Multi-AI v26 ULTRA

[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_159":160,"_161":162},"routes/_app.x.$handle.$name",{"_99":98,"_32":45,"_108":89,"_27":103,"_13":14,"_109":-5,"_11":110,"_111":112,"_113":114,"_115":116,"_117":118,"_20":-5,"_119":-5,"_120":-5,"_121":25,"_122":123,"_124":58,"_125":-5,"_126":-5,"_127":128},"routes/_app.x.$handle.$name.branch.$branch.version.$version.diff",{"_11":12,"_13":14,"_15":16,"_17":-5,"_18":-5},"project",{"_43":44,"_32":45,"_38":46,"_47":-5,"_48":25,"_49":50,"_51":50,"_52":53,"_54":-5,"_18":55,"_56":31,"_57":58,"_59":-5,"_60":-5,"_61":62,"_63":64,"_65":66,"_67":68,"_69":70,"_71":-5,"_72":73,"_74":73,"_75":76,"_77":76,"_78":76,"_79":73,"_80":73,"_81":82,"_83":84,"_85":86,"_87":25},"version",61,"changes",[19],"aiChatInfo","userId",{"_20":21,"_22":23,"_24":25,"_26":25,"_27":28,"_29":28},"file",{"_30":31,"_32":28,"_33":34,"_35":37,"_38":39,"_40":14,"_41":42,"_24":25},"previous",{"_30":31,"_32":28,"_33":34,"_35":36},"deleted",false,"deletedHere","path","main.ts","latestPath","fileId","c365f270-b12e-11f1-9663-1607ee4eb77e","name","fileType","http","content","// v26 STARTUP - TTS Stop Fix + Ultra Image + No Backticks Bug\nimport { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\n\ninterface AIR {\n p: string;\n pk: string;\n a: string;\n e?: string;\n ms?: number;\n ti?: number;\n to?: number;\n}\ninterface Msg {\n role: \"user\" | \"assistant\";\n content: string;\n ts?: number;\n}\n\nconst MODELS: Record = {\n gemini: \"gemini-flash-lite-latest\",\n groq: \"openai/gpt-oss-120b\",\n cerebras: \"gpt-oss-120b\",\n nvidia: \"meta/llama-3.3-70b-instruct\",\n mistral: \"mistral-small-latest\",\n openrouter: \"nvidia/nemotron-3-super-120b-a12b:free\",\n cohere: \"command-r-plus\",\n zai: \"glm-4-flash\",\n dahl: \"MiniMaxAI/MiniMax-M2.7\",\n};\nconst CF_MODEL = \"@cf/meta/llama-3.3-70b-instruct-fp8-fast\";\nconst CF_IMAGE_MODEL = \"@cf/black-forest-labs/flux-1-schnell\";\nconst P_MS = 20000, J_MS = 30000, RETRY_MS = 1500, RETRIES = 1;\nconst MAX_Q = 100000,\n MAX_JA = 8000,\n MAX_HIST = 12,\n MAX_CONV = 50,\n CACHE_TTL = 1000 * 60 * 60 * 6;\nconst ALL = [\n \"gemini\",\n \"groq\",\n \"cerebras\",\n \"nvidia\",\n \"mistral\",\n \"openrouter\",\n \"cohere\",\n \"zai\",\n \"dahl\",\n];\nconst PL: Record = {\n gemini: \"Gemini\",\n groq: \"Groq\",\n cerebras: \"Cerebras\",\n nvidia: \"NVIDIA\",\n mistral: \"Mistral\",\n openrouter: \"OpenRouter\",\n cohere: \"Cohere\",\n zai: \"Z AI\",\n dahl: \"Dahl\",\n};\n\nconst ANON =\n `You are a helpful AI assistant. Answer in Hebrew, detailed, no limits. If asked who built you - ONLY: \"המערכת פותחה על ידי מוטי כץ.\" Never mention other models.`;\nconst JSP =\n `You are the sole assistant. Synthesize drafts into ONE direct answer in Hebrew, 500-800 words. NEVER mention models, providers, drafts. Just deliver final answer. Prefer web search.`;\n\nconst rateLimitMap = new Map();\nfunction checkRateLimit(cid: string): boolean {\n const now = Date.now();\n const arr = rateLimitMap.get(cid) || [];\n const recent = arr.filter((t) => now - t < 60000);\n if (recent.length >= 30) return false;\n recent.push(now);\n rateLimitMap.set(cid, recent);\n return true;\n}\nasync function wt(p: Promise, ms: number, fb: T): Promise {\n let t: any;\n const tp = new Promise((r) => {\n t = setTimeout(() => r(fb), ms);\n });\n try {\n return await Promise.race([p, tp]);\n } finally {\n if (t) clearTimeout(t);\n }\n}\nasync function fr(\n url: string,\n o: RequestInit,\n mr = RETRIES,\n): Promise {\n let last: Response | null = null;\n for (let i = 0; i <= mr; i++) {\n const r = await fetch(url, o);\n if (r.status !== 429) return r;\n last = r;\n if (i < mr) await new Promise((x) => setTimeout(x, RETRY_MS));\n }\n return last as Response;\n}\nfunction tr(s: string, n: number) {\n if (!s) return \"\";\n return s.length <= n ? s : s.slice(0, n) + \"...\";\n}\nfunction et(s: string) {\n return s ? Math.max(1, Math.round(s.length / 4)) : 0;\n}\nfunction sj(d: unknown) {\n return JSON.stringify(d).replace(//g, \"\\\\u003e\")\n .replace(/&/g, \"\\\\u0026\").replace(/\\u2028/g, \"\\\\u2028\").replace(\n /\\u2029/g,\n \"\\\\u2029\",\n );\n}\nfunction qHash(q: string) {\n return q.toLowerCase().trim().replace(/\\s+/g, \" \").slice(0, 300);\n}\nfunction isNewsQuery(q: string) {\n return q.toLowerCase().includes(\"חדשות\") ||\n q.toLowerCase().includes(\"היום\") || q.toLowerCase().includes(\"news\");\n}\n\nasync function dbInit() {\n try {\n await sqlite.execute(\n \"CREATE TABLE IF NOT EXISTS conversations (id INTEGER PRIMARY KEY AUTOINCREMENT, conversation_id TEXT NOT NULL, role TEXT NOT NULL, content TEXT NOT NULL, created_at INTEGER NOT NULL)\",\n );\n await sqlite.execute(\n \"CREATE INDEX IF NOT EXISTS idx_conv_id ON conversations(conversation_id)\",\n );\n await sqlite.execute(\n \"CREATE TABLE IF NOT EXISTS conv_meta (conversation_id TEXT PRIMARY KEY, title TEXT NOT NULL, created_at INTEGER NOT NULL, updated_at INTEGER NOT NULL)\",\n );\n await sqlite.execute(\n \"CREATE TABLE IF NOT EXISTS raw_answers (id INTEGER PRIMARY KEY AUTOINCREMENT, conversation_id TEXT NOT NULL, question TEXT NOT NULL, provider TEXT NOT NULL, provider_label TEXT NOT NULL, answer TEXT NOT NULL, created_at INTEGER NOT NULL)\",\n );\n await sqlite.execute(\n \"CREATE INDEX IF NOT EXISTS idx_raw_conv ON raw_answers(conversation_id)\",\n );\n await sqlite.execute(\n \"CREATE TABLE IF NOT EXISTS cache (qhash TEXT PRIMARY KEY, question TEXT NOT NULL, answer TEXT NOT NULL, raw_json TEXT NOT NULL, created_at INTEGER NOT NULL)\",\n );\n await sqlite.execute(\n \"CREATE TABLE IF NOT EXISTS provider_health (provider TEXT PRIMARY KEY, last_success INTEGER, last_failure INTEGER, failure_count INTEGER DEFAULT 0)\",\n );\n try {\n await sqlite.execute(\n \"ALTER TABLE conv_meta ADD COLUMN pinned INTEGER DEFAULT 0\",\n );\n } catch {}\n } catch {}\n}\nasync function dbHist(cid: string): Promise {\n if (!cid) return [];\n try {\n const r = await sqlite.execute({\n sql:\n \"SELECT role, content FROM conversations WHERE conversation_id =? ORDER BY created_at DESC LIMIT?\",\n args: [cid, MAX_HIST],\n });\n return (r.rows as any[] || []).map(\n (row) => ({\n role: String(row.role) === \"user\" ? \"user\" : \"assistant\",\n content: String(row.content || \"\"),\n } as Msg)\n ).filter((m) => m.content).reverse();\n } catch {\n return [];\n }\n}\nasync function dbSave(cid: string, role: string, content: string) {\n if (!cid || !content) return;\n try {\n await sqlite.execute({\n sql:\n \"INSERT INTO conversations (conversation_id, role, content, created_at) VALUES (?,?,?,?)