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process from \"node:process\";\nconst BASE_COST = 150;\nconst USD_PER_POINT = 30 / 1_000_000;\nconst RERANK_MODELS = [\"cohere/rerank-v3.5\", \"rerank-4-fast\", \"rerank-4-fast-pro\"] as const;\nconst GROQ_MODELS = [\n \"compound-mini\",\n \"compound\",\n \"meta-llama/llama-4-scout-17b-16e-instruct\",\n \"llama-3.3-70b-versatile\",\n] as const;\nfunction verifyBotKey(req: Request): boolean {\n const botKey = process.env.BOT_ACCESS_KEY;\n if (!botKey) return false;\n const authHeader = req.headers.get(\"Authorization\") ?? \"\";\n const token = authHeader.startsWith(\"Bearer \")\n ? authHeader.slice(7).trim()\n : authHeader.trim();\n return token === botKey;\n}\nfunction formatUSD(amount: number): string {\n if (amount === 0) return \"$0.00\";\n const fixed = amount.toFixed(6);\n const trimmed = fixed\n .replace(/(\\.\\d*?[1-9])0+$/, \"$1\")\n .replace(/\\.00$/, \".00\");\n return `$${trimmed}`;\n}\ninterface SearchResult {\n title: string;\n url: string;\n snippet: string;\n quotes: string[];\n relevanceScore: number;\n source: string;\n timestamp?: string;\n}\nfunction extractRelevantQuotes(content: string, query: string): string[] {\n const quotes: string[] = [];\n const queryTerms = query.toLowerCase().split(/\\s+/).filter((t) => t.length > 2);\n const sentences = content\n .split(/[.!?]+/)\n .map((s) => s.trim())\n .filter((s) => s.length > 20);\n sentences.forEach((sentence) => {\n const lowerSentence = sentence.toLowerCase();\n const matchCount = queryTerms.filter((term) =>\n lowerSentence.includes(term)\n ).length;\n if (matchCount >= Math.min(2, queryTerms.length)) {\n const cleanQuote = sentence.replace(/\\s+/g, \" \").trim();\n if (cleanQuote.length > 30 && cleanQuote.length < 300)\n quotes.push(cleanQuote);\n }\n });\n return [...new Set(quotes)].slice(0, 5);\n}\nfunction calculateRelevance(content: string, query: string): number {\n const lowerContent = content.toLowerCase();\n const queryTerms = query.toLowerCase().split(/\\s+/);\n let score = 0;\n queryTerms.forEach((term) => {\n const regex = new RegExp(`\\\\b${term}\\\\b`, \"gi\");\n const matches = lowerContent.match(regex);\n if (matches) score += matches.length * 2;\n });\n if (lowerContent.includes(query.toLowerCase())) score += 20;\n return Math.min(score, 100);\n}\nasync function searchBrave(query: string): Promise {\n const results: SearchResult[] = [];\n const apiKey = process.env.BRAVE_API_KEY;\n if (!apiKey) return results;\n try {\n const response = await fetch(\n `https://api.search.brave.com/res/v1/web/search?q=${encodeURIComponent(query)}&count=10`,\n {\n headers: {\n Accept: \"application/json\",\n \"X-Subscription-Token\": apiKey,\n },\n signal: AbortSignal.timeout(8000),\n }\n );\n if (response.ok) {\n const data = await response.json();\n (data.web?.results ?? []).forEach((r: any) => {\n const content = `${r.title} ${r.description}`;\n results.push({\n title: r.title,\n url: r.url,\n snippet: r.description || \"\",\n quotes: extractRelevantQuotes(content, query),\n relevanceScore: calculateRelevance(content, query),\n source: new URL(r.url).hostname,\n timestamp: r.age || new Date().toISOString(),\n });\n });\n }\n } catch (error) {\n console.error(\"Brave search failed:\", error);\n }\n return results;\n}\nasync function searchSerper(query: string): Promise {\n const results: SearchResult[] = [];\n const serperKey = process.env.SERPER_API_KEY;\n if (!serperKey) return results;\n try {\n const response = await