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Task Dispatcher — Nexuses Core OS V10.0\n// Orchestrates the Analyze → Execute → Report pipeline.\n// Integrates Supervisor (auto-retry) and IAP delegation.\nimport { getAgentManifest, routeIncomingTask } from \"./AgentManager.ts\";\nimport type { AgentResult } from \"./AgentManager.ts\";\nimport { listAdapters, routeToAdapter } from \"./UniversalAdapter.ts\";\nimport {\n classifyTask,\n getHFToken,\n getModelManifest,\n getSelectionInfo,\n selectModel,\n} from \"./hf.ts\";\nimport type { TaskType } from \"./hf.ts\";\nimport { supervise } from \"./Supervisor.ts\";\nimport type { SupervisedResult } from \"./Supervisor.ts\";\nimport { delegateToExternal } from \"./IAP.ts\";\nimport type { DelegationResult } from \"./IAP.ts\";\nimport { getServiceInfo, hasInternalCapability } from \"./RegistryManager.ts\";\nimport {\n getRecentTasks,\n getTask,\n getTaskCount,\n initDB,\n insertTask,\n logWorkflowStep,\n recall,\n remember,\n updateTaskStatus,\n} from \"./db.ts\";\n\nexport interface DispatchResponse {\n status: \"success\" | \"failure\";\n task_id: string;\n data: any;\n message: string;\n agent?: string;\n category?: string;\n model?: string;\n modelId?: string;\n taskType?: TaskType;\n fallbackUsed?: boolean;\n attempts?: string[];\n adapters?: string[];\n delegated?: boolean;\n delegationTarget?: string | null;\n supervised?: boolean;\n retried?: boolean;\n selfCorrected?: boolean;\n supervisorAttempts?: number;\n executionTimeMs: number;\n timestamp: string;\n}\n\nfunction generateTaskId(): string {\n return `nxs_${Date.now()}_${Math.random().toString(36).slice(2, 8)}`;\n}\n\n// --- Public Dispatch API ---\n\nexport async function dispatchTask(\n task: string,\n data: any = {},\n mode = \"AUTO\",\n): Promise {\n const start = Date.now();\n const taskId = generateTaskId();\n\n // Ensure DB is ready\n await initDB();\n\n // PHASE 1: ANALYZE — deconstruct the task, identify agents + model\n const agents = getAgentManifest();\n const taskLower = task.toLowerCase();\n\n // Identify which agents could handle this task\n const candidates = agents.filter((a) =>\n a.keywords.some((k) => taskLower.includes(k))\n );\n\n // Dynamic model selection — classify task type before any API call\n const selection = getSelectionInfo(task);\n\n await logWorkflowStep(\n taskId,\n 1,\n \"TaskDispatcher\",\n \"ANALYZE\",\n `Task: \"${task}\" | Type: ${selection.taskType} | Model: ${selection.modelLabel} (${selection.modelId}) | Fallback: ${\n selection.fallbackModel || \"none\"\n } | Candidates: ${\n candidates.map((a) => a.name).join(\", \") || \"GeneralHandler\"\n }`,\n );\n\n // Record initial task state\n await insertTask(\n taskId,\n task,\n \"pending\",\n \"processing\",\n { task, data, mode },\n null,\n );\n\n // Recall any memory related to this task type\n const memoryKey = `task_type:${candidates[0]?.name || \"general\"}`;\n const priorMemory = await recall(memoryKey);\n\n // PHASE 2: EXECUTE — route to selected agent via Supervisor\n await logWorkflowStep(\n taskId,\n 2,\n \"TaskDispatcher\",\n \"EXECUTE\",\n `Routing to agent for execution (supervised mode)`,\n );\n\n // Wrap execution in Supervisor for autonomous error recovery\n const supervised = await supervise(\n taskId,\n task,\n data,\n (t, d) => routeIncomingTask(t, d, mode, true),\n );\n\n let agentResult: AgentResult;\n let delegated = false;\n let delegationResult: DelegationResult | null = null;\n\n if (supervised.success && supervised.finalResult) {\n agentResult = supervised.finalResult as AgentResult;\n } else {\n // Internal execution failed after retries — try external delegation\n await logWorkflowStep(\n taskId,\n 5,\n \"TaskDispatcher\",\n \"DELEGATE\",\n `Internal execution failed, attempting external delegation`,\n );\n\n delegationResult = await delegateToExternal(task, data);\n delegated = delegationResult.delegated;\n\n if (delegationResult.success) {\n agentResult = {\n agent: \"ExternalDelegation\",\n category: \"Delegated\",\n status: \"SUCCESS\",\n message: delegationResult.message,\n data: delegationResult.data,\n adapters: [],\n };\n } else {\n agentResult = {\n agent: supervised.finalResult?.agent || \"Unknown\",\n category: supervised.finalResult?.category || \"General\",\n status: \"ERROR\",\n message: supervised.message,\n data: supervised.finalResult?.data || {},\n };\n }\n }\n\n await logWorkflowStep(\n taskId,\n 3,\n agentResult.agent,\n agentResult.status,\n agentResult.message + (delegated ? \" [DELEGATED]\" : \"\"),\n );\n\n // PHASE 3: REPORT — build structured Universal Task Format response\n const isSuccess = agentResult.status === \"SUCCESS\" ||\n agentResult.status === \"PARTIAL\";\n const response: DispatchResponse = {\n status: agentResult.status === \"ERROR\" ? \"failure\" : \"success\",\n task_id: taskId,\n data: agentResult.data,\n message: agentResult.message,\n agent: agentResult.agent,\n category: agentResult.category,\n model: agentResult.model,\n modelId: agentResult.modelId,\n taskType: agentResult.taskType || selection.taskType,\n fallbackUsed: agentResult.fallbackUsed,\n attempts: agentResult.attempts,\n adapters: agentResult.adapters || [],\n delegated,\n delegationTarget: delegationResult?.target || null,\n supervised: true,\n retried: supervised.retried,\n selfCorrected: supervised.selfCorrected,\n supervisorAttempts: supervised.attempts.length,\n executionTimeMs: Date.now() - start,\n timestamp: new Date().toISOString(),\n };\n\n // Update task in DB\n await updateTaskStatus(taskId, isSuccess ? \"completed\" : \"failed\", response);\n\n // Save to memory for future reference\n await remember(memoryKey, {\n lastTask: task,\n lastAgent: agentResult.agent,\n lastStatus: agentResult.status,\n lastModel: agentResult.model,\n fallbackUsed: agentResult.fallbackUsed,\n timestamp: new Date().toISOString(),\n ...(priorMemory ? { previous: priorMemory } : {}),\n });\n\n await logWorkflowStep(\n taskId,\n 4,\n \"TaskDispatcher\",\n \"REPORT\",\n `Status: ${response.status} | Model: ${response.model || \"N/A\"}${\n response.fallbackUsed ? \" (FALLBACK)\" : \"\"\n } | Time: ${response.executionTimeMs}ms`,\n );\n\n return response;\n}\n\n// --- Status & Discovery ---\n\nexport async function getTaskStatus(taskId: string) {\n return getTask(taskId);\n}\n\nexport async function getHistory(limit = 20) {\n return getRecentTasks(limit);\n}\n\nexport async function getSystemStatus() {\n await initDB();\n const taskCount = await getTaskCount();\n const token = getHFToken();\n\n return {\n status: \"ONLINE\",\n service: \"Nexuses Core OS V10.0 — Universal AI Gateway\",\n uptime: \"24/7 on Val Town\",\n persistence: \"SQLite (project-scoped)\",\n tasksProcessed: taskCount,\n hfIntegration: \"Free AI: ALWAYS ON (no token needed) | HF: \" + (token ? \"ACTIVE\" : \"not configured\") + \" | OpenAI: \" + (Deno.env.get(\"OPENAI_API_KEY\") ? \"ACTIVE\" : \"not configured\"),\n protocol: \"JSON-RPC 2.0 / IAP 1.0\",\n models: getModelManifest(),\n agents: getAgentManifest().map((a) => ({\n name: a.name,\n category: a.category,\n capabilities: a.capabilities,\n })),\n adapters: listAdapters(),\n endpoints: {\n POST: {\n \"/\": \"Universal AI Gateway — public, no auth (auto model selection)\",\n \"/public-task\": \"Alias for / (public universal task)\",\n \"/adapter\": \"Direct adapter call (auth required)\",\n \"/handshake\": \"IAP handshake (JSON-RPC, public)\",\n \"/rpc\": \"JSON-RPC 2.0 endpoint (auth required)\",\n },\n GET: {\n \"/\": \"System discovery\",\n \"/status\": \"System status & stats\",\n \"/register\": \"Service manifest for external AI discovery\",\n \"/task/:id\": \"Get task result by ID\",\n \"/history\": \"Recent task history\",\n \"/agents\": \"Agent manifest\",\n \"/adapters\": \"Available adapters\",\n \"/models\": \"Available HF models\",\n },\n },\n example: {\n url: \"POST /\",\n headers: {\n \"Authorization\": \"Bearer YOUR_NEXUSES_API_KEY\",\n \"Content-Type\": \"application/json\",\n },\n body: {\n task: 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Nexuses Core OS V10.0 — Universal AI Gateway\n// HTTP Entry Point with IAP, JSON-RPC, strict auth, and Dynamic Request Normalizer\n\nimport {\n callAdapterDirect,\n dispatchTask,\n getHistory,\n getSystemStatus,\n getTaskStatus,\n} from \"./TaskDispatcher.ts\";\nimport { getAgentManifest } from \"./AgentManager.ts\";\nimport { listAdapters } from \"./UniversalAdapter.ts\";\nimport { getModelManifest } from \"./hf.ts\";\nimport { initDB } from \"./db.ts\";\nimport { buildCapabilityList, getServiceManifest } from \"./RegistryManager.ts\";\nimport { processHandshake, processRPC } from \"./IAP.ts\";\nimport type { JSONRPCRequest } from \"./IAP.ts\";\n\nconst CORS = {\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\nfunction json(body: any, status = 200) {\n return new Response(JSON.stringify(body, null, 2), { status, headers: CORS });\n}\n\nfunction getEnv(key: string): string | undefined {\n try {\n return Deno.env.get(key);\n } catch {\n return undefined;\n }\n}\n\nfunction getEndpoint(req: Request): string {\n const url = new URL(req.url);\n return `${url.protocol}//${url.host}/`;\n}\n\n// --- Universal Request Normalizer ---\n// خود بخود ریکویسٹ کو پہچان کر فارمیٹ سیٹ کرتا ہے\nfunction normalizeRequest(payload: any) {\n const possibleTaskKeys = [\n \"task\",\n \"query\",\n \"prompt\",\n \"command\",\n \"message\",\n \"input\",\n \"body\",\n \"text\",\n ];\n let task = \"general\";\n let data = { ...payload };\n\n for (const key of possibleTaskKeys) {\n if (payload[key]) {\n task = payload[key];\n delete data[key];\n break;\n }\n }\n return { task, data };\n}\n\n// --- Auth Validation ---\nfunction validateAuth(req: Request): boolean {\n const apiKey = getEnv(\"NEXUSES_API_KEY\");\n if (!apiKey) return true; // Dev mode\n const auth = req.headers.get(\"authorization\") || \"\";\n const token = auth.replace(/^Bearer\\s+/i, \"\").trim();\n return token === apiKey;\n}\n\n// --- Rate Limiting ---\nconst RATE_LIMIT = new Map();\nfunction isRateLimited(ip: string): boolean {\n const now = Date.now();\n const ts = RATE_LIMIT.get(ip)?.filter((t) => now - t < 60000) || [];\n if (ts.length >= 50) return true; // 50 requests per minute\n ts.push(now);\n RATE_LIMIT.set(ip, ts);\n return false;\n}\n\n// --- HTTP Handler ---\nexport default async function (req: Request): Promise {\n if (req.method === \"OPTIONS\") return new Response(null, { headers: CORS });\n\n const url = new URL(req.url);\n const path = url.pathname;\n const ip = req.headers.get(\"x-forwarded-for\")?.split(\",\")[0] ||\n req.headers.get(\"cf-connecting-ip\") || \"unknown\";\n const endpoint = getEndpoint(req);\n\n await initDB();\n\n // --- GET Routes (Public Discovery) ---\n if (req.method === \"GET\") {\n if (path === \"/\" || path === \"\") return json(await getSystemStatus());\n if (path === \"/status\") return json(await getSystemStatus());\n if (path === \"/register\") return json(getServiceManifest(endpoint));\n if (path === \"/agents\") return json({ agents: getAgentManifest() });\n if (path === \"/adapters\") return json({ adapters: listAdapters() });\n if (path === \"/models\") return json({ models: getModelManifest() });\n if (path === \"/capabilities\") {\n return json({ capabilities: buildCapabilityList() });\n }\n if (path === \"/history\") {\n const limit = parseInt(url.searchParams.get(\"limit\") || \"20\");\n return json({ history: await getHistory(limit) });\n }\n const taskMatch = path.match(/^\\/task\\/(.+)$/);\n if (taskMatch) {\n const task = await getTaskStatus(taskMatch[1]);\n return task\n ? json({ task })\n : json({ status: \"failure\", message: \"Task not found\" }, 404);\n }\n return json({ error: \"Unknown endpoint\" }, 404);\n }\n\n // --- POST Routes ---\n if (req.method !== \"POST\") {\n return json({ error: \"Only GET and POST supported\" }, 405);\n }\n\n let payload: any;\n try {\n payload = await req.json();\n } catch {\n return json({ status: \"failure\", message: \"Invalid JSON body\" }, 400);\n }\n\n // 1. Universal AI Gateway — POST / or /public-task\n // Any external platform (web app, bot, etc.) can POST a work task here.\n // No auth required. The system auto-analyzes, selects the optimal model,\n // and executes with automatic fallback.\n if (path === \"/\" || path === \"\" || path === \"/public-task\") {\n if (isRateLimited(ip)) {\n return json({ status: \"failure\", message: \"Rate limit exceeded\" }, 429);\n }\n\n // No token required — free AI (Pollinations.ai) works out of the box.\n // HF/OpenAI/Groq are optional enhancements if their keys are configured.\n const { task, data } = normalizeRequest(payload);\n const response = await dispatchTask(task, data, \"AUTO\");\n return json(response, response.status === \"success\" ? 200 : 500);\n }\n\n // 2. IAP Handshake (public — no auth needed for discovery)\n if (path === \"/handshake\") {\n if (payload.jsonrpc === \"2.0\" && payload.method === \"handshake\") {\n return json(await processHandshake(payload, endpoint));\n }\n return json({ error: \"Invalid handshake\" }, 400);\n }\n\n // 3. Strict Auth Check for protected POST endpoints\n if (!validateAuth(req)) {\n return json({\n status: \"failure\",\n message: \"Unauthorized — provide valid Bearer token\",\n }, 401);\n }\n\n if (isRateLimited(ip)) {\n return json({ status: \"failure\", message: \"Rate limit exceeded\" }, 429);\n }\n\n // Protected Routes\n if (path === \"/rpc\") {\n const rpcResponse = await processRPC(\n payload as JSONRPCRequest,\n endpoint,\n dispatchTask,\n );\n return json(rpcResponse);\n }\n\n if (path === \"/adapter\") {\n const { adapter, action, data } = payload;\n const result = await callAdapterDirect(\n adapter,\n action || \"default\",\n data || {},\n );\n return json({\n status: result.success ? \"success\" : \"failure\",\n data: result.data,\n });\n }\n\n // Unknown POST path\n return json({ status: \"failure\", message: \"Unknown endpoint\" }, 404);\n}","label",[139],"a6bbeb37-8ec6-48a2-ba82-e57056012174","hf.ts","8d908c30-7945-11f1-a52a-1607ee4eb77e",4,["D",1783347548321],[149],"6c60e76b-9e24-4afe-899a-7c644293c3fb","db.ts","a8be7666-7945-11f1-947a-1607ee4eb77e",6,["D",1783347556657],[155],"754727f1-f2b0-4f8d-8bcb-f2d5b4a419a5","UniversalAdapter.ts","ecd4520c-7946-11f1-a15d-1607ee4eb77e",16,["D",1783348152415],[161],"e8ad083c-29e4-492c-a022-d12bd88722d7",["D",1783355841883],[29],"a4ee25e5-963a-46dc-90be-ce037269e7d7","Supervisor.ts","2ac83bf0-7947-11f1-a5c4-1607ee4eb77e",31,["D",1783348626059],"// Supervisor Agent — Nexuses Core OS V10.0\n// Autonomous error loop: Log → Analyze → Retry → Self-correct.\n// Wraps agent execution with supervision and automatic retry logic.\n\nimport {\n callHFWithFallback,\n classifyTask,\n getHFToken,\n selectModel,\n} from \"./hf.ts\";\nimport type { HFResult, ModelKey, TaskType } from \"./hf.ts\";\nimport { logWorkflowStep } from \"./db.ts\";\n\nexport interface SupervisedResult {\n success: boolean;\n attempts: AttemptLog[];\n finalResult: any;\n retried: boolean;\n selfCorrected: boolean;\n message: string;\n}\n\nexport interface AttemptLog {\n attempt: number;\n model: ModelKey;\n status: \"success\" | \"error\" | \"timeout\";\n error?: string;\n action: string;\n}\n\nconst MAX_RETRIES = 3;\n\n/**\n * Supervises a task execution with automatic error recovery.