Aetherium AI Workflow Engine

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Configuration

Define the parameters for the autonomous agent.

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Operational Plan

Review the generated execution steps before authorization.

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\n\n\n\n`;\n}\n\n// ============================================================================\n// CORE ENGINE - WORKFLOW PLANNER\n// ============================================================================\n\nclass WorkflowPlanner {\n private openai: OpenAI;\n\n constructor(openai: OpenAI) {\n this.openai = openai;\n }\n\n async createPlanFromTemplate(\n template: Template,\n context: WorkflowContext,\n ): Promise {\n const filledPrompt = template.promptTemplate.replace(\n /\\{\\{(\\w+)\\}\\}/g,\n (_, key) => context[key.trim()] || `[${key.trim()}]`,\n );\n\n const planningPrompt = `\nYou are an expert workflow architect. Based on the user's goal and a predefined template, refine and detail the execution steps.\n\n**Overall Goal:** ${filledPrompt}\n\n**Template Steps:**\n${JSON.stringify(template.stepDefinitions, null, 2)}\n\n**Your Task:**\nFor each template step, create a specific, actionable, and self-contained prompt for another AI agent to execute. The prompt should incorporate relevant details from the user's context.\n\n**User Context:**\n- Company: ${context.company}\n- Industry: ${context.industry}\n- Overall Goal: ${context.goal}\n${Object.entries(context).map(([k, v]) => `- ${k}: ${v}`).join(\"\\n\")}\n\nRespond STRICTLY with a JSON object containing a single key \"steps\". This key should hold an array of step objects, where each object has \"name\", \"type\", \"dependencies\", \"estimatedTime\", and a \"prompt\" field you have generated.\n${GENERATION_STYLE_GUIDE}\n`;\n\n const response = await this.openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [\n { role: \"user\", content: planningPrompt },\n ],\n response_format: { type: \"json_object\" },\n });\n\n const planData = JSON.parse(response.choices[0].message.content);\n\n const steps: WorkflowStep[] = planData.steps.map((\n step: any,\n idx: number,\n ) => ({\n ...step,\n id: `step_${idx + 1}`,\n status: \"pending\",\n metadata: { prompt: step.prompt }, // Nest the generated prompt\n }));\n\n return {\n id: `wf_${Date.now()}`,\n context,\n steps,\n totalEstimatedTime: steps.reduce((sum, s) => sum + s.estimatedTime, 0),\n status: \"draft\",\n createdAt: new Date().toISOString(),\n };\n }\n}\n\n// ============================================================================\n// CORE ENGINE - WORKFLOW EXECUTOR\n// ============================================================================\n\nclass WorkflowExecutor {\n private openai: OpenAI;\n\n constructor(openai: OpenAI) {\n this.openai = openai;\n }\n\n async executeStep(\n step: WorkflowStep,\n planContext: WorkflowContext,\n previousResults: Map,\n ): Promise {\n const dependencyContext = this.buildStepContext(step, previousResults);\n\n const systemMessage = this.getSystemMessageForStepType(\n step.type,\n planContext,\n );\n\n const userPrompt = `\n**Execution Context:**\n- Company: ${planContext.company}\n- Industry: ${planContext.industry}\n- Language: ${planContext.language || \"English\"}\n\n**Previous Step Results (for context):**\n${dependencyContext || \"This is the first step.\"}\n\n---\n\n**Your Assigned Task:**\n${step.metadata.prompt}\n\nExecute this task and provide a comprehensive response. If the task requires structured data, respond in JSON format.