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Free-tier optimized.\n\nexport type ModelKey = \"mistral\" | \"qwen\" | \"llama\" | \"phi3\";\n\ninterface ModelConfig {\n id: string;\n label: string;\n bestFor: string[];\n maxTokens: number;\n temperature: number;\n}\n\nexport const HF_MODELS: Record = {\n mistral: {\n id: \"mistralai/Mistral-7B-Instruct-v0.2\",\n label: \"Mistral 7B Instruct\",\n bestFor: [\"general\", \"reasoning\", \"chat\", \"analysis\"],\n maxTokens: 500,\n temperature: 0.7,\n },\n qwen: {\n id: \"Qwen/Qwen2-7B-Instruct\",\n label: \"Qwen2 7B Instruct\",\n bestFor: [\"code\", \"coding\", \"programming\", \"technical\", \"translate\"],\n maxTokens: 800,\n temperature: 0.3,\n },\n llama: {\n id: \"meta-llama/Meta-Llama-3-8B-Instruct\",\n label: \"Llama 3 8B Instruct\",\n bestFor: [\"creative\", \"writing\", \"content\", \"blog\", \"story\"],\n maxTokens: 1000,\n temperature: 0.8,\n },\n phi3: {\n id: \"microsoft/Phi-3-mini-4k-instruct\",\n label: \"Phi-3 Mini 4K\",\n bestFor: [\"fast\", \"simple\", \"summarize\", \"extract\", \"data\"],\n maxTokens: 400,\n temperature: 0.5,\n },\n};\n\nfunction getEnv(key: string): string | undefined {\n try {\n return Deno.env.get(key);\n } catch {\n return undefined;\n }\n}\n\nexport function getHFToken(): string | null {\n return getEnv(\"HF_API_KEY\") || getEnv(\"HUGGING_FACE_TOKEN\") || null;\n}\n\n/**\n * Dynamically selects the best HF model for the given task text.\n * Falls back to mistral for unrecognized types.\n */\nexport function selectModel(taskText: string): ModelKey {\n const lower = taskText.toLowerCase();\n // Check each model's specialties\n for (const [key, cfg] of Object.entries(HF_MODELS)) {\n if (cfg.bestFor.some((tag) => lower.includes(tag))) {\n return key as ModelKey;\n }\n }\n // Heuristic fallbacks\n if (lower.includes(\"code\") || lower.includes(\"debug\") || lower.includes(\"fix\")) {\n return \"qwen\";\n }\n if (lower.includes(\"write\") || lower.includes(\"blog\") || lower.includes(\"article\")) {\n return \"llama\";\n }\n if (lower.includes(\"summary\") || lower.includes(\"extract\") || lower.includes(\"data\")) {\n return \"phi3\";\n }\n return \"mistral\";\n}\n\nexport interface HFResult {\n success: boolean;\n model: ModelKey;\n modelId: string;\n text: string;\n error?: string;\n}\n\n/**\n * Calls Hugging Face inference API with the selected (or specified) model.\n */\nexport async function callHF(\n prompt: string,\n model?: ModelKey,\n maxTokens?: number,\n temperature?: number,\n): Promise {\n const modelKey = model || selectModel(prompt);\n const cfg = HF_MODELS[modelKey];\n const token = getHFToken();\n\n if (!token) {\n return {\n success: false,\n model: modelKey,\n modelId: cfg.id,\n text: \"\",\n error: \"HF_API_KEY not configured. Set it in environment variables.\",\n };\n }\n\n try {\n const res = await fetch(\n `https://api-inference.huggingface.co/models/${cfg.id}`,\n {\n method: \"POST\",\n headers: {\n \"Authorization\": `Bearer ${token}`,\n \"Content-Type\": \"application/json\",\n },\n body: JSON.stringify({\n inputs: prompt,\n parameters: {\n max_new_tokens: maxTokens || cfg.maxTokens,\n temperature: temperature ?? cfg.temperature,\n return_full_text: false,\n },\n }),\n },\n );\n\n if (!res.ok) {\n return {\n success: false,\n model: modelKey,\n modelId: cfg.id,\n text: \"\",\n error: `HTTP ${res.status}: ${await res.text()}`,\n };\n }\n\n const data = await res.json();\n const text = Array.isArray(data)\n ? data[0]?.generated_text || \"\"\n : data?.generated_text || \"\";\n\n return {\n success: true,\n model: modelKey,\n modelId: cfg.id,\n text,\n };\n } catch (e: any) {\n return {\n success: false,\n model: modelKey,\n modelId: cfg.id,\n text: \"\",\n error: e.message,\n };\n }\n}\n\n/**\n * Returns manifest of available models for discovery endpoint.\n */\nexport function getModelManifest() {\n const token = getHFToken();\n return Object.entries(HF_MODELS).map(([key, cfg]) => ({\n key,\n id: cfg.id,\n label: cfg.label,\n bestFor: cfg.bestFor,\n status: token ? \"AVAILABLE\" : \"NO_TOKEN\",\n }));\n}\n","// Hugging Face Model Orchestration — Nexuses Core OS V9.0\n// Dynamic model selection, timeout handling, and fallback chains.\n// Free-tier optimized.