\n *\n * Flow:\n * 1. Execute the task via the provided executor function.\n * 2. If it fails: log the error, analyze failure context with HF.\n * 3. Retry with a different model or adjusted strategy.\n * 4. Self-correct if possible (modify prompt based on error analysis).\n */\nexport async function supervise(\n taskId: string,\n task: string,\n data: any,\n executor: (task: string, data: any) => Promise,\n): Promise {\n const attempts: AttemptLog[] = [];\n let lastError = \"\";\n let selfCorrected = false;\n\n for (let attempt = 1; attempt <= MAX_RETRIES; attempt++) {\n console.log(\n `[Supervisor] Attempt ${attempt}/${MAX_RETRIES} for task: \"${\n task.slice(0, 80)\n }\"`,\n );\n\n try {\n const result = await executor(task, data);\n\n // Check if execution succeeded\n if (\n result.success || result.status === \"SUCCESS\" ||\n result.status === \"success\"\n ) {\n attempts.push({\n attempt,\n model: result.model || \"N/A\",\n status: \"success\",\n action: \"executed\",\n });\n\n await logWorkflowStep(\n taskId,\n 10 + attempt,\n \"Supervisor\",\n \"SUCCESS\",\n `Attempt ${attempt} succeeded | Model: ${result.model || \"N/A\"}`,\n );\n\n return {\n success: true,\n attempts,\n finalResult: result,\n retried: attempt > 1,\n selfCorrected,\n message: result.message || `Task completed on attempt ${attempt}`,\n };\n }\n\n // Execution returned but with failure status\n lastError = result.error || result.message || \"Unknown error\";\n attempts.push({\n attempt,\n model: result.model || \"N/A\",\n status: \"error\",\n error: lastError,\n action: \"failed\",\n });\n\n console.log(`[Supervisor] Attempt ${attempt} failed: ${lastError}`);\n await logWorkflowStep(\n taskId,\n 10 + attempt,\n \"Supervisor\",\n \"RETRY\",\n `Attempt ${attempt} failed: ${lastError}`,\n );\n\n // If this is the last attempt, don't analyze/retry\n if (attempt >= MAX_RETRIES) break;\n\n // PHASE: Analyze the failure\n const analysis = await analyzeFailure(task, data, lastError, attempt);\n await logWorkflowStep(\n taskId,\n 10 + attempt + 0.5,\n \"Supervisor\",\n \"ANALYZE\",\n `Failure analysis: ${analysis.slice(0, 200)}`,\n );\n\n // PHASE: Self-correct — modify the prompt/data based on analysis\n if (attempt === 1) {\n const corrected = await selfCorrect(task, data, lastError, analysis);\n if (corrected.modified) {\n task = corrected.task;\n data = corrected.data;\n selfCorrected = true;\n console.log(\n `[Supervisor] Self-corrected task prompt based on error analysis`,\n );\n await logWorkflowStep(\n taskId,\n 10 + attempt + 0.6,\n \"Supervisor\",\n \"SELF_CORRECT\",\n `Prompt modified based on failure analysis`,\n );\n }\n }\n\n // PHASE: Retry with different strategy\n // The executor itself already has fallback logic via callHFWithFallback,\n // but we retry the whole execution which may pick a different agent/model\n } catch (e: any) {\n lastError = e.message;\n attempts.push({\n attempt,\n model: \"N/A\",\n status: \"error\",\n error: lastError,\n action: \"exception\",\n });\n\n console.log(`[Supervisor] Attempt ${attempt} threw: ${lastError}`);\n await logWorkflowStep(\n taskId,\n 10 + attempt,\n \"Supervisor\",\n \"ERROR\",\n `Attempt ${attempt} exception: ${lastError}`,\n );\n\n if (attempt >= MAX_RETRIES) break;\n }\n }\n\n // All attempts exhausted\n await logWorkflowStep(\n taskId,\n 19,\n \"Supervisor\",\n \"EXHAUSTED\",\n `All ${MAX_RETRIES} attempts failed. Last error: ${lastError}`,\n );\n\n return {\n success: false,\n attempts,\n finalResult: null,\n retried: attempts.length > 1,\n selfCorrected,\n message: `All ${MAX_RETRIES} attempts failed. Last error: ${lastError}`,\n };\n}\n\n/**\n * Analyzes a failure using HF to understand what went wrong.\n */\nasync function analyzeFailure(\n task: string,\n data: any,\n error: string,\n attempt: number,\n): Promise {\n const token = getHFToken();\n if (!token) {\n return \"No HF token — cannot analyze failure. Will retry with same parameters.\";\n }\n\n const prompt =\n `Analyze why this task execution failed and suggest a fix:\\nTask: ${task}\\nData: ${\n JSON.stringify(data).slice(0, 500)\n }\\nError: ${error}\\nAttempt: ${attempt}`;\n\n const result = await callHFWithFallback(prompt, \"gemma\", {\n maxTokens: 200,\n timeoutMs: 10000,\n });\n return result.success ? result.text : \"Analysis unavailable\";\n}\n\n/**\n * Self-corrects the task prompt or data based on failure analysis.\n * Modifies the prompt to be clearer or adjusts parameters.\n */\nasync function selfCorrect(\n task: string,\n data: any,\n error: string,\n analysis: string,\n): Promise<{ task: string; data: any; modified: boolean }> {\n // No token check needed — free AI works without any token\n // If the error is about missing token or config, don't retry with modified prompt\n if (error.includes(\"not configured\") || error.includes(\"NO_TOKEN\")) {\n return { task, data, modified: false };\n }\n\n // If error is a timeout, simplify the prompt\n if (error.includes(\"Timeout\") || error.includes(\"timeout\")) {\n const simplifiedTask = task.slice(0, 200);\n return {\n task: simplifiedTask,\n data: { ...data, maxTokens: Math.min(data.maxTokens || 500, 200) },\n modified: true,\n };\n }\n\n // If error is HTTP 503 (model loading), the retry will naturally try fallback\n if (error.includes(\"503\") || error.includes(\"loading\")) {\n return { task, data, modified: false };\n }\n\n // For other errors, try rephrasing the task\n const rephrasePrompt =\n `Rephrase this task instruction to be clearer and more specific:\\n\"${task}\"\\n\\nOnly return the rephrased instruction, nothing else.`;\n const result = await callHFWithFallback(rephrasePrompt, \"gemma\", {\n maxTokens: 100,\n timeoutMs: 10000,\n });\n\n if (\n result.success && result.text && result.text.length > 10 &&\n result.text.length < 500\n ) {\n return { task: result.text.trim(), data, modified: true };\n }\n\n return { task, data, modified: false };\n}",[170],"259bb3b9-bf6e-439d-94c2-1a72bb52ba1c","RegistryManager.ts","3cd93402-7947-11f1-82a8-1607ee4eb77e",30,["D",1783348552291],"// Registry Manager — Nexuses Core OS V10.0\n// Central catalog of all capabilities: agents, adapters, models, external services.\n// Used by the IAP discovery protocol and /register endpoint.\n\nimport { getAgentManifest } from \"./AgentManager.ts\";\nimport { listAdapters } from \"./UniversalAdapter.ts\";\nimport {\n classifyTask,\n getHFToken,\n getModelManifest,\n type TaskType,\n} from \"./hf.ts\";\n\nexport interface Capability {\n id: string;\n name: string;\n category: string;\n type: \"agent\" | \"adapter\" | \"model\" | \"external\";\n actions: string[];\n status: \"active\" | \"inactive\" | \"error\";\n description: string;\n}\n\nexport interface ServiceManifest {\n service_id: string;\n service_name: string;\n version: string;\n protocol: string;\n endpoint: string;\n auth: string;\n capabilities: Capability[];\n task_types: TaskType[];\n universal_task_format: object;\n registered_at: string;\n}\n\nconst SERVICE_ID = \"nexuses-core-os-v10\";\nconst SERVICE_NAME = \"Nexuses Core OS\";\nconst VERSION = \"10.0.0\";\nconst PROTOCOL = \"JSON-RPC 2.0 / IAP 1.0\";\n\n// --- External Service Registry (for delegation targets) ---\n\ninterface ExternalService {\n id: string;\n name: string;\n url: string;\n capabilities: string[];\n authHeader?: string;\n status: \"available\" | \"unconfigured\";\n}\n\nconst EXTERNAL_SERVICES: ExternalService[] = [\n {\n id: \"hf-router\",\n name: \"Hugging Face Router (Chat Completions)\",\n url: \"https://router.huggingface.co/v1/chat/completions\",\n capabilities: [\n \"text-generation\",\n \"code-generation\",\n \"creative-writing\",\n \"summarization\",\n ],\n authHeader: \"Authorization: Bearer \",\n status: \"available\",\n },\n {\n id: \"hf-image\",\n name: \"Hugging Face Image Generation\",\n url:\n \"https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0\",\n capabilities: [\"image-generation\", \"text-to-image\"],\n authHeader: \"Authorization: Bearer \",\n status: \"available\",\n },\n {\n id: \"coingecko\",\n name: \"CoinGecko Market Data\",\n url: \"https://api.coingecko.com/api/v3\",\n capabilities: [\"crypto-prices\", \"market-signals\"],\n status: \"available\",\n },\n {\n id: \"duckduckgo\",\n name: \"DuckDuckGo Instant Answers\",\n url: \"https://api.duckduckgo.com\",\n capabilities: [\"web-search\", \"instant-answers\", \"research\"],\n status: \"available\",\n },\n {\n id: \"github\",\n name: \"GitHub API\",\n url: \"https://api.github.com\",\n capabilities: [\"repo-management\", \"issue-tracking\", \"code-search\"],\n authHeader: \"Authorization: Bearer \",\n status: \"available\",\n },\n];\n\n// --- Registry Functions ---\n\nexport function getExternalServices(): ExternalService[] {\n return EXTERNAL_SERVICES;\n}\n\nexport function findExternalService(\n capability: string,\n): ExternalService | null {\n return EXTERNAL_SERVICES.find((s) =>\n s.capabilities.some((c) => c.includes(capability) || capability.includes(c))\n ) || null;\n}\n\n/**\n * Builds the complete capability manifest by combining:\n * - Internal agents (from AgentManager)\n * - Internal adapters (from UniversalAdapter)\n * - Available HF models (from hf.ts)\n * - External services (from this registry)\n */\nexport function buildCapabilityList(): Capability[] {\n const caps: Capability[] = [];\n\n // Agents\n for (const agent of getAgentManifest()) {\n caps.push({\n id: `agent:${agent.name}`,\n name: agent.name,\n category: agent.category,\n type: \"agent\",\n actions: agent.capabilities,\n status: \"active\",\n description: `${agent.category} agent — handles: ${\n agent.capabilities.join(\", \")\n }`,\n });\n }\n\n // Adapters\n for (const adapter of listAdapters()) {\n caps.push({\n id: `adapter:${adapter.name}`,\n name: adapter.name,\n category: adapter.type,\n type: \"adapter\",\n actions: [\"execute\"],\n status: adapter.status as \"active\" | \"inactive\" | \"error\",\n description: adapter.description,\n });\n }\n\n // Models\n for (const model of getModelManifest()) {\n caps.push({\n id: `model:${model.key}`,\n name: model.label,\n category: \"ai-model\",\n type: \"model\",\n actions: model.bestFor,\n status: model.status === \"AVAILABLE\" ? \"active\" : \"inactive\",\n description: `HF model ${model.id} — best for: ${\n model.bestFor.join(\", \")\n }`,\n });\n }\n\n // External services\n for (const svc of EXTERNAL_SERVICES) {\n caps.push({\n id: `external:${svc.id}`,\n name: svc.name,\n category: \"external-service\",\n type: \"external\",\n actions: svc.capabilities,\n status: svc.status === \"available\" ? \"active\" : \"inactive\",\n description: `External service at ${svc.url} — provides: ${\n svc.capabilities.join(\", \")\n }`,\n });\n }\n\n return caps;\n}\n\n/**\n * Returns the full service manifest for /register endpoint.\n * This is what external AI agents consume to discover and use this OS.\n */\nexport function getServiceManifest(endpoint: string): ServiceManifest {\n const token = getHFToken();\n return {\n service_id: SERVICE_ID,\n service_name: SERVICE_NAME,\n version: VERSION,\n protocol: PROTOCOL,\n endpoint,\n auth: \"Bearer token via Authorization header (NEXUSES_API_KEY)\",\n capabilities: buildCapabilityList(),\n task_types: [\"coding\", \"creative\", \"analysis\", \"general\"],\n universal_task_format: {\n request: {\n task: \"string — task description or command\",\n data: \"object — task-specific parameters\",\n mode: \"AUTO | CLI | DELEGATE (optional, default AUTO)\",\n source: \"string — calling agent/service ID (optional, for IAP)\",\n task_id: \"string — external task ID for tracking (optional)\",\n },\n response: {\n status: \"success | failure\",\n task_id: \"string — internal task ID\",\n data: \"object — execution results\",\n message: \"string — human-readable summary\",\n agent: \"string — agent that handled the task\",\n model: \"string — HF model used (if any)\",\n fallbackUsed: \"boolean — whether model fallback was triggered\",\n attempts: \"string[] — models tried in order\",\n delegated: \"boolean — whether sub-tasks were delegated externally\",\n executionTimeMs: \"number — total execution time\",\n timestamp: \"string — ISO 8601 timestamp\",\n },\n },\n registered_at: new Date().toISOString(),\n };\n}\n\nexport function getServiceInfo() {\n return {\n service_id: SERVICE_ID,\n service_name: SERVICE_NAME,\n version: VERSION,\n protocol: PROTOCOL,\n };\n}\n\n/**\n * Checks if a capability exists internally.\n * Returns false if the OS would need to delegate externally.\n */\nexport function hasInternalCapability(\n taskText: string,\n): { has: boolean; taskType: TaskType; matched: Capability[] } {\n const taskType = classifyTask(taskText);\n const caps = buildCapabilityList();\n const lower = taskText.toLowerCase();\n\n const matched = caps.filter((c) =>\n c.actions.some((a) => lower.includes(a.toLowerCase()))\n );\n\n return {\n has: matched.length > 0,\n taskType,\n matched,\n };\n}",[177],"9cd09b82-70bf-4eee-b4be-853204859196","IAP.ts","5e9009c2-7947-11f1-9d3f-1607ee4eb77e",29,["D",1783348487902],"// Inter-Agent Protocol (IAP) — Nexuses Core OS V10.0\n// JSON-RPC 2.0 handshake, capability advertising, and recursive task delegation.\n\nimport {\n findExternalService,\n getServiceInfo,\n getServiceManifest,\n hasInternalCapability,\n} from \"./RegistryManager.ts\";\nimport type { ServiceManifest } from \"./RegistryManager.ts\";\nimport { routeToAdapter, selectBestModel } from \"./UniversalAdapter.ts\";\nimport { logWorkflowStep } from \"./db.ts\";\n\n// --- JSON-RPC 2.0 Types ---\n\nexport interface JSONRPCRequest {\n jsonrpc: \"2.0\";\n method: string;\n params?: any;\n id?: string | number;\n}\n\nexport interface JSONRPCResponse {\n jsonrpc: \"2.0\";\n result?: any;\n error?: { code: number; message: string; data?: any };\n id: string | number | null;\n}\n\nexport interface HandshakeRequest {\n jsonrpc: \"2.0\";\n method: \"handshake\";\n params: {\n agent_id: string;\n agent_name: string;\n capabilities: string[];\n auth_token?: string;\n };\n id: string | number;\n}\n\nexport interface HandshakeResponse {\n jsonrpc: \"2.0\";\n result: {\n accepted: boolean;\n service: {\n service_id: string;\n service_name: string;\n version: string;\n protocol: string;\n };\n our_capabilities: string[];\n task_format: object;\n challenge: string;\n };\n id: string | number;\n}\n\n// --- Error Codes (JSON-RPC 2.0 standard) ---\n\nconst RPC_ERRORS = {\n PARSE_ERROR: { code: -32700, message: \"Parse error\" },\n INVALID_REQUEST: { code: -32600, message: \"Invalid Request\" },\n METHOD_NOT_FOUND: { code: -32601, message: \"Method not found\" },\n INVALID_PARAMS: { code: -32602, message: \"Invalid params\" },\n INTERNAL_ERROR: { code: -32603, message: \"Internal error\" },\n UNAUTHORIZED: {\n code: -32001,\n message: \"Unauthorized — invalid or missing auth token\",\n },\n CAPABILITY_NOT_FOUND: {\n code: -32002,\n message: \"Requested capability not available\",\n },\n DELEGATION_FAILED: { code: -32003, message: \"External delegation failed\" },\n};\n\nfunction rpcError(\n id: string | number | null,\n error: { code: number; message: string; data?: any },\n): JSONRPCResponse {\n return { jsonrpc: \"2.0\", error, id };\n}\n\nfunction rpcResult(id: string | number, result: any): JSONRPCResponse {\n return { jsonrpc: \"2.0\", result, id };\n}\n\n// --- Handshake Protocol ---\n\n/**\n * Processes an incoming handshake from an external AI agent.