[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-tanstack-ai-persistencebuild-cloudflare-artifact-store":3,"mdc--52pm4v-key":56,"related-org-tanstack-ai-persistencebuild-cloudflare-artifact-store":13987,"related-repo-tanstack-ai-persistencebuild-cloudflare-artifact-store":14131},{"slug":4,"name":5,"fn":6,"description":7,"org":8,"tags":12,"stars":27,"repoUrl":28,"updatedAt":29,"license":30,"forks":31,"topics":32,"repo":51,"sourceUrl":54,"mdContent":55},"ai-persistencebuild-cloudflare-artifact-store","ai-persistence\u002Fbuild-cloudflare-artifact-store","build Cloudflare artifact storage for AI","Use when a Cloudflare Worker needs durable byte storage for TanStack AI generated media (images, audio, video, transcripts) β€” writes a BlobStore backed by R2 and an ArtifactStore backed by D1 (or KV), composes them onto the generation persistence so withGenerationPersistence persists artifact bytes, and serves them back from a Worker GET route. Includes one-line sketches for S3, GCS, Vercel Blob, Supabase, and a dev filesystem BlobStore.",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},"tanstack","TanStack","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Ftanstack.png",[13,17,20,23,26],{"name":14,"slug":15,"type":16},"Backend","backend","tag",{"name":18,"slug":19,"type":16},"Cloudflare","cloudflare",{"name":21,"slug":22,"type":16},"AI","ai",{"name":24,"slug":25,"type":16},"Storage","storage",{"name":10,"slug":9,"type":16},2884,"https:\u002F\u002Fgithub.com\u002FTanStack\u002Fai","2026-08-02T06:09:09.070849",null,269,[22,33,34,35,36,37,38,39,40,41,42,43,44,45,46,9,47,48,49,50],"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":28,"stars":27,"forks":31,"topics":52,"description":53},[22,33,34,35,36,37,38,39,40,41,42,43,44,45,46,9,47,48,49,50],"πŸ€– 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-cloudflare-artifact-store","---\nname: ai-persistence\u002Fbuild-cloudflare-artifact-store\ndescription: Use when a Cloudflare Worker needs durable byte storage for TanStack AI generated media (images, audio, video, transcripts) β€” writes a BlobStore backed by R2 and an ArtifactStore backed by D1 (or KV), composes them onto the generation persistence so withGenerationPersistence persists artifact bytes, and serves them back from a Worker GET route. Includes one-line sketches for S3, GCS, Vercel Blob, Supabase, and a dev filesystem BlobStore.\n---\n\n# Cloudflare Artifact + Blob Store\n\n`withGenerationPersistence(persistence)` needs only `stores.generationRuns` to track a\ngeneration's lifecycle. Add `stores.artifacts` (metadata) **and** `stores.blobs`\n(the bytes) β€” both, or neither β€” and the middleware also persists the generated\nmedia: image\u002Faudio\u002FTTS\u002Fvideo\u002Ftranscription bytes land at blob key\n`artifacts\u002F\u003CrunId>\u002F\u003CartifactId>`, with an `ArtifactRecord` row describing each.\n\nThe deliverable is **one file in the Worker** β€” e.g.\n`src\u002Flib\u002Fgeneration-persistence.ts` β€” exporting a factory that builds an\n`AIPersistence` from the request's R2 + D1 bindings, plus a GET route that serves\nartifact bytes with `retrieveArtifact` \u002F `retrieveBlob`.\n\nRead the sibling **ai-persistence\u002Fbuild-cloudflare-adapter** skill for the\nper-request-binding rule, `wrangler` config shape, D1 migration workflow, and the\nchat (generation-run\u002Fmessage) side. This skill covers only the two byte-storage stores and\nhow to compose them.\n\n## The two contracts, verbatim\n\nBoth come from `@tanstack\u002Fai-persistence`. `defineBlobStore` \u002F `defineArtifactStore`\ntype an object literal inline (autocomplete + contract checking, no separate\nannotation).\n\n```ts\n\u002F\u002F BlobStore β€” the byte layer. R2 backs it.\ninterface BlobStore {\n put(\n key: string,\n body: BlobBody,\n options?: BlobPutOptions,\n ): Promise\u003CBlobRecord>\n \u002F\u002F metadata + byte accessors; `options.range` reads one slice (for `206`s)\n get(key: string, options?: BlobGetOptions): Promise\u003CBlobObject | null>\n head(key: string): Promise\u003CBlobRecord | null> \u002F\u002F metadata only\n delete(key: string): Promise\u003Cvoid> \u002F\u002F no-op if absent\n list(options?: BlobListOptions): Promise\u003CBlobListPage>\n}\n\n\u002F\u002F ArtifactStore β€” the metadata layer. D1 (or KV) backs it.\ninterface ArtifactStore {\n save(record: ArtifactRecord): Promise\u003Cvoid> \u002F\u002F insert or overwrite\n get(artifactId: string): Promise\u003CArtifactRecord | null>\n list(runId: string): Promise\u003CArray\u003CArtifactRecord>> \u002F\u002F [] when none\n delete(artifactId: string): Promise\u003Cvoid>\n deleteForRun(runId: string): Promise\u003Cvoid>\n}\n```\n\n`BlobBody` is `ReadableStream\u003CUint8Array> | ArrayBuffer | ArrayBufferView |\nstring | Blob`. The non-stream shapes flow straight into `R2Bucket.put`\nunchanged β€” but a `ReadableStream` body does **not**, in the general case:\nworkerd's `put` requires a stream with a known length (a `Response` body or the\nreadable half of a `FixedLengthStream`), and the artifact middleware hands you a\n`TransformStream`-wrapped body whenever it had to cap a fetched body as it\ndrains. Passing that stream to `bucket.put` throws `TypeError: Provided readable\nstream must have a known length`.\n\n**When does that actually happen?