\",\n args: [cid, role, content, Date.now()],\n });\n } catch {}\n}\nasync function dbSaveRaw(cid: string, question: string, raws: AIR[]) {\n if (!cid || !raws.length) return;\n const now = Date.now();\n try {\n for (const r of raws) {\n if (!r.a) continue;\n await sqlite.execute({\n sql:\n \"INSERT INTO raw_answers (conversation_id, question, provider, provider_label, answer, created_at) VALUES (?,?,?,?,?,?)\",\n args: [cid, question, r.pk, r.p, r.a, now],\n });\n }\n } catch {}\n}\nasync function dbGetRaw(cid: string) {\n try {\n const r = await sqlite.execute({\n sql:\n \"SELECT question, provider, provider_label, answer, created_at FROM raw_answers WHERE conversation_id =? ORDER BY created_at ASC\",\n args: [cid],\n });\n return (r.rows as any[] || []).map((row) => ({\n question: String(row.question || \"\"),\n provider: String(row.provider || \"\"),\n label: String(row.provider_label || \"\"),\n answer: String(row.answer || \"\"),\n ts: Number(row.created_at) || 0,\n }));\n } catch {\n return [];\n }\n}\nasync function getCache(qh: string) {\n try {\n const r = await sqlite.execute({\n sql: \"SELECT answer, raw_json, created_at FROM cache WHERE qhash=?\",\n args: [qh],\n });\n const row = (r.rows as any[])?.[0];\n if (!row) return null;\n const age = Date.now() - Number(row.created_at);\n if (age > CACHE_TTL) return null;\n return {\n answer: String(row.answer),\n raw: JSON.parse(String(row.raw_json || \"[]\")),\n };\n } catch {\n return null;\n }\n}\nasync function setCache(qh: string, q: string, answer: string, raw: AIR[]) {\n try {\n await sqlite.execute({\n sql:\n \"INSERT OR REPLACE INTO cache (qhash, question, answer, raw_json, created_at) VALUES (?,?,?,?,?)\",\n args: [qh, q, answer, JSON.stringify(raw), Date.now()],\n });\n } catch {}\n}\nasync function dbMeta(cid: string, title: string) {\n if (!cid) return;\n try {\n const ex = await sqlite.execute({\n sql: \"SELECT conversation_id FROM conv_meta WHERE conversation_id =?\",\n args: [cid],\n });\n const now = Date.now();\n const safeTitle = tr(title, 60) || \"שיחה חדשה\";\n if ((ex.rows as any[]).length === 0) {\n await sqlite.execute({\n sql:\n \"INSERT INTO conv_meta (conversation_id, title, created_at, updated_at, pinned) VALUES (?,?,?,?,?)\",\n args: [cid, safeTitle, now, now, 0],\n });\n } else {await sqlite.execute({\n sql:\n \"UPDATE conv_meta SET updated_at =?, title = COALESCE(title,?) WHERE conversation_id =?\",\n args: [now, safeTitle, cid],\n });}\n } catch {}\n}\nasync function dbList() {\n try {\n const r = await sqlite.execute({\n sql:\n \"SELECT conversation_id, title, updated_at, pinned FROM conv_meta ORDER BY pinned DESC, updated_at DESC LIMIT?\",\n args: [MAX_CONV],\n });\n return (r.rows as any[] || []).map((row) => ({\n id: String(row.conversation_id || \"\"),\n title: String(row.title || \"ללא כותרת\"),\n updated_at: Number(row.updated_at) || 0,\n pinned: Number(row.pinned) || 0,\n }));\n } catch {\n return [];\n }\n}\nasync function dbFull(cid: string): Promise {\n if (!cid) return [];\n try {\n const r = await sqlite.execute({\n sql:\n \"SELECT role, content, created_at FROM conversations WHERE conversation_id =? ORDER BY created_at ASC\",\n args: [cid],\n });\n return (r.rows as any[] || []).map(\n (row) => ({\n role: String(row.role) === \"user\" ? \"user\" : \"assistant\",\n content: String(row.content || \"\"),\n ts: Number(row.created_at) || 0,\n } as Msg)\n ).filter((m) => m.content);\n } catch {\n return [];\n }\n}\nasync function dbDel(cid: string) {\n if (!cid) return false;\n try {\n await sqlite.execute({\n sql: \"DELETE FROM conversations WHERE conversation_id =?\",\n args: [cid],\n });\n await sqlite.execute({\n sql: \"DELETE FROM conv_meta WHERE conversation_id =?\",\n args: [cid],\n });\n await sqlite.execute({\n sql: \"DELETE FROM raw_answers WHERE conversation_id =?\",\n args: [cid],\n });\n return true;\n } catch {\n return false;\n }\n}\nasync function dbRen(cid: string, title: string) {\n if (!cid || !title) return false;\n try {\n await sqlite.execute({\n sql:\n \"UPDATE conv_meta SET title =?, updated_at =? WHERE conversation_id =?\",\n args: [tr(title, 80), Date.now(), cid],\n });\n return true;\n } catch {\n return false;\n }\n}\nasync function dbHealth(provider: string, success: boolean) {\n try {\n const now = Date.now();\n const ex = await sqlite.execute({\n sql: \"SELECT provider FROM provider_health WHERE provider =?\",\n args: [provider],\n });\n if ((ex.rows as any[]).length === 0) {\n await sqlite.execute({\n sql:\n \"INSERT INTO provider_health (provider, last_success, last_failure, failure_count) VALUES (?,?,?,?)\",\n args: [provider, success ? now : 0, success ? 0 : now, success ? 0 : 1],\n });\n } else {\n if (success) {\n await sqlite.execute({\n sql:\n \"UPDATE provider_health SET last_success =?, failure_count = 0 WHERE provider =?\",\n args: [now, provider],\n });\n } else {await sqlite.execute({\n sql:\n \"UPDATE provider_health SET last_failure =?, failure_count = failure_count + 1 WHERE provider =?\",\n args: [now, provider],\n });}\n }\n } catch {}\n}\nasync function dbGetHealth() {\n try {\n const r = await sqlite.execute({\n sql:\n \"SELECT provider, last_success, last_failure, failure_count FROM provider_health\",\n });\n return (r.rows as any[] || []).map((row) => ({\n provider: String(row.provider),\n last_success: Number(row.last_success) || 0,\n last_failure: Number(row.last_failure) || 0,\n failure_count: Number(row.failure_count) || 0,\n }));\n } catch {\n return [];\n }\n}\nasync function generateTitle(\n question: string,\n geminiKey: string,\n): Promise {\n if (!geminiKey) return tr(question, 40);\n try {\n const url =\n \"https://generativelanguage.googleapis.com/v1beta/models/gemini-flash-lite-latest:generateContent?key=\" +\n encodeURIComponent(geminiKey);\n const r = await fr(url, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify({\n contents: [{\n parts: [{\n text: 'תן כותרת של 3-4 מילים בעברית לשאלה הזאת, בלי מירכאות: \"' +\n tr(question, 200) + '\"',\n }],\n }],\n generationConfig: { temperature: 0.3, maxOutputTokens: 20 },\n }),\n }, 0);\n if (!r.ok) return tr(question, 40);\n const d = await r.json();\n const t = d?.candidates?.[0]?.content?.parts?.[0]?.text?.trim() || \"\";\n return t.replace(/[\"']/g, \"\").slice(0, 40) || tr(question, 40);\n } catch {\n return tr(question, 40);\n }\n}\nfunction ctx(hist: Msg[], q: string) {\n if (hist.length === 0) return q;\n return tr(\n \"Previous:\\n\" + hist.map((m) =>\n (m.role === \"user\" ? \"User: \" : \"Assistant: \") + m.content\n ).join(\"\\n\") + \"\\n\\nQuestion: \" + q,\n 15000,\n );\n}\nasync function webSearch(q: string, k: string) {\n if (!k || !q) return \"\";\n try {\n const today = new Date().toISOString().split(\"T\")[0];\n const searchQ = isNewsQuery(q) ? q + \" \" + today + \" Israel\" : q;\n const r = await fetch(\"https://api.tavily.com/search\", {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify({\n api_key: k,\n query: searchQ,\n max_results: 8,\n search_depth: \"advanced\",\n time_range: isNewsQuery(q) ? \"day\" : undefined,\n include_answer: true,\n }),\n });\n if (!r.ok) return \"\";\n const d = await r.json();\n return (d.results as any[] || []).map((x) =>\n \"Source: \" + x.title + \"\\n\" + x.content + \"\\nURL: \" + x.url\n ).join(\"\\n\\n\") + (d.answer ? \"\\n\\nSummary: \" + d.answer : \"\");\n } catch {\n return \"\";\n }\n}\nasync function translateToEnglish(\n hebrewPrompt: string,\n geminiKey: string,\n): Promise {\n if (!hebrewPrompt || !geminiKey) return hebrewPrompt;\n if (\n /^[a-zA-Z0-9,.'