\n \n \n \n \n

\n \n `;\n}\n\n// --- Main Request Handler (Concise) ---\nexport default async function(req: Request): Promise {\n const reqId = `r-${Date.now()}-${Math.random().toString(36).slice(2, 7)}`; // Abbreviated id\n const reqLgr = new LogAgent(reqId);\n const log = reqLgr.log.bind(reqLgr);\n const url = new URL(req.url);\n const headers = {\n \"Content-Type\": \"application/json\",\n \"Access-Control-Allow-Origin\": \"*\",\n \"Access-Control-Allow-Methods\": \"GET, POST, OPTIONS\",\n \"Access-Control-Allow-Headers\": \"Content-Type, Authorization\",\n };\n\n if (req.method === \"OPTIONS\") {\n log(\"IN\", \"H\", \"OPT\");\n return new Response(null, { status: 204, headers });\n }\n\n try {\n if (req.method === \"GET\" && (url.pathname === \"/\" || url.pathname === \"\")) {\n log(\"IN\", \"H\", \"GET /\");\n const html = generateOrthogonalUI();\n return new Response(html, { status: 200, headers: { ...headers, \"Content-Type\": \"text/html; charset=utf-8\" } });\n }\n\n if (req.method === \"POST\" && url.pathname === \"/questionnaire\") {\n log(\"IN\", \"H\", \"POST /q\");\n let b;\n let rawB = \"[No body]\";\n try {\n rawB = await req.text();\n b = JSON.parse(rawB);\n if (\n !b?.task || typeof b.task !== \"string\" || !b.action\n || ![\"start\", \"answer\", \"back\", \"restart\"].includes(b.action) || (b.action === \"answer\" && !b.lastAnswer)\n ) throw new Error(\"Bad req.\");\n } catch (e: any) {\n log(\"WN\", \"H\", \"Bad /q body\", { e: e.m, b: rawB.slice(0, 300) });\n return new Response(JSON.stringify({ err: `Bad Req: ${e.m}`, st: null, dbgL: reqLgr.getLogs() }), {\n status: 400,\n headers,\n });\n }\n\n const qA = new QAgent(log);\n let qRes: QResp;\n try {\n log(\"DB\", \"H\", `Proc: ${b.action}`, { t: b.task, s: b.sessionId, hasS: !!b.state, hasA: !!b.lastAnswer });\n switch (b.action) {\n case \"start\":\n qRes = await qA.nextStep(b.sessionId, b.task, b.lastAnswer, null);\n break;\n case \"answer\":\n qRes = await qA.nextStep(b.sessionId, b.task, b.lastAnswer, b.state);\n break;\n case \"back\":\n qRes = !b.state\n ? { sid: b.sessionId || `e-${Date.now()}`, isDone: false, err: \"No state to go back.\", state: null }\n : await qA.goBack(b.sessionId, b.task, b.state);\n break;\n case \"restart\":\n qRes = await qA.restart(b.sessionId, b.task);\n break;\n default:\n qRes = {\n sid: b.sessionId || `e-${Date.now()}`,\n isDone: false,\n err: \"Invalid action.\",\n state: b.state || null,\n }; // Should not reach\n }\n const respSt = qRes.state ? { ...qRes.state } : null; // Copy state\n log(\"DB\", \"H\", \"Q step proc.\", {\n sid: qRes.sid,\n done: qRes.isDone,\n hasE: !!qRes.err,\n nextF: qRes.nextQ?.field,\n });\n return new Response(JSON.stringify({ ...qRes, state: respSt }), { status: qRes.err ? 400 : 200, headers });\n } catch (e: any) {\n log(\"ER\", \"H\", `QAgent proc err: ${b.action}.`, { e: e.m, s: e.stack?.slice(0, 300) });\n return new Response(\n JSON.stringify({ err: `Internal Q err: ${e.m}`, st: null, dbgL: reqLgr.getLogs(), mid: reqId }),\n { status: 500, headers },\n );\n }\n }\n\n if (req.method === \"POST\" && url.pathname === \"/execute\") {\n log(\"IN\", \"H\", \"POST /exec\");\n let vInput: UserIn;\n let rawP = \"[No payload]\";\n try {\n const p = await req.json();\n rawP = JSON.stringify(p).slice(0, 300);\n log(\"DB\", \"H\", \"Payload /exec\", { p: rawP });\n vInput = UserInSchema.parse(p);\n log(\"IN\", \"H\", \"Payload valid OK /exec.\", { t: vInput.task });\n } catch (e: any) {\n let d = \"Bad input.\";\n if (e instanceof z.ZodError) d = e.issues.map(i => `${i.path.join(\".\")}: ${i.m}`).join(\"; \"); else d = e.m;\n log(\"WN\", \"H\", \"Valid fail /exec.\", { e: d, p: rawP });\n return new Response(\n JSON.stringify({ err: \"Bad input data.\", details: d, dbgL: reqLgr.getLogs(), mid: `m-v-${reqId}` }),\n { status: 400, headers },\n );\n }\n const execLgr = new LogAgent();\n const orch = new Orchestrator(execLgr);\n const finalRes: FinalRes = await orch.runWorkflow(vInput);\n finalRes.dbgLog = execLgr.getLogs();\n const respS = finalRes.err ? 500 : 200;\n log(\"IN\", \"H\", `/exec wf end status ${respS}`, { mid: finalRes.mid, hasE: !!finalRes.err });\n return new Response(JSON.stringify(finalRes), { status: respS, headers });\n }\n\n log(\"WN\", \"H\", `Unsup req: ${req.method} ${url.pathname}`);\n const errL = reqLgr.getLogs();\n return new Response(JSON.stringify({ err: \"Not Found\", dbgL: errL, mid: reqId }), { status: 404, headers });\n } catch (err: any) {\n log(\"ER\", \"H\", \"Unhandled exc.\", { e: err.m, s: err.stack?.slice(0, 300) });\n const crashL = reqLgr.getLogs();\n return new Response(\n JSON.stringify({\n err: \"Internal Error\",\n details: \"Unexpected server error.\",\n dbgL: crashL,\n mid: `m-c-${reqId}`,\n st: null,\n }),\n { status: 500, headers },\n );\n }\n}","deleted","label","children",[],[152],{"_105":172,"_98":173,"_153":174,"_155":-5,"_156":136,"_157":175,"_158":159,"_107":176,"_102":29,"_162":177,"_164":71,"_166":25,"_167":-5,"_168":178,"_101":179},"65bad9e2-31b9-11f0-9937-569c3dd06744","new-file-6642.tsx","4bce7140-eb21-4344-be91-429c0d175e28",1,["D",1747333279344],"script",[],[173],"files",[150,171],"counts",{"_184":29,"_185":175,"_186":175,"_187":29},"pulls","branches","forks","envVars","contents",[190,193],{"_105":151,"_98":152,"_153":154,"_155":-5,"_156":136,"_157":135,"_158":159,"_107":191,"_102":161,"_162":163,"_164":165,"_166":25,"_167":-5,"_101":192},["D",1747341514149],[152],{"_105":172,"_98":173,"_153":174,"_155":-5,"_156":136,"_157":175,"_158":159,"_107":194,"_102":29,"_162":177,"_164":71,"_166":25,"_167":-5,"_101":195},["D",1747333279344],[173],"file","upstreamProject",{"_105":199,"_98":99,"_113":-5,"_114":-5,"_111":112,"_19":200},"850e3750-2a6e-11f0-98b1-569c3dd06744",{"_96":201,"_131":202},"Get","https://img.clerk.com/eyJ0eXBlIjoiZGVmYXVsdCIsImlpZCI6Imluc18yTm10cGhQUklwU0tqZHNiOHNnNGd2ZjJURFUiLCJyaWQiOiJ1c2VyXzJ2TTFGWERQeGFtTU5EUzFhMFh2SFdUc2xwQSJ9","upstreamBranch",{"_105":139,"_107":205,"_206":207,"_98":40,"_137":199,"_102":208,"_138":-5,"_140":-5,"_209":210,"_109":-5,"_147":25,"_111":112,"_146":201,"_14":211,"_145":99},["D",1746531461552],"updatedAt",["D",1747807698630],16,"lockfileKey","1747807821608-esm.town_v_Get_Experimental@16-main","719ff695-0114-4462-88c2-f8b51b154126","emptyEnvVars","isNew","routes/_app.x.$handle.$name.branch.$branch.history",{"_96":97,"_98":99,"_100":40,"_103":216,"_220":221,"_244":29,"_245":25},{"_105":106,"_98":99,"_107":217,"_109":-5,"_110":25,"_111":112,"_113":-5,"_114":-5,"_12":115,"_116":-5,"_117":25,"_118":-5,"_119":29,"_14":120,"_121":122,"_123":122,"_124":125,"_126":125,"_127":125,"_128":122,"_129":122,"_19":218,"_133":219,"_147":25},["D",1747333279344],{"_96":97,"_131":132},{"_102":135,"_98":40,"_105":136,"_137":106,"_138":139,"_140":141,"_142":112,"_143":144,"_145":99,"_146":97},"history",[222,227,234],{"_153":154,"_102":135,"_107":223,"_156":136,"_180":224},["D",1747341514149],[225],{"_105":151,"_156":136,"_153":154,"_98":152,"_164":165,"_162":163,"_102":161,"_155":-5,"_107":223,"_157":135,"_167":-5,"_158":159,"_166":25,"_101":226},[152],{"_153":154,"_102":161,"_107":228,"_156":136,"_180":229},["D",1747333362097],[230],{"_105":231,"_156":136,"_153":154,"_98":152,"_164":232,"_162":163,"_102":175,"_155":-5,"_107":228,"_157":161,"_167":-5,"_158":25,"_166":25,"_101":233},"97084034-31b9-11f0-8c87-569c3dd06744","import { fetch } from \"https://esm.town/v/std/fetch\";\nimport { OpenAI } from \"https://esm.town/v/std/openai\";\nimport { z } from \"npm:zod\";\n\n// --- Types (Abbreviated & Core) ---\ntype TskIn = { mid: string; tid: string; p: T };\ntype TskOut = { mid: string; cid: string; p: T; e?: string };\ntype Lvl = \"DEBUG\" | \"INFO\" | \"WARN\" | \"ERROR\";\ntype LogFn = (lvl: Lvl, comp: string, msg: string, dt?: any, mid?: string, tid?: string) => void;\ntype LogEntry = { ts: string; mid: string; tid?: string; lvl: Lvl; comp: string; msg: string; dt?: any };\ntype BaseIn = { bType: string; sDesc: string; tAud: string; bTone?: string; goals?: string };\ntype CntIn = BaseIn & {\n cType: \"promo_post\" | \"blog_idea\" | \"blog_draft\" | \"ad_copy\";\n plat: \"facebook\" | \"instagram\" | \"tiktok\" | \"linkedin\" | \"google_ads\" | \"blog\" | \"generic\";\n specInstr?: string;\n};\ntype StratIn = BaseIn & { plats: string[]; budgetLvl?: \"low\" | \"medium\" | \"high\"; duration?: string };\ntype LogoIn = BaseIn & { bName: string; stylePrefs?: string; colorPrefs?: string };\ntype BrandIn = BaseIn & { bName: string; coreVals?: string };\ntype SimIn = BaseIn & {\n simType: \"ad_response_estimate\" | \"customer_interaction\" | \"other\";\n specParams: Record | { description: string };\n};\ntype MetaIn = { pInput: string };\nconst UserInSchema = z.object({\n task: z.enum([\n \"create_content\",\n \"develop_strategy\",\n \"generate_logo_concept\",\n \"build_brand_identity\",\n \"run_simulation\",\n \"meta_prompt\",\n ]),\n data: z.record(z.any()),\n}).refine((input) => {\n const d = input.data;\n const dataKeys = Object.keys(d);\n const hasKey = (key: string) => dataKeys.includes(key) && d[key] != null && d[key] !== \"\";\n switch (input.task) {\n case \"create_content\":\n return hasKey(\"businessType\") && hasKey(\"serviceDescription\") && hasKey(\"targetAudience\") && hasKey(\"contentType\")\n && hasKey(\"platform\");\n case \"develop_strategy\":\n return hasKey(\"businessType\") && hasKey(\"serviceDescription\") && hasKey(\"targetAudience\")\n && Array.isArray(d.platforms) && d.platforms.length > 0;\n case \"generate_logo_concept\":\n return hasKey(\"businessType\") && hasKey(\"serviceDescription\") && hasKey(\"targetAudience\")\n && hasKey(\"businessName\");\n case \"build_brand_identity\":\n return hasKey(\"businessType\") && hasKey(\"serviceDescription\") && hasKey(\"targetAudience\")\n && hasKey(\"businessName\");\n case \"run_simulation\":\n return hasKey(\"businessType\") && hasKey(\"serviceDescription\") && hasKey(\"targetAudience\")\n && hasKey(\"simulationType\") && hasKey(\"specificParams\")\n && (typeof d.specificParams === \"object\" || typeof d.specificParams === \"string\");\n case \"meta_prompt\":\n return hasKey(\"prompt_input\");\n default:\n return false;\n }\n}, { message: \"Missing required fields for the selected task or invalid data format.\" });\ntype UserIn = z.infer;\ntype CntOut = { content: string; suggestions?: string };\ntype StratOut = { strategy: string; adIdeas?: string[]; audSugs?: string[] };\ntype LogoOut = { concepts: string[]; prompts?: string[]; svg?: string };\ntype BrandOut = { bVoice: string; kMsgs: string[]; cPalSugs: string; typo: string };\ntype SimOut = { simResult: string; analysis?: string };\ntype MetaOut = { sysPrompt: string };\ntype FinalRes = { res?: any; err?: string; details?: string; dbgLog: LogEntry[]; mid: string };\ntype QState = {\n sid: string;\n task: UserIn[\"task\"];\n reqFlds: string[];\n answers: Partial>;\n qHist: { qid: string; field: string; text: string }[];\n isDone: boolean;\n};\ntype Quest = {\n id: string;\n field: string;\n text: string;\n type: \"text\" | \"textarea\" | \"select\" | \"confirm\";\n opts?: { lbl: string; val: string }[];\n};\ntype QResp = { sid: string; nextQ?: Quest; isDone: boolean; data?: UserIn; err?: string; state: QState | null };\n\n// --- LogAgent Class ---\nclass LogAgent {\n logs: LogEntry[];\n midCtx?: string;\n constructor(mid?: string) {\n this.logs = [];\n this.midCtx = mid;\n }\n log(lvl: Lvl, comp: string, msg: string, dt?: any, mid?: string, tid?: string): void {\n const effMid = mid || this.midCtx || \"N/A\";\n let safeDt: any;\n if (dt != null) {\n try {\n safeDt = JSON.parse(JSON.stringify(dt, this.getCircReplacer()));\n } catch (e) {\n console.error(`[LogAgent] Failed stringify details: ${(e as Error).message}`);\n safeDt = `[Logging Error: ${(e as Error).message}]`;\n }\n } else { safeDt = dt; }\n const entry: LogEntry = { ts: new Date().toISOString(), mid: effMid, tid, lvl, comp, msg, dt: safeDt };\n this.logs.push(entry);\n const dtStr = safeDt != null ? `| Details: ${JSON.stringify(safeDt)}` : \"\";\n console.log(\n `[${entry.ts}] [${entry.mid}] [${entry.tid || \"---\"}] [${entry.lvl}] [${entry.comp}] ${entry.msg} ${dtStr}`,\n );\n }\n private getCircReplacer = () => {\n const seen = new WeakSet();\n return (_key: string, value: any) => {\n if (typeof value === \"object\" && value !== null) {\n if (seen.has(value)) { return \"[Circular Reference]\"; }\n seen.add(value);\n }\n return value;\n };\n };\n getLogs(): LogEntry[] {\n try {\n return JSON.parse(JSON.stringify(this.logs));\n } catch (e) {\n console.error(\"[LogAgent] Failed deep copy logs:\", e);\n return [...this.logs];\n }\n }\n clearLogs(): void {\n this.logs = [];\n }\n setMidCtx(mid: string): void {\n this.midCtx = mid;\n }\n}\n\n// --- callOpenAI Function ---\nasync function callOpenAI(\n sysPrompt: string,\n userPrompt: string,\n mid: string,\n tid: string,\n logFn: LogFn,\n): Promise {\n logFn(\n \"DEBUG\",\n \"callOpenAI\",\n `Initiating OpenAI call tid=${tid}`,\n { spLen: sysPrompt.length, upLen: userPrompt.length },\n mid,\n tid,\n );\n try {\n if (!process.env.OPENAI_API_KEY) {\n logFn(\"ERROR\", \"callOpenAI\", \"OpenAI API key missing.