\n\n// --- Model Registry ---\n\nexport type ModelKey = \"qwen_coder\" | \"llama\" | \"phi3\" | \"mistral\";\nexport type TaskType = \"coding\" | \"creative\" | \"analysis\" | \"general\";\n\ninterface ModelConfig {\n id: string;\n label: string;\n bestFor: TaskType[];\n keywords: string[];\n maxTokens: number;\n temperature: number;\n fallback: ModelKey | null;\n}\n\nexport const HF_MODELS: Record = {\n qwen_coder: {\n id: \"Qwen/Qwen2.5-Coder-7B-Instruct\",\n label: \"Qwen2.5 Coder 7B\",\n bestFor: [\"coding\"],\n keywords: [\"code\", \"coding\", \"debug\", \"bug\", \"fix\", \"program\", \"refactor\", \"compile\", \"syntax\", \"error\", \"deploy\", \"devops\", \"github\", \"repo\", \"vscode\", \"commit\"],\n maxTokens: 800,\n temperature: 0.3,\n fallback: \"mistral\",\n },\n llama: {\n id: \"meta-llama/Meta-Llama-3-8B-Instruct\",\n label: \"Llama 3 8B Instruct\",\n bestFor: [\"creative\"],\n keywords: [\"write\", \"writing\", \"blog\", \"content\", \"article\", \"story\", \"creative\", \"social\", \"post\", \"voice\", \"website\", \"clone\", \"html\", \"css\", \"landing\", \"seo\", \"media\"],\n maxTokens: 1000,\n temperature: 0.8,\n fallback: \"mistral\",\n },\n phi3: {\n id: \"microsoft/Phi-3-mini-4k-instruct\",\n label: \"Phi-3 Mini 4K\",\n bestFor: [\"analysis\", \"general\"],\n keywords: [\"analyze\", \"analysis\", \"data\", \"scrape\", \"pdf\", \"excel\", \"word\", \"billing\", \"invoice\", \"report\", \"csv\", \"spreadsheet\", \"summarize\", \"extract\", \"research\", \"search\", \"crypto\", \"price\", \"market\", \"automation\"],\n maxTokens: 500,\n temperature: 0.5,\n fallback: \"mistral\",\n },\n mistral: {\n id: \"mistralai/Mistral-7B-Instruct-v0.2\",\n label: \"Mistral 7B Instruct\",\n bestFor: [\"general\"],\n keywords: [\"general\", \"help\", \"reasoning\", \"chat\", \"question\", \"explain\", \"unknown\", \"test\"],\n maxTokens: 500,\n temperature: 0.7,\n fallback: null,\n },\n};\n\n// --- Environment / Token ---\n\nfunction getEnv(key: string): string | undefined {\n try {\n return Deno.env.get(key);\n } catch {\n return undefined;\n }\n}\n\nexport function getHFToken(): string | null {\n return getEnv(\"HF_API_KEY\") || getEnv(\"HUGGING_FACE_TOKEN\") || null;\n}\n\n// --- Task Classification ---\n\n/**\n * Classifies a task string into a TaskType by keyword matching.\n * This runs BEFORE any API call to determine which model to use.\n */\nexport function classifyTask(taskText: string): TaskType {\n const lower = taskText.toLowerCase();\n\n // Score each model by keyword hits\n const scores: Record = {\n coding: 0,\n creative: 0,\n analysis: 0,\n general: 0,\n };\n\n for (const cfg of Object.values(HF_MODELS)) {\n for (const type of cfg.bestFor) {\n scores[type] += cfg.keywords.filter((k) => lower.includes(k)).length;\n }\n }\n\n // Pick the highest-scoring type\n let best: TaskType = \"general\";\n let bestScore = 0;\n for (const [type, score] of Object.entries(scores)) {\n if (score > bestScore) {\n bestScore = score;\n best = type as TaskType;\n }\n }\n\n return best;\n}\n\n/**\n * Maps a TaskType to the best ModelKey.\n */\nexport function modelForTaskType(type: TaskType): ModelKey {\n switch (type) {\n case \"coding\": return \"qwen_coder\";\n case \"creative\": return \"llama\";\n case \"analysis\": return \"phi3\";\n default: return \"mistral\";\n }\n}\n\n/**\n * Dynamically selects the best HF model for the given task text.\n * Analyzes the task type first, then maps to the specialized model.\n */\nexport function selectModel(taskText: string): ModelKey {\n const taskType = classifyTask(taskText);\n return modelForTaskType(taskType);\n}\n\n// --- HF API Call ---\n\nexport interface HFResult {\n success: boolean;\n model: ModelKey;\n modelId: string;\n text: string;\n taskType: TaskType;\n error?: string;\n timedOut?: boolean;\n attempts?: ModelKey[];\n}\n\ninterface CallOptions {\n maxTokens?: number;\n temperature?: number;\n timeoutMs?: number;\n}\n\n/**\n * Calls a single HF model with timeout protection.\n */\nasync function callSingleModel(\n modelKey: ModelKey,\n prompt: string,\n token: string,\n opts: CallOptions = {},\n): Promise {\n const cfg = HF_MODELS[modelKey];\n const timeoutMs = opts.timeoutMs ?? 25000;\n const taskType = classifyTask(prompt);\n\n const controller = new AbortController();\n const timeoutId = setTimeout(() => controller.abort(), timeoutMs);\n\n try {\n const res = await fetch(\n `https://api-inference.huggingface.co/models/${cfg.id}`,\n {\n method: \"POST\",\n headers: {\n \"Authorization\": `Bearer ${token}`,\n \"Content-Type\": \"application/json\",\n },\n body: JSON.stringify({\n inputs: prompt,\n parameters: {\n max_new_tokens: opts.maxTokens ?? cfg.maxTokens,\n temperature: opts.temperature ?? cfg.temperature,\n return_full_text: false,\n },\n }),\n signal: controller.signal,\n },\n );\n\n clearTimeout(timeoutId);\n\n if (!res.ok) {\n const errBody = await res.text().catch(() => \"\");\n return {\n success: false,\n model: modelKey,\n modelId: cfg.id,\n text: \"\",\n taskType,\n error: `HTTP ${res.status}: ${errBody.slice(0, 200)}`,\n };\n }\n\n const data = await res.json();\n const text = Array.isArray(data)\n ? data[0]?.generated_text || \"\"\n : data?.generated_text || \"\";\n\n return {\n success: true,\n model: modelKey,\n modelId: cfg.id,\n text,\n taskType,\n };\n } catch (e: any) {\n clearTimeout(timeoutId);\n const timedOut = e.name === \"AbortError\";\n return {\n success: false,\n model: modelKey,\n modelId: cfg.id,\n text: \"\",\n taskType,\n error: timedOut ? `Timeout after ${timeoutMs}ms` : e.message,\n timedOut,\n };\n }\n}\n\n/**\n * Calls Hugging Face with automatic fallback.