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reason?: string }[];\n attachments: {\n url: string;\n content_type: string;\n name: string;\n parsed_content?: string;\n }[];\n}\n\ninterface Query {\n version: string;\n type: \"query\";\n query: ChatMessage[];\n message_id: string;\n user_id: string;\n conversation_id: string;\n metadata: string;\n language_code: string;\n}\n\ninterface 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 cost_label?: string;\n supports_system_messages?: boolean;\n suggested_replies?: boolean;\n}\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};\n\ntype SendEvent = (event: E, data: Events[E]) => void;\n\ninterface LLMConfig {\n url: string;\n apiKey: string;\n model: string;\n headers?: Record;\n}\n\nfunction escapeRegExp(value: string): string {\n return value.replace(/[.*+?^${}()|[\\]\\\\]/g, \"\\\\$&\");\n}\n\nfunction normalizeWhitespace(text: string): string {\n return text.replace(/\\s+/g, \" \").trim();\n}\n\nfunction extractQuotes(text: string, query: string): string[] {\n const terms = query\n .toLowerCase()\n .split(/\\s+/)\n .map((t) => t.trim())\n .filter((t) => t.length > 2);\n\n if (terms.length === 0) return [];\n\n const threshold = Math.min(2, terms.length);\n\n const sentences = text\n .split(/[.!?]+/)\n .map((s) => normalizeWhitespace(s))\n .filter((s) => s.length > 30 && s.length < 300);\n\n const seen = new Set();\n const quotes: string[] = [];\n\n for (const sentence of sentences) {\n const lower = sentence.toLowerCase();\n const hits = terms.filter((t) => lower.includes(t)).length;\n if (hits >= threshold && !seen.has(sentence)) {\n seen.add(sentence);\n quotes.push(sentence);\n if (quotes.length >= 5) break;\n }\n }\n\n return quotes;\n}\n\nfunction scoreRelevance(text: string, query: string): number {\n const lower = text.toLowerCase();\n const normalizedQuery = query.toLowerCase();\n const terms = normalizedQuery\n .split(/\\s+/)\n .map((t) => t.trim())\n .filter(Boolean);\n\n let score = 0;\n\n for (const term of terms) {\n const safe = escapeRegExp(term);\n const matches = lower.match(new RegExp(`\\\\b${safe}\\\\b`, \"gi\"));\n if (matches) score += matches.length * 2;\n }\n\n if (lower.includes(normalizedQuery)) score += 20;\n\n if (terms.length > 1) {\n const adjacent = terms.slice(0, -1).filter((t, i) => {\n const pair = `${t} ${terms[i + 1]}`;\n return lower.includes(pair);\n }).length;\n score += adjacent * 4;\n }\n\n return Math.min(score, 100);\n}\n\nfunction parseResult(\n raw: { title: string; url: string; snippet: string; age?: string },\n query: string,\n engine: string\n): SearchResult | null {\n let hostname: string;\n\n try {\n hostname = new URL(raw.url).hostname;\n } catch {\n return null;\n }\n\n const title = normalizeWhitespace(raw.title || \"\");\n const snippet = normalizeWhitespace(raw.snippet || \"\");\n const text = `${title} ${snippet}`.trim();\n\n if (!title || !raw.url) return null;\n\n return {\n title,\n url: raw.url,\n snippet,\n quotes: extractQuotes(text, query),\n relevance: scoreRelevance(text, query),\n hostname,\n timestamp: raw.age,\n engine,\n };\n}\n\nfunction dedupeAndRank(results: SearchResult[]): SearchResult[] {\n const seen = new Set();\n\n return results\n .filter((r) => {\n const normalizedUrl = r.url.replace(/\\/+$/, \"\");\n if (seen.has(normalizedUrl)) return false;\n seen.add(normalizedUrl);\n return true;\n })\n .sort((a, b) => {\n if (b.relevance !