\", undefined, mid, tid);\n throw new Error(\"OpenAI API key not configured.\");\n }\n const openai = new OpenAI();\n const completion = await openai.chat.completions.create({\n model: \"gpt-4o-mini\",\n messages: [{ role: \"system\", content: sysPrompt }, { role: \"user\", content: userPrompt }],\n temperature: 0.7,\n max_tokens: 2048,\n });\n const resText = completion.choices[0]?.message?.content;\n const usage = completion.usage;\n if (!resText) {\n logFn(\n \"WARN\",\n \"callOpenAI\",\n `OpenAI call returned no text tid=${tid}.`,\n { usage: usage, finishReason: completion.choices[0]?.finish_reason },\n mid,\n tid,\n );\n return null;\n }\n logFn(\n \"INFO\",\n \"callOpenAI\",\n `OpenAI call OK tid=${tid}`,\n { resLen: resText.length, usage: usage, finishReason: completion.choices[0]?.finish_reason },\n mid,\n tid,\n );\n return resText.trim();\n } catch (err: any) {\n const errDtls = { msg: err.message, name: err.name, status: err.status, type: err.type, code: err.code };\n logFn(\"ERROR\", \"callOpenAI\", `OpenAI API call failed tid=${tid}`, { error: errDtls }, mid, tid);\n throw new Error(`OpenAI API failed: ${err.message}` + (err.code ? ` (Code: ${err.code})` : \"\"));\n }\n}\n\n// --- QAgent Class (with loop fixes) ---\nclass QAgent {\n lg: LogFn;\n private baseReq = [\"bType\", \"sDesc\", \"tAud\"];\n private baseOpt = [\"bTone\", \"goals\"];\n private taskSpec: Record = {\n \"create_content\": { req: [\"cType\", \"plat\"], opt: [\"specInstr\"] },\n \"develop_strategy\": { req: [\"plats\"], opt: [\"budgetLvl\", \"duration\"] },\n \"generate_logo_concept\": { req: [\"bName\"], opt: [\"stylePrefs\", \"colorPrefs\"] },\n \"build_brand_identity\": { req: [\"bName\"], opt: [\"coreVals\"] },\n \"run_simulation\": { req: [\"simType\", \"specParams\"], opt: [] },\n \"meta_prompt\": { req: [\"pInput\"], opt: [] },\n };\n constructor(lgFn: LogFn) {\n this.lg = lgFn;\n }\n private getRequiredFields(task: UserIn[\"task\"]): string[] {\n if (task === \"meta_prompt\") return this.taskSpec.meta_prompt.req;\n return [...new Set([...this.baseReq, ...(this.taskSpec[task]?.req || [])])];\n }\n private getOptionalFields(task: UserIn[\"task\"]): string[] {\n if (task === \"meta_prompt\") return [];\n return [...new Set([...this.baseOpt, ...(this.taskSpec[task]?.opt || [])])];\n }\n private isOptional(field: string, task: UserIn[\"task\"]): boolean {\n return this.getOptionalFields(task).includes(field);\n }\n private selectNextField(\n required: string[],\n optional: string[],\n answers: Record,\n task: UserIn[\"task\"],\n ): string | null {\n for (const fld of required) {\n if (!(fld in answers) || (answers[fld] === \"\" && !this.isOptional(fld, task))) {\n this.lg(\"DEBUG\", \"QAgent.selectNextField\", `Selected missing/empty REQUIRED field: ${fld}`, {\n answers: Object.keys(answers),\n }, undefined);\n return fld;\n }\n }\n for (const fld of optional) {\n if (!(fld in answers)) {\n this.lg(\"DEBUG\", \"QAgent.selectNextField\", `Selected unasked OPTIONAL field: ${fld}`, {\n answers: Object.keys(answers),\n }, undefined);\n return fld;\n }\n }\n this.lg(\n \"DEBUG\",\n \"QAgent.selectNextField\",\n `All required fields populated, all optional fields considered. Done collecting.`,\n { answers: Object.keys(answers) },\n undefined,\n );\n return null;\n }\n private formatQuest(field: string, curState: QState): Quest {\n const qid = `${field}-${Date.now()}`;\n let text = `What is your ${field.replace(/([A-Z])/g, \" $1\").toLowerCase()}?`;\n let type: Quest[\"type\"] = \"text\";\n let opts: Quest[\"opts\"] | undefined = undefined;\n const bName = curState.answers.bName || \"your business\";\n const isOpt = this.isOptional(field, curState.task);\n const optSuffix = isOpt ? \" (Optional)\" : \"\";\n switch (field) {\n case \"bType\":\n text = `Type of business for ${bName}? (e.g., SaaS, Bakery)`;\n break;\n case \"sDesc\":\n text = `Describe products/services for ${bName}.`;\n type = \"textarea\";\n break;\n case \"tAud\":\n text = `Ideal customer for ${bName}? (Specific, e.g., Tech startups)`;\n type = \"textarea\";\n break;\n case \"bTone\":\n text = `Desired tone for ${bName}?${optSuffix}`;\n type = \"select\";\n opts = [\n { lbl: `-- Tone${optSuffix} --`, val: \"\" },\n { lbl: \"Professional\", val: \"professional\" },\n { lbl: \"Friendly\", val: \"friendly\" },\n { lbl: \"Casual\", val: \"casual\" },\n { lbl: \"Humorous\", val: \"humorous\" },\n { lbl: \"Informative\", val: \"informative\" },\n ];\n break;\n case \"goals\":\n text = `Main goals for this task?${optSuffix}`;\n type = \"textarea\";\n break;\n case \"bName\":\n text = `Exact business name?`;\n break;\n case \"cType\":\n text = \"Content type needed?\";\n type = \"select\";\n opts = [\n { lbl: \"-- Type --\", val: \"\" },\n { lbl: \"Promo Post\", val: \"promo_post\" },\n { lbl: \"Blog Ideas\", val: \"blog_idea\" },\n { lbl: \"Blog Draft\", val: \"blog_draft\" },\n { lbl: \"Ad Copy\", val: \"ad_copy\" },\n ];\n break;\n case \"plat\":\n text = \"Platform for content?\";\n type = \"select\";\n opts = [\n { lbl: \"-- Platform --\", val: \"\" },\n { lbl: \"Generic\", val: \"generic\" },\n { lbl: \"Facebook\", val: \"facebook\" },\n { lbl: \"Instagram\", val: \"instagram\" },\n { lbl: \"LinkedIn\", val: \"linkedin\" },\n { lbl: \"Blog\", val: \"blog\" },\n ];\n break;\n case \"specInstr\":\n text = `Specific instructions/keywords?${optSuffix}`;\n type = \"textarea\";\n break;\n case \"plats\":\n text = \"Strategy platforms? (e.g., LinkedIn, SEO - comma separated)\";\n break;\n case \"budgetLvl\":\n text = `Approx budget level?${optSuffix}`;\n type = \"select\";\n opts = [{ lbl: `-- Budget${optSuffix} --`, val: \"\" }, { lbl: \"Low (Organic)\", val: \"low\" }, {\n lbl: \"Medium (Mod Ads)\",\n val: \"medium\",\n }, { lbl: \"High (Sig Ads)\", val: \"high\" }];\n break;\n case \"duration\":\n text = `Strategy duration?${optSuffix}`;\n break;\n case \"stylePrefs\":\n text = `Logo style preferences?${optSuffix}`;\n break;\n case \"colorPrefs\":\n text = `Logo color preferences?${optSuffix}`;\n break;\n case \"coreVals\":\n text = `Core values/mission of ${bName}?${optSuffix}`;\n type = \"textarea\";\n break;\n case \"simType\":\n text = \"Simulation type?\";\n type = \"select\";\n opts = [{ lbl: \"-- Sim --\", val: \"\" }, { lbl: \"Ad Response Est.\", val: \"ad_response_estimate\" }, {\n lbl: \"Customer Interaction\",\n val: \"customer_interaction\",\n }, { lbl: \"Other\", val: \"other\" }];\n break;\n case \"specParams\":\n text = `Sim details/params? (Ad: audience, platform, offer. Cust: scenario, issue. Other: describe.)`;\n type = \"textarea\";\n break;\n case \"pInput\":\n text = \"AI task desc or prompt to refine?\";\n type = \"textarea\";\n break;\n default:\n text = `Please provide \\'${field}\\'.${optSuffix}`;\n if (field.toLowerCase().includes(\"desc\") || field.toLowerCase().includes(\"details\")) { type = \"textarea\"; }\n break;\n }\n if (isOpt && !text.includes(\"(Optional)\")) { text += \" (Optional)\"; }\n return { id: qid, field, text, type, opts };\n }\n async nextStep(\n curSid: string | null,\n task: UserIn[\"task\"],\n lastAns: { field: string; value: any } | null,\n curSt?: QState | null,\n ): Promise {\n let state: QState;\n const sid = curSid || `sess-${Date.now()}-${Math.random().toString(36).substring(2, 8)}`;\n const requiredFields = this.getRequiredFields(task);\n const optionalFields = this.getOptionalFields(task);\n const allRelevantFields = [...requiredFields, ...optionalFields];\n if (!curSt || !curSid || curSt.sid !== sid || curSt.task !== task) {\n this.lg(\"INFO\", \"QAgent\", `Initializing/Resetting state for task: ${task}`, {\n oldSid: curSt?.sid,\n oldTask: curSt?.task,\n newSid: sid,\n }, sid);\n state = { sid: sid, task: task, reqFlds: allRelevantFields, answers: {}, qHist: [], isDone: false };\n if (lastAns?.field && allRelevantFields.includes(lastAns.field)) {\n const val = typeof lastAns.value === \"string\" ? lastAns.value.trim() : lastAns.value;\n if (val !== \"\" || this.isOptional(lastAns.field, state.task)) {\n state.answers[lastAns.field] = val;\n this.lg(\n \"DEBUG\",\n \"QAgent\",\n `Applied initial answer post-reset: Field '${lastAns.field}'`,\n { value: val },\n sid,\n );\n } else {this.lg(\n \"DEBUG\",\n \"QAgent\",\n `Ignoring empty initial answer for required field '${lastAns.field}' post-reset.`,\n { value: val },\n sid,\n );}\n }\n } else {\n state = { ...curSt, answers: { ...curSt.answers }, qHist: [...curSt.qHist] };\n if (lastAns?.field && state.reqFlds.includes(lastAns.field)) {\n this.lg(\n \"DEBUG\",\n \"QAgent\",\n `Processing answer for field '${lastAns.field}'`,\n { value: lastAns.value },\n state.sid,\n );\n const val = typeof lastAns.value === \"string\" ? lastAns.value.trim() : lastAns.value;\n if (val !== \"\" || this.isOptional(lastAns.field, state.task)) { state.answers[lastAns.field] = val; } else {\n this.lg(\n \"WARN\",\n \"QAgent\",\n `Received empty value for required field '${lastAns.field}'. Storing empty string.`,\n undefined,\n state.sid,\n );\n state.answers[lastAns.field] = \"\";\n }\n const lastQAsked = state.qHist[state.qHist.length - 1];\n if (lastQAsked && lastQAsked.field !== lastAns.field) {\n this.lg(\n \"WARN\",\n \"QAgent\",\n `Answer received for field '${lastAns.field}' but last question asked was for '${lastQAsked?.field}'.`,\n undefined,\n state.sid,\n );\n }\n }\n }\n const nextFld = this.selectNextField(requiredFields, optionalFields, state.answers, state.task);\n if (!nextFld) {\n this.lg(\"INFO\", \"QAgent\", `All fields gathered for task '${state.task}'. Attempting final validation.`, {\n gathered: Object.keys(state.answers),\n }, state.sid);\n const finalData = this.finalizeData(state.answers, state.task, state.sid);\n try {\n UserInSchema.parse(finalData);\n this.lg(\"INFO\", \"QAgent\", \"Final data validation OK.\", { finalDataTask: finalData.task }, state.sid);\n state.isDone = true;\n return { sid: state.sid, isDone: true, data: finalData, state, nextQ: undefined, err: undefined };\n } catch (validErr) {\n if (validErr instanceof z.ZodError) {\n const errMsgs = validErr.issues.map(i => `Field '${i.path.join(\".\")}': ${i.message}`).join(\"; \");\n this.lg(\"ERROR\", \"QAgent\", \"Final data validation FAILED.\", {\n errs: validErr.issues,\n dataAttempted: finalData,\n }, state.sid);\n state.isDone = false;\n const firstFailedPath = validErr.issues[0]?.path;\n let fieldToReask: string | null = null;\n if (firstFailedPath && firstFailedPath.length > 1) {\n const schemaFieldName = firstFailedPath[1].toString();\n const keyMap = this.getKeyMap();\n const internalFieldName = Object.keys(keyMap).find(key => keyMap[key] === schemaFieldName);\n if (internalFieldName && allRelevantFields.includes(internalFieldName)) {\n fieldToReask = internalFieldName;\n this.lg(\n \"WARN\",\n \"QAgent\",\n `Validation failed on schema field '${schemaFieldName}', mapped back to internal field '${fieldToReask}'. Re-asking.`,\n { error: errMsgs },\n state.sid,\n );\n delete state.answers[fieldToReask];\n }\n }\n if (fieldToReask) {\n const nextQ = this.formatQuest(fieldToReask, state);\n if (state.qHist.length > 0 && state.qHist[state.qHist.length - 1].field === fieldToReask) {\n state.qHist.pop();\n }\n return {\n sid: state.sid,\n isDone: false,\n nextQ,\n state,\n data: undefined,\n err: `Please check your input for '${fieldToReask}': ${errMsgs}`,\n };\n } else {\n this.lg(\"ERROR\", \"QAgent\", \"Validation failed, but couldn't identify specific field to re-ask.\", {\n error: errMsgs,\n issues: validErr.issues,\n }, state.sid);\n return {\n sid: state.sid,\n isDone: false,\n err: `Data validation failed: ${errMsgs}. Cannot proceed. Try restarting task?`,\n state,\n nextQ: undefined,\n data: undefined,\n };\n }\n } else {\n this.lg(\"ERROR\", \"QAgent\", \"Unexpected error during final data validation.