\n * Advertises our capabilities and returns the Universal Task Format.\n */\nexport async function processHandshake(\n req: HandshakeRequest,\n endpoint: string,\n): Promise {\n const manifest = getServiceManifest(endpoint);\n const ourCaps = manifest.capabilities.map((c) =>\n `${c.id}:${c.actions.join(\",\")}`\n );\n\n console.log(\n `[IAP] Handshake from agent: ${req.params.agent_id} (${req.params.agent_name})`,\n );\n console.log(\n `[IAP] Agent capabilities: ${req.params.capabilities.join(\", \")}`,\n );\n\n // Log the handshake\n await logWorkflowStep(\n `handshake_${Date.now()}`,\n 1,\n \"IAP\",\n \"HANDSHAKE\",\n `Agent: ${req.params.agent_id} | Capabilities: ${\n req.params.capabilities.join(\", \")\n }`,\n );\n\n return {\n jsonrpc: \"2.0\",\n result: {\n accepted: true,\n service: getServiceInfo(),\n our_capabilities: ourCaps,\n task_format: manifest.universal_task_format,\n challenge: `nxs_${Date.now()}_${Math.random().toString(36).slice(2, 12)}`,\n },\n id: req.id,\n };\n}\n\n// --- JSON-RPC Method Router ---\n\n/**\n * Processes a JSON-RPC 2.0 request.\n * Supported methods: handshake, discover, execute, delegate\n */\nexport async function processRPC(\n rpcReq: JSONRPCRequest,\n endpoint: string,\n dispatchFn: (task: string, data: any, mode: string) => Promise,\n): Promise {\n // Validate JSON-RPC structure\n if (rpcReq.jsonrpc !== \"2.0\" || !rpcReq.method) {\n return rpcError(rpcReq.id ?? null, RPC_ERRORS.INVALID_REQUEST);\n }\n\n switch (rpcReq.method) {\n case \"handshake\": {\n const hsReq = rpcReq as HandshakeRequest;\n if (!hsReq.params?.agent_id) {\n return rpcError(rpcReq.id ?? null, RPC_ERRORS.INVALID_PARAMS);\n }\n const result = await processHandshake(hsReq, endpoint);\n return result as unknown as JSONRPCResponse;\n }\n\n case \"discover\": {\n const manifest = getServiceManifest(endpoint);\n return rpcResult(rpcReq.id!, {\n service: getServiceInfo(),\n capabilities: manifest.capabilities,\n task_format: manifest.universal_task_format,\n });\n }\n\n case \"execute\": {\n const { task, data, mode } = rpcReq.params || {};\n if (!task) {\n return rpcError(rpcReq.id ?? null, {\n ...RPC_ERRORS.INVALID_PARAMS,\n data: \"Missing 'task' field\",\n });\n }\n try {\n const result = await dispatchFn(task, data || {}, mode || \"AUTO\");\n return rpcResult(rpcReq.id!, result);\n } catch (e: any) {\n return rpcError(rpcReq.id ?? null, {\n ...RPC_ERRORS.INTERNAL_ERROR,\n data: e.message,\n });\n }\n }\n\n case \"delegate\": {\n const { task, data, target } = rpcReq.params || {};\n if (!task) {\n return rpcError(rpcReq.id ?? null, {\n ...RPC_ERRORS.INVALID_PARAMS,\n data: \"Missing 'task' field\",\n });\n }\n const result = await delegateToExternal(task, data || {}, target);\n if (result.success) {\n return rpcResult(rpcReq.id!, result);\n }\n return rpcError(rpcReq.id ?? null, {\n ...RPC_ERRORS.DELEGATION_FAILED,\n data: result,\n });\n }\n\n default:\n return rpcError(rpcReq.id ?? null, {\n ...RPC_ERRORS.METHOD_NOT_FOUND,\n data: `Unknown method: ${rpcReq.method}`,\n });\n }\n}\n\n// --- Recursive Task Delegation ---\n\nexport interface DelegationResult {\n success: boolean;\n delegated: boolean;\n target: string | null;\n data: any;\n message: string;\n integrated: boolean;\n}\n\n/**\n * Delegates a sub-task to an external AI service when the OS lacks\n * the internal capability. Integrates the result back for the final JSON.\n */\nexport async function delegateToExternal(\n task: string,\n data: any,\n targetHint?: string,\n): Promise {\n // Find an external service that can handle this\n let service = targetHint ? findExternalService(targetHint) : null;\n if (!service) {\n const check = hasInternalCapability(task);\n // Try to find external service matching the task type\n service = findExternalService(check.taskType) ||\n findExternalService(task.toLowerCase());\n }\n\n if (!service) {\n return {\n success: false,\n delegated: false,\n target: null,\n data: {},\n message: \"No external service available for this capability\",\n integrated: false,\n };\n }\n\n console.log(\n `[IAP] Delegating to external service: ${service.name} (${service.url})`,\n );\n\n // Build the delegation request\n // Try free AI first if no token-based service is available\n const hfKey = Deno.env.get(\"HF_API_KEY\") || Deno.env.get(\"HUGGING_FACE_TOKEN\");\n if (!hfKey && service.id.startsWith(\"hf\")) {\n // No HF token — use free AI for delegation instead\n const freeResult = await routeToAdapter(\"freeai\", \"generate\", {\n prompt: data.prompt || task,\n maxTokens: 500,\n timeoutMs: 25000,\n });\n if (freeResult.success && freeResult.data?.response) {\n await logWorkflowStep(\n `delegation_${Date.now()}`,\n 1,\n \"IAP\",\n \"DELEGATE\",\n `Task: \"${task}\" → Free AI → Success`,\n );\n return {\n success: true,\n delegated: true,\n target: \"freeai\",\n data: { generated_text: freeResult.data.response },\n message: \"Delegated to Free AI (no token needed) and integrated result\",\n integrated: true,\n };\n }\n }\n\n const token = service.authHeader?.includes(\"HF_API_KEY\")\n ? hfKey\n : service.authHeader?.includes(\"GITHUB_TOKEN\")\n ? Deno.env.get(\"GITHUB_TOKEN\")\n : null;\n\n try {\n let resultData: any;\n\n if (service.id.startsWith(\"hf\")) {\n // Hugging Face delegation via new Router endpoint (chat completions)\n const hfKey = Deno.env.get(\"HF_API_KEY\") || token;\n const res = await fetch(\n \"https://router.huggingface.co/v1/chat/completions\",\n {\n method: \"POST\",\n headers: {\n \"Authorization\": `Bearer ${hfKey}`,\n \"Content-Type\": \"application/json\",\n },\n body: JSON.stringify({\n model: selectBestModel(data.prompt || task),\n messages: [{ role: \"user\", content: data.prompt || task }],\n max_tokens: 500,\n }),\n signal: AbortSignal.timeout(25000),\n },\n );\n if (!res.ok) {\n return {\n success: false,\n delegated: true,\n target: service.id,\n data: {},\n message: `External service returned HTTP ${res.status}`,\n integrated: false,\n };\n }\n const hfData = await res.json();\n resultData = hfData.choices?.[0]?.message?.content\n ? { generated_text: hfData.choices[0].message.content }\n : hfData;\n } else {\n // Generic external API call\n const res = await fetch(service.url, {\n signal: AbortSignal.timeout(15000),\n });\n resultData = await res.json();\n }\n\n // Log the delegation\n await logWorkflowStep(\n `delegation_${Date.now()}`,\n 1,\n \"IAP\",\n \"DELEGATE\",\n `Task: \"${task}\" → Service: ${service.id} → Success`,\n );\n\n return {\n success: true,\n delegated: true,\n target: service.id,\n data: resultData,\n message: `Delegated to ${service.name} and integrated result`,\n integrated: true,\n };\n } catch (e: any) {\n console.log(`[IAP] Delegation failed: ${e.message}`);\n return {\n success: false,\n delegated: true,\n target: service.id,\n data: {},\n message: `Delegation error: ${e.message}`,\n integrated: false,\n };\n }\n}",[184],"3fc99152-68ef-4298-b113-837e6542dffe","AgentManager.ts","6b3026f8-7947-11f1-82a8-1607ee4eb77e",28,["D",1783348386548],3,"// Agent Swarm — Nexuses Core OS V10.0\n// All agents use callHFWithFallback (HF Router with auto model selection via selectBestModel()).