fetch(\"https://google.serper.dev/search\", {\n method: \"POST\",\n headers: {\n \"X-API-KEY\": serperKey,\n \"Content-Type\": \"application/json\",\n },\n body: JSON.stringify({ q: query, num: 10 }),\n signal: AbortSignal.timeout(8000),\n });\n if (response.ok) {\n const data = await response.json();\n (data.organic ?? []).forEach((r: any) => {\n const content = `${r.title} ${r.snippet}`;\n results.push({\n title: r.title,\n url: r.link,\n snippet: r.snippet || \"\",\n quotes: extractRelevantQuotes(content, query),\n relevanceScore: calculateRelevance(content, query),\n source: new URL(r.link).hostname,\n });\n });\n }\n } catch (error) {\n console.error(\"Serper failed:\", error);\n }\n return results;\n}\nasync function searchGoogleCustom(query: string): Promise {\n const results: SearchResult[] = [];\n const apiKey = process.env.GOOGLE_API_KEY;\n const cx = process.env.GOOGLE_CX;\n if (!apiKey || !cx) return results;\n try {\n const response = await fetch(\n `https://www.googleapis.com/customsearch/v1?key=${apiKey}&cx=${cx}&q=${encodeURIComponent(query)}&num=10`,\n { signal: AbortSignal.timeout(8000) }\n );\n if (response.ok) {\n const data = await response.json();\n (data.items ?? []).forEach((item: any) => {\n const content = `${item.title} ${item.snippet}`;\n results.push({\n title: item.title,\n url: item.link,\n snippet: item.snippet || \"\",\n quotes: extractRelevantQuotes(content, query),\n relevanceScore: calculateRelevance(content, query),\n source: new URL(item.link).hostname,\n });\n });\n }\n } catch (error) {\n console.error(\"Google Custom Search failed:\", error);\n }\n return results;\n}\nasync function gatherResults(query: string): Promise {\n const variations = [query, `${query} explained`, `${query} latest research`];\n const tasks = variations.flatMap((q) => [\n searchBrave(q),\n searchSerper(q),\n searchGoogleCustom(q),\n ]);\n const settled = await Promise.allSettled(tasks);\n const all: SearchResult[] = [];\n settled.forEach((r) => {\n if (r.status === \"fulfilled\") all.push(...r.value);\n });\n return all\n .filter((r, idx, arr) => arr.findIndex((t) => t.url === r.url) === idx)\n .sort((a, b) => b.relevanceScore - a.relevanceScore)\n .slice(0, 20);\n}\n// Stage 1: OpenRouter Cohere rerank — returns results re-sorted by neural relevance.\n// Tries RERANK_MODELS in order; throws if all fail.\nasync function rerankWithOpenRouter(\n query: string,\n results: SearchResult[]\n): Promise {\n const apiKey = process.env.OPENROUTER_API_KEY;\n if (!apiKey) throw new Error(\"OPENROUTER_API_KEY not set\");\n const documents = results.map((r) => `${r.title}\\n${r.snippet}`);\n let lastError: Error | null = null;\n for (const model of RERANK_MODELS) {\n try {\n const response = await fetch(\"https://openrouter.ai/api/v1/rerank\", {\n method: \"POST\",\n headers: {\n Authorization: `Bearer ${apiKey}`,\n \"Content-Type\": \"application/json\",\n \"HTTP-Referer\": \"https://deep-search.app\",\n \"X-Title\": \"Deep Search Engine\",\n },\n body: JSON.stringify({\n model,\n query,\n documents,\n top_n: Math.min(15, results.length),\n }),\n signal: AbortSignal.timeout(12000),\n });\n if (!response.ok) {\n const body = await response.text().catch(() => \"\");\n throw new Error(`OpenRouter rerank ${model} HTTP ${response.status}: ${body}`);\n }\n const data = await response.json();\n const ranked: SearchResult[] = (data.results ?? [])\n .sort((a: any, b: any) => b.relevance_score - a.relevance_score)\n .map((r: any) => ({\n ...results[r.index],\n relevanceScore: Math.round(r.relevance_score * 100),\n }));\n if (ranked.length > 0) return ranked;\n throw new Error(`${model} returned empty results`);\n } catch (err) {\n lastError = err as Error;\n console.error(`Rerank ${model} failed:`, err);\n }\n }\n throw lastError ?? new Error(\"All rerank models exhausted\");\n}\n// Stage 2: Groq synthesis — iterates keys × models, returns on first success.