AETHERIA

Intelligent Crisis Response & Communication Orchestrator (ICRCO)

Initializing...

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\n\n`;\n}","label",[130],"7ee632f0-36c2-11f0-8589-9e149126039e","orchestrator.ts","76cbe650-36c2-11f0-950c-9e149126039e",9,["D",1747886942900],"// src/orchestrator.ts\nimport { executeAIAgent } from \"./ai_agent_runner\";\nimport { AuditLogger } from \"./logger\";\nimport { getProcessDefinition } from \"./process_definitions\";\nimport { LogFunction, OrchestratorInput, SystemResponse, TaskInput } from \"./types\";\nimport { Utils } from \"./utils\";\n\nexport class CrisisWorkflowOrchestrator {\n private baseLogger: LogFunction;\n private masterIncidentId: string;\n private logger: LogFunction; // Instance-specific logger\n\n constructor(auditLoggerInstance: AuditLogger, masterIncidentId?: string) {\n // Use provided masterIncidentId or default from logger, or generate new\n this.masterIncidentId = masterIncidentId || auditLoggerInstance.getMasterIncidentIdContext()\n || `M-${Utils.generateShortId()}`;\n\n // Ensure the logger instance uses this orchestrator's masterIncidentId for its context\n auditLoggerInstance.setMasterIncidentIdContext(this.masterIncidentId);\n this.baseLogger = auditLoggerInstance.log.bind(auditLoggerInstance);\n\n this.logger = (level, component, message, details?, _masterIdOverride?, taskId?) => {\n this.baseLogger(level, component, message, details, this.masterIncidentId, taskId);\n };\n this.logger(\n \"AUDIT\",\n \"CrisisOrchestrator\",\n `New instance initialized for Master Incident ID: ${this.masterIncidentId}.`,\n );\n }\n\n public async initiateProcess(input: OrchestratorInput): Promise {\n this.logger(\"AUDIT\", \"CrisisOrchestrator\", `Initiating workflow for Process ID: ${input.processId}`, {\n inputDataKeys: Object.keys(input.data),\n });\n\n const processDefinition = getProcessDefinition(input.processId);\n if (!processDefinition) {\n const errorMessage = `FATAL: Process Definition ID \"${input.processId}\" not found. Workflow cannot proceed.`;\n this.logger(\"CRITICAL\", \"CrisisOrchestrator\", errorMessage, {\n availableProcessIds: [\n \"assess_incident_impact\",\n \"draft_stakeholder_communication\",\n \"generate_executive_briefing\",\n ],\n }); // Manually list or get from definitions\n return {\n masterIncidentId: this.masterIncidentId,\n error: errorMessage,\n diagnosticLog: [], // Logger instance will hold logs if passed externally\n operationStatus: \"ERROR\",\n };\n }\n\n const taskId = `${input.processId.substring(0, 10)}-${Utils.generateShortId(6)}`;\n const agentTaskInput: TaskInput = {\n masterIncidentId: this.masterIncidentId,\n taskId,\n payload: input.data,\n };\n\n try {\n const agentTaskOutput = await executeAIAgent(\n agentTaskInput,\n this.logger, // Pass the instance-bound logger\n processDefinition.aiAgentConfiguration,\n );\n\n if (agentTaskOutput.error) {\n this.logger(\n \"WARN\",\n \"CrisisOrchestrator\",\n `AI Agent for process ${input.processId} (Task ${taskId}) reported an error.`,\n { agentError: agentTaskOutput.error },\n );\n return {\n masterIncidentId: this.masterIncidentId,\n error: `Workflow Partially Failed: ${agentTaskOutput.error}`,\n result: agentTaskOutput.result,\n diagnosticLog: [],\n operationStatus: \"PARTIAL_SUCCESS\",\n };\n }\n\n this.logger(\n \"AUDIT\",\n \"CrisisOrchestrator\",\n `Workflow for Process ID ${input.processId} (Task ${taskId}) completed successfully.