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for quoted text, for emphasis, etc. 2. **No Full Document:** Do NOT include \\`\\`, \\`\\`, or \\`\\` tags. Your response must be an HTML snippet that can be directly injected into a \\`
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Welcome to A.I. Shine
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First, tell us about your context. This helps the AI create highly relevant agents for you.
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\n \n \n \n A.I. ShineA.I. Shine\n
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Select Your Domain
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1. Industry
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2. Occupation
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3. Task
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Generated Agent Prompt
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✅ Agent Output
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\n\n\n`;\n}\n\n// --- HONO APPLICATION SETUP ---\nconst app = new Hono();\n\n// --- API ROUTES ---\n\n// 1. Serve the frontend application\napp.get(\"/\", (c: Context) => c.html(generateHtml(c.req.url)));\n\n// 2. Get the initial list of industries\napp.get(\"/api/industries\", (c: Context) => c.json(industries));\n\n// 3. Generate occupations for an industry\napp.post(\"/api/generate/occupations\", async (c: Context) => {\n const { industry, company_context } = await c.req.json();\n if (!industry) return c.json({ error: \"Industry is a required field.\" }, 400);\n try {\n const openai = new OpenAI();\n const completion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [{ role: \"system\", content: DYNAMIC_LIST_GENERATOR_PROMPT }, {\n role: \"user\",\n content: JSON.stringify({ type: \"occupations\", industry, company_context }),\n }],\n response_format: { type: \"json_object\" },\n });\n return c.json(JSON.parse(completion.choices[0].message.content));\n } catch (e) {\n console.error(\"Error in /api/generate/occupations:\", e);\n return c.json({ error: \"AI failed to generate a valid list.\" }, 500);\n }\n});\n\n// 4. Generate tasks for an occupation\napp.post(\"/api/generate/tasks\", async (c: Context) => {\n const { occupation, company_context } = await c.req.json();\n if (!occupation) return c.json({ error: \"Occupation is a required field.\" }, 400);\n try {\n const openai = new OpenAI();\n const completion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [{ role: \"system\", content: DYNAMIC_LIST_GENERATOR_PROMPT }, {\n role: \"user\",\n content: JSON.stringify({ type: \"tasks\", occupation, company_context }),\n }],\n response_format: { type: \"json_object\" },\n });\n return c.json(JSON.parse(completion.choices[0].message.content));\n } catch (e) {\n console.error(\"Error in /api/generate/tasks:\", e);\n return c.json({ error: \"AI failed to generate a valid list.\" }, 500);\n }\n});\n\n// 5. Generate a refined agent prompt\napp.post(\"/api/prompt/dynamic\", async (c: Context) => {\n const { occupation_title, task, company_context } = await c.req.json();\n if (!occupation_title || !task) return c.json({ error: \"occupation_title and task are required.\" }, 400);\n\n const userInput = `Company Context: ${\n JSON.stringify(company_context)\n }\\n\\nOccupation: ${occupation_title}\\n\\nTask: ${task}`;\n\n try {\n const openai = new OpenAI();\n const completion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [{ role: \"system\", content: PROMPT_REFINER_SYSTEM_PROMPT }, { role: \"user\", content: userInput }],\n response_format: { type: \"json_object\" },\n });\n return c.json(JSON.parse(completion.choices[0].message.content));\n } catch (e) {\n console.error(\"Error in /api/prompt/dynamic:\", e);\n return c.json({ error: \"AI failed to generate a valid prompt.