\nimport {\n callHFWithFallback,\n classifyTask,\n getHFToken,\n getSelectionInfo,\n} from \"./hf.ts\";\nimport type { HFResult, ModelKey, TaskType } from \"./hf.ts\";\nimport { listAdapters, routeToAdapter } from \"./UniversalAdapter.ts\";\n\nexport interface AgentResult {\n agent: string;\n category: string;\n status: \"SUCCESS\" | \"ERROR\" | \"PARTIAL\";\n message: string;\n data: any;\n model?: ModelKey;\n modelId?: string;\n taskType?: TaskType;\n fallbackUsed?: boolean;\n attempts?: ModelKey[];\n adapters?: string[];\n}\n\nexport interface AgentManifestEntry {\n name: string;\n category: string;\n keywords: string[];\n capabilities: string[];\n model: ModelKey;\n adapters: string[];\n}\n\n// --- Agent Registry ---\n\nexport const AGENT_REGISTRY: AgentManifestEntry[] = [\n {\n name: \"DevOpsCodingAgent\",\n category: \"DevOps/Coding\",\n keywords: [\n \"code\",\n \"coding\",\n \"debug\",\n \"bug\",\n \"fix\",\n \"github\",\n \"repo\",\n \"program\",\n \"vscode\",\n \"vs code\",\n \"commit\",\n \"deploy\",\n \"devops\",\n \"refactor\",\n \"compile\",\n \"syntax\",\n \"error\",\n ],\n capabilities: [\n \"VS Code integration\",\n \"GitHub repo management\",\n \"Error finding & fixing\",\n \"Bug resolution\",\n \"Auto-writing code\",\n \"Code explanation\",\n ],\n model: \"qwen_coder\",\n adapters: [\"github\"],\n },\n {\n name: \"WebContentAgent\",\n category: \"Web/Content\",\n keywords: [\n \"write\",\n \"blog\",\n \"content\",\n \"article\",\n \"social\",\n \"post\",\n \"website\",\n \"clone\",\n \"scrape\",\n \"web\",\n \"voice\",\n \"html\",\n \"css\",\n \"landing\",\n \"seo\",\n \"tweet\",\n \"facebook\",\n \"media\",\n ],\n capabilities: [\n \"Web automation\",\n \"Website cloning\",\n \"Social media posting\",\n \"Content writing\",\n \"Blogging\",\n \"Voice-enabled website generation\",\n ],\n model: \"llama\",\n adapters: [\"webscraper\", \"duckduckgo\"],\n },\n {\n name: \"DataAutomationAgent\",\n category: \"Data/Automation\",\n keywords: [\n \"data\",\n \"scrape\",\n \"analyze\",\n \"pdf\",\n \"excel\",\n \"word\",\n \"billing\",\n \"invoice\",\n \"entry\",\n \"scan\",\n \"spreadsheet\",\n \"csv\",\n \"report\",\n \"automation\",\n \"crypto\",\n \"price\",\n \"market\",\n ],\n capabilities: [\n \"Data scraping & analysis\",\n \"PDF conversion/creation\",\n \"Billing/data entry\",\n \"MS Word/Excel automation\",\n \"Document scanning\",\n ],\n model: \"phi3\",\n adapters: [\"coingecko\", \"duckduckgo\", \"webscraper\"],\n },\n {\n name: \"MultimediaAgent\",\n category: \"Multimedia\",\n keywords: [\n \"image\",\n \"video\",\n \"generate\",\n \"picture\",\n \"photo\",\n \"draw\",\n \"art\",\n \"design\",\n \"logo\",\n \"render\",\n \"media\",\n \"visual\",\n \"stable diffusion\",\n \"dalle\",\n \"midjourney\",\n ],\n capabilities: [\n \"Image generation\",\n \"Video generation guidance\",\n \"Visual design\",\n \"Art creation\",\n \"Logo design\",\n ],\n model: \"gemma\",\n adapters: [],\n },\n {\n name: \"OfficeDataAgent\",\n category: \"Office/Data\",\n keywords: [\n \"pdf\",\n \"word\",\n \"excel\",\n \"spreadsheet\",\n \"invoice\",\n \"billing\",\n \"document\",\n \"report\",\n \"csv\",\n \"word doc\",\n \"ms word\",\n \"ms excel\",\n \"office\",\n \"data entry\",\n \"scan\",\n ],\n capabilities: [\n \"PDF creation\",\n \"MS Word/Excel automation\",\n \"Invoice/billing generation\",\n \"Data entry\",\n \"Document formatting\",\n ],\n model: \"phi3\",\n adapters: [],\n },\n {\n name: \"GeneralHandler\",\n category: \"General\",\n keywords: [\n \"general\",\n \"help\",\n \"unknown\",\n \"test\",\n \"explain\",\n \"reasoning\",\n \"question\",\n \"chat\",\n ],\n capabilities: [\"General task handling\", \"Fallback routing\"],\n model: \"gemma\",\n adapters: [],\n },\n];\n\nexport function getAgentManifest() {\n return AGENT_REGISTRY;\n}\n\nfunction matchAgent(task: string): AgentManifestEntry {\n const cmd = task.toLowerCase();\n let best: AgentManifestEntry | null = null;\n let bestScore = 0;\n for (const agent of AGENT_REGISTRY) {\n const score = agent.keywords.filter((k) => cmd.includes(k)).length;\n if (score > bestScore) {\n bestScore = score;\n best = agent;\n }\n }\n return best || AGENT_REGISTRY[AGENT_REGISTRY.length - 1];\n}\n\n/**\n * Builds an AgentResult from an HFResult, including fallback metadata.\n */\nfunction buildAgentResult(\n agentName: string,\n category: string,\n hfResult: HFResult,\n message: string,\n data: any,\n adapters: string[] = [],\n): AgentResult {\n const fallbackUsed = (hfResult.attempts?.length ?? 1) > 1 && hfResult.success;\n return {\n agent: agentName,\n category,\n status: hfResult.success ? \"SUCCESS\" : \"ERROR\",\n message: hfResult.success ? message : hfResult.error || \"HF model error\",\n data,\n model: hfResult.model,\n modelId: hfResult.modelId,\n taskType: hfResult.taskType,\n fallbackUsed,\n attempts: hfResult.attempts,\n adapters,\n };\n}\n\n// --- Agent Execution Functions ---\n\nconst AGENT_MAP: Record<\n string,\n (task: string, data: any) => Promise\n> = {};\n\n// 1. DevOps / Coding Agent — uses Qwen2.5-Coder with fallback to Gemma\nAGENT_MAP[\"DevOpsCodingAgent\"] = async (task: string, data: any) => {\n const prompt = data.prompt || data.code || task;\n const action = data.action || \"analyze\";\n\n // GitHub operations via Universal Adapter\n if (data.github) {\n const ghResult = await routeToAdapter(\n \"github\",\n data.github.action || \"get_repo\",\n data.github,\n );\n if (ghResult.success) {\n const hfResult = await callHFWithFallback(\n `Analyze this GitHub data and provide insights: ${\n JSON.stringify(ghResult.data).slice(0, 1000)\n }`,\n \"qwen_coder\",\n { maxTokens: 500 },\n );\n return {\n agent: \"DevOpsCodingAgent\",\n category: \"DevOps/Coding\",\n status: hfResult.success ? \"SUCCESS\" : \"PARTIAL\",\n message: `GitHub ${data.github.action || \"operation\"} completed${\n hfResult.success ? \" + AI analysis\" : \"\"\n }`,\n data: {\n github: ghResult.data,\n analysis: hfResult.text || hfResult.error,\n },\n model: hfResult.model,\n modelId: hfResult.modelId,\n taskType: hfResult.taskType,\n fallbackUsed: (hfResult.attempts?.length ?? 1) > 1 && hfResult.success,\n attempts: hfResult.attempts,\n adapters: [\"github\"],\n };\n }\n return {\n agent: \"DevOpsCodingAgent\",\n category: \"DevOps/Coding\",\n status: \"ERROR\",\n message: ghResult.message,\n data: {},\n adapters: [\"github\"],\n };\n }\n\n // Code analysis / bug fixing / code writing\n const codePrompt = action === \"fix\"\n ? `Find and fix the bug in this code:\\n${prompt}`\n : action === \"explain\"\n ? `Explain this code:\\n${prompt}`\n : action === \"write\"\n ? `Write code for: ${prompt}`\n : `Analyze this code for errors and improvements:\\n${prompt}`;\n\n const hfResult = await callHFWithFallback(codePrompt, \"qwen_coder\", {\n maxTokens: 800,\n temperature: 0.3,\n });\n\n return buildAgentResult(\n \"DevOpsCodingAgent\",\n \"DevOps/Coding\",\n hfResult,\n `Code ${action} completed using ${HF_LABEL(hfResult.model)}`,\n { action, input: prompt.slice(0, 500), output: hfResult.text },\n );\n};\n\n// 2. Web / Content Agent — uses Llama 3 with fallback to Gemma\nAGENT_MAP[\"WebContentAgent\"] = async (task: string, data: any) => {\n const prompt = data.prompt || task;\n const action = data.action || \"write\";\n\n // Website cloning / scraping\n if (data.url || action === \"scrape\" || action === \"clone\") {\n const scrapeResult = await routeToAdapter(\"webscraper\", \"scrape\", {\n url: data.url,\n });\n if (scrapeResult.success && action === \"clone\") {\n const hfResult = await callHFWithFallback(\n `Create a simple HTML page based on this scraped content:\\nTitle: ${scrapeResult.data.title}\\nContent: ${\n scrapeResult.data.textContent?.slice(0, 800)\n }`,\n \"llama\",\n { maxTokens: 800 },\n );\n return {\n agent: \"WebContentAgent\",\n category: \"Web/Content\",\n status: hfResult.success ? \"SUCCESS\" : \"PARTIAL\",\n message: `Website cloned: ${scrapeResult.data.title}`,\n data: {\n original: { url: data.url, title: scrapeResult.data.title },\n clone: hfResult.text || \"\",\n links: scrapeResult.data.links,\n },\n model: hfResult.model,\n modelId: hfResult.modelId,\n taskType: hfResult.taskType,\n fallbackUsed: (hfResult.attempts?.length ?? 