** The wrapper only exists to enforce\n`maxArtifactBytes` during the drain, so the middleware applies it only when\nnothing else bounds the transfer:\n\n| Provider response | Body handed to `put` | R2 path |\n| --------------------------------------- | --------------------------------- | ------------------- |\n| `content-length`, no `content-encoding` | untouched, declared length intact | `bucket.put` direct |\n| chunked (no declared length) | wrapped, length-less | multipart |\n| `content-encoding: gzip` | wrapped, length-less | multipart |\n\nA provider CDN normally sends `content-length`, so the first row is the common\ncase and `bucket.put(key, body)` just works. The recipe below is what makes the\nother two rows work: it re-declares the length from\n`BlobPutOptions.expectedLength` when the middleware could vouch for one, and\notherwise streams through a multipart upload (one 8 MiB part at a time β€” flat\nmemory at any artifact size). Write it once and every response shape is\ncovered.\n\n`withGenerationPersistence(persistence, { maxArtifactBytes: false })` drops the\nceiling and the wrapper altogether, so even a chunked reply arrives untouched.\nIt buys nothing extra for R2 (a chunked body has no length to preserve), so\nchoose it on its own merits: no _application_ limit on what an origin can\nstream into your bucket. R2's own limits still apply β€” 5 GiB per single-shot\nput, and 10,000 multipart parts (~80 GiB at the 8 MiB part size below). Keep\nthe cap when `allowInputUrl` lets callers name the URL.\n\n`BlobPutOptions` is\n`{ contentType?, customMetadata?, expectedLength? }`; `BlobGetOptions` is\n`{ range?: { offset: number, length?: number } }` and maps onto R2's own\n`range`; `BlobListOptions` is `{ prefix?, cursor?, limit? }`; `BlobListPage` is\n`{ objects: BlobRecord[], cursor?, truncated? }`.\n\n## 1. BlobStore backed by R2\n\n`R2Object` carries `size`, `etag`, `httpMetadata.contentType`, `customMetadata`,\nand `uploaded` (a `Date`). `BlobRecord` wants `createdAt` \u002F `updatedAt` as epoch\nms β€” R2 tracks only the single `uploaded` instant, so map it to both. `get` \u002F\n`head` are the byte-body vs metadata-only split; `R2ObjectBody` already exposes\n`body`, `arrayBuffer()`, and `text()`, so a `BlobObject` is essentially the R2\nobject plus the mapped metadata.\n\n```ts ignore\nimport { defineBlobStore, resolveBlobRange } from '@tanstack\u002Fai-persistence'\nimport type { BlobObject, BlobRecord } from '@tanstack\u002Fai-persistence'\n\n\u002F\u002F R2 multipart parts must be β‰₯ 5 MiB and β€” except for the last β€” all exactly\n\u002F\u002F the SAME size, so a part reader has to cut on an exact boundary and carry the\n\u002F\u002F remainder. 8 MiB Γ— the 10,000-part ceiling puts the multipart path's limit at\n\u002F\u002F ~80 GiB; raise this for larger objects, and check R2's current object-size\n\u002F\u002F limits before promising more.\nconst MULTIPART_PART_SIZE = 8 * 1024 * 1024\n\n\u002F**\n * Cut exactly `limit` bytes off the stream (fewer only at EOF), carrying any\n * overshoot into the next part.\n *\n * `carry` is the leftover from the previous call. Chunks are collected by\n * reference and copied once per part: growing a `Uint8Array` chunk-by-chunk\n * instead would re-copy the whole part on every read β€” quadratic work for a\n * part built from hundreds of small chunks.\n *\u002F\nasync function readPart(\n reader: ReadableStreamDefaultReader\u003CUint8Array>,\n limit: number,\n carry: Uint8Array,\n): Promise\u003C{ bytes: Uint8Array; carry: Uint8Array; eof: boolean }> {\n const chunks: Array\u003CUint8Array> = carry.byteLength > 0 ? [carry] : []\n let total = carry.byteLength\n let eof = false\n while (total \u003C limit) {\n const { value, done } = await reader.read()\n if (done) {\n eof = true\n break\n }\n chunks.push(value)\n total += value.byteLength\n }\n const joined = new Uint8Array(total)\n let offset = 0\n for (const chunk of chunks) {\n joined.set(chunk, offset)\n offset += chunk.byteLength\n }\n \u002F\u002F Equal-sized parts: hand back exactly `limit` and keep the rest for next\n \u002F\u002F time. At EOF the last part is whatever is left, which R2 allows.\n if (!eof && total > limit) {\n return {\n bytes: joined.subarray(0, limit),\n carry: joined.subarray(limit),\n eof,\n }\n }\n return { bytes: joined, carry: new Uint8Array(0), eof }\n}\n\n\u002F\u002F R2 takes a single-shot put up to 5 GiB. Above that the upload has to be\n\u002F\u002F multipart even when the length is known.\nconst MAX_SINGLE_SHOT_BYTES = 5 * 1024 * 1024 * 1024\n\n\u002F**\n * `R2Bucket.put` requires a stream with a known length; a pass-through\n * TransformStream (what the middleware sends when it had to cap the body) has\n * none. Re-declare the length when `expectedLength` provides it β€” the\n * middleware only sets it when it is the exact decoded byte count β€” and\n * otherwise stream through a multipart upload, one buffered part at a time.\n *\u002F\nasync function putStream(\n bucket: R2Bucket,\n key: string,\n body: ReadableStream\u003CUint8Array>,\n options: R2PutOptions,\n expectedLength: number | undefined,\n): Promise\u003CR2Object | null> {\n if (expectedLength !== undefined && expectedLength \u003C= MAX_SINGLE_SHOT_BYTES) {\n return bucket.put(\n key,\n body.pipeThrough(new FixedLengthStream(expectedLength)),\n options,\n )\n }\n \u002F\u002F Unknown length, or too big for one shot: multipart, one part at a time.