\", {\n error: (validErr as Error).message,\n dataAttempted: finalData,\n }, state.sid);\n state.isDone = false;\n return {\n sid: state.sid,\n isDone: false,\n err: `Unexpected validation error: ${(validErr as Error).message}`,\n state,\n nextQ: undefined,\n data: undefined,\n };\n }\n }\n } else {\n const nextQ = this.formatQuest(nextFld, state);\n if (!state.qHist.find(q => q.id === nextQ.id)) {\n state.qHist.push({ qid: nextQ.id, field: nextQ.field, text: nextQ.text });\n }\n this.lg(\"INFO\", \"QAgent\", `Asking next question for field: '${nextFld}'`, { qText: nextQ.text }, state.sid);\n return { sid: state.sid, isDone: false, nextQ, state, data: undefined, err: undefined };\n }\n }\n private getKeyMap(): Record {\n return {\n bType: \"businessType\",\n sDesc: \"serviceDescription\",\n tAud: \"targetAudience\",\n bTone: \"brandTone\",\n goals: \"goals\",\n cType: \"contentType\",\n plat: \"platform\",\n specInstr: \"specificInstructions\",\n plats: \"platforms\",\n budgetLvl: \"budgetLevel\",\n duration: \"duration\",\n bName: \"businessName\",\n stylePrefs: \"stylePreferences\",\n colorPrefs: \"colorPreferences\",\n coreVals: \"coreValues\",\n simType: \"simulationType\",\n specParams: \"specificParams\",\n pInput: \"prompt_input\",\n };\n }\n private finalizeData(gathered: Record, task: UserIn[\"task\"], sid?: string): UserIn {\n let finalPayloadData: Record = { ...gathered };\n const requiredFields = this.getRequiredFields(task);\n const optionalFields = this.getOptionalFields(task);\n const allFields = [...requiredFields, ...optionalFields];\n allFields.forEach(field => {\n if (this.isOptional(field, task) && (finalPayloadData[field] == null || finalPayloadData[field] === \"\")) {\n delete finalPayloadData[field];\n this.lg(\"DEBUG\", \"finalizeData\", `Removed empty/unanswered optional field: ${field}`, undefined, sid);\n } else if (\n !this.isOptional(field, task) && (finalPayloadData[field] == null || finalPayloadData[field] === \"\")\n ) {\n this.lg(\n \"WARN\",\n \"finalizeData\",\n `Required field '${field}' is missing or empty before final mapping. Validation will likely fail.`,\n { value: finalPayloadData[field] },\n sid,\n );\n }\n });\n if (task === \"develop_strategy\" && finalPayloadData.plats !== undefined) {\n if (typeof finalPayloadData.plats === \"string\") {\n const raw = finalPayloadData.plats;\n finalPayloadData.plats = raw.split(\",\").map((p: string) => p.trim().toLowerCase()).filter((p: string) =>\n p.length > 0\n );\n this.lg(\"DEBUG\", \"finalizeData\", `Transformed plats string to array`, {\n orig: raw,\n res: finalPayloadData.plats,\n }, sid);\n } else if (!Array.isArray(finalPayloadData.plats)) {\n this.lg(\n \"WARN\",\n \"finalizeData\",\n `Plats field not string/array. Setting empty.`,\n { val: finalPayloadData.plats },\n sid,\n );\n finalPayloadData.plats = [];\n }\n finalPayloadData.plats = (finalPayloadData.plats as any[]).filter((p: any) => typeof p === \"string\");\n }\n if (task === \"run_simulation\" && finalPayloadData.specParams !== undefined) {\n if (typeof finalPayloadData.specParams === \"string\") {\n const paramStr = finalPayloadData.specParams.trim();\n if (paramStr.startsWith(\"{\") && paramStr.endsWith(\"}\")) {\n try {\n const parsed = JSON.parse(paramStr);\n if (typeof parsed === \"object\" && parsed !== null && !Array.isArray(parsed)) {\n finalPayloadData.specParams = parsed;\n this.lg(\"DEBUG\", \"finalizeData\", `Parsed specParams string as JSON object.`, { parsed }, sid);\n } else {\n finalPayloadData.specParams = { description: paramStr };\n this.lg(\n \"WARN\",\n \"finalizeData\",\n `Sim specParams was valid JSON but not object, wrapping as description.`,\n { raw: gathered.specParams },\n sid,\n );\n }\n } catch (e) {\n finalPayloadData.specParams = { description: paramStr };\n this.lg(\n \"WARN\",\n \"finalizeData\",\n `Sim specParams looked like JSON but failed parsing, wrapping as description.`,\n { raw: gathered.specParams, err: (e as Error).message },\n sid,\n );\n }\n } else {\n finalPayloadData.specParams = { description: paramStr };\n this.lg(\"DEBUG\", \"finalizeData\", `Sim specParams string treated as description.`, { desc: paramStr }, sid);\n }\n } else if (\n typeof finalPayloadData.specParams !== \"object\" || finalPayloadData.specParams === null\n || Array.isArray(finalPayloadData.specParams)\n ) {\n this.lg(\"WARN\", \"finalizeData\", `Sim specParams not string/object. Wrapping its string value.`, {\n val: finalPayloadData.specParams,\n }, sid);\n try {\n finalPayloadData.specParams = { description: JSON.stringify(finalPayloadData.specParams) };\n } catch (e) {\n finalPayloadData.specParams = { description: \"[Error stringifying specParams]\" };\n }\n }\n }\n const finalSchemaData: Record = {};\n const keyMap = this.getKeyMap();\n for (const key in finalPayloadData) {\n if (keyMap[key]) { finalSchemaData[keyMap[key]] = finalPayloadData[key]; } else {\n finalSchemaData[key] = finalPayloadData[key];\n this.lg(\"WARN\", \"finalizeData\", `Field '${key}' not found in keyMap during finalization.`, undefined, sid);\n }\n }\n return { task: task, data: finalSchemaData };\n }\n}\n\n// --- Agent Functions ---\nasync function runCntAgent(task: TskIn, logFn: LogFn): Promise> {\n const { mid, tid, p } = task;\n logFn(\n \"INFO\",\n \"CntAgent\",\n `Starting content gen tid=${tid}`,\n { cType: p.cType, plat: p.plat, goals: p.goals },\n mid,\n tid,\n );\n const sysP = `Expert copywriter for SMBs. Goal: generate content. CONTEXT: BT: ${p.bType || \"N/A\"}, SVC: ${\n p.sDesc || \"N/A\"\n }, TA: ${p.tAud || \"General\"}, Tone: ${p.bTone || \"Pro/Approach\"}, Goal: ${\n p.goals || \"Engage/Promo\"\n }. TASK: Type: ${p.cType}, Platform: ${p.plat}, Instr: ${\n p.specInstr || \"None\"\n }. INSTR: 1. Gen '${p.cType}' for '${p.plat}'. 2. Use Tone ('${p.bTone || \"Pro/Approach\"}') for TA ('${\n p.tAud || \"General\"\n }'). 3. Integrate Instr: \"${p.specInstr || \"None\"}\". 4. Align w/ Goal ('${\n p.goals || \"Engage/Promo\"\n }'), use CTAs. 5. Platform: Socials(hashtags,length), Ads(headlines,desc,CTA), BlogIdea(3-5 titles), BlogDraft(300-500w section,markdown), Generic(adaptable). 6. Output: ONLY content. Blog Ideas: bullet points.`;\n const userP =\n `Generate the ${p.cType} for the specified platform based on the context provided in the system prompt.`;\n try {\n const genContent = await callOpenAI(sysP, userP, mid, tid, logFn);\n if (!genContent) {\n logFn(\"WARN\", \"CntAgent\", `LLM returned no content tid=${tid}.`, undefined, mid, tid);\n return { mid, cid: tid, p: { content: \"\" }, e: \"AI failed to generate content.\" };\n }\n const output: CntOut = { content: genContent };\n if (p.cType === \"promo_post\" || p.cType === \"ad_copy\") {\n output.suggestions = \"Consider pairing with a relevant image or video. Test different calls-to-action (CTAs).\";\n } else if (p.cType === \"blog_idea\") {\n output.suggestions = \"Research keywords for the chosen idea. Create a detailed outline before writing.\";\n } else if (p.cType === \"blog_draft\") {\n output.suggestions =\n \"Expand on this draft, ensuring keyword integration. Add internal/external links where appropriate.\";\n }\n logFn(\n \"INFO\",\n \"CntAgent\",\n `Content gen task OK tid=${tid}.`,\n { outLen: output.content.length, sug: !!output.suggestions },\n mid,\n tid,\n );\n return { mid, cid: tid, p: output };\n } catch (err: any) {\n logFn(\"ERROR\", \"CntAgent\", `Content gen task fail tid=${tid}.`, { err: err.message }, mid, tid);\n return { mid, cid: tid, p: { content: \"\" }, e: `Content generation failed: ${err.message}` };\n }\n}\nasync function runStratAgent(task: TskIn, logFn: LogFn): Promise> {\n const { mid, tid, p } = task;\n const platsStr = Array.isArray(p.plats) ? p.plats.join(\", \") : \"N/A\";\n logFn(\n \"INFO\",\n \"StratAgent\",\n `Starting strategy dev tid=${tid}`,\n { plats: platsStr, budget: p.budgetLvl, dur: p.duration },\n mid,\n tid,\n );\n const sysP = `Pragmatic Digital Mktg Strategist for SMBs. Task: outline concise strategy. CONTEXT: BT: ${\n p.bType || \"N/A\"\n }, SVC: ${p.sDesc || \"N/A\"}, TA: ${p.tAud || \"General\"}, Goals: ${\n p.goals || \"Incr presence/leads\"\n }, Platforms: ${platsStr}, Budget: ${p.budgetLvl || \"Low\"}, Duration: ${p.duration || \"Ongoing\"}, Tone: ${\n p.bTone || \"Pro/Trust\"\n }. FRAMEWORK (Use MD headings): ## Executive Summary - Core strategy/outcomes. ## Target Audience Insights - Online behavior, needs, reach. ## Recommended Platforms & Rationale - Eval requested ('${platsStr}'). Recommend best based on audience/goals/budget. Justify. Suggest alt if needed. ## Core Content Themes & Messaging - 2-4 themes for audience/value. Key messages. ## Platform-Specific Tactics (recommended) - 2-3 tactics per platform (e.g., LinkedIn: insights, groups; SEO: long-tail kw, citations). Prioritize by Budget (Low: organic; Med: ads; High: campaigns). ## Sample Ad Copy / Post Ideas - 2-3 examples. ## Budget Considerations (If applicable) - Med/High: spend priority. Low: acknowledge limits. ## Measurement & KPIs - 3-5 KPIs (e.g., Traffic, CVR, Engagement, CPL). ## Next Steps - Immediate actions (e.g., Profiles, KW research, Calendar). INSTR: 1. Practical, specific. 2. Prioritize by Budget. 3. Cohesive. 4. Output ONLY strategy doc (MD). No intro/outro text.`;\n const userP = `Develop the marketing strategy based on the system prompt context & framework.`;\n try {\n const stratContent = await callOpenAI(sysP, userP, mid, tid, logFn);\n if (!stratContent) {\n logFn(\"WARN\", \"StratAgent\", `LLM no content for strat tid=${tid}.`, undefined, mid, tid);\n return { mid, cid: tid, p: { strategy: \"\" }, e: \"AI failed strategy.\" };\n }\n let adIdeas: string[] = [];\n const adMatch = stratContent.match(/## Sample Ad Copy \\/ Post Ideas\\n+([\\s\\S]*?)(?=\\n##|$)/i);\n if (adMatch?.[1]) {\n adIdeas = adMatch[1].split(/[\\n\\r]+-|\\\\*|\\\\d+\\\\.\\\\s*/).map(s => s.trim()).filter(s => s && s.length > 10);\n }\n let audSugs: string[] = [];\n const audMatch = stratContent.match(/## Target Audience Insights\\n+([\\s\\S]*?)(?=\\n##|$)/i);\n if (audMatch?.[1]) {\n audSugs = audMatch[1].split(/[\\n\\r]+-|\\\\*|\\\\d+\\\\.\\\\s*/).map(s => s.trim()).filter(s => s && s.length > 10);\n }\n const output: StratOut = { strategy: stratContent, adIdeas, audSugs };\n logFn(\n \"INFO\",\n \"StratAgent\",\n `Strategy dev OK tid=${tid}.`,\n { stratLen: output.strategy.length, adIdeasCnt: adIdeas.length, audSugsCnt: audSugs.length },\n mid,\n tid,\n );\n return { mid, cid: tid, p: output };\n } catch (err: any) {\n logFn(\"ERROR\", \"StratAgent\", `Strategy dev fail tid=${tid}.`, { err: err.message }, mid, tid);\n return { mid, cid: tid, p: { strategy: \"\" }, e: `Strategy generation failed: ${err.message}` };\n }\n}\nasync function runLogoAgent(task: TskIn, logFn: LogFn): Promise> {\n const { mid, tid, p } = task;\n logFn(\n \"INFO\",\n \"LogoAgent\",\n `Starting logo concept gen tid=${tid}`,\n { bName: p.bName, style: p.stylePrefs, color: p.colorPrefs },\n mid,\n tid,\n );\n const sysP = `Creative Asst gen 2-3 logo concepts. Each: desc + AI img prompt. CONTEXT: BN: ${p.bName}, BT: ${\n p.bType || \"N/A\"\n }, Svc: ${p.sDesc || \"N/A\"}, TA: ${p.tAud || \"General\"}, Styles: ${p.stylePrefs || \"Versatile\"}, Colors: ${\n p.colorPrefs || \"Suggest\"\n }, Tone: ${\n p.bTone || \"Professional\"\n }. INSTR: 1. Gen 2-3 diff concepts (icon, wordmark, abstract/combo). 2. Format each (MD): ### Concept Title \\\\n#### Description: \\\\n- Visuals, symbolism, fonts (sans/serif), colors. \\\\n#### AI Image Generation Prompt: \\\\n- Detailed prompt for AI (DALL-E, etc). Incl: type(vector logo), subj(BN/initials), style(minimalist, flat), elements, colors, bg(white). Ex: \"/imagine prompt: vector logo for '${p.bName}', minimalist flat design [Symbol], clean sans-serif, blue (#005C99), gray (#CCCCCC), isolated white bg --style raw --ar 1:1\" 3. Separate concepts w/ '---'. 4. (Opt) If simple, attempt basic SVG: \\\\\\`\\\\\\`\\\\\\`svg ... \\\\\\`\\\\\\`\\\\\\`. 5. Output ONLY concepts. No intro/outro.`;\n const userP =\n `Generate 2-3 distinct logo concepts for \"${p.bName}\" based on the system prompt. Provide descriptions and AI prompts.`;\n try {\n const conceptContent = await callOpenAI(sysP, userP, mid, tid, logFn);\n if (!conceptContent) {\n logFn(\"WARN\", \"LogoAgent\", `LLM no content for logo tid=${tid}.`, undefined, mid, tid);\n return { mid, cid: tid, p: { concepts: [], prompts: [] }, e: \"AI failed logo concepts.\" };\n }\n const concepts: string[] = [];\n const prompts: string[] = [];\n const sections = conceptContent.split(/\\n---\\n/);\n sections.forEach(sec => {\n const titleM = sec.match(/### (.*?)\\n/);\n const descM = sec.match(/#### Description:\\n([\\s\\S]*?)(?=\\n#### AI Image Generation Prompt:|$)/i);\n const promptM = sec.match(/#### AI Image Generation Prompt:\\n([\\s\\S]*?)(?=\\n\\`\\`\\`svg|$)/i);\n if (titleM && descM && promptM) {\n concepts.push(`Title: ${titleM[1].trim()}\\n\\nDescription:\\n${descM[1].trim()}`);\n prompts.push(promptM[1].trim());\n } else {\n logFn(\n \"WARN\",\n \"LogoAgent\",\n `Could not parse logo concept section.`,\n { sectionStart: sec.substring(0, 100) },\n mid,\n tid,\n );\n if (sec.trim().length > 0) concepts.push(`Raw Section:\\n${sec.trim()}`);\n }\n });\n const svgM = conceptContent.match(/```svg\\n([\\s\\S]*?)\\n```/);\n const svgAttempt = svgM ? svgM[1].trim() : undefined;\n if (concepts.length === 0 && conceptContent.length > 0) {\n logFn(\n \"WARN\",\n \"LogoAgent\",\n `No structured concepts parsed, return raw tid=${tid}`,\n { rawLen: conceptContent.length },\n mid,\n tid,\n );\n concepts.push(`Raw Output (Parse Fail):\\n${conceptContent}`);\n }\n const output: LogoOut = { concepts, prompts, svg: svgAttempt };\n logFn(\n \"INFO\",\n \"LogoAgent\",\n `Logo concept task OK tid=${tid}.