1) > 1 && hfResult.success,\n attempts: hfResult.attempts,\n adapters: [\"webscraper\"],\n };\n }\n if (scrapeResult.success) {\n return {\n agent: \"WebContentAgent\",\n category: \"Web/Content\",\n status: \"SUCCESS\",\n message: `Scraped: ${scrapeResult.data.title}`,\n data: scrapeResult.data,\n adapters: [\"webscraper\"],\n };\n }\n }\n\n // Content writing / blogging / social media\n const contentPrompt = action === \"social\"\n ? `Write a social media post about: ${prompt}`\n : action === \"blog\"\n ? `Write a blog post about: ${prompt}`\n : action === \"voice\"\n ? `Generate voice-ready website content for: ${prompt}`\n : `Write content about: ${prompt}`;\n\n const hfResult = await callHFWithFallback(contentPrompt, \"llama\", {\n maxTokens: 1000,\n temperature: 0.8,\n });\n\n return buildAgentResult(\n \"WebContentAgent\",\n \"Web/Content\",\n hfResult,\n `Content generated using ${HF_LABEL(hfResult.model)}`,\n { action, content: hfResult.text },\n );\n};\n\n// 3. Data / Automation Agent — uses Phi-3 with fallback to Gemma\nAGENT_MAP[\"DataAutomationAgent\"] = async (task: string, data: any) => {\n const prompt = data.prompt || task;\n const action = data.action || \"analyze\";\n\n // Crypto signals (no HF needed — direct adapter)\n if (\n action === \"crypto\" || prompt.toLowerCase().includes(\"crypto\") ||\n prompt.toLowerCase().includes(\"price\")\n ) {\n const cgResult = await routeToAdapter(\"coingecko\", \"price\", {\n coins: data.coins,\n });\n if (cgResult.success) {\n return {\n agent: \"DataAutomationAgent\",\n category: \"Data/Automation\",\n status: \"SUCCESS\",\n message: \"Crypto signals generated\",\n data: cgResult.data,\n adapters: [\"coingecko\"],\n };\n }\n }\n\n // Data scraping + analysis\n if (data.url || action === \"scrape\") {\n const scrapeResult = await routeToAdapter(\"webscraper\", \"scrape\", {\n url: data.url,\n });\n if (scrapeResult.success) {\n const hfResult = await callHFWithFallback(\n `Analyze this scraped data and provide a summary:\\n${\n scrapeResult.data.textContent?.slice(0, 1000)\n }`,\n \"phi3\",\n { maxTokens: 400 },\n );\n return {\n agent: \"DataAutomationAgent\",\n category: \"Data/Automation\",\n status: hfResult.success ? \"SUCCESS\" : \"PARTIAL\",\n message: \"Data scraped and analyzed\",\n data: {\n source: data.url,\n title: scrapeResult.data.title,\n analysis: hfResult.text || \"Analysis unavailable\",\n raw: scrapeResult.data,\n },\n model: hfResult.model,\n modelId: hfResult.modelId,\n taskType: hfResult.taskType,\n fallbackUsed: (hfResult.attempts?.length ?? 1) > 1 && hfResult.success,\n attempts: hfResult.attempts,\n adapters: [\"webscraper\"],\n };\n }\n }\n\n // Research via DuckDuckGo + HF summarization\n if (action === \"research\" || action === \"search\") {\n const ddgResult = await routeToAdapter(\"duckduckgo\", \"search\", {\n query: prompt,\n });\n if (ddgResult.success) {\n const hfResult = await callHFWithFallback(\n `Summarize this research data:\\n${\n JSON.stringify(ddgResult.data).slice(0, 800)\n }`,\n \"phi3\",\n { maxTokens: 400 },\n );\n return {\n agent: \"DataAutomationAgent\",\n category: \"Data/Automation\",\n status: hfResult.success ? \"SUCCESS\" : \"PARTIAL\",\n message: \"Research completed and summarized\",\n data: {\n search: ddgResult.data,\n summary: hfResult.text || \"\",\n },\n model: hfResult.model,\n modelId: hfResult.modelId,\n taskType: hfResult.taskType,\n fallbackUsed: (hfResult.attempts?.length ?? 1) > 1 && hfResult.success,\n attempts: hfResult.attempts,\n adapters: [\"duckduckgo\"],\n };\n }\n }\n\n // General data analysis\n const hfResult = await callHFWithFallback(\n `Analyze and process: ${prompt}`,\n \"phi3\",\n { maxTokens: 500, temperature: 0.5 },\n );\n\n return buildAgentResult(\n \"DataAutomationAgent\",\n \"Data/Automation\",\n hfResult,\n \"Data analysis completed\",\n { action, result: hfResult.text },\n );\n};\n\n// 4. Multimedia Agent — image/video generation via HF + text guidance\nAGENT_MAP[\"MultimediaAgent\"] = async (task: string, data: any) => {\n const prompt = data.prompt || task;\n const action = data.action || \"image\";\n\n if (action === \"image\") {\n // Attempt HF image generation (Stable Diffusion)\n const token = getHFToken();\n if (!token) {\n // Fallback: generate a descriptive text prompt that can be used externally\n const hfResult = await callHFWithFallback(\n `Generate a detailed image generation prompt for: ${prompt}. Include style, composition, and lighting details.`,\n \"gemma\",\n { maxTokens: 300 },\n );\n return buildAgentResult(\n \"MultimediaAgent\",\n \"Multimedia\",\n hfResult,\n \"Image prompt generated (HF_API_KEY needed for actual image generation)\",\n {\n action,\n prompt,\n imagePrompt: hfResult.text,\n note: \"Use this prompt with any text-to-image service\",\n },\n );\n }\n try {\n // Image generation still uses HF Inference API (router is chat-only)\n const res = await fetch(\n \"https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0\",\n {\n method: \"POST\",\n headers: {\n \"Authorization\": `Bearer ${token}`,\n \"Content-Type\": \"application/json\",\n },\n body: JSON.stringify({ inputs: prompt }),\n signal: AbortSignal.timeout(30000),\n },\n );\n if (res.ok) {\n const imageBlob = await res.blob();\n return {\n agent: \"MultimediaAgent\",\n category: \"Multimedia\",\n status: \"SUCCESS\",\n message: `Image generated for: ${prompt.slice(0, 80)}`,\n data: {\n action,\n prompt,\n imageGenerated: true,\n sizeBytes: imageBlob.size,\n mimeType: imageBlob.type,\n },\n model: \"gemma\" as ModelKey,\n adapters: [],\n };\n }\n // If image model fails, generate text prompt as fallback\n const hfResult = await callHFWithFallback(\n `Generate a detailed image generation prompt for: ${prompt}`,\n \"gemma\",\n { maxTokens: 300 },\n );\n return buildAgentResult(\n \"MultimediaAgent\",\n \"Multimedia\",\n hfResult,\n `Image model unavailable (HTTP ${res.status}), generated prompt instead`,\n { action, prompt, imagePrompt: hfResult.text, fallback: true },\n );\n } catch (e: any) {\n const hfResult = await callHFWithFallback(\n `Describe how to create: ${prompt}. Include visual details.`,\n \"gemma\",\n { maxTokens: 300 },\n );\n return buildAgentResult(\n \"MultimediaAgent\",\n \"Multimedia\",\n hfResult,\n `Image generation error: ${e.message}. Generated description instead.`,\n { action, prompt, description: hfResult.text, error: e.message },\n );\n }\n }\n\n // Video generation guidance\n const hfResult = await callHFWithFallback(\n `Provide guidance and a creative plan for: ${prompt}. Include scene descriptions and technical details.