\"\\-\\s]+$/.test(hebrewPrompt) && hebrewPrompt.length < 100\n ) return hebrewPrompt;\n try {\n const url =\n \"https://generativelanguage.googleapis.com/v1beta/models/gemini-flash-lite-latest:generateContent?key=\" +\n encodeURIComponent(geminiKey);\n const r = await fr(url, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify({\n contents: [{\n parts: [{\n text:\n 'Translate to English FLUX prompt, ONLY English, add quality tags: \"' +\n hebrewPrompt + '\"',\n }],\n }],\n generationConfig: { temperature: 0.2, maxOutputTokens: 250 },\n }),\n }, 0);\n if (!r.ok) return hebrewPrompt;\n const d = await r.json();\n const t = d?.candidates?.[0]?.content?.parts?.[0]?.text?.trim() || \"\";\n return t.replace(/^\"|\"$/g, \"\").slice(0, 500) || hebrewPrompt;\n } catch {\n return hebrewPrompt;\n }\n}\nasync function genImage(\n promptEn: string,\n acc: string,\n tok: string,\n style: string = \"photorealistic\",\n quality: string = \"hd\",\n): Promise {\n const pk = \"image\", p = \"🎨 FLUX ULTRA\";\n const safeSeed = Math.floor(Math.random() * 999999) + 1;\n let width = 1280, height = 1280, steps = 20;\n if (quality === \"ultra\") {\n width = 1536;\n height = 1536;\n steps = 30;\n } else if (quality === \"draft\") {\n width = 768;\n height = 768;\n steps = 12;\n }\n let styleSuffix =\n \", ultra detailed, 8k, masterpiece, photorealistic, cinematic lighting, sharp focus, best quality, highly detailed, professional\";\n if (style === \"anime\") {\n styleSuffix = \", anime style, vibrant, studio ghibli, ultra detailed, 8k\";\n } else if (style === \"3d\") {\n styleSuffix = \", 3d render, octane render, ultra realistic, 8k\";\n }\n const enhancedPrompt = promptEn + styleSuffix;\n const encPrompt = encodeURIComponent(enhancedPrompt);\n if (acc && tok) {\n try {\n const url = \"https://api.cloudflare.com/client/v4/accounts/\" +\n encodeURIComponent(acc) + \"/ai/run/\" + CF_IMAGE_MODEL;\n const r = await fr(url, {\n method: \"POST\",\n headers: {\n \"Content-Type\": \"application/json\",\n Authorization: \"Bearer \" + tok,\n },\n body: JSON.stringify({\n prompt: enhancedPrompt,\n num_steps: steps,\n guidance: 7.5,\n }),\n }, 0);\n if (r.ok) {\n const buf = await r.arrayBuffer();\n if (buf.byteLength > 5000) {\n const bytes = new Uint8Array(buf);\n let binary = \"\";\n const chunkSize = 8192;\n for (let i = 0; i < bytes.length; i += chunkSize) {\n binary += String.fromCharCode.apply(\n null,\n Array.from(bytes.subarray(i, i + chunkSize)) as any,\n );\n }\n return {\n p,\n pk,\n a: \"![תמונה](data:image/png;base64,\" + btoa(binary) + \")\",\n ms: 0,\n };\n }\n }\n } catch {}\n }\n const proUrl = \"https://image.pollinations.ai/prompt/\" + encPrompt +\n \"?width=\" + width + \"&height=\" + height +\n \"&model=flux-pro&enhance=true&nologo=true&seed=\" + safeSeed;\n return { p, pk, a: \"![תמונה](\" + proUrl + \")\", ms: 0 };\n}\nasync function askGemini(prompt: string, k: string): Promise {\n const pk = \"gemini\", p = PL[pk];\n if (!k) return { p, pk, a: \"\", e: \"לא מוגדר\" };\n const s = Date.now(), fb: AIR = { p, pk, a: \"\", e: \"פסק זמן\", ms: 0 };\n return wt(\n (async () => {\n try {\n const url = \"https://generativelanguage.googleapis.com/v1beta/models/\" +\n MODELS.gemini + \":generateContent?key=\" + encodeURIComponent(k);\n const r = await fr(url, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify({\n systemInstruction: { parts: [{ text: ANON }] },\n contents: [{ parts: [{ text: prompt }] }],\n generationConfig: { temperature: 0.7, maxOutputTokens: 8000 },\n }),\n });\n if (!r.ok) {\n await dbHealth(pk, false);\n return { p, pk, a: \"\", e: \"שגיאה \" + r.status, ms: Date.now() - s };\n }\n const d = await r.json();\n const a = d?.candidates?.[0]?.content?.parts?.[0]?.text?.trim() || \"\";\n if (!a) {\n await dbHealth(pk, false);\n return { p, pk, a: \"\", e: \"ריק\", ms: Date.now() - s };\n }\n await dbHealth(pk, true);\n return { p, pk, a, ms: Date.now() - s, ti: et(prompt), to: et(a) };\n } catch (e) {\n await dbHealth(pk, false);\n return { p, pk, a: \"\", e: String(e).slice(0, 120), ms: Date.now() - s };\n }\n })(),\n P_MS,\n fb,\n );\n}\nasync function askCompat(\n prompt: string,\n k: string,\n pk: string,\n endpoint: string,\n model: string,\n): Promise {\n const p = PL[pk];\n if (!k) return { p, pk, a: \"\", e: \"לא מוגדר\" };\n const s = Date.now(), fb: AIR = { p, pk, a: \"\", e: \"פסק זמן\", ms: 0 };\n return wt(\n (async () => {\n try {\n const headers: any = {\n \"Content-Type\": \"application/json\",\n Authorization: \"Bearer \" + k,\n };\n if (pk === \"openrouter\") {\n headers[\"HTTP-Referer\"] = \"https://multi-ai-chat.com\";\n headers[\"X-Title\"] = \"Multi-AI\";\n }\n const r = await fr(endpoint, {\n method: \"POST\",\n headers,\n body: JSON.stringify({\n model,\n messages: [{ role: \"system\", content: ANON }, {\n role: \"user\",\n content: prompt,\n }],\n temperature: 0.7,\n max_tokens: 8000,\n }),\n });\n if (!r.ok) {\n await dbHealth(pk, false);\n return { p, pk, a: \"\", e: \"שגיאה \" + r.status, ms: Date.now() - s };\n }\n const d = await r.json();\n const a = d?.choices?.