\n const reader = body.getReader()\n const first = await readPart(reader, MULTIPART_PART_SIZE, new Uint8Array(0))\n if (first.eof) {\n \u002F\u002F The whole body fit in one part β€” a plain put is enough.\n return bucket.put(key, first.bytes, options)\n }\n const upload = await bucket.createMultipartUpload(key, options)\n try {\n const parts: Array\u003CR2UploadedPart> = [\n await upload.uploadPart(1, first.bytes),\n ]\n let carry = first.carry\n let partNumber = 2\n for (;;) {\n const part = await readPart(reader, MULTIPART_PART_SIZE, carry)\n carry = part.carry\n if (part.bytes.byteLength > 0) {\n \u002F\u002F 10,000 parts is R2's ceiling; failing here beats a confusing error\n \u002F\u002F from `complete` after uploading gigabytes.\n if (partNumber > 10_000) {\n throw new Error(\n `Artifact at ${key} exceeds the multipart part limit β€” raise MULTIPART_PART_SIZE.`,\n )\n }\n parts.push(await upload.uploadPart(partNumber, part.bytes))\n partNumber += 1\n }\n if (part.eof) break\n }\n return await upload.complete(parts)\n } catch (error) {\n await upload.abort().catch(() => undefined)\n throw error\n }\n}\n\nfunction toRecord(obj: R2Object): BlobRecord {\n const uploaded = obj.uploaded.getTime()\n return {\n key: obj.key,\n size: obj.size,\n etag: obj.etag,\n ...(obj.httpMetadata?.contentType\n ? { contentType: obj.httpMetadata.contentType }\n : {}),\n ...(obj.customMetadata ? { customMetadata: obj.customMetadata } : {}),\n createdAt: uploaded,\n updatedAt: uploaded,\n }\n}\n\nexport function r2BlobStore(bucket: R2Bucket) {\n return defineBlobStore({\n async put(key, body, options) {\n const r2Options = {\n ...(options?.contentType\n ? { httpMetadata: { contentType: options.contentType } }\n : {}),\n ...(options?.customMetadata\n ? { customMetadata: options.customMetadata }\n : {}),\n }\n const obj =\n body instanceof ReadableStream\n ? await putStream(\n bucket,\n key,\n body,\n r2Options,\n options?.expectedLength,\n )\n : await bucket.put(key, body, r2Options)\n \u002F\u002F R2.put returns null only when an onlyIf precondition fails β€” not used here.\n if (!obj) throw new Error(`R2 put failed for ${key}`)\n return toRecord(obj)\n },\n\n async get(key, options): Promise\u003CBlobObject | null> {\n if (!options?.range) {\n const whole = await bucket.get(key)\n if (!whole) return null\n return {\n ...toRecord(whole),\n body: whole.body,\n arrayBuffer: () => whole.arrayBuffer(),\n text: () => whole.text(),\n }\n }\n \u002F\u002F A ranged read is what a serve route turns into `206` β€” R2 slices in\n \u002F\u002F the bucket, so a seek never streams the whole object. `resolveBlobRange`\n \u002F\u002F clamps a too-long length and throws on an offset past the end (the\n \u002F\u002F route answers `416` from `record.size` before ever calling in). The\n \u002F\u002F `head` buys that clamp deterministically β€” one class-B op against\n \u002F\u002F bytes you did not need to send.\n \u002F\u002F\n \u002F\u002F Retry a bounded number of times: each attempt measures the object and\n \u002F\u002F reads a slice of THAT version, and only an overwrite landing between\n \u002F\u002F the two calls costs another lap.\n for (let attempt = 0; attempt \u003C 3; attempt++) {\n const head = await bucket.head(key)\n \u002F\u002F A ranged read of a key that is not there is a miss, not a\n \u002F\u002F whole-object read: falling through to an un-ranged `get` would\n \u002F\u002F answer a `206` carrying the entire file.\n if (!head) return null\n const served = resolveBlobRange(head.size, options.range)\n const obj = await bucket.get(key, {\n range: { offset: served.offset, length: served.length },\n \u002F\u002F Tie the slice to the version `head` measured. Without this, a\n \u002F\u002F `put` landing between the two calls yields a `Content-Range`\n \u002F\u002F computed from one object and bytes from another.\n onlyIf: { etagMatches: head.etag },\n })\n \u002F\u002F No body means the precondition failed β€” the object changed under us.\n if (!obj) return null\n if (!('body' in obj)) continue\n return {\n \u002F\u002F `toRecord(obj)` reports the WHOLE object's size even on a ranged\n \u002F\u002F read β€” R2's `R2Object.size` is the object, not the slice β€” which\n \u002F\u002F is exactly the contract, and what `Content-Range`'s total needs.\n ...toRecord(obj),\n range: served,\n body: obj.body,\n arrayBuffer: () => obj.arrayBuffer(),\n text: () => obj.text(),\n }\n }\n throw new Error(`R2 object ${key} changed under every ranged read.`)\n },\n\n async head(key) {\n const obj = await bucket.head(key)\n return obj ? toRecord(obj) : null\n },\n\n async delete(key) {\n await bucket.delete(key)\n },\n\n async list(options) {\n \u002F\u002F R2 reads `limit: 0` as \"use the default\", so short-circuit it.\n if (options?.limit === 0) {\n return { objects: [] }\n }\n const page = await bucket.list({\n ...(options?.prefix !== undefined ? { prefix: options.prefix } : {}),\n ...(options?.cursor !== undefined ? { cursor: options.cursor } : {}),\n ...(options?.limit !== undefined ? { limit: options.limit } : {}),\n \u002F\u002F R2 omits httpMetadata\u002FcustomMetadata from list rows unless asked.\n include: ['httpMetadata', 'customMetadata'],\n })\n return {\n objects: page.objects.map(toRecord),\n ...