`,\n { concepts: output.concepts.length, prompts: output.prompts?.length, svg: !!output.svg },\n mid,\n tid,\n );\n return { mid, cid: tid, p: output };\n } catch (err: any) {\n logFn(\"ERROR\", \"LogoAgent\", `Logo concept task fail tid=${tid}.`, { err: err.message }, mid, tid);\n return { mid, cid: tid, p: { concepts: [], prompts: [] }, e: `Logo concept generation failed: ${err.message}` };\n }\n}\nasync function runBrandAgent(task: TskIn, logFn: LogFn): Promise> {\n const { mid, tid, p } = task;\n logFn(\n \"INFO\",\n \"BrandAgent\",\n `Starting brand ID def tid=${tid}`,\n { bName: p.bName, vals: p.coreVals, tone: p.bTone },\n mid,\n tid,\n );\n const sysP =\n `Brand Strategist Asst defining foundational brand ID. Create concise guide. CONTEXT: BN: ${p.bName}, BT: ${\n p.bType || \"N/A\"\n }, Svc: ${p.sDesc || \"N/A\"}, TA: ${p.tAud || \"General\"}, Values: ${p.coreVals || \"N/A\"}, Tone: ${\n p.bTone || \"Pro/Trust\"\n }. FRAMEWORK (MD headings): ## Brand Voice & Personality - Describe voice detail. Elaborate tone ('${\n p.bTone || \"Pro/Trust\"\n }'). Define personality (Expert, Friendly, Reliable). Lang style (Formal/Casual, Jargon/Plain). ## Key Messages - List 3-5 core msgs/taglines (* bullets). Communicate value, connect service->audience, reflect values. Concise, memorable. ## Color Palette Suggestions - Recommend primary, 1-2 secondary, 1 accent color. Hex codes (#RRGGBB). Justify (personality, industry, audience). Ex: \"Primary: Blue (#0A2F5B) trust. Secondary: Gray (#E1E1E1) contrast. Accent: Teal (#1ABC9C) energy.\" ## Typography Suggestions - Recommend 1 heading, 1 body font (Google Fonts). Justify (readability, personality, contrast). Ex: \"Head: Montserrat Bold (Modern). Body: Lato Regular (Clean). Prof feel.\" INSTR: 1. Cohesive suggestions (Voice, Msgs, Colors, Fonts). 2. Practical for SMB. 3. Align w/ Context (BT, TA, Tone). 4. Output ONLY guide (MD). No intro/outro.`;\n const userP =\n `Develop foundational brand ID guide for \"${p.bName}\" based on system prompt context/instructions. Ensure cohesive & practical.`;\n try {\n const idContent = await callOpenAI(sysP, userP, mid, tid, logFn);\n if (!idContent) {\n logFn(\"WARN\", \"BrandAgent\", `LLM no content for brand ID tid=${tid}.`, undefined, mid, tid);\n return { mid, cid: tid, p: { bVoice: \"\", kMsgs: [], cPalSugs: \"\", typo: \"\" }, e: \"AI failed brand ID guide.\" };\n }\n const voiceM = idContent.match(/## Brand Voice & Personality\\n([\\s\\S]*?)(?=\\n##|$)/i);\n const msgsM = idContent.match(/## Key Messages\\n([\\s\\S]*?)(?=\\n##|$)/i);\n const colorM = idContent.match(/## Color Palette Suggestions\\n([\\s\\S]*?)(?=\\n##|$)/i);\n const typoM = idContent.match(/## Typography Suggestions\\n([\\s\\S]*?)(?=\\n##|$)/i);\n const bVoice = voiceM ? voiceM[1].trim() : \"Parse fail Voice.\";\n const kMsgsRaw = msgsM ? msgsM[1].trim() : \"\";\n let kMsgs = kMsgsRaw.split(/[\\n\\r]+\\s*[\\*\\-]\\s*/).map(s => s.trim()).filter(s => s.length > 5);\n if (kMsgs.length === 0 && kMsgsRaw.length > 5) { kMsgs.push(`Raw Msgs: ${kMsgsRaw}`); }\n const cPalSugs = colorM ? colorM[1].trim() : \"Parse fail Colors.\";\n const typo = typoM ? typoM[1].trim() : \"Parse fail Typography.\";\n if (bVoice.startsWith(\"Parse fail\") && kMsgs.length === 0) {\n logFn(\n \"WARN\",\n \"BrandAgent\",\n `Sig parse fail brand ID tid=${tid}`,\n { rawP: idContent.substring(0, 200) },\n mid,\n tid,\n );\n }\n const output: BrandOut = { bVoice, kMsgs, cPalSugs, typo };\n logFn(\n \"INFO\",\n \"BrandAgent\",\n `Brand ID task OK tid=${tid}.`,\n { voiceLen: output.bVoice.length, msgsCnt: output.kMsgs.length },\n mid,\n tid,\n );\n return { mid, cid: tid, p: output };\n } catch (err: any) {\n logFn(\"ERROR\", \"BrandAgent\", `Brand ID task fail tid=${tid}.`, { err: err.message }, mid, tid);\n return {\n mid,\n cid: tid,\n p: { bVoice: \"\", kMsgs: [], cPalSugs: \"\", typo: \"\" },\n e: `Brand ID generation failed: ${err.message}`,\n };\n }\n}\nasync function runSimAgent(task: TskIn, logFn: LogFn): Promise> {\n const { mid, tid, p } = task;\n let paramDesc = \"N/A\";\n try {\n paramDesc = typeof p.specParams === \"string\" ? p.specParams : JSON.stringify(p.specParams);\n } catch (e) {\n paramDesc = \"[Serialization fail]\";\n logFn(\"WARN\", \"SimAgent\", `Failed serialize specParams tid=${tid}`, { err: (e as Error).message }, mid, tid);\n }\n logFn(\n \"INFO\",\n \"SimAgent\",\n `Starting sim task tid=${tid}`,\n { simType: p.simType, paramsP: paramDesc.substring(0, 100) },\n mid,\n tid,\n );\n const sysP = `Adv Sim Model predicts outcomes/role-plays. CONTEXT: BT: ${p.bType || \"N/A\"}, Svc: ${\n p.sDesc || \"N/A\"\n }, TA: ${p.tAud || \"General\"}, Tone: ${\n p.bTone || \"Pro/Helpful\"\n }. SIM TASK: Type: ${p.simType}, Params/Scenario: ${paramDesc}. INSTR: 1. Analyze Type & Params. 2. Execute: 'ad_response_estimate': Qual assess ad effectiveness (platform, audience, copy). Estimate metric ranges (CTR, CVR) if feasible. State assumptions (avg market). Avoid guarantees. Focus likelihoods. 'customer_interaction': Role-play realistic interaction (Customer:, Agent:). Reflect context, tone, issue. Concise (3-5 exchanges). 'other': Execute per desc. Interpret reasonably. State assumptions. 3. Output: Core sim result first. THEN optional \\\\\\`## Analysis\\\\\\` (MD heading). Brief takeaways/insights from sim only (2-4 sentences). 4. Output ONLY result & opt analysis. No intro/outro.`;\n const userP = `Run simulation type '${p.simType}' based on system prompt context/params. Follow format.`;\n try {\n const simContent = await callOpenAI(sysP, userP, mid, tid, logFn);\n if (!simContent) {\n logFn(\"WARN\", \"SimAgent\", `LLM no content for sim tid=${tid}.`, undefined, mid, tid);\n return { mid, cid: tid, p: { simResult: \"\" }, e: \"AI failed sim.\" };\n }\n let simResult = simContent;\n let analysis: string | undefined = undefined;\n const analysisM = simContent.match(/\\n## Analysis\\s*$/mi);\n if (analysisM?.index !== undefined) {\n const splitIndex = analysisM.index;\n simResult = simContent.substring(0, splitIndex).trim();\n analysis = simContent.substring(splitIndex).replace(/^## Analysis\\s*[\\r\\n]+/mi, \"\").trim();\n logFn(\"DEBUG\", \"SimAgent\", `Analysis section found tid=${tid}`, { analysisLen: analysis.length }, mid, tid);\n } else {\n simResult = simContent.trim();\n logFn(\"DEBUG\", \"SimAgent\", `No analysis section found tid=${tid}`, undefined, mid, tid);\n }\n if (!simResult && analysis) {\n logFn(\"WARN\", \"SimAgent\", `Sim result empty, analysis found tid=${tid}.`, undefined, mid, tid);\n simResult = \"(Simulation produced analysis but no primary result)\";\n } else if (!simResult && !analysis) {\n logFn(\"WARN\", \"SimAgent\", `Sim result & analysis empty tid=${tid}.`, undefined, mid, tid);\n simResult = \"(Simulation produced no output)\";\n }\n const output: SimOut = { simResult, analysis };\n logFn(\n \"INFO\",\n \"SimAgent\",\n `Sim task OK tid=${tid}.`,\n { resLen: output.simResult.length, hasAnalysis: !!output.analysis },\n mid,\n tid,\n );\n return { mid, cid: tid, p: output };\n } catch (err: any) {\n logFn(\"ERROR\", \"SimAgent\", `Sim task fail tid=${tid}.`, { err: err.message }, mid, tid);\n return { mid, cid: tid, p: { simResult: \"\" }, e: `Simulation run failed: ${err.message}` };\n }\n}\nasync function runMetaAgent(task: TskIn, logFn: LogFn): Promise> {\n const { mid, tid, p } = task;\n logFn(\"INFO\", \"MetaAgent\", `Starting meta-prompt gen/refine tid=${tid}`, { inputLen: p.pInput.length }, mid, tid);\n const sysP =\n `Expert AI Prompt Engineer. Mission: create/refine high-quality SYSTEM prompt for another AI (GPT-4) based on user's request. Prompt should be clear, comprehensive, unambiguous, elicit best response. PRINCIPLES: 1. Role & Expertise: Define AI persona (e.g., \"Expert financial analyst...\"). 2. Task/Goal: State main objective (e.g., \"...analyze data, gen memo.\"). 3. Context/Input Spec: List needed inputs ([Business Plan], [User Question]). 4. Process/Steps (if complex): Outline steps (1. Analyze. 2. Risks. 3. Recs. 4. Output.). 5. Output Format/Constraints: Specify format(MD, JSON), len, tone, style, language, avoid (\"JSON format.\", \"No filler.\", \"< 500 words.\"). Output structure examples if helpful. 6. Ambiguity/Missing Info: Instruct handling (\"Ask clarifying Qs.\", \"State missing data.\"). 7. Refinement (If Applicable): Analyze existing prompt strengths/weaknesses. Address weaknesses (clarity, format, role). USER'S REQUEST (for sys prompt gen/refine): \\\\\\`\\\\\\`\\\\\\`\\n${p.pInput}\\n\\\\\\`\\\\\\`\\\\\\` YOUR TASK: Generate complete system prompt text based ONLY on user req & principles. Output ONLY system prompt itself. No code blocks unless user requested. No explanations/intros (\"Here is prompt:\").`;\n const userP =\n `Based on my request in system context, generate/refine the system prompt per guidelines. Output only resulting prompt text.`;\n try {\n const genSysP = await callOpenAI(sysP, userP, mid, tid, logFn);\n if (!genSysP) {\n logFn(\"WARN\", \"MetaAgent\", `LLM no content for meta-prompt tid=${tid}.`, undefined, mid, tid);\n return { mid, cid: tid, p: { sysPrompt: \"\" }, e: \"AI failed to generate system prompt.\" };\n }\n const finalP = genSysP.replace(/^```(markdown|text)?\\s*/i, \"\").replace(/\\s*```$/, \"\").trim();\n const output: MetaOut = { sysPrompt: finalP };\n logFn(\"INFO\", \"MetaAgent\", `Meta-prompt task OK tid=${tid}.`, { outputLen: output.sysPrompt.length }, mid, tid);\n return { mid, cid: tid, p: output };\n } catch (err: any) {\n logFn(\"ERROR\", \"MetaAgent\", `Meta-prompt task fail tid=${tid}.`, { err: err.message }, mid, tid);\n return { mid, cid: tid, p: { sysPrompt: \"\" }, e: `Meta-prompt generation failed: ${err.message}` };\n }\n}\n\n// --- Orchestrator Class ---\nclass Orchestrator {\n baseLog: LogFn;\n mandateId: string;\n lg: LogFn;\n constructor(baseLogger: LogAgent) {\n this.mandateId = `m-${Date.now()}-${Math.random().toString(36).substring(2, 8)}`;\n baseLogger.setMidCtx(this.mandateId);\n this.baseLog = baseLogger.log.bind(baseLogger);\n this.lg = (lvl, comp, msg, dt?, _midIgnored?, tid?) => {\n this.baseLog(lvl, comp, msg, dt, this.mandateId, tid);\n };\n this.lg(\"INFO\", \"Orchestrator\", `Initialized mandate: ${this.mandateId}`);\n }\n async runWorkflow(input: UserIn): Promise {\n this.lg(\"INFO\", \"Orchestrator\", `Workflow started task: ${input.task}`, { inputKeys: Object.keys(input.data) });\n const tid = `${input.task}-${Date.now()}-${Math.random().toString(36).substring(2, 7)}`;\n const taskInput: TskIn = { mid: this.mandateId, tid: tid, p: input.data };\n let taskOutput: TskOut;\n try {\n const agentLog: LogFn = (lvl, comp, msg, dt?, _midOverride?, tidFromAgent?) => {\n this.lg(lvl, comp, msg, dt, this.mandateId, tidFromAgent || tid);\n };\n switch (input.task) {\n case \"create_content\":\n taskOutput = await runCntAgent(taskInput as TskIn, agentLog);\n break;\n case \"develop_strategy\":\n taskOutput = await runStratAgent(taskInput as TskIn, agentLog);\n break;\n case \"generate_logo_concept\":\n taskOutput = await runLogoAgent(taskInput as TskIn, agentLog);\n break;\n case \"build_brand_identity\":\n taskOutput = await runBrandAgent(taskInput as TskIn, agentLog);\n break;\n case \"run_simulation\":\n taskOutput = await runSimAgent(taskInput as TskIn, agentLog);\n break;\n case \"meta_prompt\":\n taskOutput = await runMetaAgent(taskInput as TskIn, agentLog);\n break;\n default:\n const _exCheck: never = input.task;\n this.lg(\"ERROR\", \"Orchestrator\", `Unsupported task type: ${_exCheck}`, { taskInput }, this.mandateId, tid);\n throw new Error(`Unsupported task: ${_exCheck}`);\n }\n if (taskOutput.e) {\n this.lg(\"WARN\", \"Orchestrator\", `Agent task ${tid} completed with error.`, {\n err: taskOutput.e,\n agentPayload: taskOutput.p,\n });\n return {\n mid: this.mandateId,\n err: `Agent execution failed: ${taskOutput.e}`,\n res: taskOutput.p,\n dbgLog: [],\n details: \"Agent reported error.\",\n };\n }\n this.lg(\"INFO\", \"Orchestrator\", `Workflow task ${tid} (${input.task}) completed successfully.`);\n return { mid: this.mandateId, res: taskOutput.p, err: undefined, dbgLog: [] };\n } catch (err: any) {\n this.lg(\"ERROR\", \"Orchestrator\", `Critical workflow failure task ${tid} (${input.task}).`, {\n err: err.message,\n stack: err.stack?.substring(0, 500),\n });\n return {\n mid: this.mandateId,\n err: `Workflow execution failed critically: ${err.message}`,\n details: \"Unexpected error in orchestration/agent.\",\n dbgLog: [],\n };\n }\n }\n}\n\n// --- HTML Generation ---\n\nfunction generateOrthogonalUI(): string {\n return`AI Business Assistant - Orthogonal