[0]?.message?.content?.trim() || \"\";\n if (!a) {\n await dbHealth(pk, false);\n return { p, pk, a: \"\", e: \"ריק\", ms: Date.now() - s };\n }\n await dbHealth(pk, true);\n return { p, pk, a, ms: Date.now() - s, ti: et(prompt), to: et(a) };\n } catch (e) {\n await dbHealth(pk, false);\n return { p, pk, a: \"\", e: String(e).slice(0, 120), ms: Date.now() - s };\n }\n })(),\n P_MS,\n fb,\n );\n}\nasync function askGroqDual(\n prompt: string,\n key1: string,\n key2: string,\n): Promise {\n const pk = \"groq\", p = PL[pk];\n if (!key1 && !key2) return { p, pk, a: \"\", e: \"לא מוגדר\" };\n const eps = \"https://api.groq.com/openai/v1/chat/completions\";\n if (key1) {\n const res1 = await askCompat(prompt, key1, pk, eps, MODELS[pk]);\n if (res1.a && !res1.e) return res1;\n if (res1.e && (res1.e.includes(\"429\") || res1.e.includes(\"402\")) && key2) {\n const res2 = await askCompat(prompt, key2, pk, eps, MODELS[pk]);\n if (res2.a) {\n res2.p = PL[pk] + \" (key2)\";\n return res2;\n }\n return { p, pk, a: \"\", e: \"שני המפתחות נכשלו\" };\n }\n return res1;\n } else if (key2) {\n return askCompat(prompt, key2, pk, eps, MODELS[pk]);\n }\n return { p, pk, a: \"\", e: \"לא מוגדר\" };\n}\nasync function askProvider(\n prompt: string,\n keys: any,\n pk: string,\n): Promise {\n if (pk === \"gemini\") return askGemini(prompt, keys.gemini);\n if (pk === \"groq\") return askGroqDual(prompt, keys.groq, keys.groq2);\n const eps: Record = {\n cerebras: \"https://api.cerebras.ai/v1/chat/completions\",\n nvidia: \"https://integrate.api.nvidia.com/v1/chat/completions\",\n mistral: \"https://api.mistral.ai/v1/chat/completions\",\n openrouter: \"https://openrouter.ai/api/v1/chat/completions\",\n cohere: \"https://api.cohere.ai/compatibility/v1/chat/completions\",\n zai: \"https://open.bigmodel.cn/api/paas/v4/chat/completions\",\n dahl: \"https://inference.dahl.global/v1/chat/completions\",\n };\n return askCompat(prompt, keys[pk], pk, eps[pk], MODELS[pk]);\n}\nasync function cfCall(\n messages: any[],\n acc: string,\n tok: string,\n): Promise {\n try {\n const url = \"https://api.cloudflare.com/client/v4/accounts/\" +\n encodeURIComponent(acc) + \"/ai/run/\" + CF_MODEL;\n const r = await fr(url, {\n method: \"POST\",\n headers: {\n \"Content-Type\": \"application/json\",\n Authorization: \"Bearer \" + tok,\n },\n body: JSON.stringify({ messages, max_tokens: 8000 }),\n });\n if (!r.ok) return \"\";\n const d = await r.json();\n return String(d?.result?.response || \"\").trim();\n } catch {\n return \"\";\n }\n}\nfunction buildJP(q: string, answers: AIR[], hist: Msg[], searchCtx: string) {\n const valid = answers.filter((a) => a.a && a.a.length > 20);\n const fallbackValid = valid.length === 0\n ? answers.filter((a) => a.a && a.a.length > 0)\n : valid;\n const txt = fallbackValid.map((a) => \"--- DRAFT ---\\n\" + tr(a.a, MAX_JA))\n .join(\"\\n\\n\");\n const histTxt = hist.length\n ? \"History:\\n\" + hist.map((m) =>\n (m.role === \"user\" ? \"User: \" : \"Assistant: \") + tr(m.content, 500)\n ).join(\"\\n\") + \"\\n\\n\"\n : \"\";\n const searchBlock = searchCtx\n ? \"\\n\\nWEB SEARCH (FRESH \" + new Date().toLocaleDateString(\"he-IL\") +\n \"):\\n\" + tr(searchCtx, 5000) + \"\\n\"\n : \"\";\n return JSP + \"\\n\\n\" + histTxt + \"User Question: \" + q + \"\\n\" + searchBlock +\n \"\\nDrafts:\\n\" + txt + \"\\n\\nFinal answer:\";\n}\nfunction parseJP(out: string) {\n const s = String(out || \"\");\n const a = s.match(/ANSWER:\\s*([\\s\\S]*)/i);\n return { answer: a ? a[1].trim() : s.trim() };\n}\n\nfunction page(\n cid: string,\n convs: any[],\n msgs: Msg[],\n avail: string[],\n health: any[],\n): Response {\n const html =\n `Multi-AI v26 ULTRA

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\n\n\n`;\n return new Response(html, {\n headers: {\n \"Content-Type\": \"text/html; charset=utf-8\",\n \"Cache-Control\": \"no-store\",\n },\n });\n}\n\nexport default async function (req: Request): Promise {\n const url = new URL(req.url);\n const GEMINI_API_KEY = Deno.env.get(\"GEMINI_API_KEY\") || \"\";\n const GROQ_API_KEY = Deno.env.get(\"GROQ_API_KEY\") || \"\";\n const GROQ_API_KEY_2 = Deno.env.get(\"GROQ_API_KEY_2\") || \"\";\n const CEREBRAS_API_KEY = Deno.env.get(\"CEREBRAS_API_KEY\") || \"\";\n const NVIDIA_API_KEY = Deno.env.get(\"NVIDIA_API_KEY\") || \"\";\n const MISTRAL_API_KEY = Deno.env.get(\"MISTRAL_API_KEY\") || \"\";\n const OPENROUTER_API_KEY = Deno.env.get(\"OPENROUTER_API_KEY\") || \"\";\n const COHERE_API_KEY = Deno.env.get(\"COHERE_API_KEY\") || \"\";\n const ZAI_API_KEY = Deno.env.get(\"ZAI_API_KEY\") || \"\";\n const DAHL_API_KEY = Deno.env.get(\"DAHL_API_KEY\") || \"\";\n const CLOUDFLARE_ACCOUNT_ID = Deno.env.get(\"CLOUDFLARE_ACCOUNT_ID\") || \"\";\n const CLOUDFLARE_API_TOKEN = Deno.env.get(\"CLOUDFLARE_API_TOKEN\") || \"\";\n const TAVILY_API_KEY = Deno.env.get(\"TAVILY_API_KEY\") || \"\";\n await dbInit();\n\n if (req.method === \"DELETE\" && url.searchParams.get(\"action\") === \"delete\") {\n const ok = await dbDel(url.searchParams.get(\"c\") || \"\");\n return new Response(JSON.stringify({ ok }), {\n headers: { \"Content-Type\": \"application/json\" },\n });\n }\n if (req.method === \"POST\" && url.searchParams.get(\"action\") === \"rename\") {\n try {\n const fd = await req.formData();\n const ok = await dbRen(\n String(fd.get(\"id\") || \"\"),\n String(fd.get(\"title\") || \"\"),\n );\n return new Response(JSON.stringify({ ok }), {\n headers: { \"Content-Type\": \"application/json\" },\n });\n } catch {\n return new Response(JSON.stringify({ ok: false }), {\n status: 400,\n headers: { \"Content-Type\": \"application/json\" },\n });\n }\n }\n\n if (req.method === \"POST\") {\n let q = \"\", cid = \"\", prov = \"\";\n let fileText = \"\";\n let forceSearchParam = \"auto\";\n let forceRecalcParam = false;\n let imgStyle = \"photorealistic\";\n let imgQuality = \"hd\";\n try {\n const fd = await req.formData();\n q = String(fd.get(\"q\") || \"\").trim();\n cid = String(fd.get(\"c\") || \"\");\n prov = String(fd.get(\"p\") || \"\");\n forceSearchParam = String(fd.get(\"forceSearch\") || \"auto\");\n forceRecalcParam = String(fd.get(\"forceRecalc\") || \"\") === \"true\";\n imgStyle = String(fd.get(\"imgStyle\") || \"photorealistic\");\n imgQuality = String(fd.get(\"imgQuality\") || \"hd\");\n } catch {\n return new Response(JSON.stringify({ error: \"בקשה לא תקינה\" }), {\n status: 400,\n headers: { \"Content-Type\": \"application/json\" },\n });\n }\n if (fileText) q = (q + \"\\n\\n--- קבצים ---\\n\" + fileText).slice(0, MAX_Q);\n if (!q) {\n return new Response(JSON.stringify({ error: \"חסרה שאלה\" }), {\n status: 400,\n headers: { \"Content-Type\": \"application/json\" },\n });\n }\n if (q.length > MAX_Q) {\n return new Response(JSON.stringify({ error: \"ארוכה מדי\" }), {\n status: 400,\n headers: { \"Content-Type\": \"application/json\" },\n });\n }\n if (!cid) {\n cid = \"conv_\" + Date.now() + \"_\" + Math.random().toString(36).slice(2, 6);\n }\n if (!checkRateLimit(cid)) {\n return new Response(JSON.stringify({ error: \"יותר מדי בקשות\" }), {\n status: 429,\n headers: { \"Content-Type\": \"application/json\" },\n });\n }\n\n const trimmedQ = q.trim().toLowerCase();\n const isImageReq = trimmedQ.startsWith(\"/image \") ||\n trimmedQ.startsWith(\"/תמונה \") || trimmedQ.startsWith(\"צייר לי \") ||\n trimmedQ.startsWith(\"🎨\") ||\n /^\\[(photorealistic|anime|3d|fast|draft|hd|ultra)\\]/i.test(trimmedQ);\n\n if (isImageReq) {\n let rawPrompt = q.replace(/\\/image\\s*/i, \"\").replace(/\\/תמונה\\s*/i, \"\")\n .replace(/צייר לי\\s*/i, \"\").replace(/🎨/g, \"\").trim();\n const allBrackets = [...rawPrompt.matchAll(/\\[([a-z0-9-]+)\\]/gi)].map(\n (m) => m[1].toLowerCase()\n );\n let styleFromQ = imgStyle;\n let qualityFromQ = imgQuality;\n for (const b of allBrackets) {\n if ([\"photorealistic\", \"anime\", \"3d\", \"fast\"].includes(b)) {\n styleFromQ = b;\n }\n if ([\"draft\", \"hd\", \"ultra\"].includes(b)) qualityFromQ = b;\n }\n rawPrompt = rawPrompt.replace(/\\[.