\n`;\n\n const response = await this.openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [\n { role: \"system\", content: systemMessage },\n { role: \"user\", content: userPrompt },\n ],\n temperature: 0.5,\n });\n\n const content = response.choices[0].message.content;\n\n return {\n type: step.type,\n content: content,\n };\n }\n\n private buildStepContext(\n step: WorkflowStep,\n previousResults: Map,\n ): string {\n let context = \"\";\n for (const depId of step.dependencies) {\n const result = previousResults.get(depId);\n if (result) {\n context += `\\n--- Results from ${depId} ---\\n`;\n context += typeof result.content === \"string\"\n ? result.content\n : JSON.stringify(result.content, null, 2);\n }\n }\n return context;\n }\n\n private getSystemMessageForStepType(\n type: WorkflowStep[\"type\"],\n context: WorkflowContext,\n ): string {\n const baseMessages = {\n research:\n \"You are a world-class research analyst. Provide comprehensive, accurate, and well-structured information. Cite sources if possible.\",\n analyze:\n \"You are a senior strategic analyst. Identify key insights, patterns, and actionable recommendations from the provided data. Your analysis must be sharp and conclusive.\",\n generate:\n `You are an expert content creator specializing in the ${context.industry} sector. Produce professional, polished, and compelling content that is ready for publication.`,\n refine:\n \"You are a meticulous editor and quality assurance specialist. Review the provided content, correct any errors, and enhance its clarity, impact, and overall quality.\",\n };\n return `${baseMessages[type]} ${GENERATION_STYLE_GUIDE}`;\n }\n}\n\n// ============================================================================\n// TEMPLATE LIBRARY\n// ============================================================================\n\nconst TEMPLATE_LIBRARY: Template[] = [\n {\n id: \"competitor_analysis\",\n name: \"Competitor Intel Report\",\n description:\n \"Deep dive into your competitive landscape with actionable SWOT insights.\",\n category: \"strategy\",\n icon: \"🎯\",\n tags: [\"research\", \"strategy\", \"intelligence\"],\n promptTemplate:\n \"Analyze competitors in the {{industry}} space for {{company}}\",\n requiredContext: [],\n stepDefinitions: [\n {\n name: \"Identify Key Competitors\",\n type: \"research\",\n dependencies: [],\n estimatedTime: 60,\n metadata: {\n prompt:\n \"Identify and list the top 3-5 direct and indirect competitors for the company in the specified industry.\",\n },\n },\n {\n name: \"Product & Pricing Audit\",\n type: \"analyze\",\n dependencies: [\"step_1\"],\n estimatedTime: 90,\n metadata: {\n prompt:\n \"For each identified competitor, analyze their core product offerings, key features, and pricing strategies. Present this as a structured comparison.\",\n },\n },\n {\n name: \"SWOT Matrix Generation\",\n type: \"generate\",\n dependencies: [\"step_2\"],\n estimatedTime: 75,\n metadata: {\n prompt:\n \"Based on the analysis, generate a concise SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis for each competitor relative to our company.\",\n },\n },\n {\n name: \"Executive Synthesis\",\n type: \"generate\",\n dependencies: [\"step_3\"],\n estimatedTime: 90,\n metadata: {\n prompt:\n \"Synthesize all findings into a final executive summary. Highlight key strategic threats and opportunities for our company and provide 3 actionable recommendations.\",\n },\n },\n ],\n estimatedTime: 315,\n successRate: 0.94,\n usageCount: 1247,\n },\n {\n id: \"product_launch\",\n name: \"GTM Launch Protocol\",\n description:\n \"Comprehensive go-to-market strategy and initial asset generation.\",\n category: \"product\",\n icon: \"🚀\",\n tags: [\"marketing\", \"product\", \"launch\"],\n promptTemplate:\n \"Create a product launch plan for {{productName}} targeting {{targetAudience}}\",\n requiredContext: [\n {\n key: \"productName\",\n label: \"Product Name\",\n placeholder: \"e.g., Fusion Reactor Mini\",\n },\n {\n key: \"targetAudience\",\n label: \"Target Audience\",\n placeholder: \"e.g., Early-adopter tech homeowners\",\n },\n ],\n stepDefinitions: [\n {\n name: \"Messaging Framework\",\n type: \"generate\",\n dependencies: [],\n estimatedTime: 70,\n metadata: {\n prompt:\n \"Develop a core messaging framework, including a value proposition, a tagline, and three key benefit pillars for the specified product and audience.