`,\n { outputKeys: Object.keys(agentTaskOutput.result) },\n );\n return {\n masterIncidentId: this.masterIncidentId,\n result: agentTaskOutput.result,\n diagnosticLog: [],\n operationStatus: \"SUCCESS\",\n };\n } catch (orchestrationError: any) {\n const criticalErrorMessage =\n `Workflow Critically Failed for Process ID ${input.processId} (Task ${taskId}): ${orchestrationError.message}`;\n this.logger(\"CRITICAL\", \"CrisisOrchestrator\", criticalErrorMessage, {\n errorStack: orchestrationError.stack?.substring(0, 500),\n });\n return {\n masterIncidentId: this.masterIncidentId,\n error: criticalErrorMessage,\n diagnosticLog: [],\n operationStatus: \"ERROR\",\n };\n }\n }\n}",[141],"a784cb04-36c2-11f0-aed8-9e149126039e",["D",1747887011049],[27],"3246ec1e-36c2-11f0-8c4a-9e149126039e","index.ts",3,["D",1747886814348],"// src/main_handler.ts OR index.ts (entry point)\n\n// Val Town specific fetch (if not global)\n// import { fetch } from \"https://esm.town/v/std/fetch\";\nimport { z } from \"npm:zod\";\n\nimport { AuditLogger } from \"./logger\";\nimport { CrisisWorkflowOrchestrator } from \"./orchestrator\";\nimport { AETHERIA_PROCESS_DEFINITIONS, getProcessDefinition } from \"./process_definitions\"; // For UI data\nimport { QuestionnaireAgent } from \"./questionnaire_agent\";\nimport { OrchestratorInput, OrchestratorInputSchema, QuestionnaireResponse, SystemResponse } from \"./types\";\nimport { generateAetheriaUI } from \"./ui_generator\";\nimport { Utils } from \"./utils\";\n\n/**\n * Main HTTP request handler for the Aetheria ICRCO system.\n * This function routes requests to the appropriate handlers for UI,\n * questionnaire interactions, and AI process execution.\n *\n * @param request The incoming HTTP Request object.\n * @returns A Promise resolving to a Response object.\n */\nexport default async function handleRequest(request: Request): Promise {\n const requestId = `REQ-${Utils.generateShortId(10)}`;\n const requestLogger = new AuditLogger(requestId); // Logger for this request\n const log = requestLogger.log.bind(requestLogger);\n\n const url = new URL(request.url);\n const baseHeaders = {\n \"Content-Type\": \"application/json\",\n \"Access-Control-Allow-Origin\": \"*\", // Adjust for production\n \"Access-Control-Allow-Methods\": \"GET, POST, OPTIONS\",\n \"Access-Control-Allow-Headers\": \"Content-Type, Authorization, X-Aetheria-Request-ID\",\n \"X-Aetheria-Request-ID\": requestId,\n };\n\n log(\"AUDIT\", \"HTTPGateway\", `Received request: ${request.method} ${url.pathname}`, {\n headers: JSON.stringify(Object.fromEntries(request.headers)),\n });\n\n if (request.method === \"OPTIONS\") {\n log(\"INFO\", \"HTTPGateway\", \"Handling OPTIONS preflight request.\", {});\n return new Response(null, { status: 204, headers: baseHeaders });\n }\n\n try {\n // Serve UI\n if (request.method === \"GET\" && (url.pathname === \"/\" || url.pathname === \"\")) {\n log(\"INFO\", \"HTTPGateway\", \"Serving Aetheria UI.\", { path: url.pathname });\n const uiProcessDefinitions = AETHERIA_PROCESS_DEFINITIONS.map(p => ({\n id: p.id,\n title: p.title,\n objective: p.objective,\n uiColorClass: p.uiColorClass,\n questionCount: p.questions.length,\n }));\n const html = generateAetheriaUI(JSON.stringify(uiProcessDefinitions));\n return new Response(html, {\n status: 200,\n headers: { ...baseHeaders, \"Content-Type\": \"text/html;charset=utf-8\" },\n });\n }\n\n // Questionnaire Endpoint\n if (request.method === \"POST\" && url.pathname === \"/questionnaire\") {\n log(\"INFO\", \"HTTPGateway\", \"Processing POST to /questionnaire.