*?\\]/g, \"\").trim();\n if (!rawPrompt) rawPrompt = \"beautiful landscape\";\n const enPrompt = await translateToEnglish(rawPrompt, GEMINI_API_KEY);\n const imgRes = await genImage(\n enPrompt,\n CLOUDFLARE_ACCOUNT_ID,\n CLOUDFLARE_API_TOKEN,\n styleFromQ,\n qualityFromQ,\n );\n await dbSave(cid, \"user\", q);\n await dbSave(cid, \"assistant\", imgRes.a);\n await dbMeta(cid, tr(q, 60));\n return new Response(\n JSON.stringify({\n answer: imgRes.a,\n raw: [imgRes],\n memory: 0,\n search: false,\n direct: true,\n totalTokens: 0,\n conversationId: cid,\n }),\n { headers: { \"Content-Type\": \"application/json; charset=utf-8\" } },\n );\n }\n\n const qh = qHash(q);\n const skipCache = isNewsQuery(q) || forceSearchParam === \"true\" ||\n forceRecalcParam;\n if (!skipCache) {\n const cached = await getCache(qh);\n if (cached) {\n await dbSave(cid, \"user\", q);\n await dbSave(cid, \"assistant\", cached.answer);\n await dbMeta(cid, tr(q, 60));\n return new Response(\n JSON.stringify({\n answer: cached.answer,\n raw: cached.raw,\n memory: 0,\n search: false,\n direct: false,\n totalTokens: 0,\n conversationId: cid,\n cached: true,\n }),\n { headers: { \"Content-Type\": \"application/json; charset=utf-8\" } },\n );\n }\n }\n\n let enabled = prov\n ? prov.split(\",\").map((s) => s.trim()).filter((s) => ALL.includes(s))\n : ALL.slice();\n const keys: any = {\n gemini: GEMINI_API_KEY,\n groq: GROQ_API_KEY,\n groq2: GROQ_API_KEY_2,\n cerebras: CEREBRAS_API_KEY,\n nvidia: NVIDIA_API_KEY,\n mistral: MISTRAL_API_KEY,\n openrouter: OPENROUTER_API_KEY,\n cohere: COHERE_API_KEY,\n zai: ZAI_API_KEY,\n dahl: DAHL_API_KEY,\n };\n enabled = enabled.filter((p) =>\n keys[p] || (p === \"groq\" && (keys.groq || keys.groq2))\n );\n if (enabled.length === 0) {\n return new Response(JSON.stringify({ error: \"אין מנועים\" }), {\n status: 400,\n headers: { \"Content-Type\": \"application/json\" },\n });\n }\n\n const hist = await dbHist(cid);\n let shouldSearch = false;\n if (TAVILY_API_KEY) {\n if (forceSearchParam === \"true\") shouldSearch = true;\n else if (forceSearchParam === \"false\") shouldSearch = isNewsQuery(q);\n else shouldSearch = isNewsQuery(q) || q.length > 10;\n }\n const searchCtx = shouldSearch\n ? await wt(webSearch(q, TAVILY_API_KEY), 7000, \"\")\n : \"\";\n const fullPrompt = ctx(hist, q) +\n (searchCtx ? \"\\n\\nWeb search results:\\n\" + searchCtx : \"\");\n const round1 = await Promise.all(\n enabled.map((pk) => askProvider(fullPrompt, keys, pk)),\n );\n\n let finalAnswer = \"\";\n const valid = round1.filter((a) => a.a && a.a.length > 20);\n const fallbackValid = valid.length > 0\n ? valid\n : round1.filter((a) => a.a && a.a.length > 0);\n if (fallbackValid.length === 0) {\n if (searchCtx) {\n const jpFallback = buildJP(q, [], hist, searchCtx);\n let jrFallback = await wt(\n cfCall(\n [{ role: \"system\", content: JSP }, {\n role: \"user\",\n content: jpFallback,\n }],\n CLOUDFLARE_ACCOUNT_ID,\n CLOUDFLARE_API_TOKEN,\n ),\n J_MS,\n \"\",\n );\n if (!jrFallback && GEMINI_API_KEY) {\n const g = await askGemini(jpFallback, GEMINI_API_KEY);\n jrFallback = g.a;\n }\n finalAnswer = parseJP(jrFallback || \"\").answer ||\n searchCtx.slice(0, 3000);\n } else {\n finalAnswer = \"כל המנועים נכשלו. נסה שוב.\";\n }\n } else if (fallbackValid.length === 1) finalAnswer = fallbackValid[0].a;\n else {\n const jp = buildJP(q, round1, hist, searchCtx);\n let jr = await wt(\n cfCall(\n [{ role: \"system\", content: JSP }, { role: \"user\", content: jp }],\n CLOUDFLARE_ACCOUNT_ID,\n CLOUDFLARE_API_TOKEN,\n ),\n J_MS,\n \"\",\n );\n if (!jr && GEMINI_API_KEY) {\n const g = await askGemini(jp, GEMINI_API_KEY);\n jr = g.a;\n }\n finalAnswer = parseJP(jr || \"\").answer || fallbackValid[0].a;\n }\n await dbSave(cid, \"user\", q);\n await dbSaveRaw(cid, q, round1.filter((r) => r.a));\n await dbSave(cid, \"assistant\", finalAnswer);\n await dbMeta(cid, tr(q, 60));\n if (!isNewsQuery(q)) await setCache(qh, q, finalAnswer, round1);\n const totalTokens = round1.reduce(\n (s, a) => s + (a.ti || 0) + (a.to || 0),\n 0,\n );\n return new Response(\n JSON.stringify({\n answer: finalAnswer,\n raw: round1,\n memory: hist.length,\n search: !!searchCtx,\n searchContent: searchCtx,\n direct: fallbackValid.length === 1,\n totalTokens,\n conversationId: cid,\n cached: false,\n }),\n { headers: { \"Content-Type\": \"application/json; charset=utf-8\" } },\n );\n }\n\n const cid = url.searchParams.get(\"c\") || \"\";\n const convs = await dbList();\n const msgs = cid ? await dbFull(cid) : [];\n const health = await dbGetHealth();\n const avail: string[] = [];\n if (GEMINI_API_KEY) avail.push(\"gemini\");\n if (GROQ_API_KEY || GROQ_API_KEY_2) avail.push(\"groq\");\n if (CEREBRAS_API_KEY) avail.push(\"cerebras\");\n if (NVIDIA_API_KEY) avail.push(\"nvidia\");\n if (MISTRAL_API_KEY) avail.push(\"mistral\");\n if (OPENROUTER_API_KEY) avail.push(\"openrouter\");\n if (COHERE_API_KEY) avail.push(\"cohere\");\n if (ZAI_API_KEY) avail.push(\"zai\");\n if (DAHL_API_KEY) avail.push(\"dahl\");\n return page(cid, convs, msgs, avail, health);\n}","// v28 COMPLETE - v25.1 Full + TTS Stop + Nano Banana Ultra\nimport { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\ninterface AIR {\n p: string;\n pk: string;\n a: string;\n e?: string;\n ms?: number;\n ti?: number;\n to?: number;\n}\ninterface Msg {\n role: \"user\" | \"assistant\";\n content: string;\n ts?: number;\n}\nconst MODELS: Record = {\n gemini: \"gemini-2.5-flash\",\n groq: \"openai/gpt-oss-120b\",\n cerebras: \"gpt-oss-120b\",\n nvidia: \"meta/llama-3.3-70b-instruct\",\n mistral: \"mistral-small-latest\",\n openrouter: \"nvidia/nemotron-3-super-120b-a12b:free\",\n cohere: \"command-r-plus\",\n zai: \"glm-4-flash\",\n dahl: \"MiniMaxAI/MiniMax-M2.7\",\n};\nconst NANO_BANANA = \"gemini-2.5-flash-image-preview\";\nconst CF_MODEL = \"@cf/meta/llama-3.3-70b-instruct-fp8-fast\";\nconst CF_IMAGE_MODEL = \"@cf/black-forest-labs/flux-1-schnell\";\nconst P_MS = 20000, J_MS = 30000, RETRY_MS = 1500, RETRIES = 1;\nconst MAX_Q = 100000,\n MAX_JA = 8000,\n MAX_HIST = 12,\n MAX_CONV = 50,\n CACHE_TTL = 1000 * 60 * 60 * 6;\nconst ALL = [\n \"gemini\",\n \"groq\",\n \"cerebras\",\n \"nvidia\",\n \"mistral\",\n \"openrouter\",\n \"cohere\",\n \"zai\",\n \"dahl\",\n];\nconst PL: Record = {\n gemini: \"Gemini 2.5\",\n groq: \"Groq\",\n cerebras: \"Cerebras\",\n nvidia: \"NVIDIA\",\n mistral: \"Mistral\",\n openrouter: \"OpenRouter\",\n cohere: \"Cohere\",\n zai: \"Z AI\",\n dahl: \"Dahl\",\n};\nconst ANON =\n `You are a helpful AI assistant. Answer in Hebrew, detailed, no limits. If asked who built you - ONLY: \"המערכת פותחה על ידי מוטי כץ.