\nasync function synthesizeWithGroq(\n query: string,\n results: SearchResult[]\n): Promise {\n const groqKeys = [\n process.env.GROQ_API_KEY,\n process.env.GROQ_API_KEY2,\n process.env.GROQ_API_KEY3,\n process.env.GROQ_API_KEY4,\n ].filter(Boolean) as string[];\n if (groqKeys.length === 0) throw new Error(\"No GROQ_API_KEY set\");\n const systemPrompt =\n \"You are a deep search analyst. Synthesize search results into a comprehensive, structured report with key findings, relevant quotes, and source attributions. Prioritize accuracy and depth.\";\n const userPrompt =\n `Query: \"${query}\"\\n\\nSearch Results (${results.length} sources):\\n` +\n `${JSON.stringify(results, null, 2)}\\n\\n` +\n `Produce:\\n1. Executive summary\\n2. Key findings with direct quotes\\n3. Source credibility breakdown\\n4. Conclusion and knowledge gaps`;\n for (const model of GROQ_MODELS) {\n for (const apiKey of groqKeys) {\n try {\n const response = await fetch(\n \"https://api.groq.com/openai/v1/chat/completions\",\n {\n method: \"POST\",\n headers: {\n Authorization: `Bearer ${apiKey}`,\n \"Content-Type\": \"application/json\",\n },\n body: JSON.stringify({\n model,\n messages: [\n { role: \"system\", content: systemPrompt },\n { role: \"user\", content: userPrompt },\n ],\n stream: false,\n max_tokens: 8192,\n temperature: 0.3,\n }),\n signal: AbortSignal.timeout(30000),\n }\n );\n if (!response.ok)\n throw new Error(`Groq ${model} HTTP ${response.status}`);\n const data = await response.json();\n const text: string = data.choices?.[0]?.message?.content ?? \"\";\n if (text.length > 0) return text;\n } catch (err) {\n console.error(`Groq ${model} failed:`, err);\n }\n }\n }\n throw new Error(\"All Groq models exhausted\");\n}\n// Stage 3 (final fallback): raw Brave-only dump with no AI synthesis.\nasync function braveFallback(\n query: string,\n send: SendEventFn\n): Promise {\n const results = await searchBrave(query);\n if (results.length === 0) {\n send(\"text\", {\n text:\n `❌ No results found. Try:\\n` +\n `- Refining query terms\\n` +\n `- More specific keywords\\n` +\n `- Different phrasing\\n\\n` +\n `**Alternative engines:**\\n` +\n `- [Google](https://www.google.com/search?q=${encodeURIComponent(query)})\\n` +\n `- [Bing](https://www.bing.com/search?q=${encodeURIComponent(query)})\\n` +\n `- [DuckDuckGo](https://duckduckgo.com/?q=${encodeURIComponent(query)})`,\n });\n return;\n }\n send(\"text\", {\n text: `## 📋 Brave Search Results (${results.length} sources)\\n\\n`,\n });\n results.forEach((result, idx) => {\n send(\"text\", {\n text:\n `### ${idx + 1}. ${result.title}\\n` +\n `**Source:** ${result.source} | **Relevance:** ${result.relevanceScore}%\\n` +\n `**URL:** ${result.url}\\n\\n` +\n `**Snippet:** ${result.snippet.substring(0, 200)}...\\n\\n` +\n `**Key Quotes:**\\n${result.quotes.map((q) => `> \"${q}\"`).join(\"\\n\\n\")}\\n\\n` +\n `---\\n\\n`,\n });\n });\n send(\"text\", {\n text: `\\n\\n## 🔗 Sources\\n${results\n .map((r, i) => `${i + 1}. [${r.source}](${r.url})`)\n .join(\"\\n\")}\\n`,\n });\n}\nasync function getResponse(req: Query, send: SendEventFn) {\n send(\"meta\", { content_type: \"text/markdown\", suggested_replies: true });\n const searchQuery =\n req.query[req.query.length - 1].content;\n send(\"text\", { text: `🔍 Deep Search Initiated...