\", { path: url.pathname });\n let requestBody;\n let rawRequestBody = \"[NoBodyRead]\";\n try {\n rawRequestBody = await request.text(); // Read as text first for logging\n requestBody = JSON.parse(rawRequestBody);\n // Basic validation for action and processId\n if (\n !requestBody?.processId || typeof requestBody.processId !== \"string\" || !requestBody.action\n || ![\"start\", \"answer\", \"back\", \"restart\"].includes(requestBody.action)\n ) {\n throw new Error(\"Invalid questionnaire request structure: missing/invalid action or processId.\");\n }\n if ((requestBody.action === \"answer\" || requestBody.action === \"back\") && !requestBody.state) {\n throw new Error(`Invalid questionnaire request: 'state' is required for action '${requestBody.action}'.`);\n }\n if (requestBody.action === \"answer\" && !requestBody.lastAnswer) {\n throw new Error(\"Invalid questionnaire request: 'lastAnswer' is required for action 'answer'.\");\n }\n } catch (e: any) {\n log(\"WARN\", \"HTTPGateway\", \"Bad request to /questionnaire (invalid JSON or structure).\", {\n error: e.message,\n bodyPreview: rawRequestBody.substring(0, 250),\n });\n return new Response(\n JSON.stringify({\n error: `Invalid Request: ${e.message}`,\n state: null,\n diagnosticLog: requestLogger.getLogs(),\n }),\n { status: 400, headers: baseHeaders },\n );\n }\n\n const questionnaireAgent = new QuestionnaireAgent(log);\n let qResponse: QuestionnaireResponse;\n try {\n log(\"AUDIT\", \"HTTPGateway\", `Questionnaire action: ${requestBody.action}`, {\n processId: requestBody.processId,\n sessionId: requestBody.sessionId,\n lastAnswerField: requestBody.lastAnswer?.fieldKey,\n });\n\n // Type assertion after validation for state and lastAnswer where needed\n switch (requestBody.action) {\n case \"start\":\n qResponse = await questionnaireAgent.nextStep(\n requestBody.sessionId,\n requestBody.processId,\n requestBody.lastAnswer,\n null,\n );\n break;\n case \"answer\":\n qResponse = await questionnaireAgent.nextStep(\n requestBody.sessionId,\n requestBody.processId,\n requestBody.lastAnswer,\n requestBody.state,\n );\n break;\n case \"back\":\n qResponse = await questionnaireAgent.goBack(\n requestBody.sessionId,\n requestBody.processId,\n requestBody.state,\n );\n break;\n case \"restart\":\n qResponse = await questionnaireAgent.restart(requestBody.sessionId, requestBody.processId);\n break;\n default: // Should not be reached due to prior validation\n qResponse = {\n sessionId: requestBody.sessionId || `ERR-${Utils.generateShortId()}`,\n isCompleted: false,\n error: \"Invalid action specified.\",\n state: requestBody.state || null,\n };\n }\n log(\"INFO\", \"HTTPGateway\", \"Questionnaire step processed.\", {\n sessionId: qResponse.sessionId,\n isDone: qResponse.isCompleted,\n hasError: !!qResponse.error,\n hasFieldError: !!qResponse.fieldError,\n nextQKey: qResponse.nextQuestion?.fieldKey,\n });\n return new Response(JSON.stringify(qResponse), { status: 200, headers: baseHeaders });\n } catch (qError: any) {\n log(\"CRITICAL\", \"HTTPGateway\", `System error during questionnaire processing action '${requestBody.action}'.