\" Never mention other models.`;\nconst JSP =\n `You are the sole assistant. Synthesize drafts into ONE direct answer in Hebrew, 500-800 words. NEVER mention models, providers, drafts. Just deliver final answer. Prefer web search.`;\nconst rateLimitMap = new Map();\nfunction checkRateLimit(cid: string): boolean {\n const now = Date.now();\n const arr = rateLimitMap.get(cid) || [];\n const recent = arr.filter((t) => now - t < 60000);\n if (recent.length >= 30) return false;\n recent.push(now);\n rateLimitMap.set(cid, recent);\n return true;\n}\nasync function wt(p: Promise, ms: number, fb: T): Promise {\n let t: any;\n const tp = new Promise((r) => {\n t = setTimeout(() => r(fb), ms);\n });\n try {\n return await Promise.race([p, tp]);\n } finally {\n if (t) clearTimeout(t);\n }\n}\nasync function fr(\n url: string,\n o: RequestInit,\n mr = RETRIES,\n): Promise {\n let last: Response | null = null;\n for (let i = 0; i <= mr; i++) {\n const r = await fetch(url, o);\n if (r.status !== 429) return r;\n last = r;\n if (i < mr) await new Promise((x) => setTimeout(x, RETRY_MS));\n }\n return last as Response;\n}\nfunction tr(s: string, n: number) {\n if (!s) return \"\";\n return s.length <= n ? s : s.slice(0, n) + \"...\";\n}\nfunction et(s: string) {\n return s ? Math.max(1, Math.round(s.length / 4)) : 0;\n}\nfunction sj(d: unknown) {\n return JSON.stringify(d).replace(//g, \"\\\\u003e\")\n .replace(/&/g, \"\\\\u0026\").replace(/\\u2028/g, \"\\\\u2028\").replace(\n /\\u2029/g,\n \"\\\\u2029\",\n );\n}\nfunction qHash(q: string) {\n return q.toLowerCase().trim().replace(/\\s+/g, \" \").slice(0, 300);\n}\nfunction isNewsQuery(q: string) {\n return q.toLowerCase().includes(\"חדשות\") ||\n q.toLowerCase().includes(\"היום\") || q.toLowerCase().includes(\"news\");\n}\nasync function dbInit() {\n try {\n await sqlite.execute(\n \"CREATE TABLE IF NOT EXISTS conversations (id INTEGER PRIMARY KEY AUTOINCREMENT, conversation_id TEXT NOT NULL, role TEXT NOT NULL, content TEXT NOT NULL, created_at INTEGER NOT NULL)\",\n );\n await sqlite.execute(\n \"CREATE INDEX IF NOT EXISTS idx_conv_id ON conversations(conversation_id)\",\n );\n await sqlite.execute(\n \"CREATE TABLE IF NOT EXISTS conv_meta (conversation_id TEXT PRIMARY KEY, title TEXT NOT NULL, created_at INTEGER NOT NULL, updated_at INTEGER NOT NULL)\",\n );\n await sqlite.execute(\n \"CREATE TABLE IF NOT EXISTS raw_answers (id INTEGER PRIMARY KEY AUTOINCREMENT, conversation_id TEXT NOT NULL, question TEXT NOT NULL, provider TEXT NOT NULL, provider_label TEXT NOT NULL, answer TEXT NOT NULL, created_at INTEGER NOT NULL)\",\n );\n await sqlite.execute(\n \"CREATE INDEX IF NOT EXISTS idx_raw_conv ON raw_answers(conversation_id)\",\n );\n await sqlite.execute(\n \"CREATE TABLE IF NOT EXISTS cache (qhash TEXT PRIMARY KEY, question TEXT NOT NULL, answer TEXT NOT NULL, raw_json TEXT NOT NULL, created_at INTEGER NOT NULL)\",\n );\n await sqlite.execute(\n \"CREATE TABLE IF NOT EXISTS provider_health (provider TEXT PRIMARY KEY, last_success INTEGER, last_failure INTEGER, failure_count INTEGER DEFAULT 0)\",\n );\n try {\n await sqlite.execute(\n \"ALTER TABLE conv_meta ADD COLUMN pinned INTEGER DEFAULT 0\",\n );\n } catch {}\n } catch {}\n}\nasync function dbHist(cid: string): Promise {\n if (!cid) return [];\n try {\n const r = await sqlite.execute({\n sql:\n \"SELECT role, content FROM conversations WHERE conversation_id =? ORDER BY created_at DESC LIMIT?\",\n args: [cid, MAX_HIST],\n });\n return (r.rows as any[] || []).map(\n (row) => ({\n role: String(row.role) === \"user\" ? \"user\" : \"assistant\",\n content: String(row.content || \"\"),\n } as Msg)\n ).filter((m) => m.content).reverse();\n } catch {\n return [];\n }\n}\nasync function dbSave(cid: string, role: string, content: string) {\n if (!cid || !content) return;\n try {\n await sqlite.execute({\n sql:\n \"INSERT INTO conversations (conversation_id, role, content, created_at) VALUES (?,?,?,?)\",\n args: [cid, role, content, Date.now()],\n });\n } catch {}\n}\nasync function dbSaveRaw(cid: string, question: string, raws: AIR[]) {\n if (!cid || !raws.length) return;\n const now = Date.now();\n try {\n for (const r of raws) {\n if (!r.a) continue;\n await sqlite.execute({\n sql:\n \"INSERT INTO raw_answers (conversation_id, question, provider, provider_label, answer, created_at) VALUES (?,?,?,?,?,?)\",\n args: [cid, question, r.pk, r.p, r.a, now],\n });\n }\n } catch {}\n}\nasync function dbGetRaw(cid: string) {\n try {\n const r = await sqlite.execute({\n sql:\n \"SELECT question, provider, provider_label, answer, created_at FROM raw_answers WHERE conversation_id =? ORDER BY created_at ASC\",\n args: [cid],\n });\n return (r.rows as any[] || []).map((row) => ({\n question: String(row.question || \"\"),\n provider: String(row.provider || \"\"),\n label: String(row.provider_label || \"\"),\n answer: String(row.answer || \"\"),\n ts: Number(row.created_at) || 0,\n }));\n } catch {\n return [];\n }\n}\nasync function getCache(qh: string) {\n try {\n const r = await sqlite.execute({\n sql: \"SELECT answer, raw_json, created_at FROM cache WHERE qhash=?\",\n args: [qh],\n });\n const row = (r.rows as any[])?.[0];\n if (!row) return null;\n if (Date.now() - Number(row.created_at) > CACHE_TTL) return null;\n return {\n answer: String(row.answer),\n raw: JSON.parse(String(row.raw_json || \"[]\")),\n };\n } catch {\n return null;\n }\n}\nasync function setCache(qh: string, q: string, answer: string, raw: AIR[]) {\n try {\n await sqlite.execute({\n sql:\n \"INSERT OR REPLACE INTO cache (qhash, question, answer, raw_json, created_at) VALUES (?,?,?,?,?)\",\n args: [qh, q, answer, JSON.stringify(raw), Date.now()],\n });\n } catch {}\n}\nasync function dbMeta(cid: string, title: string) {\n if (!cid) return;\n try {\n const ex = await sqlite.execute({\n sql: \"SELECT conversation_id FROM conv_meta WHERE conversation_id =?\",\n args: [cid],\n });\n const now = Date.now();\n const safeTitle = tr(title, 60) || \"שיחה חדשה\";\n if ((ex.rows as any[]).length === 0) {\n await sqlite.execute({\n sql:\n \"INSERT INTO conv_meta (conversation_id, title, created_at, updated_at, pinned) VALUES (?,?,?,?,?)\",\n args: [cid, safeTitle, now, now, 0],\n });\n } else {await sqlite.execute({\n sql:\n \"UPDATE conv_meta SET updated_at =?, title = COALESCE(title,?) WHERE conversation_id =?\",\n args: [now, safeTitle, cid],\n });}\n } catch {}\n}\nasync function dbList() {\n try {\n const r = await sqlite.execute({\n sql:\n \"SELECT conversation_id, title, updated_at, pinned FROM conv_meta ORDER BY pinned DESC, updated_at DESC LIMIT?