== a.relevance) return b.relevance - a.relevance;\n if ((b.quotes?.length ?? 0) !== (a.quotes?.length ?? 0)) {\n return (b.quotes?.length ?? 0) - (a.quotes?.length ?? 0);\n }\n return a.hostname.localeCompare(b.hostname);\n })\n .slice(0, MAX_RESULTS);\n}\n\nfunction buildQueryVariations(query: string): string[] {\n const base = query.trim();\n return [\n base,\n `\"${base}\"`,\n `${base} explained`,\n `what is ${base}`,\n `${base} overview`,\n `${base} analysis`,\n `${base} source`,\n `${base} documentation`,\n ].filter((q, i, arr) => q.length > 0 && arr.indexOf(q) === i);\n}\n\nasync function searchBrave(query: string): Promise {\n const key = process.env.BRAVE_API_KEY;\n if (!key) return [];\n\n const results: SearchResult[] = [];\n\n for (const q of buildQueryVariations(query)) {\n if (results.length >= MAX_RESULTS) break;\n\n try {\n const res = await fetch(\n `https://api.search.brave.com/res/v1/web/search?q=${encodeURIComponent(q)}&count=20`,\n {\n headers: {\n Accept: \"application/json\",\n \"X-Subscription-Token\": key,\n },\n signal: AbortSignal.timeout(SEARCH_TIMEOUT_MS),\n }\n );\n\n if (!res.ok) continue;\n\n const data = await res.json();\n\n for (const item of data.web?.results ?? []) {\n const parsed = parseResult(\n {\n title: item.title,\n url: item.url,\n snippet: item.description,\n age: item.age,\n },\n query,\n \"brave\"\n );\n\n if (parsed) results.push(parsed);\n }\n } catch (err) {\n console.error(`Brave search failed for \"${q}\":`, err);\n }\n }\n\n return results;\n}\n\nasync function searchSerper(query: string): Promise {\n const key = process.env.SERPER_API_KEY;\n if (!key) return [];\n\n try {\n const res = await fetch(\"https://google.serper.dev/search\", {\n method: \"POST\",\n headers: {\n \"X-API-KEY\": key,\n \"Content-Type\": \"application/json\",\n },\n body: JSON.stringify({ q: query, num: 10 }),\n signal: AbortSignal.timeout(FALLBACK_TIMEOUT_MS),\n });\n\n if (!res.ok) return [];\n\n const data = await res.json();\n\n return (data.organic ?? [])\n .map((item: any) =>\n parseResult(\n {\n title: item.title,\n url: item.link,\n snippet: item.snippet,\n },\n query,\n \"serper\"\n )\n )\n .filter(Boolean) as SearchResult[];\n } catch (err) {\n console.error(\"Serper search failed:\", err);\n return [];\n }\n}\n\nasync function searchGoogle(query: string): Promise {\n const apiKey = process.env.GOOGLE_API_KEY;\n const cx = process.env.GOOGLE_CX;\n if (!apiKey || !cx) return [];\n\n try {\n const res = await fetch(\n `https://www.googleapis.com/customsearch/v1?key=${apiKey}&cx=${cx}&q=${encodeURIComponent(query)}&num=10`,\n { signal: AbortSignal.timeout(FALLBACK_TIMEOUT_MS) }\n );\n\n if (!res.ok) return [];\n\n const data = await res.json();\n\n return (data.items ?? [])\n .map((item: any) =>\n parseResult(\n {\n title: item.title,\n url: item.link,\n snippet: item.snippet,\n },\n query,\n \"google-cse\"\n )\n )\n .filter(Boolean) as SearchResult[];\n } catch (err) {\n console.error(\"Google search failed:\", err);\n return [];\n }\n}\n\nasync function searchDuckDuckGo(query: string): Promise {\n const results: SearchResult[] = [];\n\n for (const q of buildQueryVariations(query).slice(0, 4)) {\n try {\n const url = `https://html.duckduckgo.com/html/?q=${encodeURIComponent(q)}`;\n\n const res = await fetch(url, {\n headers: {\n \"User-Agent\":\n \"Mozilla/5.0 (compatible; DeepResearchBot/1.0; +https://poe.com)\",\n Accept: \"text/html,application/xhtml+xml\",\n },\n signal: AbortSignal.timeout(FALLBACK_TIMEOUT_MS),\n });\n\n if (!res.ok) continue;\n\n const html = await res.text();\n\n const resultBlocks = html.split('class=\"result\"');\n\n for (const block of resultBlocks) {\n const titleMatch =\n block.match(/class=\"result__a\"[^>]*href=\"([^\"]+)\"[^>]*>([\\s\\S]*?)<\\/a>/i) ||\n block.match(/class=\"result__title\"[\\s\\S]*?]*href=\"([^\"]+)\"[^>]*>([\\s\\S]*?)<\\/a>/i);\n\n const snippetMatch =\n block.match(/class=\"result__snippet\"[^>]*>([\\s\\S]*?)<\\/a>/i) ||\n block.match(/class=\"result__snippet\"[^>]*>([\\s\\S]*?)<\\/div>/i);\n\n if (!titleMatch) continue;\n\n const rawUrl = titleMatch[1]\n .replace(/&/g, \"&\")\n .trim();\n const rawTitle = titleMatch[2]\n .replace(/<[^>]+>/g, \" \")\n .replace(/&/g, \"&\")\n .trim();\n const rawSnippet = snippetMatch\n ? snippetMatch[1].replace(/<[^>]+>/g, \" \").replace(/&/g, \"&\").trim()\n : \"\";\n\n let finalUrl = rawUrl;\n\n try {\n if (rawUrl.startsWith(\"//\")) {\n finalUrl = `https:${rawUrl}`;\n } else if (rawUrl.startsWith(\"/l/?\")) {\n const ddgUrl = new URL(`https://html.duckduckgo.com${rawUrl}`);\n const uddg = ddgUrl.searchParams.get(\"uddg\");\n if (uddg) finalUrl = decodeURIComponent(uddg);\n }\n } catch {\n continue;\n }\n\n const parsed = parseResult(\n {\n title: rawTitle,\n url: finalUrl,\n snippet: rawSnippet,\n },\n query,\n \"duckduckgo\"\n );\n\n if (parsed) results.push(parsed);\n }\n } catch (err) {\n console.error(`DuckDuckGo search failed for \"${q}\":`, err);\n }\n }\n\n return results;\n}\n\nfunction getSearxngInstances(): string[] {\n const envList = process.env.SEARXNG_INSTANCES\n ?.split(\",\")\n .map((s) => s.trim())\n .filter(Boolean);\n\n return envList && envList.length > 0 ? envList : DEFAULT_SEARXNG_INSTANCES;\n}\n\nasync function searchSearXNG(query: string): Promise {\n const instances = getSearxngInstances();\n const allResults: SearchResult[] = [];\n\n for (const instance of instances) {\n if (allResults.length >= MAX_RESULTS) break;\n\n try {\n const url =\n `${instance}/search?q=${encodeURIComponent(query)}` +\n `&format=json&categories=general&language=all`;\n\n const res = await fetch(url, {\n headers: {\n Accept: \"application/json\",\n \"User-Agent\":\n \"Mozilla/5.0 (compatible; DeepResearchBot/1.0; +https://poe.com)\",\n },\n signal: AbortSignal.timeout(FALLBACK_TIMEOUT_MS),\n });\n\n if (!res.ok) continue;\n\n const data = await res.json();\n\n for (const item of data.results ?? []) {\n const parsed = parseResult(\n {\n title: item.title,\n url: item.url,\n snippet: item.content || item.snippet || \"\",\n age: item.publishedDate,\n },\n query,\n `searxng:${new URL(instance).hostname}`\n );\n\n if (parsed) allResults.push(parsed);\n }\n } catch (err) {\n console.error(`SearXNG search failed for \"${instance}\":`, err);\n }\n }\n\n return allResults;\n}\n\nasync function search(query: string): Promise {\n const aggregate: SearchResult[] = [];\n\n const brave = await searchBrave(query);\n aggregate.push(...brave);\n\n if (aggregate.length < 10) {\n aggregate.push(...