`, {\n error: qError.message,\n stack: qError.stack?.substring(0, 300),\n });\n return new Response(\n JSON.stringify({\n error: `Internal Questionnaire System Error: ${qError.message}`,\n state: requestBody.state || null,\n diagnosticLog: requestLogger.getLogs(),\n masterIncidentId: requestId,\n }),\n { status: 500, headers: baseHeaders },\n );\n }\n }\n\n // Execution Endpoint\n if (request.method === \"POST\" && url.pathname === \"/execute\") {\n log(\"INFO\", \"HTTPGateway\", \"Processing POST to /execute for AI agent execution.\", { path: url.pathname });\n let validatedInput: OrchestratorInput;\n let rawPayload = \"[NoPayloadRead]\";\n try {\n const payload = await request.json();\n rawPayload = JSON.stringify(payload).substring(0, 500);\n log(\"AUDIT\", \"HTTPGateway\", \"Received payload for /execute.\", { payloadPreview: rawPayload });\n\n // Validate processId exists before full Zod parse\n const processDefExists = getProcessDefinition(payload.processId);\n if (!processDefExists) {\n throw new z.ZodError([{\n path: [\"processId\"],\n message: `Process ID '${payload.processId}' not found or is invalid.`,\n code: z.ZodIssueCode.custom,\n }]);\n }\n validatedInput = OrchestratorInputSchema.parse(payload);\n log(\"INFO\", \"HTTPGateway\", \"Payload for /execute validated successfully.\", {\n processId: validatedInput.processId,\n dataKeys: Object.keys(validatedInput.data),\n });\n } catch (e: any) {\n let errorDetail = \"Invalid input structure or data.\";\n if (e instanceof z.ZodError) {\n errorDetail = e.issues.map(issue => `${issue.path.join(\".\") || \"input\"}: ${issue.message}`).join(\"; \");\n } else {\n errorDetail = e.message;\n }\n log(\"WARN\", \"HTTPGateway\", \"Validation failed for /execute payload.\", {\n error: errorDetail,\n payloadPreview: rawPayload,\n });\n return new Response(\n JSON.stringify({\n error: \"Invalid Input Data.\",\n details: errorDetail,\n diagnosticLog: requestLogger.getLogs(),\n masterIncidentId: `M-VALIDATION-${requestId}`,\n }),\n { status: 400, headers: baseHeaders },\n );\n }\n\n const orchestratorLogger = new AuditLogger(requestId); // Orchestrator uses this request's ID as its MasterIncidentID\n const orchestrator = new CrisisWorkflowOrchestrator(orchestratorLogger);\n const finalSystemResponse: SystemResponse = await orchestrator.initiateProcess(validatedInput);\n\n finalSystemResponse.diagnosticLog = orchestratorLogger.getLogs();\n\n // Server-side render example (if a resultRenderer is defined)\n const processDef = getProcessDefinition(validatedInput.processId);\n if (processDef?.aiAgentConfiguration.resultRenderer && finalSystemResponse.result && !finalSystemResponse.error) {\n try {\n finalSystemResponse.details = processDef.aiAgentConfiguration.resultRenderer(\n finalSystemResponse.result,\n Utils.escapeHTML,\n );\n } catch (renderError: any) {\n log(\"WARN\", \"HTTPGateway\", `Server-side result rendering failed for process ${validatedInput.processId}.`, {\n error: renderError.message,\n });\n // Optionally add this detail to the response if helpful for debugging\n // finalSystemResponse.details = (finalSystemResponse.details || \"\") + ` [RenderError: ${renderError.message}]`;\n }\n }\n\n const responseStatus = finalSystemResponse.error\n ? (finalSystemResponse.error.includes(\"AI output was unparseable\") ? 422 : 500)\n : 200;\n log(\"AUDIT\", \"HTTPGateway\", `/execute workflow finished with status ${responseStatus}.