt(Date.now()),\n          ...(response !== undefined\n            ? { responseJson: JSON.stringify(response) }\n            : {}),\n        },\n      })\n    },\n    async cancel(interruptId) {\n      await db.chatInterrupt.updateMany({\n        where: { interruptId },\n        data: { status: 'cancelled', resolvedAt: BigInt(Date.now()) },\n      })\n    },\n    async get(interruptId) {\n      const row = await db.chatInterrupt.findUnique({ where: { interruptId } })\n      return row ? mapInterrupt(row) : null\n    },\n    list: (threadId) => listWhere({ threadId }),\n    listPending: (threadId) => listWhere({ threadId, status: 'pending' }),\n    listByRun: (runId) => listWhere({ runId }),\n    listPendingByRun: (runId) => listWhere({ runId, status: 'pending' }),\n  }\n}\n\nfunction createMetadataStore(db: PrismaClient): MetadataStore {\n  return {\n    async get(namespace, key) {\n      const row = await db.chatMetadata.findUnique({\n        where: { namespace_key: { namespace, key } },\n      })\n      return row ? parseJson\u003Cunknown>(row.valueJson) : null\n    },\n    async set(namespace, key, value) {\n      \u002F\u002F JSON.stringify(undefined) is undefined, which Prisma rejects against a\n      \u002F\u002F required column with an opaque error. Fail clearly instead.\n      if (value == null) {\n        throw new TypeError(\n          `Cannot store ${value} for (${namespace}, ${key}) — use delete() to clear metadata.`,\n        )\n      }\n      const valueJson = JSON.stringify(value)\n      await db.chatMetadata.upsert({\n        where: { namespace_key: { namespace, key } },\n        create: { namespace, key, valueJson },\n        update: { valueJson },\n      })\n    },\n    async delete(namespace, key) {\n      await db.chatMetadata.deleteMany({ where: { namespace, key } })\n    },\n  }\n}\n\n\u002F** The four chat state stores backed by the app's Prisma client. *\u002F\nexport const chatPersistence: ChatPersistence = defineAIPersistence({\n  stores: {\n    messages: createMessageStore(prisma),\n    runs: createRunStore(prisma),\n    interrupts: createInterruptStore(prisma),\n    metadata: createMetadataStore(prisma),\n  },\n})\n```\n\nNotes that bite:\n\n- **`updateMany`, not `update`, for patches.** `update` throws\n  `P2025` on a missing row; the contract says a patch to an unknown id is a\n  silent no-op.\n- **`namespace_key`** is Prisma's generated alias for the `@@id([namespace, key])`\n  composite. If you rename the fields, the alias name changes with them.\n- Annotate `ChatPersistence` — bare `AIPersistence` is the all-optional bag and\n  `withPersistence` rejects it. There is no `locks` store: `stores` accepts only\n  those four keys, and coordination is wired separately with `withLocks` (see\n  **ai-core\u002Flocks**).\n- If the app renamed the models, the delegate accessors are **camelCase**\n  (`prisma.chatThread` for `model ChatThread`), and the row types imported from\n  the client are PascalCase.\n\n## 4. Wire it into the chat route\n\n```ts ignore\nimport {\n  chat,\n  chatParamsFromRequest,\n  toServerSentEventsResponse,\n} from '@tanstack\u002Fai'\nimport { openaiText } from '@tanstack\u002Fai-openai'\nimport { withPersistence } from '@tanstack\u002Fai-persistence'\nimport { chatPersistence } from '@\u002Flib\u002Fchat-persistence'\n\nexport async function POST(request: Request) {\n  const params = await chatParamsFromRequest(request)\n  const stream = chat({\n    adapter: openaiText('gpt-5.5'),\n    messages: params.messages,\n    threadId: params.threadId,\n    runId: params.runId,\n    ...(params.resume ? { resume: params.resume } : {}),\n    middleware: [withPersistence(chatPersistence)],\n  })\n  return toServerSentEventsResponse(stream)\n}\n```\n\n`threadId` is a bare string to the stores. **Authorize thread access at the\nroute** — derive the user from the session, never trust a client-supplied id.