`;\n}\n// --- Main Request Handler ---\nexport default async function(req: Request): Promise {\n const reqId = `req-${Date.now()}-${Math.random().toString(36).substring(2, 7)}`;\n const reqLogger = new LogAgent(reqId);\n const log = reqLogger.log.bind(reqLogger);\n const url = new URL(req.url);\n const commonHeaders = {\n \"Content-Type\": \"application/json\",\n \"Access-Control-Allow-Origin\": \"*\",\n \"Access-Control-Allow-Methods\": \"GET, POST, OPTIONS\",\n \"Access-Control-Allow-Headers\": \"Content-Type, Authorization\",\n };\n\n if (req.method === \"OPTIONS\") {\n log(\"INFO\", \"Handler\", \"Handling OPTIONS request\");\n return new Response(null, { status: 204, headers: commonHeaders });\n }\n\n try {\n if (req.method === \"GET\" && (url.pathname === \"/\" || url.pathname === \"\")) {\n log(\"INFO\", \"Handler\", \"GET / : Serving Orthogonal UI\");\n const html = generateOrthogonalUI();\n return new Response(html, {\n status: 200,\n headers: { ...commonHeaders, \"Content-Type\": \"text/html; charset=utf-8\" },\n });\n } else if (req.method === \"POST\" && url.pathname === \"/questionnaire\") {\n log(\"INFO\", \"Handler\", \"POST /questionnaire : Handling step.\");\n let reqBody;\n let rawReqBody = \"[Could not read body]\";\n try {\n rawReqBody = await req.text();\n reqBody = JSON.parse(rawReqBody);\n if (\n !reqBody || typeof reqBody !== \"object\" || !reqBody.task || typeof reqBody.task !== \"string\"\n ) { throw new Error(\"Invalid request structure: 'task' (string) is required.\"); }\n if (!reqBody.action || ![\"start\", \"answer\", \"back\", \"restart\"].includes(reqBody.action)) {\n throw new Error(\"Invalid request: 'action' ('start', 'answer', 'back', 'restart') required.\");\n }\n if (\n reqBody.action === \"answer\" && (!reqBody.lastAnswer || typeof reqBody.lastAnswer !== \"object\")\n ) { throw new Error(\"Invalid request: 'lastAnswer' object required for 'answer' action.\"); }\n } catch (e: any) {\n log(\"WARN\", \"Handler\", \"Failed parse/validate JSON body for /questionnaire\", {\n err: e.message,\n bodyAttempt: rawReqBody.substring(0, 500),\n });\n const errLogs = reqLogger.getLogs();\n return new Response(JSON.stringify({ err: `Bad Request: ${e.message}`, state: null, dbgLog: errLogs }), {\n status: 400,\n headers: commonHeaders,\n });\n }\n const qAgent = new QAgent(log);\n const { sessionId, task, action, lastAnswer, state: clientState } = reqBody;\n let qResult: QResp;\n try {\n log(\"DEBUG\", \"Handler\", `Processing action: ${action}`, {\n task,\n sessionId,\n hasState: !!clientState,\n hasAnswer: !!lastAnswer,\n });\n if (action === \"back\") {\n if (!clientState || !clientState.qHist || clientState.qHist.length < 1) {\n log(\"WARN\", \"Handler\", \"Back action requested but no history in state.\", { state: clientState });\n qResult = await qAgent.nextStep(sessionId, task, null, null);\n qResult.err = \"Cannot go back further. Restarting task questions.\";\n } else {\n const prevState = { ...clientState };\n const lastQAsked = prevState.qHist.pop();\n if (lastQAsked && prevState.answers) {\n delete prevState.answers[lastQAsked.field];\n log(\n \"DEBUG\",\n \"Handler\",\n `Back action: Removed answer for '${lastQAsked.field}' and question from history.`,\n { qid: lastQAsked.qid },\n );\n }\n qResult = await qAgent.nextStep(sessionId, task, null, prevState);\n }\n } else if (action === \"restart\") {\n log(\"INFO\", \"Handler\", `Restart action: Clearing state for task '${task}'`, { sessionId });\n qResult = await qAgent.nextStep(sessionId, task, null, null);\n } else if (action === \"start\") {\n log(\"INFO\", \"Handler\", `Start action: Initializing state for task '${task}'`, { sessionId });\n qResult = await qAgent.nextStep(sessionId, task, null, null);\n } else if (action === \"answer\") {\n qResult = await qAgent.nextStep(sessionId, task, lastAnswer, clientState);\n } else {\n log(\"ERROR\", \"Handler\", `Invalid action received: ${action}`, { reqBody });\n qResult = {\n sid: sessionId || `err-${Date.now()}`,\n isDone: false,\n err: \"Invalid action specified.\",\n state: clientState || null,\n };\n }\n const responseState = qResult.state ? { ...qResult.state } : null;\n log(\"DEBUG\", \"Handler\", \"Questionnaire step processed.\", {\n sid: qResult.sid,\n isDone: qResult.isDone,\n hasErr: !!qResult.err,\n nextQField: qResult.nextQ?.field,\n });\n const responsePayload = { ...qResult, state: responseState };\n return new Response(JSON.stringify(responsePayload), {\n status: qResult.err\n ? (qResult.err.startsWith(\"Validation Error:\") || qResult.err.startsWith(\"Please check your input\")\n || qResult.err.startsWith(\"Cannot go back\")\n ? 400\n : 500)\n : 200,\n headers: commonHeaders,\n });\n } catch (qAgentError: any) {\n log(\"ERROR\", \"Handler\", `Error during QAgent processing for action ${action}.`, {\n err: qAgentError.message,\n stack: qAgentError.stack?.substring(0, 300),\n });\n const errLogs = reqLogger.getLogs();\n return new Response(\n JSON.stringify({\n err: `Internal error processing questionnaire: ${qAgentError.message}`,\n state: null,\n dbgLog: errLogs,\n }),\n { status: 500, headers: commonHeaders },\n );\n }\n } else if (req.method === \"POST\" && url.pathname === \"/execute\") {\n log(\"INFO\", \"Handler\", \"POST /execute : Handling workflow execution.\");\n let validatedInput: UserIn;\n let rawPayload = \"[Could not read body]\";\n try {\n const payload = await req.json();\n rawPayload = JSON.stringify(payload).substring(0, 500);\n log(\"DEBUG\", \"Handler\", \"Received payload /execute\", { payloadPreview: rawPayload });\n validatedInput = UserInSchema.parse(payload);\n log(\"INFO\", \"Handler\", \"Payload validation OK /execute.\", { task: validatedInput.task });\n } catch (error: any) {\n let errDetails = \"Invalid input format/fields.\";\n let validationIssues;\n if (error instanceof z.ZodError) {\n validationIssues = error.issues;\n errDetails = validationIssues.map(i => `Field '${i.path.join(\".\")}': ${i.message}`).join(\"; \");\n log(\"WARN\", \"Handler\", \"Zod validation failed /execute.\", {\n err: errDetails,\n issues: validationIssues,\n receivedPreview: rawPayload,\n });\n } else {\n errDetails = error.message;\n log(\"WARN\", \"Handler\", \"Error parsing/validating /execute.\", {\n err: errDetails,\n receivedPreview: rawPayload,\n });\n }\n const errLogs = reqLogger.getLogs();\n return new Response(\n JSON.stringify({\n err: \"Invalid input data for execution.\",\n details: errDetails,\n dbgLog: errLogs,\n mid: `m-validate-err-${reqId}`,\n }),\n { status: 400, headers: commonHeaders },\n );\n }\n const execLogger = new LogAgent();\n const orchestrator = new Orchestrator(execLogger);\n const finalResult: FinalRes = await orchestrator.runWorkflow(validatedInput);\n finalResult.dbgLog = execLogger.getLogs();\n const respStatus = finalResult.err ? 500 : 200;\n log(\"INFO\", \"Handler\", `/execute workflow finished status ${respStatus}`, {\n mid: finalResult.mid,\n hasErr: !!finalResult.err,\n });\n return new Response(JSON.stringify(finalResult), { status: respStatus, headers: commonHeaders });\n } else {\n log(\"WARN\", \"Handler\", `Unsupported request: ${req.method} ${url.pathname}`);\n const errLogs = reqLogger.getLogs();\n return new Response(JSON.stringify({ err: \"Not Found or Method Not Allowed\", dbgLog: errLogs }), {\n status: 404,\n headers: commonHeaders,\n });\n }\n } catch (err: any) {\n log(\"ERROR\", \"Handler\", \"Unhandled exception during request.\", {\n err: err.message,\n stack: err.stack?.substring(0, 500),\n });\n const crashLogs = reqLogger.getLogs();\n return new Response(\n JSON.stringify({\n err: \"Internal Server Error\",\n details: \"Unexpected server error.\",\n dbgLog: crashLogs,\n mid: `m-crash-${reqId}`,\n state: null,\n }),\n { status: 500, headers: commonHeaders },\n );\n }\n}",[152],{"_153":154,"_102":175,"_107":235,"_156":136,"_180":236},["D",1747333279344],[237,241],{"_105":238,"_156":136,"_153":154,"_98":152,"_164":239,"_162":163,"_102":29,"_155":-5,"_107":235,"_157":175,"_167":-5,"_158":25,"_166":25,"_101":240},"65ba8460-31b9-11f0-9937-569c3dd06744","import { fetch } from \"https://esm.town/v/std/fetch\";\nimport { OpenAI } from \"https://esm.town/v/std/openai\";\nimport { z } from \"npm:zod\";\n\n// --- Types (Abbreviated & Core) ---\ntype TskIn = { mid: string; tid: string; p: T };\ntype TskOut = { mid: string; cid: string; p: T; e?: string };\ntype Lvl = \"DEBUG\" | \"INFO\" | \"WARN\" | \"ERROR\";\ntype LogFn = (lvl: Lvl, comp: string, msg: string, dt?: any, mid?: string, tid?: string) => void;\ntype LogEntry = { ts: string; mid: string; tid?: string; lvl: Lvl; comp: string; msg: string; dt?: any };\ntype BaseIn = { bType: string; sDesc: string; tAud: string; bTone?: string; goals?: string };\ntype CntIn = BaseIn & {\n cType: \"promo_post\" | \"blog_idea\" | \"blog_draft\" | \"ad_copy\";\n plat: \"facebook\" | \"instagram\" | \"tiktok\" | \"linkedin\" | \"google_ads\" | \"blog\" | \"generic\";\n specInstr?: string;\n};\ntype StratIn = BaseIn & { plats: string[]; budgetLvl?: \"low\" | \"medium\" | \"high\"; duration?: string };\ntype LogoIn = BaseIn & { bName: string; stylePrefs?: string; colorPrefs?: string };\ntype BrandIn = BaseIn & { bName: string; coreVals?: string };\ntype SimIn = BaseIn & {\n simType: \"ad_response_estimate\" | \"customer_interaction\" | \"other\";\n specParams: Record | { description: string };\n};\ntype MetaIn = { pInput: string };\nconst UserInSchema = z.object({\n task: z.enum([\n \"create_content\",\n \"develop_strategy\",\n \"generate_logo_concept\",\n \"build_brand_identity\",\n \"run_simulation\",\n \"meta_prompt\",\n ]),\n data: z.record(z.any()),\n}).refine((input) => {\n const d = input.data;\n const dataKeys = Object.keys(d);\n const hasKey = (key: string) => dataKeys.includes(key) && d[key] != null && d[key] !== \"\";\n switch (input.task) {\n case \"create_content\":\n return hasKey(\"businessType\") && hasKey(\"serviceDescription\") && hasKey(\"targetAudience\") && hasKey(\"contentType\")\n && hasKey(\"platform\");\n case \"develop_strategy\":\n return hasKey(\"businessType\") && hasKey(\"serviceDescription\") && hasKey(\"targetAudience\")\n && Array.isArray(d.platforms) && d.platforms.length > 0;\n case \"generate_logo_concept\":\n return hasKey(\"businessType\") && hasKey(\"serviceDescription\") && hasKey(\"targetAudience\")\n && hasKey(\"businessName\");\n case \"build_brand_identity\":\n return hasKey(\"businessType\") && hasKey(\"serviceDescription\") && hasKey(\"targetAudience\")\n && hasKey(\"businessName\");\n case \"run_simulation\":\n return hasKey(\"businessType\") && hasKey(\"serviceDescription\") && hasKey(\"targetAudience\")\n && hasKey(\"simulationType\") && hasKey(\"specificParams\")\n && (typeof d.specificParams === \"object\" || typeof d.specificParams === \"string\");\n case \"meta_prompt\":\n return hasKey(\"prompt_input\");\n default:\n return false;\n }\n}, { message: \"Missing required fields for the selected task or invalid data format.\" });\ntype UserIn = z.infer;\ntype CntOut = { content: string; suggestions?: string };\ntype StratOut = { strategy: string; adIdeas?: string[]; audSugs?: string[] };\ntype LogoOut = { concepts: string[]; prompts?: string[]; svg?: string };\ntype BrandOut = { bVoice: string; kMsgs: string[]; cPalSugs: string; typo: string };\ntype SimOut = { simResult: string; analysis?: string };\ntype MetaOut = { sysPrompt: string };\ntype FinalRes = { res?: any; err?: string; details?: string; dbgLog: LogEntry[]; mid: string };\ntype QState = {\n sid: string;\n task: UserIn[\"task\"];\n reqFlds: string[];\n answers: Partial>;\n qHist: { qid: string; field: string; text: string }[];\n isDone: boolean;\n};\ntype Quest = {\n id: string;\n field: string;\n text: string;\n type: \"text\" | \"textarea\" | \"select\" | \"confirm\";\n opts?: { lbl: string; val: string }[];\n};\ntype QResp = { sid: string; nextQ?: Quest; isDone: boolean; data?: UserIn; err?: string; state: QState | null };\n\n// --- LogAgent Class ---\nclass LogAgent {\n logs: LogEntry[];\n midCtx?: string;\n constructor(mid?: string) {\n this.logs = [];\n this.midCtx = mid;\n }\n log(lvl: Lvl, comp: string, msg: string, dt?: any, mid?: string, tid?: string): void {\n const effMid = mid || this.midCtx || \"N/A\";\n let safeDt: any;\n if (dt != null) {\n try {\n safeDt = JSON.parse(JSON.stringify(dt, this.getCircReplacer()));\n } catch (e) {\n console.error(`[LogAgent] Failed stringify details: ${(e as Error).message}`);\n safeDt = `[Logging Error: ${(e as Error).message}]`;\n }\n } else { safeDt = dt; }\n const entry: LogEntry = { ts: new Date().toISOString(), mid: effMid, tid, lvl, comp, msg, dt: safeDt };\n this.logs.push(entry);\n const dtStr = safeDt != null ? `| Details: ${JSON.stringify(safeDt)}` : \"\";\n console.log(\n `[${entry.ts}] [${entry.mid}] [${entry.tid || \"---\"}] [${entry.lvl}] [${entry.comp}] ${entry.msg} ${dtStr}`,\n );\n }\n private getCircReplacer = () => {\n const seen = new WeakSet();\n return (_key: string, value: any) => {\n if (typeof value === \"object\" && value !