(page.truncated ? { cursor: page.cursor, truncated: true } : {}),\n }\n },\n })\n}\n```\n\nInvariants that matter (asserted by the conformance testkit):\n\n- `get` \u002F `head` return `null` for a missing key; `delete` is a silent no-op.\n- `put` **overwrites** an existing key.\n- `put` accepts a `ReadableStream` body with **no declared length** β€” the\n middleware streams URL-fetched artifacts as exactly that. This is where the\n naive \"pass the body straight to `bucket.put`\" recipe fails at runtime\n (workerd requires a known length), which is what `putStream` above handles.\n- `get` honours `options.range`: it returns **only** that slice, reports it as\n `range`, and keeps `size` on the whole object. That is the `206` a video\n player's seeking depends on, and R2 slices in the bucket so the bytes never\n cross the Worker.\n- `list` filters by `prefix` literally (R2 prefix is a literal byte prefix β€” no\n glob), returns keys in ascending order, and pages via the opaque `cursor` when\n `truncated`. R2's own cursor is opaque and satisfies this directly. `limit: 0`\n must yield an empty, untruncated page β€” R2 treats `limit: 0` as \"use the\n default\", so special-case it: `if (options?.limit === 0) return { objects: [] }`.\n\n## 2. ArtifactStore backed by D1\n\n`ArtifactRecord` is `{ artifactId, runId, threadId, name, mimeType, size,\nsourceUrl?, createdAt }` (`createdAt` epoch ms). One flat table, keyed by\n`artifact_id`, indexed by `run_id` for `list`.\n\n```sql\nCREATE TABLE IF NOT EXISTS generation_artifacts (\n artifact_id text PRIMARY KEY NOT NULL,\n run_id text NOT NULL,\n thread_id text NOT NULL,\n blob_key text,\n name text NOT NULL,\n mime_type text NOT NULL,\n size integer NOT NULL,\n source_url text,\n created_at integer NOT NULL\n);\nCREATE INDEX IF NOT EXISTS generation_artifacts_run ON generation_artifacts (run_id);\n```\n\n```ts ignore\nimport { defineArtifactStore } from '@tanstack\u002Fai-persistence'\nimport type { ArtifactRecord } from '@tanstack\u002Fai-persistence'\n\ninterface ArtifactRow {\n artifact_id: string\n run_id: string\n thread_id: string\n blob_key: string | null\n name: string\n mime_type: string\n size: number\n source_url: string | null\n created_at: number\n}\n\nfunction fromRow(row: ArtifactRow): ArtifactRecord {\n return {\n artifactId: row.artifact_id,\n runId: row.run_id,\n threadId: row.thread_id,\n ...(row.blob_key != null ? { blobKey: row.blob_key } : {}),\n name: row.name,\n mimeType: row.mime_type,\n size: row.size,\n ...(row.source_url != null ? { sourceUrl: row.source_url } : {}),\n createdAt: row.created_at,\n }\n}\n\nexport function d1ArtifactStore(db: D1Database) {\n return defineArtifactStore({\n async save(record) {\n \u002F\u002F Insert or overwrite (artifact ids are unique).\n await db\n .prepare(\n `INSERT INTO generation_artifacts\n (artifact_id, run_id, thread_id, blob_key, name, mime_type, size, source_url, created_at)\n VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)\n ON CONFLICT(artifact_id) DO UPDATE SET\n run_id = excluded.run_id, thread_id = excluded.thread_id,\n blob_key = excluded.blob_key, name = excluded.name,\n mime_type = excluded.mime_type, size = excluded.size,\n source_url = excluded.source_url, created_at = excluded.created_at`,\n )\n .bind(\n record.artifactId,\n record.runId,\n record.threadId,\n record.blobKey ?? null,\n record.name,\n record.mimeType,\n record.size,\n record.sourceUrl ?? null,\n record.createdAt,\n )\n .run()\n },\n\n async get(artifactId) {\n const row = await db\n .prepare(`SELECT * FROM generation_artifacts WHERE artifact_id = ?`)\n .bind(artifactId)\n .first\u003CArtifactRow>()\n return row ? fromRow(row) : null\n },\n\n async list(runId) {\n const { results } = await db\n .prepare(`SELECT * FROM generation_artifacts WHERE run_id = ?`)\n .bind(runId)\n .all\u003CArtifactRow>()\n return results.map(fromRow)\n },\n\n async delete(artifactId) {\n await db\n .prepare(`DELETE FROM generation_artifacts WHERE artifact_id = ?`)\n .bind(artifactId)\n .run()\n },\n\n async deleteForRun(runId) {\n await db\n .prepare(`DELETE FROM generation_artifacts WHERE run_id = ?`)\n .bind(runId)\n .run()\n },\n })\n}\n```\n\nOmitting `source_url` \u002F `blob_key` from the record when the column is `NULL`\nkeeps records comparing cleanly against the reference in-memory store. Persist\n`blob_key` verbatim: a `storageKey` mapper can put the bytes anywhere, so a\nreader cannot recompute the path β€” `resolveArtifactBlobKey(record)` falls back\nto the default convention only for rows written before the column existed.\n**KV alternative:** if\nyou have no D1, back `save`\u002F`get` with `KV.put(artifactId, JSON.stringify(record))`\n\u002F `KV.get(artifactId, 'json')`, and maintain a `run:\u003CrunId>` index key (a JSON\narray of artifact ids) for `list` β€” KV has no query, so `list` needs that\nsecondary index.\n\n## 3. Compose and wire\n\nBindings are per-request on Workers, so export a **factory**. Combine the byte\nstores with a generation-run store (and, if this Worker also does chat, the chat stores).\nEither build the whole `AIPersistence` with `defineAIPersistence`, or layer the\nartifact stores onto an existing chat persistence with `composePersistence`:\n\n```ts ignore\nimport {\n defineAIPersistence,\n composePersistence,\n withGenerationPersistence,\n} from '@tanstack\u002Fai-persistence'\nimport { r2BlobStore } from '.\u002Fr2-blob-store'\nimport { d1ArtifactStore } from '.