\",\n },\n },\n {\n name: \"Channel Strategy Analysis\",\n type: \"analyze\",\n dependencies: [\"step_1\"],\n estimatedTime: 60,\n metadata: {\n prompt:\n \"Based on the target audience, identify the top 5 most effective marketing channels for the initial launch phase. Justify each choice.\",\n },\n },\n {\n name: \"Press Release Draft\",\n type: \"generate\",\n dependencies: [\"step_1\", \"step_2\"],\n estimatedTime: 90,\n metadata: {\n prompt:\n \"Write a compelling press release announcing the product launch. Incorporate the core messaging and structure it for high engagement.\",\n },\n },\n {\n name: \"Social Sequence Generation\",\n type: \"generate\",\n dependencies: [\"step_1\", \"step_3\"],\n estimatedTime: 80,\n metadata: {\n prompt:\n \"Draft a sequence of 5 social media posts (for LinkedIn and Twitter) for the week of the launch. Include text and suggestions for visuals.\",\n },\n },\n ],\n estimatedTime: 360,\n successRate: 0.91,\n usageCount: 892,\n },\n];\n\n// ============================================================================\n// API & APPLICATION LOGIC\n// ============================================================================\n\nconst app = new Hono();\nconst openai = new OpenAI({ apiKey: Deno.env.get(\"OPENAI_API_KEY\") });\n\napp.get(\"/api/templates\", (c) => {\n return c.json({ templates: TEMPLATE_LIBRARY });\n});\n\napp.post(\"/api/workflow/plan\", async (c) => {\n try {\n const { context, templateId } = await c.req.json();\n if (!context || !templateId) {\n return c.json({ error: \"Context and templateId are required\" }, 400);\n }\n\n const template = TEMPLATE_LIBRARY.find((t) => t.id === templateId);\n if (!template) {\n return c.json({ error: \"Template not found\" }, 404);\n }\n\n const planner = new WorkflowPlanner(openai);\n const plan = await planner.createPlanFromTemplate(template, context);\n\n await blob.setJSON(plan.id, plan);\n\n return c.json({ plan });\n } catch (error) {\n console.error(\"Planning error:\", error);\n return c.json(\n { error: \"Failed to create plan\", details: error.message },\n 500,\n );\n }\n});\n\napp.post(\"/api/workflow/:id/start\", async (c) => {\n const workflowId = c.req.param(\"id\");\n const plan: WorkflowPlan = await blob.getJSON(workflowId);\n\n if (!plan) {\n return c.json({ error: \"Workflow not found\" }, 404);\n }\n\n plan.status = \"approved\";\n await blob.setJSON(workflowId, plan);\n\n return c.json({ success: true, workflowId });\n});\n\napp.get(\"/api/workflow/:id/execute\", (c) => {\n const workflowId = c.req.param(\"id\");\n\n return streamSSE(c, async (stream) => {\n const plan: WorkflowPlan = await blob.getJSON(workflowId);\n if (!plan || plan.status !== \"approved\") {\n await stream.writeSSE({\n data: JSON.stringify({\n type: \"workflow_error\",\n error: \"Workflow not found or not approved.\",\n }),\n });\n stream.close();\n return;\n }\n\n plan.status = \"running\";\n await blob.setJSON(workflowId, plan);\n\n const executor = new WorkflowExecutor(openai);\n const results = new Map();\n\n try {\n for (const step of plan.steps) {\n await stream.writeSSE({\n data: JSON.stringify({\n type: \"step_start\",\n step: step.id,\n name: step.name,\n }),\n });\n step.status = \"running\";\n await blob.setJSON(workflowId, plan);\n\n try {\n const result = await executor.executeStep(\n step,\n plan.context,\n results,\n );\n step.status = \"complete\";\n step.result = result;\n results.set(step.id, result);\n await stream.writeSSE({\n data: JSON.stringify({\n type: \"step_complete\",\n step: step.id,\n result,\n }),\n });\n } catch (stepError) {\n console.error(`Error in step ${step.id}:`, stepError);\n step.status = \"error\";\n step.error = stepError.message;\n await stream.writeSSE({\n data: JSON.stringify({\n type: \"step_error\",\n step: step.id,\n error: stepError.message,\n }),\n });\n throw new Error(`Execution failed at step: ${step.name}`);\n } finally {\n await blob.setJSON(workflowId, plan);\n }\n }\n\n plan.status = \"complete\";\n plan.completedAt = new Date().toISOString();\n await