\n\n## 5. Verify\n\n```ts ignore\nimport { runPersistenceConformance } from '@tanstack\u002Fai-persistence\u002Ftestkit'\nimport { chatPersistence } from '..\u002Fsrc\u002Flib\u002Fchat-persistence'\n\nrunPersistenceConformance('app-prisma', () => chatPersistence)\n```\n\nPoint the client at a throwaway database with the migration applied (a scratch\nSQLite file is enough) and reset it between runs. All four state stores are\nprovided, so pass no `skip` — and `skip` never accepts `'locks'`, which is not\na state store.\n\n## Only if you are publishing this as a package\n\nEverything above assumes the file lives in the app. For a reusable npm adapter,\nthe same store bodies apply, plus:\n\n- **Peer dep** `@prisma\u002Fclient >=6.7.0`. Ship no datasource, generator,\n  connection URL, or prebuilt SQL migration — those stay in the consumer's\n  schema.\n- **Type the client structurally** (a `PrismaClientLike` shape) and read model\n  delegates off it at runtime, so Prisma 6 and 7 clients both satisfy it\n  regardless of where they were generated.\n- **Ship the models as a raw string asset** plus a CLI\n  (`tanstack-ai-prisma-models`) that copies a provider-neutral fragment into the\n  consumer's multi-file schema directory. They then run `prisma migrate`.\n- **Let consumers rename**: `prismaPersistence(prisma, { models: { messages: 'chatMessage' } })`,\n  where map values are the camelCase client accessors. Throw a\n  `PrismaModelError` naming every store whose delegate cannot be found. Keep the\n  field surface and the composite-id alias fixed; database names and extra\n  app-owned fields are theirs.\n- Run `runPersistenceConformance` over a temporary SQLite database generated\n  from the fragment.\n",{"data":55,"body":56},{"name":5,"description":7},{"type":57,"children":58},"root",[59,68,123,128,171,178,477,519,551,557,616,1007,1043,1092,1103,1115,8083,8088,8239,8245,8830,8847,8853,8983,9011,9017,9022,9122],{"type":60,"tag":61,"props":62,"children":64},"element","h1",{"id":63},"prisma-chat-persistence",[65],{"type":66,"value":67},"text","Prisma Chat Persistence",{"type":60,"tag":69,"props":70,"children":71},"p",{},[72,74,80,82,89,91,97,99,105,107,113,115,121],{"type":66,"value":73},"The deliverable is ",{"type":60,"tag":75,"props":76,"children":77},"strong",{},[78],{"type":66,"value":79},"one file in the app",{"type":66,"value":81}," — ",{"type":60,"tag":83,"props":84,"children":86},"code",{"className":85},[],[87],{"type":66,"value":88},"src\u002Flib\u002Fchat-persistence.ts",{"type":66,"value":90}," —\nexporting a ",{"type":60,"tag":83,"props":92,"children":94},{"className":93},[],[95],{"type":66,"value":96},"ChatPersistence",{"type":66,"value":98}," built from the app's existing ",{"type":60,"tag":83,"props":100,"children":102},{"className":101},[],[103],{"type":66,"value":104},"PrismaClient",{"type":66,"value":106},". 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Ship no datasource, generator,\nconnection URL, or prebuilt SQL migration — those stay in the consumer's\nschema.",{"type":60,"tag":8093,"props":9043,"children":9044},{},[9045,9050,9052,9058],{"type":60,"tag":75,"props":9046,"children":9047},{},[9048],{"type":66,"value":9049},"Type the client structurally",{"type":66,"value":9051}," (a ",{"type":60,"tag":83,"props":9053,"children":9055},{"className":9054},[],[9056],{"type":66,"value":9057},"PrismaClientLike",{"type":66,"value":9059}," shape) and read model\ndelegates off it at runtime, so Prisma 6 and 7 clients both satisfy it\nregardless of where they were generated.",{"type":60,"tag":8093,"props":9061,"children":9062},{},[9063,9068,9070,9076,9078,9083],{"type":60,"tag":75,"props":9064,"children":9065},{},[9066],{"type":66,"value":9067},"Ship the models as a raw string asset",{"type":66,"value":9069}," plus a CLI\n(",{"type":60,"tag":83,"props":9071,"children":9073},{"className":9072},[],[9074],{"type":66,"value":9075},"tanstack-ai-prisma-models",{"type":66,"value":9077},") that copies a provider-neutral fragment into the\nconsumer's multi-file schema directory. They