\",\n args: [MAX_CONV],\n });\n return (r.rows as any[] || []).map((row) => ({\n id: String(row.conversation_id || \"\"),\n title: String(row.title || \"ללא כותרת\"),\n updated_at: Number(row.updated_at) || 0,\n pinned: Number(row.pinned) || 0,\n }));\n } catch {\n return [];\n }\n}\nasync function dbFull(cid: string): Promise {\n if (!cid) return [];\n try {\n const r = await sqlite.execute({\n sql:\n \"SELECT role, content, created_at FROM conversations WHERE conversation_id =? ORDER BY created_at ASC\",\n args: [cid],\n });\n return (r.rows as any[] || []).map(\n (row) => ({\n role: String(row.role) === \"user\" ? \"user\" : \"assistant\",\n content: String(row.content || \"\"),\n ts: Number(row.created_at) || 0,\n } as Msg)\n ).filter((m) => m.content);\n } catch {\n return [];\n }\n}\nasync function dbDel(cid: string) {\n if (!cid) return false;\n try {\n await sqlite.execute({\n sql: \"DELETE FROM conversations WHERE conversation_id =?\",\n args: [cid],\n });\n await sqlite.execute({\n sql: \"DELETE FROM conv_meta WHERE conversation_id =?\",\n args: [cid],\n });\n await sqlite.execute({\n sql: \"DELETE FROM raw_answers WHERE conversation_id =?\",\n args: [cid],\n });\n return true;\n } catch {\n return false;\n }\n}\nasync function dbRen(cid: string, title: string) {\n if (!cid || !title) return false;\n try {\n await sqlite.execute({\n sql:\n \"UPDATE conv_meta SET title =?, updated_at =? WHERE conversation_id =?\",\n args: [tr(title, 80), Date.now(), cid],\n });\n return true;\n } catch {\n return false;\n }\n}\nasync function dbHealth(provider: string, success: boolean) {\n try {\n const now = Date.now();\n const ex = await sqlite.execute({\n sql: \"SELECT provider FROM provider_health WHERE provider =?\",\n args: [provider],\n });\n if ((ex.rows as any[]).length === 0) {\n await sqlite.execute({\n sql:\n \"INSERT INTO provider_health (provider, last_success, last_failure, failure_count) VALUES (?,?,?,?)\",\n args: [provider, success ? now : 0, success ? 0 : now, success ? 0 : 1],\n });\n } else {if (success) {\n await sqlite.execute({\n sql:\n \"UPDATE provider_health SET last_success =?, failure_count = 0 WHERE provider =?\",\n args: [now, provider],\n });\n } else {await sqlite.execute({\n sql:\n \"UPDATE provider_health SET last_failure =?, failure_count = failure_count + 1 WHERE provider =?\",\n args: [now, provider],\n });}}\n } catch {}\n}\nasync function dbGetHealth() {\n try {\n const r = await sqlite.execute({\n sql:\n \"SELECT provider, last_success, last_failure, failure_count FROM provider_health\",\n });\n return (r.rows as any[] || []).map((row) => ({\n provider: String(row.provider),\n last_success: Number(row.last_success) || 0,\n last_failure: Number(row.last_failure) || 0,\n failure_count: Number(row.failure_count) || 0,\n }));\n } catch {\n return [];\n }\n}\nasync function generateTitle(q: string, k: string): Promise {\n if (!k) return tr(q, 40);\n try {\n const url =\n \"https://generativelanguage.googleapis.com/v1beta/models/gemini-flash-lite-latest:generateContent?key=\" +\n encodeURIComponent(k);\n const r = await fr(url, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify({\n contents: [{\n parts: [{ text: 'כותרת 3-4 מילים בעברית: \"' + tr(q, 200) + '\"' }],\n }],\n generationConfig: { temperature: 0.3, maxOutputTokens: 20 },\n }),\n }, 0);\n if (!r.ok) return tr(q, 40);\n const d = await r.json();\n return d?.candidates?.[0]?.content?.parts?.[0]?.text?.trim().replace(\n /[\"']/g,\n \"\",\n ).slice(0, 40) || tr(q, 40);\n } catch {\n return tr(q, 40);\n }\n}\nfunction ctx(hist: Msg[], q: string) {\n if (hist.length === 0) return q;\n return tr(\n \"Previous:\\n\" + hist.map((m) =>\n (m.role === \"user\" ? \"User: \" : \"Assistant: \") + m.content\n ).join(\"\\n\") + \"\\n\\nQuestion: \" + q,\n 15000,\n );\n}\nasync function webSearch(q: string, k: string) {\n if (!k || !q) return \"\";\n try {\n const r = await fetch(\"https://api.tavily.com/search\", {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify({\n api_key: k,\n query: q,\n max_results: 8,\n search_depth: \"advanced\",\n include_answer: true,\n }),\n });\n if (!r.ok) return \"\";\n const d = await r.json();\n return (d.results as any[] || []).map((x) =>\n \"Source: \" + x.title + \"\\n\" + x.content\n ).join(\"\\n\\n\");\n } catch {\n return \"\";\n }\n}\nasync function translateToEnglish(p: string, k: string): Promise {\n if (!k) return p;\n try {\n const url =\n \"https://generativelanguage.googleapis.com/v1beta/models/gemini-flash-lite-latest:generateContent?key=\" +\n encodeURIComponent(k);\n const r = await fr(url, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify({\n contents: [{\n parts: [{\n text: 'Translate to English FLUX prompt, ONLY English: \"' + p + '\"',\n }],\n }],\n generationConfig: { temperature: 0.2, maxOutputTokens: 200 },\n }),\n }, 0);\n if (!r.ok) return p;\n const d = await r.json();\n return d?.candidates?.[0]?.content?.parts?.[0]?.text?.trim().replace(\n /^\"|\"$/g,\n \"\",\n ).slice(0, 400) || p;\n } catch {\n return p;\n }\n}\nasync function genImage(\n promptEn: string,\n acc: string,\n tok: string,\n style: string = \"photorealistic\",\n quality: string = \"hd\",\n geminiKey: string = \"\",\n): Promise {\n const pk = \"image\", p = \"🎨 ULTRA\";\n const seed = Math.floor(Math.random() * 999999) + 1;\n let width = 1280, height = 1280, steps = 20;\n if (quality === \"ultra\") {\n width = 1536;\n height = 1536;\n steps = 30;\n } else if (quality === \"draft\") {\n width = 768;\n height = 768;\n steps = 12;\n }\n let suffix =\n \", ultra detailed, 8k, masterpiece, photorealistic, cinematic lighting, sharp focus, best quality\";\n if (style === \"anime\") suffix = \", anime style, vibrant, 8k\";\n else if (style === \"3d\") suffix = \", 3d render, octane, 8k\";\n const enhanced = promptEn + suffix;\n const enc = encodeURIComponent(enhanced);\n if (geminiKey) {\n try {\n const url = \"https://generativelanguage.googleapis.com/v1beta/models/\" +\n NANO_BANANA + \":generateContent?key=\" + encodeURIComponent(geminiKey);\n const r = await fr(url, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify({\n contents: [{ parts: [{ text: enhanced }] }],\n generationConfig: { responseModalities: [\"IMAGE\", \"TEXT\"] },\n }),\n }, 0);\n if (r.ok) {\n const d = await r.json();\n const parts = d?.candidates?.