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feat(api): add docs assistant endpoint with OpenRouter integration
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@@ -1,3 +1,4 @@
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GH_PAT=github_pat_or_gho_token_with_issues_and_projects_rw
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WEBHOOK_SECRET=random_hex_matching_the_repo_webhook
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LINK_KEY=random_hex_signing_one_tap_links
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OPENROUTER_API_KEY=sk-or-v1_key_for_the_docs_assistant
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@@ -0,0 +1,290 @@
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/**
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* POST /ask — the docs assistant's backend.
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*
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* The docs are a static GitHub Pages site, and Blume's own assistant route is
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* server-rendered (it reads the provider key per request), so the site points
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* `ai.assistant.endpoint` here instead. This speaks the Blume island's wire
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* contract (`blume/components/islands/hooks.ts`):
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*
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* - request: `{ messages: [{ role, content }], page: { path } }` as JSON,
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* `path` the base-stripped route the reader is on;
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* - response: the answer as a plain UTF-8 text stream; any non-2xx shows the
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* island's error notice, and a 503 whose body starts "The assistant is not
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* configured" shows that body verbatim.
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*
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* Validation matches Blume's generated route: 1–40 user/assistant messages of
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* string content, ≤ 24 000 chars serialized, a 64 KB body, and only role and
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* content ever reach the model, so the endpoint cannot be repurposed as an
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* open LLM proxy with a caller's own system prompt.
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*
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* Grounding reads what the site already publishes: `llms-full.txt`, every
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* page's Markdown under `# Title` / `Source: <url>`. The page the reader is on
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* goes in first, then the best keyword matches, within Blume's default budget
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* (6 pages, 2 000 chars each, 10 000 total), under Blume's grounded system
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* prompt — answer only from the excerpts, cite pages as `[Title](/route)`.
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*
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* The model call is OpenRouter's OpenAI-compatible chat endpoint over plain
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* `fetch` (no SDK — see the repo's near-zero-dependency rule), streamed, with
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* `reasoning.effort: "none"`; its SSE deltas are re-emitted as bare text. The
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* reader closing the panel aborts the request, which aborts the model call.
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*/
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const MODEL = "qwen/qwen3.8-27b:free";
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const BODY_LIMIT = 64 * 1024;
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const MAX_MESSAGES = 40;
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const MAX_CHARS = 24_000;
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const MAX_RESULTS = 6;
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const EXCERPT_CHARS = 2000;
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const CONTEXT_BUDGET = 10_000;
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/** Lead-in kept before the matched region of a long page. */
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const EXCERPT_LEAD = 160;
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/** How long one isolate reuses the parsed corpus (the edge caches the fetch as long). */
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const CORPUS_TTL_MS = 5 * 60_000;
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const SYSTEM_PROMPT =
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"You are a helpful documentation assistant for this project, a LeetCode interview-prep campaign: solved problems grouped by topic, with guides to the techniques behind them. Answer the user's question using ONLY the documentation excerpts below. Each excerpt is headed by its page as `## Page Title (/route)`. If the answer is not covered by the excerpts, say you don't know and suggest where in the docs to look — do not invent details. Always cite the pages you drew from, and write every citation as a Markdown link to that page using its route, e.g. [Page Title](/route).";
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/** Words that match everything and rank nothing. */
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const STOPWORDS = new Set(
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"a an and are as at be but by can do does for from how i if in is it its me my of on or so that the this to was what when where which who why with you your".split(
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" ",
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),
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);
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interface AskMessage {
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role: "user" | "assistant";
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content: string;
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}
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interface Section {
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title: string;
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route: string;
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body: string;
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/** Lower-cased title + body, searched per query term. */
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text: string;
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titleText: string;
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}
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// ── corpus ───────────────────────────────────────────────────────
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let corpus: { at: number; sections: Section[] } | undefined;
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/** `llms-full.txt` split into pages, cached per isolate for `CORPUS_TTL_MS`. */
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async function sections(docsUrl: string): Promise<Section[]> {
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if (corpus && Date.now() - corpus.at < CORPUS_TTL_MS) return corpus.sections;
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const res = await fetch(`${docsUrl}/llms-full.txt`, {
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cf: { cacheTtl: CORPUS_TTL_MS / 1000, cacheEverything: true },
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});
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if (!res.ok) throw new Error(`GET llms-full.txt -> ${res.status}`);
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const full = await res.text();
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const heads = [...full.matchAll(/^# (.+)\nSource: (\S+)$/gm)];
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const out = heads.map((head, i): Section => {
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const start = head.index + head[0].length;
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const end = heads[i + 1]?.index ?? full.length;
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const body = full.slice(start, end).replace(/\n-{3,}\s*$/, "").trim();
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const title = head[1]!.trim();
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return {
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title,
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route: new URL(head[2]!).pathname.replace(/(.)\/+$/, "$1"),
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body,
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text: `${title}\n${body}`.toLowerCase(),
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titleText: title.toLowerCase(),
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};
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});
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corpus = { at: Date.now(), sections: out };
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return out;
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}
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// ── retrieval ────────────────────────────────────────────────────
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function terms(text: string): string[] {
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return [...new Set(text.toLowerCase().match(/[a-z0-9][a-z0-9+#-]*/g) ?? [])].filter(
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(t) => !STOPWORDS.has(t) && (t.length > 1 || /\d/.test(t)),
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);
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}
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function occurrences(haystack: string, needle: string): number {
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let count = 0;
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for (let at = haystack.indexOf(needle); at !== -1; at = haystack.indexOf(needle, at + needle.length)) count++;
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return count;
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}
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/**
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* The pages to inject, best first: term frequency damped by log and weighted
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* by rarity across pages (idf), a title hit counting triple — so "217" or
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* "sliding window" lands on the page named that rather than every page that
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* mentions it in passing.