\u002Fd1-artifact-store'\nimport { d1GenerationRunStore } from '.\u002Fd1-job-store' \u002F\u002F your GenerationRunStore\n\n\u002F** Call inside a request handler β€” bindings are not available at module scope. *\u002F\nexport function generationPersistence(env: Env) {\n return defineAIPersistence({\n stores: {\n generationRuns: d1GenerationRunStore(env.DB),\n artifacts: d1ArtifactStore(env.DB),\n blobs: r2BlobStore(env.ARTIFACTS_BUCKET),\n },\n })\n}\n\n\u002F\u002F …or add bytes to a persistence that already has chat + generation runs:\n\u002F\u002F composePersistence(chatAndJobsPersistence(env), {\n\u002F\u002F overrides: {\n\u002F\u002F artifacts: d1ArtifactStore(env.DB),\n\u002F\u002F blobs: r2BlobStore(env.ARTIFACTS_BUCKET),\n\u002F\u002F },\n\u002F\u002F })\n```\n\n`withGenerationPersistence` throws if exactly one of `artifacts` \u002F `blobs` is\npresent β€” provide both or neither. Wire it as generation middleware:\n\n```ts ignore\nimport { generateImage, toServerSentEventsResponse } from '@tanstack\u002Fai'\nimport { openaiImage } from '@tanstack\u002Fai-openai'\nimport { withGenerationPersistence } from '@tanstack\u002Fai-persistence'\nimport { generationPersistence } from '.\u002Flib\u002Fgeneration-persistence'\n\nexport default {\n async fetch(request: Request, env: Env) {\n const { prompt, threadId } = await request.json()\n const stream = generateImage({\n adapter: openaiImage('gpt-image-1'),\n prompt,\n threadId, \u002F\u002F the slot recorded on the job + artifacts\n stream: true,\n middleware: [\n \u002F\u002F Nothing is buffered: the artifact streams from the provider CDN\n \u002F\u002F into R2. Add `maxArtifactBytes: false` if you want no ceiling at\n \u002F\u002F all on what an origin can stream into your bucket (the default is\n \u002F\u002F 1 GiB); it is not needed for the streaming itself.\n withGenerationPersistence(generationPersistence(env), { threadId }),\n ],\n })\n return toServerSentEventsResponse(stream)\n },\n}\n```\n\n## 4. Serve the bytes back\n\nA GET route resolves an `artifactId` to its record and its stored bytes.\n`retrieveArtifact` returns the `ArtifactRecord` (or `null` β†’ 404);\n`retrieveBlob` returns the `BlobObject` (metadata + a streamable `body`). Both\nresolve the blob key from the record internally, so you never build the key\nyourself.\n\nHonour `Range` requests: `\u003Cvideo>` seeking is built on `206` \u002F `Content-Range`,\nand Safari refuses to play a source that ignores `Range` entirely. Images never\nnotice; a few-hundred-MB clip is unwatchable without it. Pass `range` to\n`retrieveBlob` β€” the store slices in R2 β€” rather than reaching into the bucket\nbinding from the route, which would tie the route to R2 and bypass the store's\nown key resolution.\n\n```ts ignore\nimport {\n parseRangeHeader,\n retrieveArtifact,\n retrieveBlob,\n} from '@tanstack\u002Fai-persistence'\nimport { generationPersistence } from '.\u002Flib\u002Fgeneration-persistence'\n\nexport async function GET(request: Request, env: Env) {\n const artifactId = new URL(request.url).searchParams.get('id') ?? ''\n const persistence = generationPersistence(env)\n\n \u002F\u002F Authorize before serving β€” derive the owner from the session, never trust\n \u002F\u002F a client-supplied id. (The record carries runId\u002FthreadId to check against.)\n const record = await retrieveArtifact(persistence, artifactId)\n if (!record) return new Response('Not found', { status: 404 })\n\n \u002F\u002F `parseRangeHeader` resolves the header against the size on the record β€”\n \u002F\u002F suffix ranges included β€” so an unsatisfiable range is a 416 here and the\n \u002F\u002F store only ever sees a range it can serve.\n const range = parseRangeHeader(request.headers.get('range'), record.size)\n if (range === 'unsatisfiable') {\n return new Response('Range not satisfiable', {\n status: 416,\n headers: { 'content-range': `bytes *\u002F${record.size}` },\n })\n }\n\n \u002F\u002F Pass the record, not the id: no second metadata lookup.\n const blob = await retrieveBlob(\n persistence,\n record,\n range ? { range } : undefined,\n )\n if (!blob?.body) return new Response('Not found', { status: 404 })\n\n \u002F\u002F `accept-ranges` on every response, including the whole-file one: it is how\n \u002F\u002F a player learns it may seek at all.\n const headers = {\n 'content-type': record.mimeType,\n 'accept-ranges': 'bytes',\n }\n if (!blob.range) {\n return new Response(blob.body, {\n headers: { ...headers, 'content-length': String(record.size) },\n })\n }\n const { offset, length } = blob.range\n return new Response(blob.body, {\n status: 206,\n headers: {\n ...headers,\n 'content-length': String(length),\n 'content-range': `bytes ${offset}-${offset + length - 1}\u002F${record.size}`,\n },\n })\n}\n```\n\nTo hydrate a **server-driven generation client** (`persistence: true` + a stable\n`threadId`) on mount, also expose `reconstructGeneration(persistence, request)`\non a GET that reads `?threadId=` \u002F `?runId=` β€” see `ai-core\u002Fclient-persistence`.\n\n## Other backends β€” the contract is tiny, here's how each maps\n\n`BlobStore` is five methods over an object store. Any of these backs it; swap the\nfactory, keep everything else. `put` maps to the SDK's upload, `get` to a\ndownload that exposes `body`\u002F`arrayBuffer`\u002F`text`, `head` to a metadata fetch,\n`delete` to a delete, `list` to a prefixed, cursor-paged list.