blob.setJSON(workflowId, plan);\n\n await stream.writeSSE({\n data: JSON.stringify({ type: \"workflow_complete\", workflowId }),\n });\n } catch (workflowError) {\n plan.status = \"failed\";\n await blob.setJSON(workflowId, plan);\n await stream.writeSSE({\n data: JSON.stringify({\n type: \"workflow_error\",\n error: workflowError.message,\n }),\n });\n } finally {\n stream.close();\n }\n });\n});\n\nexport default async function (req: Request) {\n const url = new URL(req.url);\n if (url.pathname.startsWith(\"/api/\")) {\n return app.fetch(req);\n }\n const sourceUrl = `https://${url.hostname}${url.pathname}`;\n return new Response(generateHtml(sourceUrl), {\n headers: { \"Content-Type\": \"text/html\" },\n });\n}","label","children",[70],"contentHash","42d4a9b2b542ac69a11b57530780a86d4145c5faccdbe63f4852924b9452897e","b4a1fb32-a4da-11f0-b426-0224a6c84d84","f8c59b0a-a4c3-11f0-83d5-0224a6c84d84",["D",1759991968869],41,"// @ts-ignore\nimport { OpenAI } from \"https://esm.town/v/std/openai?v=4\";\n// @ts-ignore\nimport { blob } from \"https://esm.town/v/std/blob?v=11\";\nimport { Hono } from \"npm:hono@4.4.12\";\nimport { streamSSE } from \"npm:hono@4.4.12/streaming\";\n\n// ============================================================================\n// AI BEHAVIORAL GUIDELINES\n// ============================================================================\n\nconst GENERATION_STYLE_GUIDE =\n \"As an AI agent, you must adopt the persona of a senior business strategist. Your analysis and generated content must be articulated with precise, intelligent language suitable for executive review. Avoid clichés, jargon, and speculative phrasing. The objective is to produce output that is insightful, actionable, and indistinguishable from that of a seasoned human expert.\";\n\n// ============================================================================\n// TYPES & INTERFACES\n// ============================================================================\n\ninterface WorkflowContext {\n company: string;\n industry: string;\n goal: string;\n language?: string;\n [key: string]: string; // For template-specific variables\n}\n\ninterface WorkflowStep {\n id: string;\n name: string;\n type: \"research\" | \"analyze\" | \"generate\" | \"refine\";\n status: \"pending\" | \"running\" | \"complete\" | \"error\";\n dependencies: string[];\n estimatedTime: number; // seconds\n result?: any;\n error?: string;\n metadata?: {\n prompt: string;\n [key: string]: any;\n };\n}\n\ninterface WorkflowPlan {\n id: string;\n context: WorkflowContext;\n steps: WorkflowStep[];\n totalEstimatedTime: number;\n status: \"draft\" | \"approved\" | \"running\" | \"complete\" | \"failed\";\n createdAt: string;\n completedAt?: string;\n}\n\ninterface Template {\n id: string;\n name: string;\n description: string;\n category: \"marketing\" | \"sales\" | \"product\" | \"strategy\" | \"operations\";\n icon: string;\n tags: string[];\n promptTemplate: string;\n requiredContext: { key: string; label: string; placeholder: string }[];\n stepDefinitions: Omit[];\n estimatedTime: number;\n successRate: number;\n usageCount: number;\n}\n\n// ============================================================================\n// HTML & FRONTEND\n// ============================================================================\n\nfunction generateHtml(sourceUrl: string) {\n return `\n\n\n \n \n Aetherium AI Workflow Engine\n \n \n \n\n\n\n

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Execution Plan

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Workflow Execution