\n * 1. Selects the best model for the task (or uses the specified one).\n * 2. If that model fails or times out, tries the fallback model.\n * 3. Returns the first successful result, or the last error.\n */\nexport async function callHFWithFallback(\n prompt: string,\n modelOverride?: ModelKey,\n opts: CallOptions = {},\n): Promise {\n const token = getHFToken();\n\n if (!token) {\n return {\n success: false,\n model: modelOverride || selectModel(prompt),\n modelId: HF_MODELS[modelOverride || selectModel(prompt)].id,\n text: \"\",\n taskType: classifyTask(prompt),\n error: \"HF_API_KEY not configured. Set it in environment variables.\",\n attempts: [],\n };\n }\n\n const primaryModel = modelOverride || selectModel(prompt);\n const attempts: ModelKey[] = [];\n\n // Build fallback chain: primary → its fallback → mistral (if different)\n const chain: ModelKey[] = [primaryModel];\n const fb1 = HF_MODELS[primaryModel].fallback;\n if (fb1 && !chain.includes(fb1)) chain.push(fb1);\n if (!chain.includes(\"mistral\")) chain.push(\"mistral\");\n\n let lastResult: HFResult | null = null;\n\n for (const modelKey of chain) {\n attempts.push(modelKey);\n console.log(`[HF] Trying model: ${HF_MODELS[modelKey].label} (${HF_MODELS[modelKey].id})`);\n\n const result = await callSingleModel(modelKey, prompt, token, opts);\n lastResult = result;\n\n if (result.success) {\n result.attempts = attempts;\n if (attempts.length > 1) {\n console.log(`[HF] Success on fallback model: ${HF_MODELS[modelKey].label}`);\n }\n return result;\n }\n\n console.log(`[HF] Model ${HF_MODELS[modelKey].label} failed: ${result.error}`);\n // Continue to next model in chain\n }\n\n // All models failed\n lastResult!.attempts = attempts;\n return lastResult!;\n}\n\n/**\n * Backwards-compatible wrapper — calls callHFWithFallback and\n * returns the same shape as the old callHF.\n */\nexport async function callHF(\n prompt: string,\n model?: ModelKey,\n maxTokens?: number,\n temperature?: number,\n): Promise {\n return callHFWithFallback(prompt, model, { maxTokens, temperature });\n}\n\n// --- Discovery ---\n\nexport function getModelManifest() {\n const token = getHFToken();\n return Object.entries(HF_MODELS).map(([key, cfg]) => ({\n key,\n id: cfg.id,\n label: cfg.label,\n bestFor: cfg.bestFor,\n fallback: cfg.fallback,\n status: token ? \"AVAILABLE\" : \"NO_TOKEN\",\n }));\n}\n\nexport function getSelectionInfo(taskText: string) {\n const taskType = classifyTask(taskText);\n const modelKey = modelForTaskType(taskType);\n const cfg = HF_MODELS[modelKey];\n return {\n taskType,\n selectedModel: modelKey,\n modelId: cfg.id,\n modelLabel: cfg.label,\n fallbackModel: cfg.fallback,\n 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Nexuses Core OS V9.0 — HTTP Entry Point\n// Webhook & M2M Interface with auth validation\nimport { dispatchTask, getTaskStatus, getHistory, getSystemStatus, callAdapterDirect } from \"./TaskDispatcher.ts\";\nimport { getAgentManifest } from \"./AgentManager.ts\";\nimport { listAdapters } from \"./UniversalAdapter.ts\";\nimport { getModelManifest } from \"./hf.ts\";\nimport { initDB } from \"./db.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 { return Deno.env.get(key); } catch { return undefined; }\n}\n\n// --- Auth Validation ---\nfunction validateAuth(req: Request): boolean {\n const apiKey = getEnv(\"NEXUSES_API_KEY\");\n // If no key is configured, allow all requests (dev mode)\n if (!apiKey) return true;\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 (in-memory per instance) ---\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;\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\n // --- GET Routes ---\n if (req.method === \"GET\") {\n // System discovery\n if (path === \"/\" || path === \"\") {\n const status = await getSystemStatus();\n return json(status);\n }\n\n // System status & stats\n if (path === \"/status\") {\n const status = await getSystemStatus();\n return json(status);\n }\n\n // Agent manifest\n if (path === \"/agents\") {\n return json({ agents: getAgentManifest().map((a) => ({\n name: a.name,\n category: a.category,\n capabilities: a.capabilities,\n model: a.model,\n adapters: a.adapters,\n })) });\n }\n\n // Available adapters\n if (path === \"/adapters\") {\n return json({ adapters: listAdapters() });\n }\n\n // Available HF models\n if (path === \"/models\") {\n return json({ models: getModelManifest() });\n }\n\n // Task history\n if (path === \"/history\") {\n const limit = parseInt(url.searchParams.get(\"limit\") || \"20\");\n const history = await getHistory(limit);\n return json({ history });\n }\n\n // Get task by ID\n const taskMatch = path.match(/^\\/task\\/(.