(await searchDuckDuckGo(query)));\n }\n\n if (aggregate.length < 10) {\n aggregate.push(...(await searchSearXNG(query)));\n }\n\n if (aggregate.length < 10) {\n aggregate.push(...(await searchSerper(query)));\n }\n\n if (aggregate.length < 10) {\n aggregate.push(...(await searchGoogle(query)));\n }\n\n return dedupeAndRank(aggregate);\n}\n\nfunction buildPrompt(\n query: string,\n results: SearchResult[]\n): { system: string; user: string } {\n const sources = results\n .map((r, i) => {\n return [\n `[${i + 1}] ${r.title}`,\n `URL: ${r.url}`,\n `Host: ${r.hostname}`,\n `Engine: ${r.engine}`,\n r.timestamp ? `Timestamp: ${r.timestamp}` : \"\",\n `Snippet: ${r.snippet || \"(none)\"}`,\n r.quotes.length\n ? `Relevant excerpts: ${r.quotes.map((q) => `\"${q}\"`).join(\"; \")}`\n : \"\",\n ]\n .filter(Boolean)\n .join(\"\\n\");\n })\n .join(\"\\n\\n\");\n\n return {\n system:\n \"You are an elite deep research analyst. Your task is to synthesize search results into a \" +\n \"detailed, careful, evidence-based report. Cite sources by number like [1], [2]. \" +\n \"Do not fabricate facts. Distinguish clearly between well-supported facts, plausible \" +\n \"inferences, open questions, and conflicts between sources. \" +\n \"Be comprehensive and significantly more detailed than a normal assistant response. \" +\n \"Structure the response with: Executive Summary, Key Findings, Detailed Analysis, \" +\n \"Source Comparison, Caveats and Uncertainties, and Practical Takeaways. \" +\n \"Where useful, include bullet points and short subsections. \" +\n \"If sources are weak or incomplete, say so explicitly.\",\n user:\n `Research query: \"${query}\"\\n\\n` +\n `Source set:\\n${sources}\\n\\n` +\n \"Write a long-form research answer with clear citations. Include:\\n\" +\n \"1. A concise executive summary.\\n\" +\n \"2. A detailed analysis with multiple paragraphs.\\n\" +\n \"3. Areas of agreement and disagreement across sources.\\n\" +\n \"4. Important caveats, missing context, and uncertainty.\\n\" +\n \"5. A practical bottom line.\\n\" +\n \"6. A brief appendix listing the most useful sources.\\n\",\n };\n}\n\nasync function callLLM(\n config: LLMConfig,\n system: string,\n user: string\n): Promise {\n const res = await fetch(config.url, {\n method: \"POST\",\n headers: {\n Authorization: `Bearer ${config.apiKey}`,\n \"Content-Type\": \"application/json\",\n ...config.headers,\n },\n body: JSON.stringify({\n model: config.model,\n messages: [\n { role: \"system\", content: system },\n { role: \"user\", content: user },\n ],\n stream: false,\n max_tokens: 16384,\n temperature: 0.2,\n }),\n });\n\n if (!res.ok) {\n throw new Error(`LLM ${config.model}: ${res.status} ${res.statusText}`);\n }\n\n const data = await res.json();\n const content = data.choices?.