`, {\n masterIncidentId: finalSystemResponse.masterIncidentId,\n hasError: !!finalSystemResponse.error,\n operationStatus: finalSystemResponse.operationStatus,\n });\n return new Response(JSON.stringify(finalSystemResponse), { status: responseStatus, headers: baseHeaders });\n }\n\n log(\"WARN\", \"HTTPGateway\", `Unsupported route or method: ${request.method} ${url.pathname}.`, {});\n return new Response(\n JSON.stringify({\n error: \"Not Found. The requested resource or method is not available on this server.\",\n diagnosticLog: requestLogger.getLogs(),\n masterIncidentId: requestId,\n }),\n { status: 404, headers: baseHeaders },\n );\n } catch (criticalError: any) {\n log(\"CRITICAL\", \"HTTPGateway\", \"Unhandled critical error at HTTP Gateway.\", {\n error: criticalError.message,\n stack: criticalError.stack?.substring(0, 500),\n });\n return new Response(\n JSON.stringify({\n error: \"Internal Server Error.\",\n details: \"An unexpected critical error occurred. The technical team has been notified.\",\n diagnosticLog: requestLogger.getLogs(),\n masterIncidentId: `M-CRITICAL-${requestId}`,\n }),\n { status: 500, headers: baseHeaders },\n );\n }\n}\n\n// Example of how this might be exported or run in a Val Town like environment:\nexport default handleRequest;",[151],"9288ce30-36c2-11f0-a058-9e149126039e","ai_agent_runner.ts","8a87167e-36c2-11f0-b034-9e149126039e",12,["D",1747886975843],"// src/ai_agent_runner.ts\nimport { invokeOpenAIChatCompletion } from \"./openai_service\";\nimport { BaseIncidentContext, LogFunction, ProcessDefinition, TaskInput, TaskOutput } from \"./types\";\n\n/**\n * Executes a defined AI agent based on the provided task input and agent configuration.\n * @param taskInput Contains masterIncidentId, taskId, and payload for the AI.\n * @param logger A logging function instance.\n * @param agentConfig The configuration for the AI agent, including prompt engineering and parsing.\n * @returns A promise resolving to the TaskOutput from the AI agent.\n */\nexport async function executeAIAgent<\n T_Context extends BaseIncidentContext,\n T_Output extends Record,\n>(\n taskInput: TaskInput,\n logger: LogFunction,\n agentConfig: ProcessDefinition[\"aiAgentConfiguration\"],\n): Promise> {\n const { masterIncidentId, taskId, payload } = taskInput;\n const { agentName, promptEngineer, outputSchemaParser, outputPostProcessor } = agentConfig;\n\n logger(\n \"AUDIT\",\n agentName,\n `Executing agent for task ${taskId}.`,\n { inputKeys: Object.keys(payload) },\n masterIncidentId,\n taskId,\n );\n\n try {\n const { systemPrompt, userPrompt } = promptEngineer(payload);\n if (!systemPrompt || !userPrompt) {\n const msg = `Prompt generation failed for task ${taskId}. System or user prompt is empty.`;\n logger(\n \"CRITICAL\",\n agentName,\n msg,\n { systemPromptExists: !!systemPrompt, userPromptExists: !!userPrompt },\n masterIncidentId,\n taskId,\n );\n return { masterIncidentId, correlationId: taskId, result: {} as T_Output, error: `${agentName} Error: ${msg}` };\n }\n\n const rawOpenAIResult = await invokeOpenAIChatCompletion(\n systemPrompt,\n userPrompt,\n masterIncidentId,\n taskId,\n logger,\n );\n if (!rawOpenAIResult) {\n const msg = `LLM returned no content for task ${taskId}.