\n\n| Backend | npm | One-line sketch |\n| ------------------------- | ----------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| **AWS S3** | `@aws-sdk\u002Fclient-s3` | `put`β†’`PutObjectCommand`; `get`β†’`GetObjectCommand` (`Body` is a stream β†’ `body`, `.transformToByteArray()`\u002F`.transformToString()`); `head`β†’`HeadObjectCommand`; `delete`β†’`DeleteObjectCommand`; `list`β†’`ListObjectsV2Command` (`Prefix`, `ContinuationToken`↔`cursor`, `MaxKeys`↔`limit`, `IsTruncated`↔`truncated`). |\n| **Google Cloud Storage** | `@google-cloud\u002Fstorage` | `bucket.file(key)`: `put`β†’`.save(body, { contentType, metadata })`; `get`β†’`.createReadStream()` for `body` + `.download()` for bytes; `head`β†’`.getMetadata()`; `delete`β†’`.delete({ ignoreNotFound: true })`; `list`β†’`bucket.getFiles({ prefix, maxResults, pageToken })`. |\n| **Vercel Blob** | `@vercel\u002Fblob` | `put`β†’`put(key, body, { access: 'public', contentType })`; `get`β†’`fetch(head(key).url)` (stream `res.body`); `head`β†’`head(key)` (returns `null`β†’catch as absent); `delete`β†’`del(key)`; `list`β†’`list({ prefix, cursor, limit })` (`hasMore`↔`truncated`). |\n| **Supabase Storage** | `@supabase\u002Fsupabase-js` | `storage.from(bucket)`: `put`β†’`.upload(key, body, { contentType, upsert: true })`; `get`β†’`.download(key)` (returns a `Blob` β†’ `body`\u002F`arrayBuffer`\u002F`text`); `head`β†’`.info(key)` or list-one; `delete`β†’`.remove([key])`; `list`β†’`.list(prefix, { limit })` (offset\u002Flimit paging β†’ synthesize a `cursor`). |\n| **Filesystem (dev only)** | `node:fs\u002Fpromises` | Root each key under a dir: `put`β†’`mkdir(dirname, { recursive: true })` + `writeFile`; `get`β†’`createReadStream` for `body` + `readFile`; `head`β†’`stat` (`size`, `mtimeMs`β†’`updatedAt`); `delete`β†’`rm(path, { force: true })`; `list`β†’recursive `readdir` filtered by prefix, sorted, sliced by `limit`, cursor = last key. Not for production β€” no concurrency guarantees. |\n\nFor each: `contentType` and `customMetadata` ride the SDK's own metadata fields;\n`BlobRecord.createdAt`\u002F`updatedAt` come from the object's stored timestamps\n(epoch ms); return `null` from `get`\u002F`head` on a not-found rather than throwing.\n\n## Verify\n\nThe shared `runPersistenceConformance` testkit covers all seven stores, including\n`generationRuns`, `artifacts`, and `blobs` β€” point it at your factory rather than\nhand-writing these assertions:\n\n```ts ignore\nimport { runPersistenceConformance } from '@tanstack\u002Fai-persistence\u002Ftestkit'\nimport { env } from 'cloudflare:test'\nimport { generationPersistence } from '..\u002Fsrc\u002Flib\u002Fgeneration-persistence'\n\n\u002F\u002F A generation-only Worker declares the chat state stores it does not provide.\nrunPersistenceConformance('app-r2', () => generationPersistence(env), {\n skip: ['messages', 'runs', 'interrupts', 'metadata'],\n})\n```\n\nRun it against a Miniflare R2 + D1 binding with the migration applied, reset\nbetween runs (see **ai-persistence\u002Fbuild-cloudflare-adapter** for the\n`cloudflare:test` harness pattern). It exercises, among the rest:\n\n- `put` then `get` round-trips bytes and metadata; `get`\u002F`head` return `null` for\n a missing key; `delete` is a silent no-op on an absent key.\n- `put` accepts a `ReadableStream` body with no declared length (a\n `TransformStream`-wrapped stream) and records the real drained size β€” the\n shape every URL-fetched artifact arrives in.\n- `get` with a `range` returns just that slice, reports it as `range`, and\n still reports the whole object's `size` β€” what a `206` \u002F `Content-Range`\n response is built from.\n- `put` overwrites an existing key (and its `contentType`\u002F`customMetadata`).\n- `list` filters by `prefix` **literally and case-sensitively**, returns\n ascending keys, pages through the `cursor` when `truncated` without gaps or\n repeats, and returns an empty untruncated page for `limit: 0`.\n- The `ArtifactStore`: `save` is insert-or-overwrite, `get` returns `null` when\n absent, `list(runId)` returns `[]` for an unknown run, and `delete` \u002F\n `deleteForRun` remove exactly the expected rows.\n- The `GenerationRunStore`: `createOrResume` idempotency, no-op `update` on an\n unknown id, and `findLatestForThread` returning the most recently started\n linked run (terminal ones included).\n\nAn end-to-end check is the strongest signal: run `generateImage` through\n`withGenerationPersistence(generationPersistence(env), { threadId })`, then confirm the blob\nexists at `artifacts\u002F\u003CrunId>\u002F\u003CartifactId>` and `retrieveBlob` streams it back.\n",{"data":57,"body":58},{"name":5,"description":7},{"type":59,"children":60},"root",[61,70,131,175,195,202,230,941,1030,1048,1159,1187,1214,1282,1288,1428,7404,7409,7600,7606,7651,7756,9552,9661,9667,9700,10194,10220,10798,10804,10857,10913,12466,12522,12528,12592,13280,13333,13339,13372,13655,13673,13947,13981],{"type":62,"tag":63,"props":64,"children":66},"element","h1",{"id":65},"cloudflare-artifact-blob-store",[67],{"type":68,"value":69},"text","Cloudflare Artifact + Blob Store",{"type":62,"tag":71,"props":72,"children":73},"p",{},[74,81,83,89,91,97,99,105,107,113,115,121,123,129],{"type":62,"tag":75,"props":76,"children":78},"code",{"className":77},[],[79],{"type":68,"value":80},"withGenerationPersistence(persistence)",{"type":68,"value":82}," needs only ",{"type":62,"tag":75,"props":84,"children":86},{"className":85},[],[87],{"type":68,"value":88},"stores.generationRuns",{"type":68,"value":90}," to track a\ngeneration's lifecycle. 