== null) {\n if (seen.has(value)) { return \"[Circular Reference]\"; }\n seen.add(value);\n }\n return value;\n };\n };\n getLogs(): LogEntry[] {\n try {\n return JSON.parse(JSON.stringify(this.logs));\n } catch (e) {\n console.error(\"[LogAgent] Failed deep copy logs:\", e);\n return [...this.logs];\n }\n }\n clearLogs(): void {\n this.logs = [];\n }\n setMidCtx(mid: string): void {\n this.midCtx = mid;\n }\n}\n\n// --- callOpenAI Function ---\nasync function callOpenAI(\n sysPrompt: string,\n userPrompt: string,\n mid: string,\n tid: string,\n logFn: LogFn,\n): Promise {\n logFn(\n \"DEBUG\",\n \"callOpenAI\",\n `Initiating OpenAI call tid=${tid}`,\n { spLen: sysPrompt.length, upLen: userPrompt.length },\n mid,\n tid,\n );\n try {\n if (!process.env.OPENAI_API_KEY) {\n logFn(\"ERROR\", \"callOpenAI\", \"OpenAI API key missing.\", undefined, mid, tid);\n throw new Error(\"OpenAI API key not configured.\");\n }\n const openai = new OpenAI();\n const completion = await openai.chat.completions.create({\n model: \"gpt-4o-mini\",\n messages: [{ role: \"system\", content: sysPrompt }, { role: \"user\", content: userPrompt }],\n temperature: 0.7,\n max_tokens: 2048,\n });\n const resText = completion.choices[0]?.message?.content;\n const usage = completion.usage;\n if (!resText) {\n logFn(\n \"WARN\",\n \"callOpenAI\",\n `OpenAI call returned no text tid=${tid}.`,\n { usage: usage, finishReason: completion.choices[0]?.finish_reason },\n mid,\n tid,\n );\n return null;\n }\n logFn(\n \"INFO\",\n \"callOpenAI\",\n `OpenAI call OK tid=${tid}`,\n { resLen: resText.length, usage: usage, finishReason: completion.choices[0]?.finish_reason },\n mid,\n tid,\n );\n return resText.trim();\n } catch (err: any) {\n const errDtls = { msg: err.message, name: err.name, status: err.status, type: err.type, code: err.code };\n logFn(\"ERROR\", \"callOpenAI\", `OpenAI API call failed tid=${tid}`, { error: errDtls }, mid, tid);\n throw new Error(`OpenAI API failed: ${err.message}` + (err.code ? ` (Code: ${err.code})` : \"\"));\n }\n}\n\n// --- QAgent Class (with loop fixes) ---\nclass QAgent {\n lg: LogFn;\n private baseReq = [\"bType\", \"sDesc\", \"tAud\"];\n private baseOpt = [\"bTone\", \"goals\"];\n private taskSpec: Record = {\n \"create_content\": { req: [\"cType\", \"plat\"], opt: [\"specInstr\"] },\n \"develop_strategy\": { req: [\"plats\"], opt: [\"budgetLvl\", \"duration\"] },\n \"generate_logo_concept\": { req: [\"bName\"], opt: [\"stylePrefs\", \"colorPrefs\"] },\n \"build_brand_identity\": { req: [\"bName\"], opt: [\"coreVals\"] },\n \"run_simulation\": { req: [\"simType\", \"specParams\"], opt: [] },\n \"meta_prompt\": { req: [\"pInput\"], opt: [] },\n };\n constructor(lgFn: LogFn) {\n this.lg = lgFn;\n }\n private getRequiredFields(task: UserIn[\"task\"]): string[] {\n if (task === \"meta_prompt\") return this.taskSpec.meta_prompt.req;\n return [...new Set([...this.baseReq, ...(this.taskSpec[task]?.req || [])])];\n }\n private getOptionalFields(task: UserIn[\"task\"]): string[] {\n if (task === \"meta_prompt\") return [];\n return [...new Set([...this.baseOpt, ...(this.taskSpec[task]?.opt || [])])];\n }\n private isOptional(field: string, task: UserIn[\"task\"]): boolean {\n return this.getOptionalFields(task).includes(field);\n }\n private selectNextField(\n required: string[],\n optional: string[],\n answers: Record,\n task: UserIn[\"task\"],\n ): string | null {\n for (const fld of required) {\n if (!(fld in answers) || (answers[fld] === \"\" && !this.isOptional(fld, task))) {\n this.lg(\"DEBUG\", \"QAgent.selectNextField\", `Selected missing/empty REQUIRED field: ${fld}`, {\n answers: Object.keys(answers),\n }, undefined);\n return fld;\n }\n }\n for (const fld of optional) {\n if (!(fld in answers)) {\n this.lg(\"DEBUG\", \"QAgent.selectNextField\", `Selected unasked OPTIONAL field: ${fld}`, {\n answers: Object.keys(answers),\n }, undefined);\n return fld;\n }\n }\n this.lg(\n \"DEBUG\",\n \"QAgent.selectNextField\",\n `All required fields populated, all optional fields considered. Done collecting.`,\n { answers: Object.keys(answers) },\n undefined,\n );\n return null;\n }\n private formatQuest(field: string, curState: QState): Quest {\n const qid = `${field}-${Date.now()}`;\n let text = `What is your ${field.replace(/([A-Z])/g, \" $1\").toLowerCase()}?`;\n let type: Quest[\"type\"] = \"text\";\n let opts: Quest[\"opts\"] | undefined = undefined;\n const bName = curState.answers.bName || \"your business\";\n const isOpt = this.isOptional(field, curState.task);\n const optSuffix = isOpt ? \" (Optional)\" : \"\";\n switch (field) {\n case \"bType\":\n text = `Type of business for ${bName}? (e.g., SaaS, Bakery)`;\n break;\n case \"sDesc\":\n text = `Describe products/services for ${bName}.`;\n type = \"textarea\";\n break;\n case \"tAud\":\n text = `Ideal customer for ${bName}? (Specific, e.g., Tech startups)`;\n type = \"textarea\";\n break;\n case \"bTone\":\n text = `Desired tone for ${bName}?${optSuffix}`;\n type = \"select\";\n opts = [\n { lbl: `-- Tone${optSuffix} --`, val: \"\" },\n { lbl: \"Professional\", val: \"professional\" },\n { lbl: \"Friendly\", val: \"friendly\" },\n { lbl: \"Casual\", val: \"casual\" },\n { lbl: \"Humorous\", val: \"humorous\" },\n { lbl: \"Informative\", val: \"informative\" },\n ];\n break;\n case \"goals\":\n text = `Main goals for this task?${optSuffix}`;\n type = \"textarea\";\n break;\n case \"bName\":\n text = `Exact business name?`;\n break;\n case \"cType\":\n text = \"Content type needed?\";\n type = \"select\";\n opts = [\n { lbl: \"-- Type --\", val: \"\" },\n { lbl: \"Promo Post\", val: \"promo_post\" },\n { lbl: \"Blog Ideas\", val: \"blog_idea\" },\n { lbl: \"Blog Draft\", val: \"blog_draft\" },\n { lbl: \"Ad Copy\", val: \"ad_copy\" },\n ];\n break;\n case \"plat\":\n text = \"Platform for content?\";\n type = \"select\";\n opts = [\n { lbl: \"-- Platform --\", val: \"\" },\n { lbl: \"Generic\", val: \"generic\" },\n { lbl: \"Facebook\", val: \"facebook\" },\n { lbl: \"Instagram\", val: \"instagram\" },\n { lbl: \"LinkedIn\", val: \"linkedin\" },\n { lbl: \"Blog\", val: \"blog\" },\n ];\n break;\n case \"specInstr\":\n text = `Specific instructions/keywords?${optSuffix}`;\n type = \"textarea\";\n break;\n case \"plats\":\n text = \"Strategy platforms? (e.g., LinkedIn, SEO - comma separated)\";\n break;\n case \"budgetLvl\":\n text = `Approx budget level?${optSuffix}`;\n type = \"select\";\n opts = [{ lbl: `-- Budget${optSuffix} --`, val: \"\" }, { lbl: \"Low (Organic)\", val: \"low\" }, {\n lbl: \"Medium (Mod Ads)\",\n val: \"medium\",\n }, { lbl: \"High (Sig Ads)\", val: \"high\" }];\n break;\n case \"duration\":\n text = `Strategy duration?${optSuffix}`;\n break;\n case \"stylePrefs\":\n text = `Logo style preferences?${optSuffix}`;\n break;\n case \"colorPrefs\":\n text = `Logo color preferences?${optSuffix}`;\n break;\n case \"coreVals\":\n text = `Core values/mission of ${bName}?${optSuffix}`;\n type = \"textarea\";\n break;\n case \"simType\":\n text = \"Simulation type?\";\n type = \"select\";\n opts = [{ lbl: \"-- Sim --\", val: \"\" }, { lbl: \"Ad Response Est.\", val: \"ad_response_estimate\" }, {\n lbl: \"Customer Interaction\",\n val: \"customer_interaction\",\n }, { lbl: \"Other\", val: \"other\" }];\n break;\n case \"specParams\":\n text = `Sim details/params? (Ad: audience, platform, offer. Cust: scenario, issue. Other: describe.)`;\n type = \"textarea\";\n break;\n case \"pInput\":\n text = \"AI task desc or prompt to refine?\";\n type = \"textarea\";\n break;\n default:\n text = `Please provide \\'${field}\\'.${optSuffix}`;\n if (field.toLowerCase().includes(\"desc\") || field.toLowerCase().includes(\"details\")) { type = \"textarea\"; }\n break;\n }\n if (isOpt && !text.includes(\"(Optional)\")) { text += \" (Optional)\"; }\n return { id: qid, field, text, type, opts };\n }\n async nextStep(\n curSid: string | null,\n task: UserIn[\"task\"],\n lastAns: { field: string; value: any } | null,\n curSt?: QState | null,\n ): Promise {\n let state: QState;\n const sid = curSid || `sess-${Date.now()}-${Math.random().toString(36).substring(2, 8)}`;\n const requiredFields = this.getRequiredFields(task);\n const optionalFields = this.getOptionalFields(task);\n const allRelevantFields = [...requiredFields, ...optionalFields];\n if (!curSt || !curSid || curSt.sid !== sid || curSt.task !== task) {\n this.lg(\"INFO\", \"QAgent\", `Initializing/Resetting state for task: ${task}`, {\n oldSid: curSt?.sid,\n oldTask: curSt?.task,\n newSid: sid,\n }, sid);\n state = { sid: sid, task: task, reqFlds: allRelevantFields, answers: {}, qHist: [], isDone: false };\n if (lastAns?.field && allRelevantFields.includes(lastAns.field)) {\n const val = typeof lastAns.value === \"string\" ? lastAns.value.trim() : lastAns.value;\n if (val !== \"\" || this.isOptional(lastAns.field, state.task)) {\n state.answers[lastAns.field] = val;\n this.lg(\n \"DEBUG\",\n \"QAgent\",\n `Applied initial answer post-reset: Field '${lastAns.field}'`,\n { value: val },\n sid,\n );\n } else {this.lg(\n \"DEBUG\",\n \"QAgent\",\n `Ignoring empty initial answer for required field '${lastAns.field}' post-reset.`,\n { value: val },\n sid,\n );}\n }\n } else {\n state = { ...curSt, answers: { ...curSt.answers }, qHist: [...curSt.qHist] };\n if (lastAns?.field && state.reqFlds.includes(lastAns.field)) {\n this.lg(\n \"DEBUG\",\n \"QAgent\",\n `Processing answer for field '${lastAns.field}'`,\n { value: lastAns.value },\n state.sid,\n );\n const val = typeof lastAns.value === \"string\" ? lastAns.value.trim() : lastAns.value;\n if (val !== \"\" || this.isOptional(lastAns.field, state.task)) { state.answers[lastAns.field] = val; } else {\n this.lg(\n \"WARN\",\n \"QAgent\",\n `Received empty value for required field '${lastAns.field}'. Storing empty string.`,\n undefined,\n state.sid,\n );\n state.answers[lastAns.field] = \"\";\n }\n const lastQAsked = state.qHist[state.qHist.length - 1];\n if (lastQAsked && lastQAsked.field !== lastAns.field) {\n this.lg(\n \"WARN\",\n \"QAgent\",\n `Answer received for field '${lastAns.field}' but last question asked was for '${lastQAsked?.field}'.`,\n undefined,\n state.sid,\n );\n }\n }\n }\n const nextFld = this.selectNextField(requiredFields, optionalFields, state.answers, state.task);\n if (!nextFld) {\n this.lg(\"INFO\", \"QAgent\", `All fields gathered for task '${state.task}'. Attempting final validation.`, {\n gathered: Object.keys(state.answers),\n }, state.sid);\n const finalData = this.finalizeData(state.answers, state.task, state.sid);\n try {\n UserInSchema.parse(finalData);\n this.lg(\"INFO\", \"QAgent\", \"Final data validation OK.\", { finalDataTask: finalData.task }, state.sid);\n state.isDone = true;\n return { sid: state.sid, isDone: true, data: finalData, state, nextQ: undefined, err: undefined };\n } catch (validErr) {\n if (validErr instanceof z.ZodError) {\n const errMsgs = validErr.issues.map(i => `Field '${i.path.join(\".\")}': ${i.message}`).join(\"; \");\n this.lg(\"ERROR\", \"QAgent\", \"Final data validation FAILED.\", {\n errs: validErr.issues,\n dataAttempted: finalData,\n }, state.sid);\n state.isDone = false;\n const firstFailedPath = validErr.issues[0]?.path;\n let fieldToReask: string | null = null;\n if (firstFailedPath && firstFailedPath.length > 1) {\n const schemaFieldName = firstFailedPath[1].toString();\n const keyMap = this.getKeyMap();\n const internalFieldName = Object.keys(keyMap).find(key => keyMap[key] === schemaFieldName);\n if (internalFieldName && allRelevantFields.includes(internalFieldName)) {\n fieldToReask = internalFieldName;\n this.lg(\n \"WARN\",\n \"QAgent\",\n `Validation failed on schema field '${schemaFieldName}', mapped back to internal field '${fieldToReask}'. Re-asking.`,\n { error: errMsgs },\n state.sid,\n );\n delete state.answers[fieldToReask];\n }\n }\n if (fieldToReask) {\n const nextQ = this.formatQuest(fieldToReask, state);\n if (state.qHist.length > 0 && state.qHist[state.qHist.length - 1].field === fieldToReask) {\n state.qHist.pop();\n }\n return {\n sid: state.sid,\n isDone: false,\n nextQ,\n state,\n data: undefined,\n err: `Please check your input for '${fieldToReask}': ${errMsgs}`,\n };\n } else {\n this.lg(\"ERROR\", \"QAgent\", \"Validation failed, but couldn't identify specific field to re-ask.\", {\n error: errMsgs,\n issues: validErr.issues,\n }, state.sid);\n return {\n sid: state.sid,\n isDone: false,\n err: `Data validation failed: ${errMsgs}. Cannot proceed. Try restarting task?`,\n state,\n nextQ: undefined,\n data: undefined,\n };\n }\n } else {\n this.lg(\"ERROR\", \"QAgent\", \"Unexpected error during final data validation.