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\"\";\n if (!VALID_KEYS.has(key)) {\n return new Response(JSON.stringify({ error: \"unauthorized\" }), {\n status: 401,\n headers: { \"content-type\": \"application/json\" },\n });\n }\n return null;\n}\n\nexport async function embedText(text: string): Promise {\n const embed = await getBiEncoder();\n const out = await embed(text, { pooling: \"mean\", normalize: true });\n if (!(out instanceof Tensor)) {\n throw new Error(\"Expected Tensor from bi-encoder\");\n }\n return flattenEmbedding(out.tolist());\n}\n\nexport async function biRank(query: string, docs: string[]) {\n const qEmb = await embedText(query);\n const dEmbeds = await Promise.all(docs.map(embedText));\n return dEmbeds.map((e, i) => ({\n index: i,\n score: cosineSimilarity(qEmb, e),\n })).sort((a, b) => b.score - a.score);\n}\n\nexport async function crossScore(query: string, doc: string): Promise {\n const cross = await getCrossEncoder();\n const res = await cross(`${query} ${doc}`);\n // assume first label score is relevant; adjust per model\n const first = Array.isArray(res) ? res[0] : res;\n const score = typeof first?.score === \"number\" ? first.score : 0;\n return score;\n}\n\nexport async function hybridRank(\n query: string,\n docs: string[],\n alpha: number,\n topK: number,\n) {\n const biScores = await biRank(query, docs);\n const candidates = biScores.slice(0, Math.min(topK, docs.length));\n const crossScores = await Promise.all(\n candidates.map((c) => crossScore(query, docs[c.index])),\n );\n return candidates\n .map((c, i) => ({\n index: c.index,\n bi: c.score,\n cross: crossScores[i],\n hybrid: alpha * crossScores[i] + (1 - alpha) * c.score,\n }))\n .sort((a, b) => b.hybrid - a.hybrid);\n}","import { pipeline, Tensor } from \"npm:@xenova/transformers\";\n\ntype Embedding = number[];\n\nlet biEncoderPromise: Promise | null = null;\nlet crossEncoderPromise: Promise | null = null;\n\nfunction getBiEncoder() {\n if (!biEncoderPromise) {\n biEncoderPromise = pipeline(\n \"feature-extraction\",\n \"Xenova/all-MiniLM-L6-v2\",\n );\n }\n return biEncoderPromise;\n}\n\nfunction getCrossEncoder() {\n if (!crossEncoderPromise) {\n // any cross-encoder / NLI / pairwise scoring model\n crossEncoderPromise = pipeline(\n \"text-classification\",\n \"Xenova/nli-deberta-v3-small\",\n );\n }\n return crossEncoderPromise;\n}\n\nfunction flattenEmbedding(x: unknown): Embedding {\n if (Array.isArray(x) && Array.isArray(x[0])) return x[0] as number[];\n if (Array.isArray(x)) return x as number[];\n throw new Error(\"Unexpected embedding shape\");\n}\n\nfunction cosineSimilarity(a: Embedding, b: Embedding): number {\n if (a.length !== b.length) throw new Error(\"Length mismatch\");\n let dot = 0, na = 0, nb = 0;\n for (let i = 0; i < a.length; i++) {\n const ai = a[i]!;\n const bi = b[i]!;\n dot += ai * bi;\n na += ai * ai;\n nb += bi * bi;\n }\n return dot / (Math.sqrt(na) * Math.sqrt(nb) + 1e-12);\n}\n\nconst VALID_KEYS = new Set([\"YOUR_API_KEY_HERE\"]);\n\nexport async function requireAuth(req: Request) {\n const key = req.headers.get(\"x-api-key\") ?? \"\";\n if (!VALID_KEYS.has(key)) {\n return new Response(JSON.stringify({ error: \"unauthorized\" }), {\n status: 401,\n headers: { \"content-type\": \"application/json\" },\n });\n }\n return null;\n}\n\nexport async function embedText(text: string): Promise {\n const embed = await getBiEncoder();\n const out = await embed(text, { pooling: \"mean\", normalize: true });\n if (!