then run ",{"type":60,"tag":83,"props":9079,"children":9081},{"className":9080},[],[9082],{"type":66,"value":120},{"type":66,"value":122},{"type":60,"tag":8093,"props":9085,"children":9086},{},[9087,9092,9094,9100,9102,9108],{"type":60,"tag":75,"props":9088,"children":9089},{},[9090],{"type":66,"value":9091},"Let consumers rename",{"type":66,"value":9093},": ",{"type":60,"tag":83,"props":9095,"children":9097},{"className":9096},[],[9098],{"type":66,"value":9099},"prismaPersistence(prisma, { models: { messages: 'chatMessage' } })",{"type":66,"value":9101},",\nwhere map values are the camelCase client accessors. Throw a\n",{"type":60,"tag":83,"props":9103,"children":9105},{"className":9104},[],[9106],{"type":66,"value":9107},"PrismaModelError",{"type":66,"value":9109}," naming every store whose delegate cannot be found. Keep the\nfield surface and the composite-id alias fixed; database names and extra\napp-owned fields are theirs.",{"type":60,"tag":8093,"props":9111,"children":9112},{},[9113,9115,9120],{"type":66,"value":9114},"Run ",{"type":60,"tag":83,"props":9116,"children":9118},{"className":9117},[],[9119],{"type":66,"value":8947},{"type":66,"value":9121}," over a temporary SQLite database generated\nfrom the fragment.",{"type":60,"tag":9123,"props":9124,"children":9125},"style",{},[9126],{"type":66,"value":9127},"html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"items":9129,"total":4496},[9130,9146,9158,9170,9185,9197,9207,9217,9230,9240,9251,9261],{"slug":9131,"name":9131,"fn":9132,"description":9133,"org":9134,"tags":9135,"stars":9143,"repoUrl":9144,"updatedAt":9145},"aggregation","perform data aggregation in TanStack Table","Aggregate TanStack Table columns independently of grouping, including grand totals, caller-selected row totals, multiple keyed aggregations, custom context-based definitions, grouped merges, manual values, and worker constraints.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[9136,9139,9142],{"name":9137,"slug":9138,"type":16},"Data Analysis","data-analysis",{"name":9140,"slug":9141,"type":16},"Frontend","frontend",{"name":10,"slug":9,"type":16},28175,"https:\u002F\u002Fgithub.com\u002FTanStack\u002Ftable","2026-07-30T05:25:59.429787",{"slug":9147,"name":9147,"fn":9148,"description":9149,"org":9150,"tags":9151,"stars":9143,"repoUrl":9144,"updatedAt":9157},"api-not-found","diagnose TanStack Table API errors","Diagnose missing TanStack Table v9 exports, options, state slices, and instance methods. Load before inventing an API when code sees a type error, undefined feature method, absent object key, adapter mismatch, or v8-shaped example.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[9152,9155,9156],{"name":9153,"slug":9154,"type":16},"Debugging","debugging",{"name":9140,"slug":9141,"type":16},{"name":10,"slug":9,"type":16},"2026-07-30T05:26:05.418735",{"slug":9159,"name":9159,"fn":9160,"description":9161,"org":9162,"tags":9163,"stars":9143,"repoUrl":9144,"updatedAt":9169},"cell-selection","select rectangular cell ranges in tables","Select rectangular cell ranges with cellSelectionFeature: two-corner range state keyed by row and column id, mousedown\u002Fmouseenter handlers, selection edges, render-order resolution under pinning, and autoResetCellSelection. Load when ranges widen unexpectedly after sorting or column reordering, when a drag re-renders the whole table, or when building copy-to-clipboard from a selection.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[9164,9165,9166],{"name":9137,"slug":9138,"type":16},{"name":10,"slug":9,"type":16},{"name":9167,"slug":9168,"type":16},"UI Components","ui-components","2026-07-30T05:25:38.403427",{"slug":9171,"name":9171,"fn":9172,"description":9173,"org":9174,"tags":9175,"stars":9143,"repoUrl":9144,"updatedAt":9184},"client-vs-server","manage TanStack Table data pipelines","Choose client or server ownership for filtering, grouping, sorting, expanding, and pagination in TanStack Table v9. Load for manual* flags, mixed pipelines, server counts, or deciding which dataset each row-model stage receives.