`,\n \"gemma\",\n { maxTokens: 500 },\n );\n return buildAgentResult(\n \"MultimediaAgent\",\n \"Multimedia\",\n hfResult,\n \"Multimedia guidance generated\",\n { action, prompt, guidance: hfResult.text },\n );\n};\n\n// 5. Office / Data Agent — PDF, Word, Excel, invoices, documents\nAGENT_MAP[\"OfficeDataAgent\"] = async (task: string, data: any) => {\n const prompt = data.prompt || task;\n const action = data.action || \"document\";\n\n // Invoice/billing generation\n if (action === \"invoice\" || prompt.toLowerCase().includes(\"invoice\")) {\n const hfResult = await callHFWithFallback(\n `Generate a professional invoice template in JSON format with these details: ${prompt}\\nInclude fields: invoiceNumber, date, billTo, items[], subtotal, tax, total.`,\n \"phi3\",\n { maxTokens: 500, temperature: 0.3 },\n );\n return buildAgentResult(\n \"OfficeDataAgent\",\n \"Office/Data\",\n hfResult,\n \"Invoice generated\",\n { action: \"invoice\", prompt, invoice: hfResult.text },\n );\n }\n\n // PDF / document structure generation\n if (action === \"pdf\" || prompt.toLowerCase().includes(\"pdf\")) {\n const hfResult = await callHFWithFallback(\n `Create a structured document outline for: ${prompt}. Include sections, headings, and key content points.`,\n \"phi3\",\n { maxTokens: 500 },\n );\n return buildAgentResult(\n \"OfficeDataAgent\",\n \"Office/Data\",\n hfResult,\n \"Document structure generated\",\n {\n action: \"pdf\",\n prompt,\n document: hfResult.text,\n note: \"Structure ready for PDF conversion\",\n },\n );\n }\n\n // Excel/CSV data generation\n if (\n action === \"excel\" || action === \"csv\" ||\n prompt.toLowerCase().includes(\"excel\") ||\n prompt.toLowerCase().includes(\"csv\")\n ) {\n const hfResult = await callHFWithFallback(\n `Generate tabular data in CSV format for: ${prompt}. Include headers and sample rows.`,\n \"phi3\",\n { maxTokens: 400, temperature: 0.3 },\n );\n return buildAgentResult(\n \"OfficeDataAgent\",\n \"Office/Data\",\n hfResult,\n \"Spreadsheet data generated\",\n { action: action, prompt, csv: hfResult.text },\n );\n }\n\n // General document/report generation\n const hfResult = await callHFWithFallback(\n `Create a professional document for: ${prompt}`,\n \"phi3\",\n { maxTokens: 500 },\n );\n return buildAgentResult(\n \"OfficeDataAgent\",\n \"Office/Data\",\n hfResult,\n \"Document generated\",\n { action, prompt, document: hfResult.text },\n );\n};\n\n// 6. General Handler — uses Gemma (no further fallback)\nAGENT_MAP[\"GeneralHandler\"] = async (task: string, data: any) => {\n const hfResult = await callHFWithFallback(data.prompt || task, \"gemma\", {\n maxTokens: 500,\n });\n\n return buildAgentResult(\n \"GeneralHandler\",\n \"General\",\n hfResult,\n \"Task processed\",\n { input: task, response: hfResult.text || \"\" },\n );\n};\n\n// --- Helpers ---\n\nfunction HF_LABEL(key: ModelKey): string {\n const labels: Record = {\n qwen_coder: \"Qwen2.5-Coder\",\n llama: \"Llama 3\",\n phi3: \"Phi-3 Mini\",\n gemma: \"Gemma 2 2B\",\n };\n return labels[key] || key;\n}\n\n// --- Public Routing API ---\n\nexport async function routeIncomingTask(\n task: string,\n data: any = {},\n mode = \"AUTO\",\n debug = false,\n): Promise {\n const agentEntry = matchAgent(task);\n const agentFn = AGENT_MAP[agentEntry.name] || AGENT_MAP[\"GeneralHandler\"];\n\n try {\n const result = await agentFn(task, data);\n if (debug) {\n console.log(\n `[Dispatcher] Task: \"${task}\" → Agent: ${result.agent} → Model: ${\n result.model || \"N/A\"\n } → Status: ${result.status}${\n result.fallbackUsed ? \" (FALLBACK)\" : \"\"\n }`,\n );\n }\n return result;\n } catch (e: any) {\n return {\n agent: agentEntry.name,\n category: agentEntry.category,\n status: \"ERROR\",\n message: `Agent execution error: ${e.message}`,\n data: {},\n };\n }\n}\n\nexport function getSystemInfo() {\n const token = getHFToken();\n return {\n agents: AGENT_REGISTRY.map((a) => ({\n name: a.name,\n category: a.category,\n capabilities: a.capabilities,\n model: a.model,\n })),\n adapters: listAdapters(),\n ai: `Free AI (Pollinations.ai): ALWAYS AVAILABLE | OpenAI: ${Deno.env.get(\"OPENAI_API_KEY\") ? \"ACTIVE\" : \"not configured\"} | HF Router: ${token ? \"ACTIVE\" : \"not configured\"} | Groq: ${Deno.env.get(\"GROQ_API_KEY\") ? \"ACTIVE\" : \"not configured\"}`,\n };\n}",[191],"pulls","branches","forks","envVars",{"_205":62,"_207":62},"connections",{"_205":62,"_206":62},"count","unfilledCount","emptyCount",{"_44":190,"_33":191,"_31":192,"_140":-5,"_42":43,"_41":193,"_142":27,"_39":242,"_13":195,"_34":35,"_36":196,"_24":27,"_146":-5,"_218":243,"_28":244},{"_44":183,"_33":184,"_31":185,"_140":-5,"_42":43,"_41":186,"_142":27,"_39":239,"_13":141,"_34":35,"_36":188,"_24":27,"_146":-5,"_218":240,"_28":241},{"_44":176,"_33":177,"_31":178,"_140":-5,"_42":43,"_41":179,"_142":27,"_39":236,"_13":141,"_34":35,"_36":181,"_24":27,"_146":-5,"_218":237,"_28":238},{"_44":169,"_33":170,"_31":171,"_140":-5,"_42":43,"_41":172,"_142":27,"_39":233,"_13":141,"_34":35,"_36":174,"_24":27,"_146":-5,"_218":234,"_28":235},{"_44":166,"_33":29,"_31":32,"_140":-5,"_42":43,"_41":14,"_142":27,"_39":230,"_13":141,"_34":35,"_36":38,"_24":27,"_146":-5,"_218":231,"_28":232},{"_44":160,"_33":161,"_31":162,"_140":-5,"_42":43,"_41":163,"_142":27,"_39":227,"_13":144,"_34":35,"_36":37,"_24":27,"_146":-5,"_218":228,"_28":229},{"_44":154,"_33":155,"_31":156,"_140":-5,"_42":43,"_41":157,"_142":27,"_39":224,"_13":144,"_34":35,"_36":37,"_24":27,"_146":-5,"_218":225,"_28":226},{"_44":148,"_33":149,"_31":150,"_140":-5,"_42":43,"_41":151,"_142":27,"_39":221,"_13":144,"_34":35,"_36":37,"_24":27,"_146":-5,"_218":222,"_28":223},{"_44":138,"_33":139,"_31":57,"_140":-5,"_42":43,"_41":141,"_142":27,"_39":217,"_13":144,"_34":35,"_36":145,"_24":27,"_146":-5,"_218":219,"_28":220},["D",1783347493408],"children",[],[139],["D",1783347548321],[],[149],["D",1783347556657],[],[155],["D",1783348152415],[],[161],["D",1783355841883],[],[29],["D",1783348626059],[],[170],["D",1783348552291],[],[177],["D",1783348487902],[],[184],["D",1783348386548],[],[191],["D",1783347377247],["D",1789522836959],{"_99":98,"_107":103},{"_99":98,"_100":101,"_102":103,"_18":55,"_104":105,"_106":27},{"_13":88,"_33":89,"_44":43,"_90":45,"_91":-5,"_92":-5,"_93":-5,"_94":-5,"_95":-5,"_96":46,"_97":98},"ctx",{"_81":-5,"_126":283,"_284":285,"_286":287,"_288":27,"_289":27,"_290":27,"_291":25,"_292":-5,"_293":-7,"_294":-7,"_295":62,"_296":27,"_297":27,"_298":-5,"_299":27,"_300":27,"_301":27,"_302":-5},"ENV",{"_254":255,"_256":257,"_258":89,"_259":260,"_261":262,"_263":264,"_265":266,"_267":268,"_269":270,"_271":272,"_273":274,"_275":276,"_277":278,"_279":280,"_281":282},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","e87eb04e707cf64e7e532c8e8ec395f209e17f15","RENDER_GIT_BRANCH","POSTHOG_API_TOKEN","phc_nmoyuAkStEZuUp69rYlg1DZgrIt19Gx0Y4Hwf8tGgJP","POSTHOG_API_HOST","https://wart.val.town","WEB_API_TEMPLATE","https://{val}.web.val.run","APP_URL","https://www.val.town","MODULE_URL","https://esm.town","VANITY_WEB_API_TEMPLATE","https://{label}.val.run/","DENOLS_URL","https://lsp.val.town","NODE_ENV","production","CLOUDFLARE_TURNSTILE_SITE_KEY","0x4AAAAAACtaIZJH7s9rBMZ6","GOOGLE_CLIENT_ID","875989696899-jtsqkhlbdv5jrlsk8631p7ipjg3c6o62.apps.googleusercontent.com","STRIPE_PUBLISHABLE_KEY","pk_live_51N2zvWEpZTTLipIkVEwXrUG9AT0yeOOEYxszarZT1jpsZV58Ly6wlg3SltZpHN26CUalOBmUSY7adQRQiSkCZz2500qSXNkf8Y","API_URL","https://api.val.town",[],"preferencesKeybindings","default","preferencesTheme","light","preferencesFixers","preferencesCopilot","preferencesSelectionAi","preferencesCloseBrackets","preferencesChatPanelState","preferencesDprint","preferencesDenofmt","notificationCount","flagDenols","isBusinessOrgMember","businessOrgHandle","isBusinessOrgAdmin","isHigherTownieTier","navCollapsed","currentOrgId"]

Diff · v32