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*/
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function rank(all: Section[], query: string[]): Section[] {
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const idf = new Map(
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query.map((t) => [t, Math.log(1 + all.length / (1 + all.filter((s) => s.text.includes(t)).length))]),
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);
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return all
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.map((section) => {
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let score = 0;
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for (const t of query) {
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const tf = occurrences(section.text, t);
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if (tf) score += idf.get(t)! * (Math.log(1 + tf) + (section.titleText.includes(t) ? 3 : 0));
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}
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return { section, score };
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})
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.filter((r) => r.score > 0)
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.sort((a, b) => b.score - a.score)
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.slice(0, MAX_RESULTS)
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.map((r) => r.section);
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}
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/** A page whole when it fits, else `chars` from just before its first query hit. */
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function excerpt(section: Section, query: string[], chars: number): string {
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if (section.body.length <= chars) return section.body;
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const lower = section.body.toLowerCase();
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const hits = query.map((t) => lower.indexOf(t)).filter((i) => i !== -1);
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const start = hits.length ? Math.max(0, Math.min(...hits) - EXCERPT_LEAD) : 0;
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return `${start > 0 ? "…" : ""}${section.body.slice(start, start + chars)}…`;
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}
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/** The system prompt: the current page, then the ranked pages, within the budget. */
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async function instructions(env: Env, messages: AskMessage[], path: string | undefined): Promise<string> {
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const all = await sections(env.DOCS_URL);
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// A follow-up ("and in Python?") leans on the question before it.
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const asked = messages.filter((m) => m.role === "user").slice(-2).map((m) => m.content);
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const query = terms(asked.join(" "));
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const current = path ? all.find((s) => s.route === path) : undefined;
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const picked = [...(current ? [current] : []), ...rank(all, query).filter((s) => s !== current)];
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const parts: string[] = [];
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let budget = CONTEXT_BUDGET;
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for (const section of picked) {
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if (budget < 200) break;
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const text = excerpt(section, query, Math.min(EXCERPT_CHARS, budget));
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parts.push(`## ${section.title} (${section.route})\n\n${text}`);
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budget -= text.length;
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}
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return parts.length ? `${SYSTEM_PROMPT}\n\n# Documentation excerpts\n\n${parts.join("\n\n")}` : SYSTEM_PROMPT;
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}
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// ── request handling ─────────────────────────────────────────────
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/** The validated conversation, or a reason it was turned away. */
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function readMessages(body: unknown): AskMessage[] | undefined {
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if (!body || typeof body !== "object" || !("messages" in body) || !Array.isArray(body.messages)) return;
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const raw: unknown[] = body.messages;
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if (raw.length === 0 || raw.length > MAX_MESSAGES || JSON.stringify(raw).length > MAX_CHARS) return;
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const messages: AskMessage[] = [];
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for (const m of raw) {
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if (!m || typeof m !== "object" || !("role" in m) || !("content" in m)) return;
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if ((m.role !== "user" && m.role !== "assistant") || typeof m.content !== "string") return;
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messages.push({ role: m.role, content: m.content });
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}
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return messages;
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}
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function readPath(body: unknown): string | undefined {
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if (!body || typeof body !== "object" || !("page" in body)) return;
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const page = body.page;
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if (!page || typeof page !== "object" || !("path" in page) || typeof page.path !== "string") return;
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return page.path.replace(/(.)\/+$/, "$1");
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}
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/** OpenRouter's SSE (`data: {…choices[0].delta.content…}`) → the answer's bare text. */
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function textStream(sse: ReadableStream<Uint8Array>): ReadableStream<Uint8Array> {
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const decoder = new TextDecoder();
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const encoder = new TextEncoder();
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let buffer = "";
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return sse.pipeThrough(
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new TransformStream<Uint8Array, Uint8Array>({
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transform(chunk, controller) {
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buffer += decoder.decode(chunk, { stream: true });
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const lines = buffer.split("\n");
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buffer = lines.pop() ?? "";
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for (const line of lines) {
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if (!line.startsWith("data: ")) continue; // `: OPENROUTER PROCESSING` keep-alives
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const data = line.slice(6).trim();
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if (data === "[DONE]") continue;
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let event: unknown;
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try {
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event = JSON.parse(data);
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} catch {
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continue;
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}
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if (event && typeof event === "object" && "error" in event) {
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// After the 200: the stream just ends, and the island shows its
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// error notice for an empty answer.