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[9176,9179,9180,9183],{"name":9177,"slug":9178,"type":16},"Data Pipeline","data-pipeline",{"name":9140,"slug":9141,"type":16},{"name":9181,"slug":9182,"type":16},"Performance","performance",{"name":10,"slug":9,"type":16},"2026-07-30T05:25:45.400104",{"slug":9186,"name":9186,"fn":9187,"description":9188,"org":9189,"tags":9190,"stars":9143,"repoUrl":9144,"updatedAt":9196},"column-faceting","build faceted filter UIs","Build faceted filter UIs with columnFacetingFeature, facetedRowModel, facetedUniqueValues, and facetedMinMaxValues. Load for facet counts, numeric ranges, own-filter exclusion, or server-page facet completeness.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[9191,9194,9195],{"name":9192,"slug":9193,"type":16},"Data Visualization","data-visualization",{"name":9140,"slug":9141,"type":16},{"name":10,"slug":9,"type":16},"2026-07-30T05:25:41.397257",{"slug":9198,"name":9198,"fn":9199,"description":9200,"org":9201,"tags":9202,"stars":9143,"repoUrl":9144,"updatedAt":9206},"column-filtering","implement column filtering in TanStack Table","Filter columns with columnFilteringFeature, filteredRowModel, filterFns, filterMeta, nested-row direction, and manualFiltering. Load for accessor compatibility, controlled filter updaters, fuzzy metadata, or client\u002Fserver ownership.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[9203,9204,9205],{"name":9137,"slug":9138,"type":16},{"name":9140,"slug":9141,"type":16},{"name":10,"slug":9,"type":16},"2026-07-30T05:25:53.391632",{"slug":9208,"name":9208,"fn":9209,"description":9210,"org":9211,"tags":9212,"stars":9143,"repoUrl":9144,"updatedAt":9216},"column-ordering","manage TanStack Table column ordering","Control TanStack Table v9 leaf columnOrder with stable IDs while accounting for pinning regions, visibility, and groupedColumnMode precedence. Load for drag-and-drop columns or rendered order that differs from state.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[9213,9214,9215],{"name":9140,"slug":9141,"type":16},{"name":10,"slug":9,"type":16},{"name":9167,"slug":9168,"type":16},"2026-07-30T05:26:03.37801",{"slug":9218,"name":9218,"fn":9219,"description":9220,"org":9221,"tags":9222,"stars":9143,"repoUrl":9144,"updatedAt":9229},"column-pinning","configure column pinning in TanStack Table","Pin columns into logical start, center, and end regions with columnPinningFeature and renderer-owned sticky CSS. Load for RTL offsets, z-index, backgrounds, overflow, widths, gaps, or overlaps.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[9223,9226,9227,9228],{"name":9224,"slug":9225,"type":16},"CSS","css",{"name":9140,"slug":9141,"type":16},{"name":10,"slug":9,"type":16},{"name":9167,"slug":9168,"type":16},"2026-07-30T05:25:55.377366",{"slug":9231,"name":9231,"fn":9232,"description":9233,"org":9234,"tags":9235,"stars":9143,"repoUrl":9144,"updatedAt":9239},"column-resizing","implement column resizing in TanStack Table","Wire columnResizingFeature, header.getResizeHandler, resize mode and direction, pointer or touch events, and performant CSS-variable updates. Load when resize state changes but widths do not, or large tables resize slowly.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[9236,9237,9238],{"name":9140,"slug":9141,"type":16},{"name":10,"slug":9,"type":16},{"name":9167,"slug":9168,"type":16},"2026-07-30T05:25:51.400011",{"slug":9241,"name":9241,"fn":9242,"description":9243,"org":9244,"tags":9245,"stars":9143,"repoUrl":9144,"updatedAt":9250},"column-sizing","configure column sizing in TanStack Table","Use columnSizingFeature numeric size, minSize, maxSize, getSize, getStart, getAfter, and total-size APIs in table, grid, or flex CSS. Load for auto or percentage misconceptions and sizing\u002Fpinning layout mismatch.