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\n\n\n\n`;\n}\n\n// ============================================================================\n// CORE ENGINE - WORKFLOW PLANNER\n// ============================================================================\n\nclass WorkflowPlanner {\n private openai: OpenAI;\n\n constructor(openai: OpenAI) {\n this.openai = openai;\n }\n\n async createPlanFromTemplate(\n template: Template,\n context: WorkflowContext,\n ): Promise {\n const filledPrompt = template.promptTemplate.replace(\n /\\{\\{(\\w+)\\}\\}/g,\n (_, key) => context[key.trim()] || `[${key.trim()}]`,\n );\n\n const planningPrompt = `\nYou are an expert workflow architect. Based on the user's goal and a predefined template, refine and detail the execution steps.\n\n**Overall Goal:** ${filledPrompt}\n\n**Template Steps:**\n${JSON.stringify(template.stepDefinitions, null, 2)}\n\n**Your Task:**\nFor each template step, create a specific, actionable, and self-contained prompt for another AI agent to execute. The prompt should incorporate relevant details from the user's context.\n\n**User Context:**\n- Company: ${context.company}\n- Industry: ${context.industry}\n- Overall Goal: ${context.goal}\n${Object.entries(context).map(([k, v]) => `- ${k}: ${v}`).join(\"\\n\")}\n\nRespond STRICTLY with a JSON object containing a single key \"steps\". This key should hold an array of step objects, where each object has \"name\", \"type\", \"dependencies\", \"estimatedTime\", and a \"prompt\" field you have generated.\n${GENERATION_STYLE_GUIDE}\n`;\n\n const response = await this.openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [\n { role: \"user\", content: planningPrompt },\n ],\n response_format: { type: \"json_object\" },\n });\n\n const planData = JSON.parse(response.choices[0].message.content);\n\n const steps: WorkflowStep[] = planData.steps.map((step: any, idx: number) => ({\n ...step,\n id: `step_${idx + 1}`,\n status: \"pending\",\n metadata: { prompt: step.prompt }, // Nest the generated prompt\n }));\n\n return {\n id: `wf_${Date.now()}`,\n context,\n steps,\n totalEstimatedTime: steps.reduce((sum, s) => sum + s.estimatedTime, 0),\n status: \"draft\",\n createdAt: new Date().toISOString(),\n };\n }\n}\n\n// ============================================================================\n// CORE ENGINE - WORKFLOW EXECUTOR\n// ============================================================================\n\nclass WorkflowExecutor {\n private openai: OpenAI;\n\n constructor(openai: OpenAI) {\n this.openai = openai;\n }\n\n async executeStep(\n step: WorkflowStep,\n planContext: WorkflowContext,\n previousResults: Map,\n ): Promise {\n const dependencyContext = this.buildStepContext(step, previousResults);\n\n const systemMessage = this.getSystemMessageForStepType(step.type, planContext);\n\n const userPrompt = `\n**Execution Context:**\n- Company: ${planContext.company}\n- Industry: ${planContext.industry}\n- Language: ${planContext.language || \"English\"}\n\n**Previous Step Results (for context):**\n${dependencyContext || \"This is the first step.\"}\n\n---\n\n**Your Assigned Task:**\n${step.metadata.prompt}\n\nExecute this task and provide a comprehensive response. If the task requires structured data, respond in JSON format.\n`;\n\n const response = await this.openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [\n { role: \"system\", content: systemMessage },\n { role: \"user\", content: userPrompt },\n ],\n temperature: 0.5,\n });\n \n const content = response.choices[0].message.content;\n\n return {\n type: step.type,\n content: content,\n };\n }\n\n private buildStepContext(step: WorkflowStep, previousResults: Map): string {\n let context = \"\";\n for (const depId of step.dependencies) {\n const result = previousResults.get(depId);\n if (result) {\n context += `\\n--- Results from ${depId} ---\\n`;\n context += typeof result.content === \"string\" ? result.content : JSON.stringify(result.content, null, 2);\n }\n }\n return context;\n }\n\n private getSystemMessageForStepType(type: WorkflowStep[\"type\"], context: WorkflowContext): string {\n const baseMessages = {\n research:\n \"You are a world-class research analyst. Provide comprehensive, accurate, and well-structured information. Cite sources if possible.\",\n analyze:\n \"You are a senior strategic analyst. Identify key insights, patterns, and actionable recommendations from the provided data. Your analysis must be sharp and conclusive.