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console.error(`ask: provider error mid-stream: ${JSON.stringify(event.error)}`);
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continue;
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}
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if (!event || typeof event !== "object" || !("choices" in event) || !Array.isArray(event.choices)) continue;
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const choice: unknown = event.choices[0];
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if (!choice || typeof choice !== "object" || !("delta" in choice)) continue;
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const delta = choice.delta;
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if (!delta || typeof delta !== "object" || !("content" in delta)) continue;
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const content = delta.content;
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if (typeof content === "string" && content) controller.enqueue(encoder.encode(content));
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}
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},
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}),
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);
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}
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export async function handleAsk(request: Request, env: Env): Promise<Response> {
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// The docs serve from the custom domain and the Pages origin; reflect the
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// requesting origin only when it is on the allowlist (as /api/stats does).
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const allowed = env.DOCS_ORIGIN.split(",").map((o) => o.trim());
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const origin = request.headers.get("origin");
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const cors = {
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"access-control-allow-origin": origin && allowed.includes(origin) ? origin : allowed[0]!,
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"access-control-allow-methods": "POST",
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"access-control-allow-headers": "content-type",
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"access-control-max-age": "86400",
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vary: "Origin",
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};
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const text = (body: string, status: number) =>
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new Response(body, { status, headers: { ...cors, "content-type": "text/plain; charset=utf-8" } });
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if (request.method === "OPTIONS") return new Response(null, { status: 204, headers: cors });
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if (request.method !== "POST") return text("POST only.", 405);
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const raw = await request.arrayBuffer();
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if (raw.byteLength > BODY_LIMIT) return text("Request too large: the body must be at most 64 KB.", 413);
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let body: unknown;
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try {
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body = JSON.parse(new TextDecoder().decode(raw));
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} catch {
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body = undefined;
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}
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const messages = readMessages(body);
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if (!messages) return text("Invalid request: send 1-40 user/assistant messages with string content.", 400);
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if (!env.OPENROUTER_API_KEY) return text("The assistant is not configured: set OPENROUTER_API_KEY.", 503);
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let system: string;
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try {
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system = await instructions(env, messages, readPath(body));
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} catch (err) {
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// Ungrounded beats unanswered: the prompt still forbids inventing details.
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console.warn(`ask: grounding unavailable: ${err}`);
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system = SYSTEM_PROMPT;
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}
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const res = await fetch("https://openrouter.ai/api/v1/chat/completions", {
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method: "POST",
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headers: {
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authorization: `Bearer ${env.OPENROUTER_API_KEY}`,
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"content-type": "application/json",
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},
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body: JSON.stringify({
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model: MODEL,
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stream: true,
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reasoning: { effort: "none" },
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messages: [{ role: "system", content: system }, ...messages],
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}),
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signal: request.signal,
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});
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if (!res.ok || !res.body) {
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console.error(`ask: POST /chat/completions -> ${res.status} ${await res.text().catch(() => "")}`);
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return text("Failed to generate a response.", res.status === 429 ? 429 : 502);
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}
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return new Response(textStream(res.body), {
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headers: { ...cors, "content-type": "text/plain; charset=utf-8", "cache-control": "no-store" },
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});
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}
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@@ -9,6 +9,7 @@
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* Writes are owner-only (webhook author check, HMAC one-tap links, bearer
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* admin routes); everything else is read-only public.
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*/
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import { handleAsk } from "./ask.ts";
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import { reconcileCatalog } from "./catalog.ts";
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import { gateBadge, heatmapChart, heatmapPng, ladderChart, progressChart } from "./charts.ts";
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import { sendDigest } from "./digest.ts";
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@@ -322,6 +323,8 @@ export default {
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if (path.startsWith("/admin/") && request.method === "POST") {
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return await handleAdmin(request, env, path);
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}
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// The docs assistant (the static Pages site's `ai.assistant.endpoint`).
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if (path === "/ask") return await handleAsk(request, env);
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if (path === "/chart/progress.svg") {
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return new Response(await progressChart(env.DB), { headers: SVG_HEADERS });
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@@ -38,4 +38,6 @@
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}
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// Secrets (wrangler secret put): GH_PAT, WEBHOOK_SECRET, LINK_KEY.
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// OPENROUTER_API_KEY (the docs assistant, POST /ask) is the repo's Actions
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// secret of that name, put by deploy.yml before every deploy.
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}
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