`;\n logger(\"WARN\", agentName, msg, {}, masterIncidentId, taskId);\n return { masterIncidentId, correlationId: taskId, result: {} as T_Output, error: `${agentName} Error: ${msg}` };\n }\n\n let parsedOutput: T_Output;\n try {\n parsedOutput = outputSchemaParser(rawOpenAIResult);\n } catch (parseError: any) {\n const msg = `Failed to parse LLM output for task ${taskId}. Error: ${parseError.message}`;\n logger(\n \"ERROR\",\n agentName,\n msg,\n { rawResponsePreview: rawOpenAIResult.substring(0, 500) },\n masterIncidentId,\n taskId,\n );\n return { masterIncidentId, correlationId: taskId, result: {} as T_Output, error: `${agentName} Error: ${msg}` };\n }\n\n if (outputPostProcessor) {\n try {\n parsedOutput = outputPostProcessor(parsedOutput, payload);\n logger(\n \"INFO\",\n agentName,\n `Output post-processor applied successfully for task ${taskId}.`,\n {},\n masterIncidentId,\n taskId,\n );\n } catch (postProcessError: any) {\n // Log warning but proceed with pre-processed data\n logger(\n \"WARN\",\n agentName,\n `Output post-processor failed for task ${taskId}. Error: ${postProcessError.message}. Proceeding with pre-processed data.`,\n { currentOutputData: parsedOutput },\n masterIncidentId,\n taskId,\n );\n }\n }\n\n logger(\n \"AUDIT\",\n agentName,\n `Agent execution successful for task ${taskId}.`,\n { outputKeys: Object.keys(parsedOutput) },\n masterIncidentId,\n taskId,\n );\n return { masterIncidentId, correlationId: taskId, result: parsedOutput };\n } catch (criticalError: any) {\n const msg = `Critical unhandled error during agent execution for task ${taskId}: ${criticalError.message}`;\n logger(\n \"CRITICAL\",\n agentName,\n msg,\n { errorStack: criticalError.stack?.substring(0, 500) },\n masterIncidentId,\n taskId,\n );\n return {\n masterIncidentId,\n correlationId: taskId,\n result: {} as T_Output,\n error: `${agentName} Critical Failure: ${msg}`,\n };\n }\n}",[157],"pulls","branches",1,"forks","envVars",{"_171":61,"_173":61},"connections",{"_171":61,"_172":61},"count","unfilledCount","emptyCount",{"_42":156,"_32":157,"_30":158,"_132":-5,"_40":41,"_39":159,"_134":24,"_37":192,"_13":136,"_33":34,"_35":161,"_23":24,"_138":-5,"_180":193,"_26":194},{"_42":150,"_32":151,"_30":55,"_132":-5,"_40":41,"_39":152,"_134":24,"_37":189,"_13":136,"_33":34,"_35":154,"_23":24,"_138":-5,"_180":190,"_26":191},{"_42":147,"_32":27,"_30":31,"_132":-5,"_40":41,"_39":14,"_134":24,"_37":186,"_13":61,"_33":34,"_35":36,"_23":24,"_138":-5,"_180":187,"_26":188},{"_42":140,"_32":141,"_30":142,"_132":-5,"_40":41,"_39":143,"_134":24,"_37":183,"_13":136,"_33":34,"_35":145,"_23":24,"_138":-5,"_180":184,"_26":185},{"_42":129,"_32":130,"_30":131,"_132":-5,"_40":41,"_39":133,"_134":24,"_37":179,"_13":136,"_33":34,"_35":137,"_23":24,"_138":-5,"_180":181,"_26":182},["D",1747886903953],"children",[],[130],["D",1747886942900],[],[141],["D",1747887011049],[],[27],["D",1747886814348],[],[151],["D",1747886975843],[],[157],["D",1747886779243],{"_95":94,"_102":98},{"_95":94,"_96":-5,"_97":98,"_18":53,"_99":100,"_101":24},{"_13":84,"_32":85,"_42":41,"_86":43,"_87":-5,"_88":-5,"_89":-5,"_90":-5,"_91":-5,"_92":44,"_93":94},"ctx",{"_77":-5,"_121":232,"_233":234,"_235":236,"_237":24,"_238":24,"_239":24,"_240":57,"_241":-5,"_242":-7,"_243":-7,"_244":61,"_245":24,"_246":24,"_247":-5,"_248":24,"_249":24,"_250":24,"_251":-5},"ENV",{"_203":204,"_205":206,"_207":85,"_208":209,"_210":211,"_212":213,"_214":215,"_216":217,"_218":219,"_220":221,"_222":223,"_224":225,"_226":227,"_228":229,"_230":231},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","d010005ccf3ba21435d5d6fb7028afb409c58b2e","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 · v13