[0]?.message?.content;\n\n if (!content) throw new Error(`LLM ${config.model}: empty response`);\n return content;\n}\n\nfunction getLLMConfigs(): LLMConfig[] {\n const groqKeys = [\n process.env.GROQ_API_KEY,\n process.env.GROQ_API_KEY2,\n process.env.GROQ_API_KEY3,\n process.env.GROQ_API_KEY4,\n ].filter(Boolean) as string[];\n\n const groqModels = [\n \"compound\",\n \"compound-mini\",\n \"meta-llama/llama-4-scout-17b-16e-instruct\",\n \"llama-3.3-70b-versatile\",\n ];\n\n const configs: LLMConfig[] = [];\n\n for (const model of groqModels) {\n for (const apiKey of groqKeys) {\n configs.push({\n url: \"https://api.groq.com/openai/v1/chat/completions\",\n apiKey,\n model,\n });\n }\n }\n\n const openRouterKey = process.env.OPENROUTER_API_KEY;\n if (openRouterKey) {\n configs.push({\n url: \"https://openrouter.ai/api/v1/chat/completions\",\n apiKey: openRouterKey,\n model: \"alibaba/tongyi-deepresearch-30b-a3b:free\",\n headers: {\n \"HTTP-Referer\": \"https://deep-search.app\",\n \"X-Title\": \"Deep Search\",\n },\n });\n }\n\n return configs;\n}\n\nasync function synthesize(\n query: string,\n results: SearchResult[]\n): Promise {\n const { system, user } = buildPrompt(query, results);\n\n for (const config of getLLMConfigs()) {\n try {\n return await callLLM(config, system, user);\n } catch (err) {\n console.error(`LLM failed (${config.model}):`, err);\n }\n }\n\n return null;\n}\n\nfunction formatRawResults(results: SearchResult[]): string {\n let out = `## Search Results (${results.length} sources)\\n\\n`;\n\n for (let i = 0; i < results.length; i++) {\n const r = results[i];\n out += `### ${i + 1}. ${r.title}\\n`;\n out += `- **Source:** ${r.hostname}\\n`;\n out += `- **Engine:** ${r.engine}\\n`;\n out += `- **Relevance:** ${r.relevance}%\\n`;\n if (r.timestamp) out += `- **Timestamp:** ${r.timestamp}\\n`;\n out += `- **URL:** ${r.url}\\n\\n`;\n out += `${r.snippet ? r.snippet.slice(0, 400) : \"No snippet available.\"}\\n\\n`;\n\n if (r.quotes.length > 0) {\n out += `**Relevant excerpts**\\n\\n`;\n out += r.quotes.map((q) => `> ${q}`).join(\"\\n\\n\") + \"\\n\\n\";\n }\n\n out += `---\\n\\n`;\n }\n\n return out;\n}\n\nfunction formatEngineBreakdown(results: SearchResult[]): string {\n const byEngine = new Map();\n\n for (const r of results) {\n byEngine.set(r.engine, (byEngine.get(r.engine) ?? 0) + 1);\n }\n\n const lines = [...byEngine.entries()]\n .sort((a, b) => b[1] - a[1])\n .map(([engine, count]) => `- **${engine}**: ${count}`);\n\n return `## Search Coverage\\n\\n${lines.join(\"\\n\")}\\n`;\n}\n\nfunction formatSourceList(results: SearchResult[]): string {\n return (\n \"\\n\\n## Sources\\n\" +\n results\n .map(\n (r, i) =>\n `${i + 1}. [${r.title}](${r.url}) — ${r.hostname} _via ${r.engine}_`\n )\n .join(\"\\n\") +\n \"\\n\"\n );\n}\n\nfunction formatSuggestedReplies(query: string, results: SearchResult[]): string[] {\n const topHosts = [...new Set(results.slice(0, 5).map((r) => r.hostname))];\n return [\n `Summarize this in simpler terms`,\n `Compare the top sources and their reliability`,\n `What are the biggest caveats or uncertainties here?`,\n topHosts.length\n ? `Focus only on sources from ${topHosts[0]}`\n : `Give me the strongest sources only`,\n ];\n}\n\nasync function handleQuery(req: Query, send: SendEvent): Promise {\n send(\"meta\", { content_type: \"text/markdown\", suggested_replies: true });\n\n const query = req.query[req.query.length - 1]?.content?.trim() || \"\";\n\n if (!query) {\n send(\"error\", {\n allow_retry: true,\n text: \"Missing query text.