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Chunks are collected by\n * reference and copied once per part: growing a `Uint8Array` chunk-by-chunk\n * instead would re-copy the whole part on every read β€” quadratic work for a\n * part built from hundreds of small chunks.\n *\u002F\nasync function readPart(\n reader: ReadableStreamDefaultReader\u003CUint8Array>,\n limit: number,\n carry: Uint8Array,\n): Promise\u003C{ bytes: Uint8Array; carry: Uint8Array; eof: boolean }> {\n const chunks: Array\u003CUint8Array> = carry.byteLength > 0 ? [carry] : []\n let total = carry.byteLength\n let eof = false\n while (total \u003C limit) {\n const { value, done } = await reader.read()\n if (done) {\n eof = true\n break\n }\n chunks.push(value)\n total += value.byteLength\n }\n const joined = new Uint8Array(total)\n let offset = 0\n for (const chunk of chunks) {\n joined.set(chunk, offset)\n offset += chunk.byteLength\n }\n \u002F\u002F Equal-sized parts: hand back exactly `limit` and keep the rest for next\n \u002F\u002F time. At EOF the last part is whatever is left, which R2 allows.\n if (!eof && total > limit) {\n return {\n bytes: joined.subarray(0, limit),\n carry: joined.subarray(limit),\n eof,\n }\n }\n return { bytes: joined, carry: new Uint8Array(0), eof }\n}\n\n\u002F\u002F R2 takes a single-shot put up to 5 GiB. Above that the upload has to be\n\u002F\u002F multipart even when the length is known.\nconst MAX_SINGLE_SHOT_BYTES = 5 * 1024 * 1024 * 1024\n\n\u002F**\n * `R2Bucket.put` requires a stream with a known length; a pass-through\n * TransformStream (what the middleware sends when it had to cap the body) has\n * none. Re-declare the length when `expectedLength` provides it β€” the\n * middleware only sets it when it is the exact decoded byte count β€” and\n * otherwise stream through a multipart upload, one buffered part at a time.\n *\u002F\nasync function putStream(\n bucket: R2Bucket,\n key: string,\n body: ReadableStream\u003CUint8Array>,\n options: R2PutOptions,\n expectedLength: number | undefined,\n): Promise\u003CR2Object | null> {\n if (expectedLength !== undefined && expectedLength \u003C= MAX_SINGLE_SHOT_BYTES) {\n return bucket.put(\n key,\n body.pipeThrough(new FixedLengthStream(expectedLength)),\n options,\n )\n }\n \u002F\u002F Unknown length, or too big for one shot: multipart, one part at a time.\n const reader = body.getReader()\n const first = await readPart(reader, MULTIPART_PART_SIZE, new Uint8Array(0))\n if (first.eof) {\n \u002F\u002F The whole body fit in one part β€” a plain put is enough.\n return bucket.put(key, first.bytes, options)\n }\n const upload = await bucket.createMultipartUpload(key, options)\n try {\n const parts: Array\u003CR2UploadedPart> = [\n await upload.uploadPart(1, first.bytes),\n ]\n let carry = first.carry\n let partNumber = 2\n for (;;) {\n const part = await readPart(reader, MULTIPART_PART_SIZE, carry)\n carry = part.carry\n if (part.bytes.byteLength > 0) {\n \u002F\u002F 10,000 parts is R2's ceiling; failing here beats a confusing error\n \u002F\u002F from `complete` after uploading gigabytes.\n if (partNumber > 10_000) {\n throw new Error(\n `Artifact at ${key} exceeds the multipart part limit β€” raise MULTIPART_PART_SIZE.`,\n )\n }\n parts.push(await upload.uploadPart(partNumber, part.bytes))\n partNumber += 1\n }\n if (part.eof) break\n }\n return await upload.complete(parts)\n } catch (error) {\n await upload.abort().catch(() => undefined)\n throw error\n }\n}\n\nfunction toRecord(obj: R2Object): BlobRecord {\n const uploaded = obj.uploaded.getTime()\n return {\n key: obj.key,\n size: obj.size,\n etag: obj.etag,\n ...(obj.httpMetadata?.contentType\n ? { contentType: obj.httpMetadata.contentType }\n : {}),\n ...(obj.customMetadata ? { customMetadata: obj.customMetadata } : {}),\n createdAt: uploaded,\n updatedAt: uploaded,\n }\n}\n\nexport function r2BlobStore(bucket: R2Bucket) {\n return defineBlobStore({\n async put(key, body, options) {\n const r2Options = {\n ...(options?.contentType\n ? { httpMetadata: { contentType: options.contentType } }\n : {}),\n ...(options?.customMetadata\n ? { customMetadata: options.customMetadata }\n : {}),\n }\n const obj =\n body instanceof ReadableStream\n ? await putStream(\n bucket,\n key,\n body,\n r2Options,\n options?.expectedLength,\n )\n : await bucket.put(key, body, r2Options)\n \u002F\u002F R2.put returns null only when an onlyIf precondition fails β€” not used here.\n if (!obj) throw new Error(`R2 put failed for ${key}`)\n return toRecord(obj)\n },\n\n async get(key, options): Promise\u003CBlobObject | null> {\n if (!options?.range) {\n const whole = await bucket.get(key)\n if (!whole) return null\n return {\n ...toRecord(whole),\n body: whole.body,\n arrayBuffer: () => whole.arrayBuffer(),\n text: () => whole.text(),\n }\n }\n \u002F\u002F A ranged read is what a serve route turns into `206` β€” R2 slices in\n \u002F\u002F the bucket, so a seek never streams the whole object. `resolveBlobRange`\n \u002F\u002F clamps a too-long length and throws on an offset past the end (the\n \u002F\u002F route answers `416` from `record.size` before ever calling in). The\n \u002F\u002F `head` buys that clamp deterministically β€” one class-B op against\n \u002F\u002F bytes you did not need to send.