+)$/);\n if (taskMatch) {\n const task = await getTaskStatus(taskMatch[1]);\n if (!task) return json({ status: \"failure\", message: \"Task not found\" }, 404);\n return json({ task });\n }\n\n return json({ error: \"Unknown endpoint\", available: [\"/\", \"/status\", \"/agents\", \"/adapters\", \"/models\", \"/history\", \"/task/:id\"] }, 404);\n }\n\n // --- POST Routes ---\n if (req.method !== \"POST\") return json({ error: \"Only GET and POST supported\" }, 405);\n\n // Auth check\n if (!validateAuth(req)) {\n return json({\n status: \"failure\",\n message: \"Unauthorized — provide valid Bearer token in Authorization header\",\n }, 401);\n }\n\n // Rate limit\n if (isRateLimited(ip)) {\n return json({ status: \"failure\", message: \"Rate limit exceeded (50 req/min)\" }, 429);\n }\n\n // Parse body\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 // Direct adapter call\n if (path === \"/adapter\") {\n const { adapter, action, data } = payload;\n if (!adapter) return json({ status: \"failure\", message: \"Missing 'adapter' field\" }, 400);\n const result = await callAdapterDirect(adapter, action || \"default\", data || {});\n return json({\n status: result.success ? \"success\" : \"failure\",\n task_id: `adapter_${Date.now()}`,\n data: result.data,\n message: result.message,\n adapter: result.adapter,\n action: result.action,\n });\n }\n\n // Main task dispatch (POST /)\n const task = payload?.task || \"general\";\n const data = payload?.data || {};\n const mode = payload?.mode || \"AUTO\";\n\n try {\n const response = await dispatchTask(task, data, mode);\n return json(response, response.status === \"success\" ? 200 : 500);\n } catch (e: any) {\n return json({\n status: \"failure\",\n task_id: `err_${Date.now()}`,\n data: {},\n message: `Internal error: ${e.message}`,\n }, 500);\n }\n}\n","label","nexuses-core-os",[140],"34570400-5ece-40e9-8e11-7d92e6dee8f8",["D",1783324640839],1,[34],"feeb9ec8-f78f-42b5-b4ea-206d557ad526","db.ts","d2af9306-790e-11f1-ac91-1607ee4eb77e",9,["D",1783323999632],"// SQLite Persistent State Layer — Nexuses Core OS V9.0\nimport { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\n\nexport interface TaskRecord {\n id: string;\n task: string;\n agent: string;\n status: string;\n data: string;\n result: string;\n created_at: string;\n updated_at: string;\n}\n\nexport interface MemoryRecord {\n key: string;\n value: string;\n created_at: string;\n}\n\nconst INIT_SQL = [\n `CREATE TABLE IF NOT EXISTS tasks (\n id TEXT PRIMARY KEY,\n task TEXT NOT NULL,\n agent TEXT,\n status TEXT NOT NULL,\n data TEXT,\n result TEXT,\n created_at TEXT NOT NULL,\n updated_at TEXT NOT NULL\n )`,\n `CREATE TABLE IF NOT EXISTS memory (\n key TEXT PRIMARY KEY,\n value TEXT NOT NULL,\n created_at TEXT NOT NULL\n )`,\n `CREATE TABLE IF NOT EXISTS workflows (\n id TEXT PRIMARY KEY,\n task_id TEXT NOT NULL,\n step INTEGER NOT NULL,\n agent TEXT,\n status TEXT,\n detail TEXT,\n created_at TEXT NOT NULL\n )`,\n];\n\nlet initialized = false;\n\nexport async function initDB() {\n if (initialized) return;\n await sqlite.batch(INIT_SQL.map((sql) => ({ sql })));\n initialized = true;\n}\n\nexport async function insertTask(\n id: string,\n task: string,\n agent: string,\n status: string,\n data: any,\n result: any,\n) {\n const now = new Date().toISOString();\n await sqlite.execute({\n sql: `INSERT INTO tasks (id, task, agent, status, data, result, created_at, updated_at)\n VALUES (?, ?, ?, ?, ?, ?, ?, ?)`,\n args: [id, task, agent, status, JSON.stringify(data), JSON.stringify(result), now, now],\n });\n}\n\nexport async function updateTaskStatus(id: string, status: string, result: any) {\n const now = new Date().toISOString();\n await sqlite.execute({\n sql: `UPDATE tasks SET status = ?, result = ?, updated_at = ? WHERE id = ?`,\n args: [status, JSON.stringify(result), now, id],\n });\n}\n\nexport async function getTask(id: string): Promise {\n const res = await sqlite.execute({\n sql: `SELECT * FROM tasks WHERE id = ?`,\n args: [id],\n });\n return (res.rows[0] as TaskRecord) || null;\n}\n\nexport async function getRecentTasks(limit = 20): Promise {\n const res = await sqlite.execute({\n sql: `SELECT * FROM tasks ORDER BY created_at DESC LIMIT ?`,\n args: [limit],\n });\n return res.rows as TaskRecord[];\n}\n\nexport async function logWorkflowStep(\n taskId: string,\n step: number,\n agent: string,\n status: string,\n detail: string,\n) {\n const id = `wf_${taskId}_${step}`;\n const now = new Date().toISOString();\n await sqlite.execute({\n sql: `INSERT INTO workflows (id, task_id, step, agent, status, detail, created_at)\n VALUES (?, ?, ?, ?, ?, ?, ?)`,\n args: [id, taskId, step, agent, status, detail, now],\n });\n}\n\nexport async function remember(key: string, value: any) {\n const now = new Date().toISOString();\n await sqlite.execute({\n sql: `INSERT OR REPLACE INTO memory (key, value, created_at) VALUES (?, ?, ?)`,\n args: [key, JSON.stringify(value), now],\n });\n}\n\nexport async function recall(key: string): Promise {\n const res = await sqlite.execute({\n sql: `SELECT * FROM memory WHERE key = ?