\\n\\n` });\n send(\"text\", { text: `⏳ Gathering results in parallel...\\n\\n` });\n let gathered: SearchResult[] = [];\n try {\n gathered = await gatherResults(searchQuery);\n send(\"text\", {\n text: `✅ Collected ${gathered.length} deduplicated results\\n\\n`,\n });\n } catch (err) {\n send(\"text\", {\n text: `⚠️ Search aggregation error: ${(err as Error).message}\\n\\n`,\n });\n }\n if (gathered.length === 0) {\n send(\"text\", { text: `🔄 Falling back to Brave direct search...\\n\\n` });\n await braveFallback(searchQuery, send);\n send(\"done\", {});\n return;\n }\n // Stage 1: rerank\n let ranked = gathered;\n try {\n send(\"text\", { text: `🎯 Reranking with Cohere...\\n\\n` });\n ranked = await rerankWithOpenRouter(searchQuery, gathered);\n send(\"text\", {\n text: `✅ Reranked to ${ranked.length} top results\\n\\n`,\n });\n } catch (err) {\n console.error(\"Rerank pipeline failed:\", err);\n send(\"text\", {\n text: `⚠️ Rerank unavailable — using heuristic scores\\n\\n`,\n });\n ranked = gathered.slice(0, 15);\n }\n // Stage 2: Groq synthesis\n send(\"text\", { text: `🤖 Synthesizing with Groq...\\n\\n` });\n try {\n const analysis = await synthesizeWithGroq(searchQuery, ranked);\n send(\"text\", { text: analysis });\n send(\"text\", {\n text: `\\n\\n## 🔗 Sources\\n${ranked\n .map((r, i) => `${i + 1}. [${r.source}](${r.url})`)\n .join(\"\\n\")}\\n`,\n });\n } catch (err) {\n console.error(\"Groq synthesis failed:\", err);\n send(\"text\", {\n text: `⚠️ AI synthesis failed — falling back to Brave raw results\\n\\n`,\n });\n await braveFallback(searchQuery, send);\n }\n send(\"done\", {});\n}\nasync function getBotSettings(): Promise {\n const costUSD = BASE_COST * USD_PER_POINT;\n const rateCard =\n \"| Type | Rate (USD) | Rate (Points) |\\n\" +\n \"|------|--------------|------------|\\n\" +\n `| Total Cost | ${formatUSD(costUSD)}/message | ${BASE_COST} points |\\n`;\n return {\n allow_attachments: false,\n expand_text_attachments: false,\n enable_multi_bot_chat_prompting: true,\n enable_suggested_replies: true,\n rate_card: rateCard,\n supports_system_messages: true,\n suggested_replies: true,\n };\n}\ntype BotSettings = {\n allow_attachments?: boolean;\n expand_text_attachments?: boolean;\n enable_multi_bot_chat_prompting?: boolean;\n enable_suggested_replies?: boolean;\n rate_card?: string;\n supports_system_messages?: boolean;\n suggested_replies?: boolean;\n};\ntype Query = {\n version: string;\n type: \"query\";\n query: {\n role: \"system\" | \"user\" | \"bot\";\n content: string;\n content_type: string;\n timestamp: number;\n message_id: string;\n feedback: { type: \"like\" | \"dislike\"; reason?: string }[];\n attachments: {\n url: string;\n content_type: string;\n name: string;\n parsed_content?: string;\n }[];\n }[];\n message_id: string;\n user_id: string;\n conversation_id: string;\n metadata: string;\n language_code: string;\n};\ntype Events = {\n meta: { content_type: string; suggested_replies?: boolean };\n text: { text: string };\n replace_response: { text: string };\n suggested_reply: { text: string };\n error: { allow_retry?: boolean; text: string };\n done: {};\n};\ntype SendEventFn = (\n eventName: EventName,\n data: Events[EventName]\n) => void;\nfunction encodeEvent(event: string, data: any = {}) {\n return new 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