\n \u002F\u002F\n \u002F\u002F Retry a bounded number of times: each attempt measures the object and\n \u002F\u002F reads a slice of THAT version, and only an overwrite landing between\n \u002F\u002F the two calls costs another lap.\n for (let attempt = 0; attempt \u003C 3; attempt++) {\n const head = await bucket.head(key)\n \u002F\u002F A ranged read of a key that is not there is a miss, not a\n \u002F\u002F whole-object read: falling through to an un-ranged `get` would\n \u002F\u002F answer a `206` carrying the entire file.\n if (!head) return null\n const served = resolveBlobRange(head.size, options.range)\n const obj = await bucket.get(key, {\n range: { offset: served.offset, length: served.length },\n \u002F\u002F Tie the slice to the version `head` measured. Without this, a\n \u002F\u002F `put` landing between the two calls yields a `Content-Range`\n \u002F\u002F computed from one object and bytes from another.\n onlyIf: { etagMatches: head.etag },\n })\n \u002F\u002F No body means the precondition failed β€” the object changed under us.\n if (!obj) return null\n if (!('body' in obj)) continue\n return {\n \u002F\u002F `toRecord(obj)` reports the WHOLE object's size even on a ranged\n \u002F\u002F read β€” R2's `R2Object.size` is the object, not the slice β€” which\n \u002F\u002F is exactly the contract, and what `Content-Range`'s total needs.\n ...toRecord(obj),\n range: served,\n body: obj.body,\n arrayBuffer: () => obj.arrayBuffer(),\n text: () => obj.text(),\n }\n }\n throw new Error(`R2 object ${key} changed under every ranged read.`)\n },\n\n async head(key) {\n const obj = await bucket.head(key)\n return obj ? toRecord(obj) : null\n },\n\n async delete(key) {\n await bucket.delete(key)\n },\n\n async list(options) {\n \u002F\u002F R2 reads `limit: 0` as \"use the default\", so short-circuit it.\n if (options?.limit === 0) {\n return { objects: [] }\n }\n const page = await bucket.list({\n ...(options?.prefix !== undefined ? { prefix: options.prefix } : {}),\n ...(options?.cursor !== undefined ? { cursor: options.cursor } : {}),\n ...(options?.limit !== undefined ? { limit: options.limit } : {}),\n \u002F\u002F R2 omits httpMetadata\u002FcustomMetadata from list rows unless asked.\n include: ['httpMetadata', 'customMetadata'],\n })\n return {\n objects: page.objects.map(toRecord),\n ...(page.truncated ? { cursor: page.cursor, truncated: true } : {}),\n }\n },\n 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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},[14157,14160,14161],{"name":14158,"slug":14159,"type":16},"Agents","agents",{"name":21,"slug":22,"type":16},{"name":14162,"slug":14163,"type":16},"Middleware","middleware","2026-07-30T05:26:10.404565",{"slug":14166,"name":14167,"fn":14168,"description":14169,"org":14170,"tags":14171,"stars":27,"repoUrl":28,"updatedAt":14179},"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},[14172,14173,14176,14178],{"name":14140,"slug":34,"type":16},{"name":14174,"slug":14175,"type":16},"Configuration","configuration",{"name":14177,"slug":40,"type":16},"LLM",{"name":10,"slug":9,"type":16},"2026-07-16T06:04:17.82075",{"slug":14181,"name":14182,"fn":14183,"description":14184,"org":14185,"tags":14186,"stars":27,"repoUrl":28,"updatedAt":14192},"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},[14187,14190,14191],{"name":14188,"slug":14189,"type":16},"API Development","api-development",{"name":14177,"slug":40,"type":16},{"name":10,"slug":9,"type":16},"2026-07-16T06:04:10.093367",{"slug":14194,"name":14195,"fn":14196,"description":14197,"org":14198,"tags":14199,"stars":27,"repoUrl":28,"updatedAt":14204},"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 β€” uses chat() not streamText().\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[14200,14201,14202,14203],{"name":14188,"slug":14189,"type":16},{"name":13999,"slug":14000,"type":16},{"name":14177,"slug":40,"type":16},{"name":10,"slug":9,"type":16},"2026-07-30T05:26:11.505241",{"slug":14206,"name":12520,"fn":14207,"description":14208,"org":14209,"tags":14210,"stars":27,"repoUrl":28,"updatedAt":14216},"ai-coreclient-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 β€” NOT server history alone. Also covers generation hooks (useGenerateImage etc.), which take only the server-driven mode: persistence: true hydrates the last generation for the (REQUIRED) threadId from the server on mount and repaints status\u002Fresult\u002Ferror, nothing is cached in the browser. No extra package: the adapters ship in the framework packages.\n",{"slug":9,"name":10,"logoUrl":11,"githubOrg":10},[14211,14212,14213,14215],{"name":21,"slug":22,"type":16},{"name":13999,"slug":14000,"type":16},{"name":14214,"slug":11275,"type":16},"Persistence",{"name":10,"slug":9,"type":16},"2026-08-02T05:42:41.847424",{"slug":14218,"name":14219,"fn":14220,"description":14221,"org":14222,"tags":14223,"stars":27,"repoUrl":28,"updatedAt":14228},"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},[14224,14225,14226,14227],{"name":21,"slug":22,"type":16},{"name":14188,"slug":14189,"type":16},{"name":14,"slug":15,"type":16},{"name":10,"slug":9,"type":16},"2026-07-17T06:06:39.855351"]