\", {\n error: (validErr as Error).message,\n dataAttempted: finalData,\n }, state.sid);\n state.isDone = false;\n return {\n sid: state.sid,\n isDone: false,\n err: `Unexpected validation error: ${(validErr as Error).message}`,\n state,\n nextQ: undefined,\n data: undefined,\n };\n }\n }\n } else {\n const nextQ = this.formatQuest(nextFld, state);\n if (!state.qHist.find(q => q.id === nextQ.id)) {\n state.qHist.push({ qid: nextQ.id, field: nextQ.field, text: nextQ.text });\n }\n this.lg(\"INFO\", \"QAgent\", `Asking next question for field: '${nextFld}'`, { qText: nextQ.text }, state.sid);\n return { sid: state.sid, isDone: false, nextQ, state, data: undefined, err: undefined };\n }\n }\n private getKeyMap(): Record {\n return {\n bType: \"businessType\",\n sDesc: \"serviceDescription\",\n tAud: \"targetAudience\",\n bTone: \"brandTone\",\n goals: \"goals\",\n cType: \"contentType\",\n plat: \"platform\",\n specInstr: \"specificInstructions\",\n plats: \"platforms\",\n budgetLvl: \"budgetLevel\",\n duration: \"duration\",\n bName: \"businessName\",\n stylePrefs: \"stylePreferences\",\n colorPrefs: \"colorPreferences\",\n coreVals: \"coreValues\",\n simType: \"simulationType\",\n specParams: \"specificParams\",\n pInput: \"prompt_input\",\n };\n }\n private finalizeData(gathered: Record, task: UserIn[\"task\"], sid?: string): UserIn {\n let finalPayloadData: Record = { ...gathered };\n const requiredFields = this.getRequiredFields(task);\n const optionalFields = this.getOptionalFields(task);\n const allFields = [...requiredFields, ...optionalFields];\n allFields.forEach(field => {\n if (this.isOptional(field, task) && (finalPayloadData[field] == null || finalPayloadData[field] === \"\")) {\n delete finalPayloadData[field];\n this.lg(\"DEBUG\", \"finalizeData\", `Removed empty/unanswered optional field: ${field}`, undefined, sid);\n } else if (\n !this.isOptional(field, task) && (finalPayloadData[field] == null || finalPayloadData[field] === \"\")\n ) {\n this.lg(\n \"WARN\",\n \"finalizeData\",\n `Required field '${field}' is missing or empty before final mapping. Validation will likely fail.`,\n { value: finalPayloadData[field] },\n sid,\n );\n }\n });\n if (task === \"develop_strategy\" && finalPayloadData.plats !== undefined) {\n if (typeof finalPayloadData.plats === \"string\") {\n const raw = finalPayloadData.plats;\n finalPayloadData.plats = raw.split(\",\").map((p: string) => p.trim().toLowerCase()).filter((p: string) =>\n p.length > 0\n );\n this.lg(\"DEBUG\", \"finalizeData\", `Transformed plats string to array`, {\n orig: raw,\n res: finalPayloadData.plats,\n }, sid);\n } else if (!Array.isArray(finalPayloadData.plats)) {\n this.lg(\n \"WARN\",\n \"finalizeData\",\n `Plats field not string/array. Setting empty.`,\n { val: finalPayloadData.plats },\n sid,\n );\n finalPayloadData.plats = [];\n }\n finalPayloadData.plats = (finalPayloadData.plats as any[]).filter((p: any) => typeof p === \"string\");\n }\n if (task === \"run_simulation\" && finalPayloadData.specParams !== undefined) {\n if (typeof finalPayloadData.specParams === \"string\") {\n const paramStr = finalPayloadData.specParams.trim();\n if (paramStr.startsWith(\"{\") && paramStr.endsWith(\"}\")) {\n try {\n const parsed = JSON.parse(paramStr);\n if (typeof parsed === \"object\" && parsed !== null && !Array.isArray(parsed)) {\n finalPayloadData.specParams = parsed;\n this.lg(\"DEBUG\", \"finalizeData\", `Parsed specParams string as JSON object.`, { parsed }, sid);\n } else {\n finalPayloadData.specParams = { description: paramStr };\n this.lg(\n \"WARN\",\n \"finalizeData\",\n `Sim specParams was valid JSON but not object, wrapping as description.`,\n { raw: gathered.specParams },\n sid,\n );\n }\n } catch (e) {\n finalPayloadData.specParams = { description: paramStr };\n this.lg(\n \"WARN\",\n \"finalizeData\",\n `Sim specParams looked like JSON but failed parsing, wrapping as description.`,\n { raw: gathered.specParams, err: (e as Error).message },\n sid,\n );\n }\n } else {\n finalPayloadData.specParams = { description: paramStr };\n this.lg(\"DEBUG\", \"finalizeData\", `Sim specParams string treated as description.`, { desc: paramStr }, sid);\n }\n } else if (\n typeof finalPayloadData.specParams !== \"object\" || finalPayloadData.specParams === null\n || Array.isArray(finalPayloadData.specParams)\n ) {\n this.lg(\"WARN\", \"finalizeData\", `Sim specParams not string/object. Wrapping its string value.`, {\n val: finalPayloadData.specParams,\n }, sid);\n try {\n finalPayloadData.specParams = { description: JSON.stringify(finalPayloadData.specParams) };\n } catch (e) {\n finalPayloadData.specParams = { description: \"[Error stringifying specParams]\" };\n }\n }\n }\n const finalSchemaData: Record = {};\n const keyMap = this.getKeyMap();\n for (const key in finalPayloadData) {\n if (keyMap[key]) { finalSchemaData[keyMap[key]] = finalPayloadData[key]; } else {\n finalSchemaData[key] = finalPayloadData[key];\n this.lg(\"WARN\", \"finalizeData\", `Field '${key}' not found in keyMap during finalization.`, undefined, sid);\n }\n }\n return { task: task, data: finalSchemaData };\n }\n}\n\n// --- Agent Functions ---\nasync function runCntAgent(task: TskIn, logFn: LogFn): Promise> {\n const { mid, tid, p } = task;\n logFn(\n \"INFO\",\n \"CntAgent\",\n `Starting content gen tid=${tid}`,\n { cType: p.cType, plat: p.plat, goals: p.goals },\n mid,\n tid,\n );\n const sysP = `Expert copywriter for SMBs. Goal: generate content. CONTEXT: BT: ${p.bType || \"N/A\"}, SVC: ${\n p.sDesc || \"N/A\"\n }, TA: ${p.tAud || \"General\"}, Tone: ${p.bTone || \"Pro/Approach\"}, Goal: ${\n p.goals || \"Engage/Promo\"\n }. TASK: Type: ${p.cType}, Platform: ${p.plat}, Instr: ${\n p.specInstr || \"None\"\n }. INSTR: 1. Gen '${p.cType}' for '${p.plat}'. 2. Use Tone ('${p.bTone || \"Pro/Approach\"}') for TA ('${\n p.tAud || \"General\"\n }'). 3. Integrate Instr: \"${p.specInstr || \"None\"}\". 4. Align w/ Goal ('${\n p.goals || \"Engage/Promo\"\n }'), use CTAs. 5. Platform: Socials(hashtags,length), Ads(headlines,desc,CTA), BlogIdea(3-5 titles), BlogDraft(300-500w section,markdown), Generic(adaptable). 6. Output: ONLY content. Blog Ideas: bullet points.`;\n const userP =\n `Generate the ${p.cType} for the specified platform based on the context provided in the system prompt.`;\n try {\n const genContent = await callOpenAI(sysP, userP, mid, tid, logFn);\n if (!genContent) {\n logFn(\"WARN\", \"CntAgent\", `LLM returned no content tid=${tid}.`, undefined, mid, tid);\n return { mid, cid: tid, p: { content: \"\" }, e: \"AI failed to generate content.\" };\n }\n const output: CntOut = { content: genContent };\n if (p.cType === \"promo_post\" || p.cType === \"ad_copy\") {\n output.suggestions = \"Consider pairing with a relevant image or video. Test different calls-to-action (CTAs).\";\n } else if (p.cType === \"blog_idea\") {\n output.suggestions = \"Research keywords for the chosen idea. Create a detailed outline before writing.\";\n } else if (p.cType === \"blog_draft\") {\n output.suggestions =\n \"Expand on this draft, ensuring keyword integration. Add internal/external links where appropriate.\";\n }\n logFn(\n \"INFO\",\n \"CntAgent\",\n `Content gen task OK tid=${tid}.`,\n { outLen: output.content.length, sug: !!output.suggestions },\n mid,\n tid,\n );\n return { mid, cid: tid, p: output };\n } catch (err: any) {\n logFn(\"ERROR\", \"CntAgent\", `Content gen task fail tid=${tid}.`, { err: err.message }, mid, tid);\n return { mid, cid: tid, p: { content: \"\" }, e: `Content generation failed: ${err.message}` };\n }\n}\nasync function runStratAgent(task: TskIn, logFn: LogFn): Promise> {\n const { mid, tid, p } = task;\n const platsStr = Array.isArray(p.plats) ? p.plats.join(\", \") : \"N/A\";\n logFn(\n \"INFO\",\n \"StratAgent\",\n `Starting strategy dev tid=${tid}`,\n { plats: platsStr, budget: p.budgetLvl, dur: p.duration },\n mid,\n tid,\n );\n const sysP = `Pragmatic Digital Mktg Strategist for SMBs. Task: outline concise strategy. CONTEXT: BT: ${\n p.bType || \"N/A\"\n }, SVC: ${p.sDesc || \"N/A\"}, TA: ${p.tAud || \"General\"}, Goals: ${\n p.goals || \"Incr presence/leads\"\n }, Platforms: ${platsStr}, Budget: ${p.budgetLvl || \"Low\"}, Duration: ${p.duration || \"Ongoing\"}, Tone: ${\n p.bTone || \"Pro/Trust\"\n }. FRAMEWORK (Use MD headings): ## Executive Summary - Core strategy/outcomes. ## Target Audience Insights - Online behavior, needs, reach. ## Recommended Platforms & Rationale - Eval requested ('${platsStr}'). Recommend best based on audience/goals/budget. Justify. Suggest alt if needed. ## Core Content Themes & Messaging - 2-4 themes for audience/value. Key messages. ## Platform-Specific Tactics (recommended) - 2-3 tactics per platform (e.g., LinkedIn: insights, groups; SEO: long-tail kw, citations). Prioritize by Budget (Low: organic; Med: ads; High: campaigns). ## Sample Ad Copy / Post Ideas - 2-3 examples. ## Budget Considerations (If applicable) - Med/High: spend priority. Low: acknowledge limits. ## Measurement & KPIs - 3-5 KPIs (e.g., Traffic, CVR, Engagement, CPL). ## Next Steps - Immediate actions (e.g., Profiles, KW research, Calendar). INSTR: 1. Practical, specific. 2. Prioritize by Budget. 3. Cohesive. 4. Output ONLY strategy doc (MD). No intro/outro text.`;\n const userP = `Develop the marketing strategy based on the system prompt context & framework.`;\n try {\n const stratContent = await callOpenAI(sysP, userP, mid, tid, logFn);\n if (!stratContent) {\n logFn(\"WARN\", \"StratAgent\", `LLM no content for strat tid=${tid}.`, undefined, mid, tid);\n return { mid, cid: tid, p: { strategy: \"\" }, e: \"AI failed strategy.\" };\n }\n let adIdeas: string[] = [];\n const adMatch = stratContent.match(/## Sample Ad Copy \\/ Post Ideas\\n+([\\s\\S]*?)(?=\\n##|$)/i);\n if (adMatch?.[1]) {\n adIdeas = adMatch[1].split(/[\\n\\r]+-|\\\\*|\\\\d+\\\\.\\\\s*/).map(s => s.trim()).filter(s => s && s.length > 10);\n }\n let audSugs: string[] = [];\n const audMatch = stratContent.match(/## Target Audience Insights\\n+([\\s\\S]*?)(?=\\n##|$)/i);\n if (audMatch?.[1]) {\n audSugs = audMatch[1].split(/[\\n\\r]+-|\\\\*|\\\\d+\\\\.\\\\s*/).map(s => s.trim()).filter(s => s && s.length > 10);\n }\n const output: StratOut = { strategy: stratContent, adIdeas, audSugs };\n logFn(\n \"INFO\",\n \"StratAgent\",\n `Strategy dev OK tid=${tid}.`,\n { stratLen: output.strategy.length, adIdeasCnt: adIdeas.length, audSugsCnt: audSugs.length },\n mid,\n tid,\n );\n return { mid, cid: tid, p: output };\n } catch (err: any) {\n logFn(\"ERROR\", \"StratAgent\", `Strategy dev fail tid=${tid}.`, { err: err.message }, mid, tid);\n return { mid, cid: tid, p: { strategy: \"\" }, e: `Strategy generation failed: ${err.message}` };\n }\n}\nasync function runLogoAgent(task: TskIn, logFn: LogFn): Promise> {\n const { mid, tid, p } = task;\n logFn(\n \"INFO\",\n \"LogoAgent\",\n `Starting logo concept gen tid=${tid}`,\n { bName: p.bName, style: p.stylePrefs, color: p.colorPrefs },\n mid,\n tid,\n );\n const sysP = `Creative Asst gen 2-3 logo concepts. Each: desc + AI img prompt. CONTEXT: BN: ${p.bName}, BT: ${\n p.bType || \"N/A\"\n }, Svc: ${p.sDesc || \"N/A\"}, TA: ${p.tAud || \"General\"}, Styles: ${p.stylePrefs || \"Versatile\"}, Colors: ${\n p.colorPrefs || \"Suggest\"\n }, Tone: ${\n p.bTone || \"Professional\"\n }. INSTR: 1. Gen 2-3 diff concepts (icon, wordmark, abstract/combo). 2. Format each (MD): ### Concept Title \\\\n#### Description: \\\\n- Visuals, symbolism, fonts (sans/serif), colors. \\\\n#### AI Image Generation Prompt: \\\\n- Detailed prompt for AI (DALL-E, etc). Incl: type(vector logo), subj(BN/initials), style(minimalist, flat), elements, colors, bg(white). Ex: \"/imagine prompt: vector logo for '${p.bName}', minimalist flat design [Symbol], clean sans-serif, blue (#005C99), gray (#CCCCCC), isolated white bg --style raw --ar 1:1\" 3. Separate concepts w/ '---'. 4. (Opt) If simple, attempt basic SVG: \\\\\\`\\\\\\`\\\\\\`svg ... \\\\\\`\\\\\\`\\\\\\`. 5. Output ONLY concepts. No intro/outro.`;\n const userP =\n `Generate 2-3 distinct logo concepts for \"${p.bName}\" based on the system prompt. Provide descriptions and AI prompts.`;\n try {\n const conceptContent = await callOpenAI(sysP, userP, mid, tid, logFn);\n if (!conceptContent) {\n logFn(\"WARN\", \"LogoAgent\", `LLM no content for logo tid=${tid}.`, undefined, mid, tid);\n return { mid, cid: tid, p: { concepts: [], prompts: [] }, e: \"AI failed logo concepts.\" };\n }\n const concepts: string[] = [];\n const prompts: string[] = [];\n const sections = conceptContent.split(/\\n---\\n/);\n sections.forEach(sec => {\n const titleM = sec.match(/### (.*?)\\n/);\n const descM = sec.match(/#### Description:\\n([\\s\\S]*?)(?=\\n#### AI Image Generation Prompt:|$)/i);\n const promptM = sec.match(/#### AI Image Generation Prompt:\\n([\\s\\S]*?)(?=\\n\\`\\`\\`svg|$)/i);\n if (titleM && descM && promptM) {\n concepts.push(`Title: ${titleM[1].trim()}\\n\\nDescription:\\n${descM[1].trim()}`);\n prompts.push(promptM[1].trim());\n } else {\n logFn(\n \"WARN\",\n \"LogoAgent\",\n `Could not parse logo concept section.`,\n { sectionStart: sec.substring(0, 100) },\n mid,\n tid,\n );\n if (sec.trim().length > 0) concepts.push(`Raw Section:\\n${sec.trim()}`);\n }\n });\n const svgM = conceptContent.match(/```svg\\n([\\s\\S]*?)