\",\n });\n send(\"done\", {});\n return;\n }\n\n send(\"text\", {\n text:\n `## Deep Research Mode\\n\\n` +\n `Searching across Brave, DuckDuckGo, SearXNG, Serper, and Google CSE...\\n\\n`,\n });\n\n let results: SearchResult[];\n\n try {\n results = await search(query);\n send(\"text\", {\n text: `Found ${results.length} ranked results.\\n\\n`,\n });\n } catch (err) {\n const msg = err instanceof Error ? err.message : String(err);\n send(\"error\", {\n allow_retry: true,\n text: `Search failed: ${msg}`,\n });\n send(\"done\", {});\n return;\n }\n\n if (results.length === 0) {\n const encoded = encodeURIComponent(query);\n send(\"text\", {\n text:\n \"No relevant results found. Try refining your query or searching directly:\\n\\n\" +\n `- [DuckDuckGo](https://duckduckgo.com/?q=${encoded})\\n` +\n `- [Google](https://www.google.com/search?q=${encoded})\\n` +\n `- [Bing](https://www.bing.com/search?q=${encoded})\\n`,\n });\n send(\"done\", {});\n return;\n }\n\n send(\"text\", { text: formatEngineBreakdown(results) });\n send(\"text\", { text: \"## Synthesizing a detailed report...\\n\\n\" });\n\n const analysis = await synthesize(query, results);\n\n if (analysis) {\n send(\"text\", { text: analysis });\n } else {\n send(\"text\", {\n text:\n \"## Synthesis unavailable\\n\\n\" +\n \"Falling back to structured raw search output.\\n\\n\" +\n formatRawResults(results),\n });\n }\n\n send(\"text\", { text: formatRawResults(results) });\n send(\"text\", { text: formatSourceList(results) });\n\n for (const reply of formatSuggestedReplies(query, results)) {\n send(\"suggested_reply\", { text: reply });\n }\n\n send(\"done\", {});\n}\n\nfunction getSettings(): BotSettings {\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: `| Type | Cost |\n|------|------|\n| Search | ${POINTS_PER_QUERY} points |`,\n cost_label: `${POINTS_PER_QUERY} points`,\n supports_system_messages: true,\n suggested_replies: true,\n };\n}\n\nfunction encodeSSE(event: string, data: unknown): Uint8Array {\n return new TextEncoder().encode(\n `event: ${event}\\ndata: ${JSON.stringify(data)}\\n\\n`\n );\n}\n\nexport default async function handler(req: Request): Promise {\n const body = await req.json().catch((err) => {\n console.error(\"Failed to parse request body:\", err);\n return {} as Record;\n });\n\n if (body.type === \"settings\") {\n return new Response(JSON.stringify(getSettings()), {\n status: 200,\n headers: { \"Content-Type\": \"application/json\" },\n });\n }\n\n const stream = new ReadableStream({\n start(controller) {\n const send: SendEvent = (event, data) => {\n controller.enqueue(encodeSSE(event, data));\n };\n\n handleQuery(body as Query, send)\n .catch((err) => {\n console.error(\"Response handler error:\", err);\n send(\"error\", {\n allow_retry: true,\n text: \"Unexpected internal error while handling the query.\",\n });\n })\n .finally(() => controller.close());\n },\n });\n\n return new Response(stream, {\n status: 200,\n headers: {\n \"Content-Type\": \"text/event-stream\",\n \"Cache-Control\": \"no-cache, no-transform\",\n Connection: \"keep-alive\",\n },\n });\n}","deleted","label",[102],"permalink","https://www.val.town/x/aibotcommander/Deep-Search-Pro/code/main.tsx","extension","actionData","errors"]