`,\n args: [key],\n });\n const row = res.rows[0] as MemoryRecord | undefined;\n return row ? JSON.parse(row.value) : null;\n}\n\nexport async function getWorkflowHistory(taskId: string) {\n const res = await sqlite.execute({\n sql: `SELECT * FROM workflows WHERE task_id = ? ORDER BY step ASC`,\n args: [taskId],\n });\n return res.rows;\n}\n\nexport async function getTaskCount(): Promise {\n const res = await sqlite.execute(`SELECT COUNT(*) as count FROM tasks`);\n return (res.rows[0] as any)?.count || 0;\n}\n",[157],"756b7f35-048d-4e7c-9e28-529563d89287","UniversalAdapter.ts","dec8a808-790e-11f1-8185-1607ee4eb77e",11,["D",1783324019927],"// Universal Adapter Layer — Nexuses Core OS V9.0\n// M2M middleware that connects the OS to third-party plugins, browsers, and applications.\n\nexport interface Adapter {\n name: string;\n type: \"api\" | \"browser\" | \"service\" | \"plugin\";\n status: \"active\" | \"inactive\" | \"error\";\n description: string;\n execute: (action: string, data: any) => Promise;\n}\n\nexport interface AdapterResult {\n success: boolean;\n adapter: string;\n action: string;\n data: any;\n message: string;\n}\n\n// --- Built-in Adapters ---\n\nconst GitHubAdapter: Adapter = {\n name: \"github\",\n type: \"api\",\n status: \"active\",\n description: \"GitHub repository management, issue tracking, code search\",\n async execute(action: string, data: any): Promise {\n const token = Deno.env.get(\"GITHUB_TOKEN\");\n if (!token) {\n return {\n success: false, adapter: \"github\", action, data: {},\n message: \"GITHUB_TOKEN not configured\",\n };\n }\n try {\n let url = \"\";\n let method = \"GET\";\n let body: string | undefined;\n\n switch (action) {\n case \"search_code\":\n url = `https://api.github.com/search/code?q=${encodeURIComponent(data.query)}`;\n break;\n case \"get_repo\":\n url = `https://api.github.com/repos/${data.owner}/${data.repo}`;\n break;\n case \"list_issues\":\n url = `https://api.github.com/repos/${data.owner}/${data.repo}/issues?state=open`;\n break;\n case \"create_issue\":\n url = `https://api.github.com/repos/${data.owner}/${data.repo}/issues`;\n method = \"POST\";\n body = JSON.stringify({ title: data.title, body: data.body });\n break;\n case \"get_file\":\n url = `https://api.github.com/repos/${data.owner}/${data.repo}/contents/${data.path}`;\n break;\n default:\n return {\n success: false, adapter: \"github\", action, data: {},\n message: `Unknown action: ${action}`,\n };\n }\n\n const res = await fetch(url, {\n method,\n headers: {\n \"Authorization\": `Bearer ${token}`,\n \"Accept\": \"application/vnd.github.v3+json\",\n \"Content-Type\": \"application/json\",\n },\n body,\n });\n\n const result = await res.json();\n return {\n success: res.ok, adapter: \"github\", action,\n data: result,\n message: res.ok ? `GitHub ${action} completed` : `GitHub API error: ${res.status}`,\n };\n } catch (e: any) {\n return {\n success: false, adapter: \"github\", action, data: {},\n message: e.message,\n };\n }\n },\n};\n\nconst DuckDuckGoAdapter: Adapter = {\n name: \"duckduckgo\",\n type: \"service\",\n status: \"active\",\n description: \"Free-tier web search and instant answers\",\n async execute(action: string, data: any): Promise {\n try {\n const query = data.query || data.q || \"\";\n const res = await fetch(\n `https://api.duckduckgo.com/?q=${encodeURIComponent(query)}&format=json`,\n );\n const result = await res.json();\n return {\n success: true, adapter: \"duckduckgo\", action: \"search\",\n data: {\n abstract: result.AbstractText || \"\",\n answer: result.Answer || \"\",\n related: (result.RelatedTopics || []).slice(0, 5).map((t: any) => t.Text || t.Topics?.[0]?.Text).filter(Boolean),\n },\n message: \"Search completed\",\n };\n } catch (e: any) {\n return {\n success: false, adapter: \"duckduckgo\", action, data: {},\n message: e.message,\n };\n }\n },\n};\n\nconst CoinGeckoAdapter: Adapter = {\n name: \"coingecko\",\n type: \"api\",\n status: \"active\",\n description: \"Cryptocurrency price data and market signals\",\n async execute(action: string, data: any): Promise {\n try {\n const coins = data.coins || [\"bitcoin\", \"ethereum\"];\n const res = await fetch(\n `https://api.coingecko.com/api/v3/simple/price?ids=${coins.join(\",\")}&vs_currencies=usd&include_24hr_change=true`,\n );\n const prices = await res.json();\n const signals = coins.map((c: string) => {\n const change = prices[c]?.usd_24h_change || 0;\n return {\n coin: c,\n price: prices[c]?.usd,\n change24h: change,\n signal: change > 5 ? \"BUY\" : change < -5 ? \"SELL\" : \"HOLD\",\n };\n });\n return {\n success: true, adapter: \"coingecko\", action: \"price\",\n data: { signals },\n message: \"Crypto signals generated\",\n };\n } catch (e: any) {\n return {\n success: false, adapter: \"coingecko\", action, data: {},\n message: e.message,\n };\n }\n },\n};\n\nconst WebScraperAdapter: Adapter = {\n name: \"webscraper\",\n type: \"browser\",\n status: \"active\",\n description: \"Web page scraping and content extraction\",\n async execute(action: string, data: any): Promise {\n const url = data.url;\n if (!url || !url.startsWith(\"http\")) {\n return {\n success: false, adapter: \"webscraper\", action, data: {},\n message: \"No valid URL provided\",\n };\n }\n try {\n const res = await fetch(url);\n const html = await res.text();\n const title = html.match(/]*>([^<]+)<\\/title>/i)?.