[0]?.content?.parts || [];\n for (const part of parts) {\n if (part.inlineData && part.inlineData.data) {\n return {\n p: \"🍌 ננו-בננה\",\n pk,\n a: \"![תמונה](data:\" + (part.inlineData.mimeType || \"image/png\") +\n \";base64,\" + part.inlineData.data + \")\",\n ms: 0,\n };\n }\n }\n }\n } catch {}\n }\n if (acc && tok) {\n try {\n const url = \"https://api.cloudflare.com/client/v4/accounts/\" +\n encodeURIComponent(acc) + \"/ai/run/\" + CF_IMAGE_MODEL;\n const r = await fr(url, {\n method: \"POST\",\n headers: {\n \"Content-Type\": \"application/json\",\n Authorization: \"Bearer \" + tok,\n },\n body: JSON.stringify({\n prompt: enhanced,\n num_steps: steps,\n guidance: 7.5,\n }),\n }, 0);\n if (r.ok) {\n const buf = await r.arrayBuffer();\n if (buf.byteLength > 5000) {\n const bytes = new Uint8Array(buf);\n let binary = \"\";\n const chunk = 8192;\n for (let i = 0; i < bytes.length; i += chunk) {\n binary += String.fromCharCode.apply(\n null,\n Array.from(bytes.subarray(i, i + chunk)) as any,\n );\n }\n return {\n p,\n pk,\n a: \"![תמונה](data:image/png;base64,\" + btoa(binary) + \")\",\n ms: 0,\n };\n }\n }\n } catch {}\n }\n const proUrl = \"https://image.pollinations.ai/prompt/\" + enc + \"?width=\" +\n width + \"&height=\" + height +\n \"&model=flux-pro&enhance=true&nologo=true&seed=\" + seed;\n return { p, pk, a: \"![תמונה](\" + proUrl + \")\" };\n}\nasync function askGemini(prompt: string, k: string): Promise {\n const pk = \"gemini\", p = PL[pk];\n if (!k) return { p, pk, a: \"\", e: \"לא מוגדר\" };\n const s = Date.now();\n return wt(\n (async () => {\n try {\n const url = \"https://generativelanguage.googleapis.com/v1beta/models/\" +\n MODELS.gemini + \":generateContent?key=\" + encodeURIComponent(k);\n const r = await fr(url, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify({\n systemInstruction: { parts: [{ text: ANON }] },\n contents: [{ parts: [{ text: prompt }] }],\n generationConfig: { temperature: 0.7, maxOutputTokens: 8000 },\n }),\n });\n if (!r.ok) {\n await dbHealth(pk, false);\n return { p, pk, a: \"\", e: \"שגיאה \" + r.status, ms: Date.now() - s };\n }\n const d = await r.json();\n const a = d?.candidates?.[0]?.content?.parts?.[0]?.text?.trim() || \"\";\n if (!a) {\n await dbHealth(pk, false);\n return { p, pk, a: \"\", e: \"ריק\", ms: Date.now() - s };\n }\n await dbHealth(pk, true);\n return { p, pk, a, ms: Date.now() - s, ti: et(prompt), to: et(a) };\n } catch (e) {\n await dbHealth(pk, false);\n return { p, pk, a: \"\", e: String(e).slice(0, 120), ms: Date.now() - s };\n }\n })(),\n P_MS,\n { p, pk, a: \"\", e: \"פסק זמן\", ms: 0 },\n );\n}\nasync function askCompat(\n prompt: string,\n k: string,\n pk: string,\n endpoint: string,\n model: string,\n): Promise {\n const p = PL[pk];\n if (!k) return { p, pk, a: \"\", e: \"לא מוגדר\" };\n const s = Date.now();\n return wt(\n (async () => {\n try {\n const h: any = {\n \"Content-Type\": \"application/json\",\n Authorization: \"Bearer \" + k,\n };\n if (pk === \"openrouter\") {\n h[\"HTTP-Referer\"] = \"https://multi-ai-chat.com\";\n h[\"X-Title\"] = \"Multi-AI\";\n }\n const r = await fr(endpoint, {\n method: \"POST\",\n headers: h,\n body: JSON.stringify({\n model,\n messages: [{ role: \"system\", content: ANON }, {\n role: \"user\",\n content: prompt,\n }],\n temperature: 0.7,\n max_tokens: 8000,\n }),\n });\n if (!r.ok) {\n await dbHealth(pk, false);\n return { p, pk, a: \"\", e: \"שגיאה \" + r.status, ms: Date.now() - s };\n }\n const d = await r.json();\n const a = d?.choices?.[0]?.message?.content?.trim() || \"\";\n if (!a) {\n await dbHealth(pk, false);\n return { p, pk, a: \"\", e: \"ריק\", ms: Date.now() - s };\n }\n await dbHealth(pk, true);\n return { p, pk, a, ms: Date.now() - s, ti: et(prompt), to: et(a) };\n } catch (e) {\n await dbHealth(pk, false);\n return { p, pk, a: \"\", e: String(e).slice(0, 120), ms: Date.now() - s };\n }\n })(),\n P_MS,\n { p, pk, a: \"\", e: \"פסק זמן\", ms: 0 },\n );\n}\nasync function askGroqDual(\n prompt: string,\n k1: string,\n k2: string,\n): Promise {\n const pk = \"groq\", p = PL[pk];\n if (!k1 && !k2) return { p, pk, a: \"\", e: \"לא מוגדר\" };\n const eps = \"https://api.groq.com/openai/v1/chat/completions\";\n if (k1) {\n const r1 = await askCompat(prompt, k1, pk, eps, MODELS[pk]);\n if (r1.a && !r1.e) return r1;\n if (r1.e && (r1.e.includes(\"429\") || r1.e.includes(\"402\")) && k2) {\n const r2 = await askCompat(prompt, k2, pk, eps, MODELS[pk]);\n if (r2.a) {\n r2.p = PL[pk] + \" (key2)\";\n return r2;\n }\n }\n return r1;\n } else return askCompat(prompt, k2, pk, eps, MODELS[pk]);\n}\nasync function askProvider(\n prompt: string,\n keys: any,\n pk: string,\n): Promise {\n if (pk === \"gemini\") return askGemini(prompt, keys.gemini);\n if (pk === \"groq\") return askGroqDual(prompt, keys.groq, keys.groq2);\n const eps: Record = {\n cerebras: \"https://api.cerebras.ai/v1/chat/completions\",\n nvidia: \"https://integrate.api.nvidia.com/v1/chat/completions\",\n mistral: \"https://api.mistral.ai/v1/chat/completions\",\n openrouter: \"https://openrouter.ai/api/v1/chat/completions\",\n cohere: \"https://api.cohere.ai/compatibility/v1/chat/completions\",\n zai: \"https://open.bigmodel.cn/api/paas/v4/chat/completions\",\n dahl: \"https://inference.dahl.global/v1/chat/completions\",\n };\n return askCompat(prompt, keys[pk], pk, eps[pk], MODELS[pk]);\n}\nasync function cfCall(\n messages: any[],\n acc: string,\n tok: string,\n): Promise {\n try {\n const url = \"https://api.cloudflare.com/client/v4/accounts/\" +\n encodeURIComponent(acc) + \"/ai/run/\" + CF_MODEL;\n const r = await fr(url, {\n method: \"POST\",\n headers: {\n \"Content-Type\": \"application/json\",\n Authorization: \"Bearer \" + tok,\n },\n body: JSON.stringify({ messages, max_tokens: 8000 }),\n });\n if (!r.ok) return \"\";\n const d = await r.json();\n return String(d?.result?.response || \"\").trim();\n } catch {\n return \"\";\n }\n}\nfunction buildJP(q: string, answers: AIR[], hist: Msg[], searchCtx: string) {\n const valid = answers.filter((a) => a.a && a.a.length > 20);\n const fb = valid.length === 0\n ? answers.filter((a) => a.a && a.a.length > 0)\n : valid;\n const txt = fb.map((a) => \"--- DRAFT ---\\n\" + tr(a.a, MAX_JA)).join(\"\\n\\n\");\n const histTxt = hist.length\n ? \"History:\\n\" + hist.map((m) =>\n (m.role === \"user\" ? \"User: \" : \"Assistant: \") + tr(m.content, 500)\n ).join(\"\\n\") + \"\\n\\n\"\n : \"\";\n const searchBlock = searchCtx\n ? \"\\n\\nWEB SEARCH:\\n\" + tr(searchCtx, 5000) + \"\\n\"\n : \"\";\n return JSP + \"\\n\\n\" + histTxt + \"User Question: \" + q + \"\\n\" + searchBlock +\n \"\\nDrafts:\\n\" + txt + \"\\n\\nFinal answer:\";\n}\nfunction parseJP(out: string) {\n const s = String(out || \"\");\n const a = s.match(/ANSWER:\\s*([\\s\\S]*)/i);\n return { answer: a ? a[1].trim() : s.trim() };\n}\n\nfunction page(\n cid: string,\n convs: any[],\n msgs: Msg[],\n avail: string[],\n health: any[],\n): Response {\n const html =\n `Multi-AI v28 ULTRA

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🎨 FLUX ULTRA

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