\",\n generate:\n `You are an expert content creator specializing in the ${context.industry} sector. Produce professional, polished, and compelling content that is ready for publication.`,\n refine:\n \"You are a meticulous editor and quality assurance specialist. Review the provided content, correct any errors, and enhance its clarity, impact, and overall quality.\",\n };\n return `${baseMessages[type]} ${GENERATION_STYLE_GUIDE}`;\n }\n}\n\n// ============================================================================\n// TEMPLATE LIBRARY\n// ============================================================================\n\nconst TEMPLATE_LIBRARY: Template[] = [\n {\n id: \"competitor_analysis\",\n name: \"Competitor Analysis Report\",\n description: \"Deep dive into your competitive landscape with actionable insights.\",\n category: \"strategy\",\n icon: \"🎯\",\n tags: [\"research\", \"strategy\", \"market-analysis\"],\n promptTemplate: \"Analyze competitors in the {{industry}} space for {{company}}\",\n requiredContext: [],\n stepDefinitions: [\n {\n name: \"Identify Key Competitors\",\n type: \"research\",\n dependencies: [],\n estimatedTime: 60,\n metadata: {\n prompt: \"Identify and list the top 3-5 direct and indirect competitors for the company in the specified industry.\",\n }\n },\n {\n name: \"Analyze Competitor Products & Pricing\",\n type: \"analyze\",\n dependencies: [\"step_1\"],\n estimatedTime: 90,\n metadata: {\n prompt: \"For each identified competitor, analyze their core product offerings, key features, and pricing strategies. Present this as a structured comparison.\",\n }\n },\n {\n name: \"Generate SWOT Analysis\",\n type: \"generate\",\n dependencies: [\"step_2\"],\n estimatedTime: 75,\n metadata: {\n prompt: \"Based on the analysis, generate a concise SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis for each competitor relative to our company.\",\n }\n },\n {\n name: \"Synthesize Executive Report\",\n type: \"generate\",\n dependencies: [\"step_3\"],\n estimatedTime: 90,\n metadata: {\n prompt: \"Synthesize all findings into a final executive summary. Highlight key strategic threats and opportunities for our company and provide 3 actionable recommendations.\",\n }\n },\n ],\n estimatedTime: 315,\n successRate: 0.94,\n usageCount: 1247,\n },\n {\n id: 'product_launch',\n name: 'Product Launch Marketing Plan',\n description: 'Go-to-market strategy and initial marketing materials for a new product.',\n category: 'product',\n icon: '🚀',\n tags: ['gtm', 'marketing', 'product'],\n promptTemplate: 'Create a product launch plan for {{productName}} targeting {{targetAudience}}',\n requiredContext: [\n { key: 'productName', label: 'Product Name', placeholder: 'e.g., Fusion Reactor Mini' },\n { key: 'targetAudience', label: 'Target Audience', placeholder: 'e.g., Early-adopter tech homeowners' }\n ],\n stepDefinitions: [\n { name: 'Define Core Messaging', type: 'generate', dependencies: [], estimatedTime: 70, metadata: { prompt: 'Develop a core messaging framework, including a value proposition, a tagline, and three key benefit pillars for the specified product and audience.' } },\n { name: 'Identify Marketing Channels', type: 'analyze', dependencies: ['step_1'], estimatedTime: 60, metadata: { prompt: 'Based on the target audience, identify the top 5 most effective marketing channels for the initial launch phase. Justify each choice.' } },\n { name: 'Create Launch Blog Post', type: 'generate', dependencies: ['step_1', 'step_2'], estimatedTime: 90, metadata: { prompt: 'Write a compelling 600-word blog post announcing the product launch. Incorporate the core messaging and structure it for high engagement.' } },\n { name: 'Draft Social Media Campaign', type: 'generate', dependencies: ['step_1', 'step_3'], estimatedTime: 80, metadata: { prompt: 'Draft a sequence of 5 social media posts (for LinkedIn and Twitter) for the week of the launch. Include text and suggestions for visuals.' } },\n { name: 'Outline Launch Timeline', type: 