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[9246,9247,9248,9249],{"name":9224,"slug":9225,"type":16},{"name":9140,"slug":9141,"type":16},{"name":10,"slug":9,"type":16},{"name":9167,"slug":9168,"type":16},"2026-07-30T05:25:48.703799",{"slug":9252,"name":9252,"fn":9253,"description":9254,"org":9255,"tags":9256,"stars":9143,"repoUrl":9144,"updatedAt":9260},"column-visibility","manage column visibility in TanStack Table","Hide columns with columnVisibilityFeature while rendering visibility-aware header, column, and cell collections. Load when hidden columns remain in the DOM, false-versus-absent state is confused, or enableHiding is misunderstood.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[9257,9258,9259],{"name":9140,"slug":9141,"type":16},{"name":10,"slug":9,"type":16},{"name":9167,"slug":9168,"type":16},"2026-07-30T05:25:47.367943",{"slug":9262,"name":9262,"fn":9263,"description":9264,"org":9265,"tags":9266,"stars":9143,"repoUrl":9144,"updatedAt":9270},"core","build data grids with TanStack Table","Use TanStack Table v9 as a headless data-grid state and row-processing engine. Load for first-table architecture, stable data and columns, row numbering with getDisplayIndex, semantic rendering, framework adapter choice, or deciding what Table owns versus the renderer.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[9267,9268,9269],{"name":9137,"slug":9138,"type":16},{"name":9140,"slug":9141,"type":16},{"name":9167,"slug":9168,"type":16},"2026-07-30T05:25:52.366295",{"items":9272,"total":861},[9273,9291,9306,9321,9334,9346,9358],{"slug":9274,"name":9274,"fn":9275,"description":9276,"org":9277,"tags":9278,"stars":24,"repoUrl":25,"updatedAt":9290},"ai-code-mode","execute sandboxed TypeScript code with LLMs","LLM-generated TypeScript execution in sandboxed environments: createCodeModeTool() with isolate drivers (createNodeIsolateDriver, createQuickJSIsolateDriver, createCloudflareIsolateDriver), codeModeWithSkills() for persistent skill libraries, trust strategies, skill storage (FileSystem, LocalStorage, InMemory, Mongo), client-side execution progress via code_mode:* custom events in useChat.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[9279,9281,9284,9287,9288],{"name":9280,"slug":32,"type":16},"AI SDK",{"name":9282,"slug":9283,"type":16},"Code Execution","code-execution",{"name":9285,"slug":9286,"type":16},"Sandboxing","sandboxing",{"name":10,"slug":9,"type":16},{"name":9289,"slug":46,"type":16},"TypeScript","2026-07-16T06:04:13.597905",{"slug":9292,"name":9292,"fn":9293,"description":9294,"org":9295,"tags":9296,"stars":24,"repoUrl":25,"updatedAt":9305},"ai-core","configure TanStack AI agent features","Entry point for TanStack AI skills. Routes to chat-experience, tool-calling, media-generation, structured-outputs, adapter-configuration, ag-ui-protocol, middleware, locks, custom-backend-integration, and debug-logging, plus the skills shipped by companion packages (@tanstack\u002Fai-persistence, @tanstack\u002Fai-code-mode). Use chat() not streamText(), openaiText() not createOpenAI(), toServerSentEventsResponse() not manual SSE, middleware hooks not onEnd callbacks.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[9297,9300,9302],{"name":9298,"slug":9299,"type":16},"Agents","agents",{"name":9301,"slug":30,"type":16},"AI",{"name":9303,"slug":9304,"type":16},"Middleware","middleware","2026-07-30T05:26:10.404565",{"slug":9307,"name":9308,"fn":9309,"description":9310,"org":9311,"tags":9312,"stars":24,"repoUrl":25,"updatedAt":9320},"ai-coreadapter-configuration","ai-core\u002Fadapter-configuration","configure AI provider adapters","Provider adapter selection and configuration: openaiText, anthropicText, geminiText, ollamaText, grokText, groqText, openRouterText, bedrockText, openaiCompatible. Per-model type safety with modelOptions, reasoning\u002Fthinking configuration, runtime adapter switching, extendAdapter() for custom models, createModel(). Generic OpenAI-compatible providers (DeepSeek, Together, Fireworks, etc.) via openaiCompatible({ baseURL, apiKey, models }) from @tanstack\u002Fai-openai\u002Fcompatible. API key env vars: OPENAI_API_KEY, ANTHROPIC_API_KEY, GOOGLE_API_KEY\u002FGEMINI_API_KEY, XAI_API_KEY, GROQ_API_KEY, OPENROUTER_API_KEY, OLLAMA_HOST, BEDROCK_API_KEY (or AWS_BEARER_TOKEN_BEDROCK).