[1]?.trim() || \"\";\n const links = (html.match(/]+href=[\"']([^\"']+)[\"']/gi) || [])\n .slice(0, 20)\n .map((m: string) => m.match(/href=[\"']([^\"']+)[\"']/i)?.[1])\n .filter(Boolean);\n const textContent = html.replace(/<[^>]+>/g, \" \").replace(/\\s+/g, \" \").trim().slice(0, 2000);\n return {\n success: true, adapter: \"webscraper\", action: \"scrape\",\n data: { url, title, links, textContent },\n message: `Scraped ${url}`,\n };\n } catch (e: any) {\n return {\n success: false, adapter: \"webscraper\", action, data: {},\n message: e.message,\n };\n }\n },\n};\n\n// --- Adapter Registry ---\n\nconst REGISTRY = new Map();\n[GitHubAdapter, DuckDuckGoAdapter, CoinGeckoAdapter, WebScraperAdapter].forEach(\n (a) => REGISTRY.set(a.name, a),\n);\n\nexport function registerAdapter(adapter: Adapter) {\n REGISTRY.set(adapter.name, adapter);\n}\n\nexport function getAdapter(name: string): Adapter | null {\n return REGISTRY.get(name) || null;\n}\n\nexport function listAdapters() {\n return Array.from(REGISTRY.values()).map((a) => ({\n name: a.name,\n type: a.type,\n status: a.status,\n description: a.description,\n }));\n}\n\nexport async function routeToAdapter(\n name: string,\n action: string,\n data: any,\n): Promise {\n const adapter = getAdapter(name);\n if (!adapter) {\n return {\n success: false,\n adapter: name,\n action,\n data: {},\n message: `Adapter '${name}' not found in registry`,\n };\n }\n return adapter.execute(action, data);\n}\n",[164],"69e5bb45-8624-4e06-aece-ae979e01bb1b","TaskDispatcher.ts","fde83000-790e-11f1-9c16-1607ee4eb77e",13,["D",1783324072140],"// Task Dispatcher — Nexuses Core OS V9.0\n// Orchestrates the Analyze → Execute → Report pipeline.\nimport { routeIncomingTask, getAgentManifest } from \"./AgentManager.ts\";\nimport type { AgentResult } from \"./AgentManager.ts\";\nimport { listAdapters, routeToAdapter } from \"./UniversalAdapter.ts\";\nimport { getModelManifest, getHFToken, selectModel } from \"./hf.ts\";\nimport {\n initDB,\n insertTask,\n updateTaskStatus,\n getTask,\n logWorkflowStep,\n remember,\n recall,\n getRecentTasks,\n getTaskCount,\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 adapters?: string[];\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\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 await logWorkflowStep(taskId, 1, \"TaskDispatcher\", \"ANALYZE\",\n `Task: \"${task}\" | Candidates: ${candidates.map((a) => a.name).join(\", \") || \"GeneralHandler\"}`);\n\n // Record initial task state\n await insertTask(taskId, task, \"pending\", \"processing\", { task, data, mode }, null);\n\n // Recall any memory related to this task type\n const memoryKey = `task_type:${candidates[0]?.name || \"general\"}`;\n const priorMemory = await recall(memoryKey);\n\n // PHASE 2: EXECUTE — route to selected agent\n await logWorkflowStep(taskId, 2, \"TaskDispatcher\", \"EXECUTE\",\n `Routing to agent for execution`);\n\n const agentResult: AgentResult = await routeIncomingTask(task, data, mode, true);\n\n await logWorkflowStep(taskId, 3, agentResult.agent, agentResult.status,\n agentResult.message);\n\n // PHASE 3: REPORT — build structured response\n const isSuccess = agentResult.status === \"SUCCESS\";\n const response: DispatchResponse = {\n status: isSuccess ? \"success\" : \"failure\",\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 adapters: agentResult.adapters || [],\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 timestamp: new Date().toISOString(),\n ...(priorMemory ? { previous: priorMemory } : {}),\n });\n\n await logWorkflowStep(taskId, 4, \"TaskDispatcher\", \"REPORT\",\n `Status: ${response.status} | Time: ${response.executionTimeMs}ms`);\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 V9.0\",\n uptime: \"24/7 on Val Town\",\n persistence: \"SQLite (project-scoped)\",\n tasksProcessed: taskCount,\n hfIntegration: token ? \"ACTIVE\" : \"NOT_CONFIGURED\",\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 \"/\": \"Dispatch task (requires auth)\",\n \"/adapter\": \"Direct adapter call (requires auth)\",\n },\n GET: {\n \"/\": \"System discovery\",\n \"/status\": \"System status & stats\",\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: { \"Authorization\": \"Bearer YOUR_API_KEY\", \"Content-Type\": \"application/json\" },\n body: { task: \"debug my code\", data: { code: \"function add(a,b){return a-b}\" } },\n },\n };\n}\n\nexport async function callAdapterDirect(name: string, action: string, data: any) {\n return routeToAdapter(name, action, data);\n}\n",[171],"a164f78d-0790-4900-b81b-889b55efc4ae","AgentManager.ts","f7361f90-790b-11f1-95a6-1607ee4eb77e",12,["D",1783324071609],4,"// Agent Swarm — Nexuses Core OS V9.0\n// Three primary agents: DevOps/Coding, Web/Content, Data/Automation\nimport { callHF, selectModel, getHFToken } from \"./hf.ts\";\nimport type { ModelKey } from \"./hf.ts\";\nimport { routeToAdapter, listAdapters } 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 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: [\"code\", \"coding\", \"debug\", \"bug\", \"fix\", \"github\", \"repo\", \"program\", \"vscode\", \"vs code\", \"commit\", \"deploy\", \"devops\", \"refactor\", \"compile\", \"syntax\", \"error\"],\n capabilities: [\"VS Code integration\", \"GitHub repo management\", \"Error finding & fixing\", \"Bug resolution\", \"Auto-writing code\", \"Code explanation\"],\n model: \"qwen\",\n adapters: [\"github\"],\n },\n {\n name: \"WebContentAgent\",\n category: \"Web/Content\",\n keywords: [\"write\", \"blog\", \"content\", \"article\", \"social\", \"post\", \"website\", \"clone\", \"scrape\", \"web\", \"voice\", \"html\", \"css\", \"landing\", \"seo\", \"tweet\", \"facebook\", \"media\"],\n capabilities: [\"Web automation\", \"Website cloning\", \"Social media posting\", \"Content writing\", \"Blogging\", \"Voice-enabled website generation\"],\n model: \"llama\",\n adapters: [\"webscraper\", \"duckduckgo\"],\n },\n {\n name: \"DataAutomationAgent\",\n category: \"Data/Automation\",\n keywords: [\"data\", \"scrape\", \"analyze\", \"pdf\", \"excel\", \"word\", \"billing\", \"invoice\", \"entry\", \"scan\", \"spreadsheet\", \"csv\", \"report\", \"automation\", \"crypto\", \"price\", \"market\"],\n capabilities: [\"Data scraping & analysis\", \"PDF conversion/creation\", \"Billing/data entry\", \"MS Word/Excel automation\", \"Document scanning\"],\n model: \"phi3\",\n adapters: [\"coingecko\", \"duckduckgo\", \"webscraper\"],\n },\n {\n name: \"GeneralHandler\",\n category: \"General\",\n keywords: [\"general\", \"help\", \"unknown\", \"test\"],\n capabilities: [\"General task handling\", \"Fallback routing\"],\n model: \"mistral\",\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// --- Agent Execution Functions ---\n\nconst AGENT_MAP: Record Promise> = {};\n\n// 1. DevOps / Coding Agent\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(\"github\", data.github.action || \"get_repo\", data.github);\n if (ghResult.success) {\n // Use HF to analyze/summarize the GitHub data\n const hfResult = await callHF(\n `Analyze this GitHub data and provide insights: ${JSON.stringify(ghResult.data).slice(0, 1000)}`,\n \"qwen\",\n 500,\n );\n return {\n agent: \"DevOpsCodingAgent\",\n category: \"DevOps/Coding\",\n status: hfResult.success ? \"SUCCESS\" : \"PARTIAL\",\n message: `GitHub ${data.github.action || \"operation\"} completed${hfResult.success ? \" + AI analysis\" : \"\"}`,\n data: { github: ghResult.data, analysis: hfResult.text || hfResult.error },\n model: \"qwen\",\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 callHF(codePrompt, \"qwen\", 800, 0.3);\n\n return {\n agent: \"DevOpsCodingAgent\",\n category: \"DevOps/Coding\",\n status: hfResult.success ? \"SUCCESS\" : \"ERROR\",\n message: hfResult.success\n ? `Code ${action} completed using Qwen2`\n : hfResult.error || \"HF model error\",\n data: {\n action,\n input: prompt.slice(0, 500),\n output: hfResult.text,\n },\n model: \"qwen\",\n adapters: [],\n };\n};\n\n// 2. Web / Content Agent\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\", { url: data.url });\n if (scrapeResult.success && action === \"clone\") {\n // Generate a simplified HTML clone using HF\n const hfResult = await callHF(\n `Create a simple HTML page based on this scraped content:\\nTitle: ${scrapeResult.data.title}\\nContent: ${scrapeResult.data.textContent?.slice(0, 800)}`,\n \"llama\",\n 800,\n );\n return {\n agent: \"WebContentAgent\",\n category: \"Web/Content\",\n status: \"SUCCESS\",\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: \"llama\",\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: ${prompt}`;\n\n const hfResult = await callHF(contentPrompt, \"llama\", 1000, 0.8);\n\n return {\n agent: \"WebContentAgent\",\n category: \"Web/Content\",\n status: hfResult.success ? \"SUCCESS\" : \"ERROR\",\n message: hfResult.success\n ? `Content generated using Llama 3`\n : hfResult.error || \"HF model error\",\n data: {\n action,\n content: hfResult.text,\n },\n model: \"llama\",\n adapters: [],\n };\n};\n\n// 3. Data / Automation Agent\nAGENT_MAP[\"DataAutomationAgent\"] = async (task: string, data: any) => {\n const prompt = data.prompt || task;\n const action = data.action || \"analyze\";\n\n // Crypto signals\n if (action === \"crypto\" || prompt.toLowerCase().includes(\"crypto\") || prompt.toLowerCase().includes(\"price\")) {\n