'generate', dependencies: ['step_2', 'step_4'], estimatedTime: 60, metadata: { prompt: 'Create a high-level Gantt chart timeline for the two weeks leading up to launch day and the week after. Output as a JSON object.' } },\n ],\n estimatedTime: 360,\n successRate: 0.91,\n usageCount: 892,\n },\n];\n\n\n// ============================================================================\n// API & APPLICATION LOGIC\n// ============================================================================\n\nconst app = new Hono();\nconst openai = new OpenAI({ apiKey: Deno.env.get(\"OPENAI_API_KEY\") });\n\napp.get(\"/api/templates\", (c) => {\n return c.json({ templates: TEMPLATE_LIBRARY });\n});\n\napp.post(\"/api/workflow/plan\", async (c) => {\n try {\n const { context, templateId } = await c.req.json();\n if (!context || !templateId) {\n return c.json({ error: \"Context and templateId are required\" }, 400);\n }\n\n const template = TEMPLATE_LIBRARY.find((t) => t.id === templateId);\n if (!template) {\n return c.json({ error: \"Template not found\" }, 404);\n }\n \n const planner = new WorkflowPlanner(openai);\n const plan = await planner.createPlanFromTemplate(template, context);\n\n await blob.setJSON(plan.id, plan);\n\n return c.json({ plan });\n } catch (error) {\n console.error(\"Planning error:\", error);\n return c.json({ error: \"Failed to create plan\", details: error.message }, 500);\n }\n});\n\napp.post(\"/api/workflow/:id/start\", async (c) => {\n const workflowId = c.req.param(\"id\");\n const plan: WorkflowPlan = await blob.getJSON(workflowId);\n\n if (!plan) {\n return c.json({ error: \"Workflow not found\" }, 404);\n }\n\n plan.status = \"approved\";\n await blob.setJSON(workflowId, plan);\n\n return c.json({ success: true, workflowId });\n});\n\napp.get(\"/api/workflow/:id/execute\", (c) => {\n const workflowId = c.req.param(\"id\");\n \n return streamSSE(c, async (stream) => {\n const plan: WorkflowPlan = await blob.getJSON(workflowId);\n if (!plan || plan.status !== 'approved') {\n await stream.writeSSE({ data: JSON.stringify({ type: 'workflow_error', error: 'Workflow not found or not approved.' }) });\n stream.close();\n return;\n }\n\n plan.status = \"running\";\n await blob.setJSON(workflowId, plan);\n \n const executor = new WorkflowExecutor(openai);\n const results = new Map();\n \n try {\n for (const step of plan.steps) {\n await stream.writeSSE({ data: JSON.stringify({ type: 'step_start', step: step.id, name: step.name }) });\n step.status = 'running';\n await blob.setJSON(workflowId, plan);\n \n try {\n const result = await executor.executeStep(step, plan.context, results);\n step.status = 'complete';\n step.result = result;\n results.set(step.id, result);\n await stream.writeSSE({ data: JSON.stringify({ type: 'step_complete', step: step.id, result }) });\n } catch(stepError) {\n console.error(`Error in step ${step.id}:`, stepError);\n step.status = 'error';\n step.error = stepError.message;\n await stream.writeSSE({ data: JSON.stringify({ type: 'step_error', step: step.id, error: stepError.message }) });\n throw new Error(`Execution failed at step: ${step.name}`);\n } finally {\n await blob.setJSON(workflowId, plan);\n }\n }\n \n plan.status = 'complete';\n plan.completedAt = new Date().toISOString();\n await blob.setJSON(workflowId, plan);\n \n await stream.writeSSE({ data: JSON.stringify({ type: 'workflow_complete', workflowId }) });\n } catch(workflowError) {\n plan.status = 'failed';\n await blob.setJSON(workflowId, plan);\n await stream.writeSSE({ data: JSON.stringify({ type: 'workflow_error', error: workflowError.message }) });\n } finally {\n stream.close();\n }\n });\n});\n\nexport default async function(req: Request) {\n const url = new URL(req.url);\n if (url.pathname.startsWith(\"/api/\")) {\n return app.fetch(req);\n }\n const sourceUrl = `https://${url.hostname}${url.pathname}`;\n return new Response(generateHtml(sourceUrl), { headers: { \"Content-Type\": \"text/html\" } 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