\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[9313,9314,9317,9319],{"name":9280,"slug":32,"type":16},{"name":9315,"slug":9316,"type":16},"Configuration","configuration",{"name":9318,"slug":38,"type":16},"LLM",{"name":10,"slug":9,"type":16},"2026-07-16T06:04:17.82075",{"slug":9322,"name":9323,"fn":9324,"description":9325,"org":9326,"tags":9327,"stars":24,"repoUrl":25,"updatedAt":9333},"ai-coreag-ui-protocol","ai-core\u002Fag-ui-protocol","implement TanStack AI streaming protocol","Server-side AG-UI streaming protocol implementation: StreamChunk event types (RUN_STARTED, TEXT_MESSAGE_START\u002FCONTENT\u002FEND, TOOL_CALL_START\u002FARGS\u002FEND, RUN_FINISHED, RUN_ERROR, STEP_STARTED\u002FSTEP_FINISHED, STATE_SNAPSHOT\u002FDELTA, CUSTOM), toServerSentEventsStream() for SSE format, toHttpStream() for NDJSON format. For backends serving AG-UI events without client packages.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[9328,9331,9332],{"name":9329,"slug":9330,"type":16},"API Development","api-development",{"name":9318,"slug":38,"type":16},{"name":10,"slug":9,"type":16},"2026-07-16T06:04:10.093367",{"slug":9335,"name":9336,"fn":9337,"description":9338,"org":9339,"tags":9340,"stars":24,"repoUrl":25,"updatedAt":9345},"ai-corechat-experience","ai-core\u002Fchat-experience","implement chat experiences with TanStack AI","End-to-end chat implementation: server endpoint with chat() and toServerSentEventsResponse(), client-side useChat hook with fetchServerSentEvents(), message rendering with UIMessage parts, multimodal content, thinking\u002Freasoning display. Covers streaming states, connection adapters, and message format conversions. NOT Vercel AI SDK — uses chat() not streamText().\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[9341,9342,9343,9344],{"name":9329,"slug":9330,"type":16},{"name":9140,"slug":9141,"type":16},{"name":9318,"slug":38,"type":16},{"name":10,"slug":9,"type":16},"2026-07-30T05:26:11.505241",{"slug":9347,"name":9348,"fn":9349,"description":9350,"org":9351,"tags":9352,"stars":24,"repoUrl":25,"updatedAt":9357},"ai-coreclient-persistence","ai-core\u002Fclient-persistence","implement browser chat persistence for TanStack AI","Browser chat persistence on useChat \u002F ChatClient: localStoragePersistence, sessionStoragePersistence, indexedDBPersistence. Client-authoritative (adapter, full transcript) vs server-authoritative (persistence: true, no client cache). Reload restore, pending interrupts, mid-stream rejoin with delivery durability. Use for SPA reload durability — NOT server history alone. No extra package: the adapters ship in the framework packages.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[9353,9354,9355,9356],{"name":9301,"slug":30,"type":16},{"name":9140,"slug":9141,"type":16},{"name":21,"slug":22,"type":16},{"name":10,"slug":9,"type":16},"2026-07-30T05:53:35.503176",{"slug":9359,"name":9360,"fn":9361,"description":9362,"org":9363,"tags":9364,"stars":24,"repoUrl":25,"updatedAt":9371},"ai-corecustom-backend-integration","ai-core\u002Fcustom-backend-integration","integrate custom backends with TanStack AI","Connect useChat to a non-TanStack-AI backend through custom connection adapters. ConnectConnectionAdapter (single async iterable) vs SubscribeConnectionAdapter (separate subscribe\u002Fsend). Customize fetchServerSentEvents() and fetchHttpStream() with auth headers, custom URLs, and request options. Import from framework package, not @tanstack\u002Fai-client.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[9365,9366,9367,9370],{"name":9301,"slug":30,"type":16},{"name":9329,"slug":9330,"type":16},{"name":9368,"slug":9369,"type":16},"Backend","backend",{"name":10,"slug":9,"type":16},"2026-07-17T06:06:39.855351"]