\\n```/);\n const svgAttempt = svgM ? svgM[1].trim() : undefined;\n if (concepts.length === 0 && conceptContent.length > 0) {\n logFn(\n \"WARN\",\n \"LogoAgent\",\n `No structured concepts parsed, return raw tid=${tid}`,\n { rawLen: conceptContent.length },\n mid,\n tid,\n );\n concepts.push(`Raw Output (Parse Fail):\\n${conceptContent}`);\n }\n const output: LogoOut = { concepts, prompts, svg: svgAttempt };\n logFn(\n \"INFO\",\n \"LogoAgent\",\n `Logo concept task OK tid=${tid}.`,\n { concepts: output.concepts.length, prompts: output.prompts?.length, svg: !!output.svg },\n mid,\n tid,\n );\n return { mid, cid: tid, p: output };\n } catch (err: any) {\n logFn(\"ERROR\", \"LogoAgent\", `Logo concept task fail tid=${tid}.`, { err: err.message }, mid, tid);\n return { mid, cid: tid, p: { concepts: [], prompts: [] }, e: `Logo concept generation failed: ${err.message}` };\n }\n}\nasync function runBrandAgent(task: TskIn, logFn: LogFn): Promise> {\n const { mid, tid, p } = task;\n logFn(\n \"INFO\",\n \"BrandAgent\",\n `Starting brand ID def tid=${tid}`,\n { bName: p.bName, vals: p.coreVals, tone: p.bTone },\n mid,\n tid,\n );\n const sysP =\n `Brand Strategist Asst defining foundational brand ID. Create concise guide. CONTEXT: BN: ${p.bName}, BT: ${\n p.bType || \"N/A\"\n }, Svc: ${p.sDesc || \"N/A\"}, TA: ${p.tAud || \"General\"}, Values: ${p.coreVals || \"N/A\"}, Tone: ${\n p.bTone || \"Pro/Trust\"\n }. FRAMEWORK (MD headings): ## Brand Voice & Personality - Describe voice detail. Elaborate tone ('${\n p.bTone || \"Pro/Trust\"\n }'). Define personality (Expert, Friendly, Reliable). Lang style (Formal/Casual, Jargon/Plain). ## Key Messages - List 3-5 core msgs/taglines (* bullets). Communicate value, connect service->audience, reflect values. Concise, memorable. ## Color Palette Suggestions - Recommend primary, 1-2 secondary, 1 accent color. Hex codes (#RRGGBB). Justify (personality, industry, audience). Ex: \"Primary: Blue (#0A2F5B) trust. Secondary: Gray (#E1E1E1) contrast. Accent: Teal (#1ABC9C) energy.\" ## Typography Suggestions - Recommend 1 heading, 1 body font (Google Fonts). Justify (readability, personality, contrast). Ex: \"Head: Montserrat Bold (Modern). Body: Lato Regular (Clean). Prof feel.\" INSTR: 1. Cohesive suggestions (Voice, Msgs, Colors, Fonts). 2. Practical for SMB. 3. Align w/ Context (BT, TA, Tone). 4. Output ONLY guide (MD). No intro/outro.`;\n const userP =\n `Develop foundational brand ID guide for \"${p.bName}\" based on system prompt context/instructions. Ensure cohesive & practical.`;\n try {\n const idContent = await callOpenAI(sysP, userP, mid, tid, logFn);\n if (!idContent) {\n logFn(\"WARN\", \"BrandAgent\", `LLM no content for brand ID tid=${tid}.`, undefined, mid, tid);\n return { mid, cid: tid, p: { bVoice: \"\", kMsgs: [], cPalSugs: \"\", typo: \"\" }, e: \"AI failed brand ID guide.\" };\n }\n const voiceM = idContent.match(/## Brand Voice & Personality\\n([\\s\\S]*?)(?=\\n##|$)/i);\n const msgsM = idContent.match(/## Key Messages\\n([\\s\\S]*?)(?=\\n##|$)/i);\n const colorM = idContent.match(/## Color Palette Suggestions\\n([\\s\\S]*?)(?=\\n##|$)/i);\n const typoM = idContent.match(/## Typography Suggestions\\n([\\s\\S]*?)(?=\\n##|$)/i);\n const bVoice = voiceM ? voiceM[1].trim() : \"Parse fail Voice.\";\n const kMsgsRaw = msgsM ? msgsM[1].trim() : \"\";\n let kMsgs = kMsgsRaw.split(/[\\n\\r]+\\s*[\\*\\-]\\s*/).map(s => s.trim()).filter(s => s.length > 5);\n if (kMsgs.length === 0 && kMsgsRaw.length > 5) { kMsgs.push(`Raw Msgs: ${kMsgsRaw}`); }\n const cPalSugs = colorM ? colorM[1].trim() : \"Parse fail Colors.\";\n const typo = typoM ? typoM[1].trim() : \"Parse fail Typography.\";\n if (bVoice.startsWith(\"Parse fail\") && kMsgs.length === 0) {\n logFn(\n \"WARN\",\n \"BrandAgent\",\n `Sig parse fail brand ID tid=${tid}`,\n { rawP: idContent.substring(0, 200) },\n mid,\n tid,\n );\n }\n const output: BrandOut = { bVoice, kMsgs, cPalSugs, typo };\n logFn(\n \"INFO\",\n \"BrandAgent\",\n `Brand ID task OK tid=${tid}.`,\n { voiceLen: output.bVoice.length, msgsCnt: output.kMsgs.length },\n mid,\n tid,\n );\n return { mid, cid: tid, p: output };\n } catch (err: any) {\n logFn(\"ERROR\", \"BrandAgent\", `Brand ID task fail tid=${tid}.`, { err: err.message }, mid, tid);\n return {\n mid,\n cid: tid,\n p: { bVoice: \"\", kMsgs: [], cPalSugs: \"\", typo: \"\" },\n e: `Brand ID generation failed: ${err.message}`,\n };\n }\n}\nasync function runSimAgent(task: TskIn, logFn: LogFn): Promise> {\n const { mid, tid, p } = task;\n let paramDesc = \"N/A\";\n try {\n paramDesc = typeof p.specParams === \"string\" ? p.specParams : JSON.stringify(p.specParams);\n } catch (e) {\n paramDesc = \"[Serialization fail]\";\n logFn(\"WARN\", \"SimAgent\", `Failed serialize specParams tid=${tid}`, { err: (e as Error).message }, mid, tid);\n }\n logFn(\n \"INFO\",\n \"SimAgent\",\n `Starting sim task tid=${tid}`,\n { simType: p.simType, paramsP: paramDesc.substring(0, 100) },\n mid,\n tid,\n );\n const sysP = `Adv Sim Model predicts outcomes/role-plays. CONTEXT: BT: ${p.bType || \"N/A\"}, Svc: ${\n p.sDesc || \"N/A\"\n }, TA: ${p.tAud || \"General\"}, Tone: ${\n p.bTone || \"Pro/Helpful\"\n }. SIM TASK: Type: ${p.simType}, Params/Scenario: ${paramDesc}. INSTR: 1. Analyze Type & Params. 2. Execute: 'ad_response_estimate': Qual assess ad effectiveness (platform, audience, copy). Estimate metric ranges (CTR, CVR) if feasible. State assumptions (avg market). Avoid guarantees. Focus likelihoods. 'customer_interaction': Role-play realistic interaction (Customer:, Agent:). Reflect context, tone, issue. Concise (3-5 exchanges). 'other': Execute per desc. Interpret reasonably. State assumptions. 3. Output: Core sim result first. THEN optional \\\\\\`## Analysis\\\\\\` (MD heading). Brief takeaways/insights from sim only (2-4 sentences). 4. Output ONLY result & opt analysis. No intro/outro.`;\n const userP = `Run simulation type '${p.simType}' based on system prompt context/params. Follow format.`;\n try {\n const simContent = await callOpenAI(sysP, userP, mid, tid, logFn);\n if (!simContent) {\n logFn(\"WARN\", \"SimAgent\", `LLM no content for sim tid=${tid}.`, undefined, mid, tid);\n return { mid, cid: tid, p: { simResult: \"\" }, e: \"AI failed sim.\" };\n }\n let simResult = simContent;\n let analysis: string | undefined = undefined;\n const analysisM = simContent.match(/\\n## Analysis\\s*$/mi);\n if (analysisM?.index !== undefined) {\n const splitIndex = analysisM.index;\n simResult = simContent.substring(0, splitIndex).trim();\n analysis = simContent.substring(splitIndex).replace(/^## Analysis\\s*[\\r\\n]+/mi, \"\").trim();\n logFn(\"DEBUG\", \"SimAgent\", `Analysis section found tid=${tid}`, { analysisLen: analysis.length }, mid, tid);\n } else {\n simResult = simContent.trim();\n logFn(\"DEBUG\", \"SimAgent\", `No analysis section found tid=${tid}`, undefined, mid, tid);\n }\n if (!simResult && analysis) {\n logFn(\"WARN\", \"SimAgent\", `Sim result empty, analysis found tid=${tid}.`, undefined, mid, tid);\n simResult = \"(Simulation produced analysis but no primary result)\";\n } else if (!simResult && !analysis) {\n logFn(\"WARN\", \"SimAgent\", `Sim result & analysis empty tid=${tid}.`, undefined, mid, tid);\n simResult = \"(Simulation produced no output)\";\n }\n const output: SimOut = { simResult, analysis };\n logFn(\n \"INFO\",\n \"SimAgent\",\n `Sim task OK tid=${tid}.`,\n { resLen: output.simResult.length, hasAnalysis: !!output.analysis },\n mid,\n tid,\n );\n return { mid, cid: tid, p: output };\n } catch (err: any) {\n logFn(\"ERROR\", \"SimAgent\", `Sim task fail tid=${tid}.`, { err: err.message }, mid, tid);\n return { mid, cid: tid, p: { simResult: \"\" }, e: `Simulation run failed: ${err.message}` };\n }\n}\nasync function runMetaAgent(task: TskIn, logFn: LogFn): Promise> {\n const { mid, tid, p } = task;\n logFn(\"INFO\", \"MetaAgent\", `Starting meta-prompt gen/refine tid=${tid}`, { inputLen: p.pInput.length }, mid, tid);\n const sysP =\n `Expert AI Prompt Engineer. Mission: create/refine high-quality SYSTEM prompt for another AI (GPT-4) based on user's request. Prompt should be clear, comprehensive, unambiguous, elicit best response. PRINCIPLES: 1. Role & Expertise: Define AI persona (e.g., \"Expert financial analyst...\"). 2. Task/Goal: State main objective (e.g., \"...analyze data, gen memo.\"). 3. Context/Input Spec: List needed inputs ([Business Plan], [User Question]). 4. Process/Steps (if complex): Outline steps (1. Analyze. 2. Risks. 3. Recs. 4. Output.). 5. Output Format/Constraints: Specify format(MD, JSON), len, tone, style, language, avoid (\"JSON format.\", \"No filler.\", \"< 500 words.\"). Output structure examples if helpful. 6. Ambiguity/Missing Info: Instruct handling (\"Ask clarifying Qs.\", \"State missing data.\"). 7. Refinement (If Applicable): Analyze existing prompt strengths/weaknesses. Address weaknesses (clarity, format, role). USER'S REQUEST (for sys prompt gen/refine): \\\\\\`\\\\\\`\\\\\\`\\n${p.pInput}\\n\\\\\\`\\\\\\`\\\\\\` YOUR TASK: Generate complete system prompt text based ONLY on user req & principles. Output ONLY system prompt itself. No code blocks unless user requested. No explanations/intros (\"Here is prompt:\").`;\n const userP =\n `Based on my request in system context, generate/refine the system prompt per guidelines. Output only resulting prompt text.`;\n try {\n const genSysP = await callOpenAI(sysP, userP, mid, tid, logFn);\n if (!genSysP) {\n logFn(\"WARN\", \"MetaAgent\", `LLM no content for meta-prompt tid=${tid}.`, undefined, mid, tid);\n return { mid, cid: tid, p: { sysPrompt: \"\" }, e: \"AI failed to generate system prompt.\" };\n }\n const finalP = genSysP.replace(/^```(markdown|text)?\\s*/i, \"\").replace(/\\s*```$/, \"\").trim();\n const output: MetaOut = { sysPrompt: finalP };\n logFn(\"INFO\", \"MetaAgent\", `Meta-prompt task OK tid=${tid}.`, { outputLen: output.sysPrompt.length }, mid, tid);\n return { mid, cid: tid, p: output };\n } catch (err: any) {\n logFn(\"ERROR\", \"MetaAgent\", `Meta-prompt task fail tid=${tid}.`, { err: err.message }, mid, tid);\n return { mid, cid: tid, p: { sysPrompt: \"\" }, e: `Meta-prompt generation failed: ${err.message}` };\n }\n}\n\n// --- Orchestrator Class ---\nclass Orchestrator {\n baseLog: LogFn;\n mandateId: string;\n lg: LogFn;\n constructor(baseLogger: LogAgent) {\n this.mandateId = `m-${Date.now()}-${Math.random().toString(36).substring(2, 8)}`;\n baseLogger.setMidCtx(this.mandateId);\n this.baseLog = baseLogger.log.bind(baseLogger);\n this.lg = (lvl, comp, msg, dt?, _midIgnored?, tid?) => {\n this.baseLog(lvl, comp, msg, dt, this.mandateId, tid);\n };\n this.lg(\"INFO\", \"Orchestrator\", `Initialized mandate: ${this.mandateId}`);\n }\n async runWorkflow(input: UserIn): Promise {\n this.lg(\"INFO\", \"Orchestrator\", `Workflow started task: ${input.task}`, { inputKeys: Object.keys(input.data) });\n const tid = `${input.task}-${Date.now()}-${Math.random().toString(36).substring(2, 7)}`;\n const taskInput: TskIn = { mid: this.mandateId, tid: tid, p: input.data };\n let taskOutput: TskOut;\n try {\n const agentLog: LogFn = (lvl, comp, msg, dt?, _midOverride?, tidFromAgent?) => {\n this.lg(lvl, comp, msg, dt, this.mandateId, tidFromAgent || tid);\n };\n switch (input.task) {\n case \"create_content\":\n taskOutput = await runCntAgent(taskInput as TskIn, agentLog);\n break;\n case \"develop_strategy\":\n taskOutput = await runStratAgent(taskInput as TskIn, agentLog);\n break;\n case \"generate_logo_concept\":\n taskOutput = await runLogoAgent(taskInput as TskIn, agentLog);\n break;\n case \"build_brand_identity\":\n taskOutput = await runBrandAgent(taskInput as TskIn, agentLog);\n break;\n case \"run_simulation\":\n taskOutput = await runSimAgent(taskInput as TskIn, agentLog);\n break;\n case \"meta_prompt\":\n taskOutput = await runMetaAgent(taskInput as TskIn, agentLog);\n break;\n default:\n const _exCheck: never = input.task;\n this.lg(\"ERROR\", \"Orchestrator\", `Unsupported task type: ${_exCheck}`, { taskInput }, this.mandateId, tid);\n throw new Error(`Unsupported task: ${_exCheck}`);\n }\n if (taskOutput.e) {\n this.lg(\"WARN\", \"Orchestrator\", `Agent task ${tid} completed with error.`, {\n err: taskOutput.e,\n agentPayload: taskOutput.p,\n });\n return {\n mid: this.mandateId,\n err: `Agent execution failed: ${taskOutput.e}`,\n res: taskOutput.p,\n dbgLog: [],\n details: \"Agent reported error.\",\n };\n }\n this.lg(\"INFO\", \"Orchestrator\", `Workflow task ${tid} (${input.task}) completed successfully.`);\n return { mid: this.mandateId, res: taskOutput.p, err: undefined, dbgLog: [] };\n } catch (err: any) {\n this.lg(\"ERROR\", \"Orchestrator\", `Critical workflow failure task ${tid} (${input.task}).`, {\n err: err.message,\n stack: err.stack?.substring(0, 500),\n });\n return {\n mid: this.mandateId,\n err: `Workflow execution failed critically: ${err.message}`,\n details: \"Unexpected error in orchestration/agent.\",\n dbgLog: [],\n };\n }\n }\n}\n\n// --- HTML Generation ---\n\nfunction generateOrthogonalUI(): string {\n // generate HTML here\n return `Orthogonal UI

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