const cgResult = await routeToAdapter(\"coingecko\", \"price\", { coins: data.coins });\n if (cgResult.success) {\n return {\n agent: \"DataAutomationAgent\",\n category: \"Data/Automation\",\n status: \"SUCCESS\",\n message: \"Crypto signals generated\",\n data: cgResult.data,\n adapters: [\"coingecko\"],\n };\n }\n }\n\n // Data scraping + analysis\n if (data.url || action === \"scrape\") {\n const scrapeResult = await routeToAdapter(\"webscraper\", \"scrape\", { url: data.url });\n if (scrapeResult.success) {\n const hfResult = await callHF(\n `Analyze this scraped data and provide a summary:\\n${scrapeResult.data.textContent?.slice(0, 1000)}`,\n \"phi3\",\n 400,\n );\n return {\n agent: \"DataAutomationAgent\",\n category: \"Data/Automation\",\n status: \"SUCCESS\",\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: \"phi3\",\n adapters: [\"webscraper\"],\n };\n }\n }\n\n // Research via DuckDuckGo\n if (action === \"research\" || action === \"search\") {\n const ddgResult = await routeToAdapter(\"duckduckgo\", \"search\", { query: prompt });\n if (ddgResult.success) {\n const hfResult = await callHF(\n `Summarize this research data:\\n${JSON.stringify(ddgResult.data).slice(0, 800)}`,\n \"phi3\",\n 400,\n );\n return {\n agent: \"DataAutomationAgent\",\n category: \"Data/Automation\",\n status: \"SUCCESS\",\n message: \"Research completed and summarized\",\n data: {\n search: ddgResult.data,\n summary: hfResult.text || \"\",\n },\n model: \"phi3\",\n adapters: [\"duckduckgo\"],\n };\n }\n }\n\n // General data analysis\n const hfResult = await callHF(`Analyze and process: ${prompt}`, \"phi3\", 400, 0.5);\n return {\n agent: \"DataAutomationAgent\",\n category: \"Data/Automation\",\n status: hfResult.success ? \"SUCCESS\" : \"ERROR\",\n message: hfResult.success ? \"Data analysis completed\" : hfResult.error || \"HF model error\",\n data: { action, result: hfResult.text },\n model: \"phi3\",\n adapters: [],\n };\n};\n\n// 4. General Handler\nAGENT_MAP[\"GeneralHandler\"] = async (task: string, data: any) => {\n const hfResult = await callHF(data.prompt || task, \"mistral\", 500);\n return {\n agent: \"GeneralHandler\",\n category: \"General\",\n status: hfResult.success ? \"SUCCESS\" : \"ERROR\",\n message: hfResult.success ? \"Task processed\" : hfResult.error || \"No HF token\",\n data: { input: task, response: hfResult.text || \"\" },\n model: \"mistral\",\n adapters: [],\n };\n};\n\n// --- Public Routing API ---\n\nexport async function routeIncomingTask(\n task: string,\n data: any = {},\n mode = \"AUTO\",\n debug = false,\n): Promise {\n const agentEntry = matchAgent(task);\n const agentFn = AGENT_MAP[agentEntry.name] || AGENT_MAP[\"GeneralHandler\"];\n\n try {\n const result = await agentFn(task, data);\n if (debug) {\n console.log(`[Dispatcher] Task: \"${task}\" → Agent: ${result.agent} → Status: ${result.status}`);\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 models: token ? \"Hugging Face ACTIVE\" : \"Hugging Face NOT_CONFIGURED\",\n };\n}\n",[178],"pulls","branches","forks","envVars",{"_192":67,"_194":67},"connections",{"_192":67,"_193":67},"count","unfilledCount","emptyCount",{"_49":177,"_38":178,"_36":179,"_142":-5,"_47":48,"_46":180,"_144":31,"_44":217,"_13":182,"_39":40,"_41":183,"_30":31,"_149":-5,"_202":218,"_33":219},{"_49":170,"_38":171,"_36":172,"_142":-5,"_47":48,"_46":173,"_144":31,"_44":214,"_13":67,"_39":40,"_41":175,"_30":31,"_149":-5,"_202":215,"_33":216},{"_49":163,"_38":164,"_36":165,"_142":-5,"_47":48,"_46":166,"_144":128,"_44":211,"_13":67,"_39":40,"_41":168,"_30":31,"_149":-5,"_202":212,"_33":213},{"_49":156,"_38":157,"_36":158,"_142":-5,"_47":48,"_46":159,"_144":31,"_44":208,"_13":67,"_39":40,"_41":161,"_30":31,"_149":-5,"_202":209,"_33":210},{"_49":152,"_38":34,"_36":37,"_142":-5,"_47":48,"_46":14,"_144":128,"_44":205,"_13":154,"_39":40,"_41":43,"_30":31,"_149":-5,"_202":206,"_33":207},{"_49":139,"_38":140,"_36":141,"_142":-5,"_47":48,"_46":143,"_144":31,"_44":201,"_13":146,"_39":147,"_41":148,"_30":31,"_149":150,"_202":203,"_33":204},["D",1783324103933],"children",[],[140],["D",1783324640839],[],[34],["D",1783323999632],[],[157],["D",1783324019927],[],[164],["D",1783324072140],[],[171],["D",1783324071609],[],[178],["D",1783322691823],["D",1789525843977],{"_104":103,"_110":59},{"_104":103,"_105":59,"_106":59,"_19":61,"_107":108,"_109":31},{"_13":93,"_38":94,"_49":48,"_95":50,"_96":-5,"_97":-5,"_98":-5,"_99":-5,"_100":-5,"_101":51,"_102":103},"ctx",{"_86":-5,"_130":258,"_259":260,"_261":262,"_263":31,"_264":31,"_265":31,"_266":128,"_267":-5,"_268":-7,"_269":-7,"_270":67,"_271":31,"_272":31,"_273":-5,"_274":31,"_275":31,"_276":31,"_277":-5},"ENV",{"_229":230,"_231":232,"_233":94,"_234":235,"_236":237,"_238":239,"_240":241,"_242":243,"_244":245,"_246":247,"_248":249,"_250":251,"_252":253,"_254":255,"_256":257},"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 · v16