\" }, 500);\n }\n});\n\n// 6. Extract input fields from the prompt\napp.post(\"/api/inputs\", async (c: Context) => {\n const { refined_prompt } = await c.req.json();\n if (!refined_prompt) return c.json({ error: \"refined_prompt is required\" }, 400);\n try {\n const openai = new OpenAI();\n const completion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [{ role: \"system\", content: INPUT_EXTRACTOR_SYSTEM_PROMPT }, {\n role: \"user\",\n content: refined_prompt,\n }],\n response_format: { type: \"json_object\" },\n });\n return c.json(JSON.parse(completion.choices[0].message.content));\n } catch (e) {\n console.error(\"Error in /api/inputs:\", e);\n return c.json({ error: \"AI failed to extract inputs.\" }, 500);\n }\n});\n\n// ⭐️ 7. NEW: Generate clarification questions from the prompt\napp.post(\"/api/clarify\", async (c: Context) => {\n const { refined_prompt } = await c.req.json();\n if (!refined_prompt) return c.json({ error: \"refined_prompt is required\" }, 400);\n try {\n const openai = new OpenAI();\n const completion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [{ role: \"system\", content: CLARIFICATION_AGENT_SYSTEM_PROMPT }, {\n role: \"user\",\n content: refined_prompt,\n }],\n response_format: { type: \"json_object\" },\n });\n return c.json(JSON.parse(completion.choices[0].message.content));\n } catch (e) {\n console.error(\"Error in /api/clarify:\", e);\n return c.json({ error: \"AI failed to extract clarification questions.\" }, 500);\n }\n});\n\n// 8. Execute the final agent task (UPDATED)\napp.post(\"/api/execute\", async (c: Context) => {\n const { refined_prompt, user_inputs, clarifications, company_context } = await c.req.json();\n if (!refined_prompt || !user_inputs) return c.json({ error: \"refined_prompt and user_inputs are required\" }, 400);\n\n let finalUserPrompt = refined_prompt;\n for (const [key, value] of Object.entries(user_inputs)) {\n const placeholder = new RegExp(`\\\\{\\\\{\\\\s*${key}\\\\s*\\\\}\\\\}`, \"g\");\n finalUserPrompt = finalUserPrompt.replace(placeholder, String(value));\n }\n\n // Build the strategic guidance section from clarifications\n let strategicGuidance = \"\";\n if (clarifications && Object.keys(clarifications).length > 0) {\n const guidancePoints = Object.entries(clarifications)\n .map(([question, answer]) => `- Q: ${question}\\n - A: ${answer}`)\n .join(\"\\n\");\n strategicGuidance = `\n# USER'S STRATEGIC GUIDANCE\nBefore you begin, consider these additional clarifications and constraints provided by the user. Use this information to guide your approach, tone, and final output.\n${guidancePoints}\n---\n`;\n }\n\n // Prepend the company context and strategic guidance to the final system prompt\n const systemPromptWithContext = `\n# YOUR CONTEXT\nYou are performing this task for the following company. Keep this context in mind for all of your analysis, tone, and final output.\n- Company Name: ${company_context?.company_name}\n- Company Description: ${company_context?.company_description}\n- Primary Goal for this Task: ${company_context?.use_case}\n---\n${strategicGuidance}\n# YOUR TASK BRIEFING\n${finalUserPrompt}\n `;\n\n try {\n const openai = new OpenAI();\n const agentCompletion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [{ role: \"system\", content: systemPromptWithContext }, {\n role: \"user\",\n content:\n \"Proceed with the task as instructed, keeping my company's context and strategic guidance at the forefront of your response.\",\n }],\n });\n const agentOutput = agentCompletion.choices[0].message.content;\n if (!agentOutput) throw new Error(\"The agent returned no content.\");\n\n const htmlCompletion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [{ role: \"system\", content: HTML_FORMATTER_SYSTEM_PROMPT }, { role: \"user\", content: agentOutput }],\n });\n const htmlOutput = htmlCompletion.choices[0].message.content;\n return c.json({ output: htmlOutput });\n } catch (e) {\n console.error(\"Error during execution:\", e);\n return c.json({ error: `AI execution failed: ${e.message}` }, 500);\n }\n});\n\n// --- EXPORT THE VAL ---\nexport default app.fetch;","deleted","label",[98],"permalink","https://www.val.town/x/real/ai-shine/code/main.tsx","extension","actionData","errors"]

for the main title,

Welcome to A.I. Shine

Select Your Domain

Your AI Agent Workspace