(out instanceof Tensor)) {\n throw new Error(\"Expected Tensor from bi-encoder\");\n }\n return flattenEmbedding(out.tolist());\n}\n\nexport async function biRank(query: string, docs: string[]) {\n const qEmb = await embedText(query);\n const dEmbeds = await Promise.all(docs.map(embedText));\n return dEmbeds.map((e, i) => ({\n index: i,\n score: cosineSimilarity(qEmb, e),\n })).sort((a, b) => b.score - a.score);\n}\n\nexport async function crossScore(query: string, doc: string): Promise {\n const cross = await getCrossEncoder();\n const res = await cross(`${query} ${doc}`);\n // assume first label score is relevant; adjust per model\n const first = Array.isArray(res) ? res[0] : res;\n const score = typeof first?.score === \"number\" ? first.score : 0;\n return score;\n}\n\nexport async function hybridRank(\n query: string,\n docs: string[],\n alpha: number,\n topK: number,\n) {\n const biScores = await biRank(query, docs);\n const candidates = biScores.slice(0, Math.min(topK, docs.length));\n const crossScores = await Promise.all(\n candidates.map((c) => crossScore(query, docs[c.index])),\n );\n return candidates\n .map((c, i) => ({\n index: c.index,\n bi: c.score,\n cross: crossScores[i],\n hybrid: alpha * crossScores[i] + (1 - alpha) * c.score,\n }))\n .sort((a, b) => b.hybrid - a.hybrid);\n}","createdAt",["D",1779535145654],"branchVersion","branchId","17efdd52-5698-11f1-81ea-ee650bb23af1","id","17ef466c-5698-11f1-81ea-ee650bb23af1","DualScore",["D",1779534666176],"deletedAt","legacyEnvVars","privacy","public","httpPrivacy","description","Document scoring and search retrieval","imageUrl","2c6d46b0-54dd-11f0-a86c-6fbc2b29331a","pinnedFileId","pinPreview","pinMigrated","screenshotVersion","likeCount",0,"orgId","850db142-aa5e-4914-bceb-1e2e085ae4c5","tursoName","tursoHostname","tursoMeasuredAt","pinned","userPerm","r","valPerm","blobPerm","rw","emailPerm","sqlitePerm","projectPerm","telemetryPerm","user",{"_95":94,"_102":98},"org",{"_95":94,"_96":-5,"_97":98,"_18":55,"_99":100,"_101":25},"branch",{"_13":84,"_32":85,"_43":42,"_86":44,"_87":-5,"_88":-5,"_89":-5,"_90":-5,"_91":-5,"_92":45,"_93":94},"isOwned",32,"main","projectId","forkedBranchId","forkedBranchVersion","forkedProjectPrivacy","forkedProjectId","forkedProjectOrgId","projectName","userHandle","ziggyware","handle","displayName","avatar","https://img.clerk.com/eyJ0eXBlIjoicHJveHkiLCJzcmMiOiJodHRwczovL2ltYWdlcy5jbGVyay5kZXYvb2F1dGhfZ2l0aHViL2ltZ18yekJHRDE5SGVoUHUzUENQaXY2MTRkT3h0cncifQ","tier","free","canRestrictVals","profileImageUrl","branchName","","adoptOrgId",{"_43":44,"_32":45,"_38":177,"_47":-5,"_48":25,"_49":50,"_51":50,"_52":53,"_54":-5,"_18":55,"_56":-5,"_57":25,"_58":-5,"_59":-5,"_60":61,"_62":63,"_64":-5,"_65":-5,"_66":-5,"_67":-5,"_68":69,"_70":69,"_71":72,"_73":72,"_74":72,"_75":69,"_76":69,"_77":178,"_79":179,"_81":180,"_83":25},"tree",[164,165,166],"files",[164,165,166],"counts",{"_153":61,"_154":155,"_156":61,"_157":158,"_159":160},"contents",[126,127,128],"upstreamProject","upstreamBranch","emptyEnvVars","flags",[],"hasHttpFiles",true,"grants","orgs","customDomains",{},{"_43":145,"_32":146,"_30":147,"_132":-5,"_41":42,"_40":148,"_134":121,"_38":149,"_13":150,"_33":137,"_35":151,"_24":25,"_139":-5,"_27":152},{"_43":141,"_32":28,"_30":31,"_132":-5,"_41":42,"_40":14,"_134":25,"_38":142,"_13":143,"_33":34,"_35":37,"_24":25,"_139":-5,"_27":144},{"_43":129,"_32":130,"_30":131,"_132":-5,"_41":42,"_40":133,"_134":121,"_38":135,"_13":136,"_33":137,"_35":138,"_24":25,"_139":-5,"_27":140},"d8a9ac6c-5698-11f1-95e3-ee650bb23af1","rank.ts","caec8fd6-5698-11f1-82d7-ee650bb23af1","parentId",27,"latest",["D",1779534989508],5,"http","// @you/rank\nimport { biRank, requireAuth } from \"./hybridCore.ts\";\n\nexport default async function (req: Request): Promise {\n const auth = await requireAuth(req);\n if (auth) return auth;\n\n const body = await req.json().catch(() => ({}));\n const query = body.query as string | undefined;\n const documents = body.documents as string[] | undefined;\n\n if (!query || !Array.isArray(documents) || documents.length === 0) {\n return new Response(\n JSON.stringify({ error: \"missing 'query' or 'documents'\" }),\n {\n status: 400,\n headers: { \"content-type\": \"application/json\" },\n },\n );\n }\n\n try {\n const scores = await biRank(query, documents);\n return new Response(\n JSON.stringify({\n scores: scores.map((s) => ({\n index: s.index,\n doc: documents[s.index],\n score: s.score,\n })),\n }),\n {\n headers: { \"content-type\": \"application/json\" },\n },\n );\n } catch (e: any) {\n return new Response(JSON.stringify({ error: String(e?.message ?? 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Diff · v30