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, etc.). 2. Do NOT include \\`\\`, \\`\\`, or \\`\\` tags. 3. Do NOT include any CSS, \\`\n\n\n\n
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\n Welcome to Agentive\n
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\n First, tell us about your context. This helps the AI create highly relevant agents for you.\n
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\n \n Company Name\n \n \n
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\n \n What does your company do?\n \n \n
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\n \n How will you use these AI agents?\n \n \n
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Agentive
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Agentive
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\n\n \n\n`;\n}\n\n// --- HONO APPLICATION SETUP ---\nconst app = new Hono();\n\n// --- API ROUTES ---\n\napp.get(\"/\", (c: Context) => c.html(generateHtml(c.req.url)));\napp.get(\"/api/industries\", (c: Context) => c.json(industries));\n\napp.post(\"/api/generate/occupations\", async (c: Context) => {\n const { industry, company_context } = await c.req.json<\n GenerateOccupationsBody\n >();\n if (!industry) return c.json({ error: \"Industry 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: DYNAMIC_LIST_GENERATOR_PROMPT }, {\n role: \"user\",\n content: JSON.stringify({\n type: \"occupations\",\n industry,\n company_context,\n }),\n }],\n response_format: { type: \"json_object\" },\n });\n return c.json(JSON.parse(completion.choices[0].message.content));\n } catch (e) {\n return c.json({ error: \"AI failed to generate occupations.\" }, 500);\n }\n});\n\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 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: 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 return c.json({ error: \"AI failed to generate tasks.\" }, 500);\n }\n});\n\napp.post(\"/api/prompt/dynamic\", async (c: Context) => {\n const { occupation_title, task, company_context } = await c.req.json<\n DynamicPromptBody\n >();\n if (!occupation_title || !task) {\n return c.json({ error: \"Occupation 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 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 }, {\n role: \"user\",\n content: userInput,\n }],\n response_format: { type: \"json_object\" },\n });\n return c.json(JSON.parse(completion.choices[0].message.content));\n } catch (e) {\n return c.json({ error: \"AI failed to generate prompt.\" }, 500);\n }\n});\n\napp.post(\"/api/inputs\", async (c: Context) => {\n const { refined_prompt } = await c.req.json();\n if (!refined_prompt) {\n return c.json({ error: \"refined_prompt is required\" }, 400);\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: 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 return c.json({ error: \"AI failed to extract inputs.\" }, 500);\n }\n});\n\napp.post(\"/api/clarify\", async (c: Context) => {\n const { refined_prompt } = await c.req.json();\n if (!refined_prompt) {\n return c.json({ error: \"refined_prompt is required\" }, 400);\n }\n try {\n const openai = new OpenAI();\n const completion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [\n { role: \"system\", content: CLARIFICATION_AGENT_SYSTEM_PROMPT },\n { role: \"user\", 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 return c.json({ error: \"AI failed to extract clarifications.\" }, 500);\n }\n});\n\napp.post(\"/api/execute-stream\", async (c: Context) => {\n const { refined_prompt, user_inputs, clarifications, company_context } =\n await c.req.json();\n if (!refined_prompt || !user_inputs) {\n return c.json({ error: \"Prompt and inputs are required\" }, 400);\n }\n\n let finalUserPrompt = refined_prompt;\n for (const [key, value] of Object.entries(user_inputs)) {\n finalUserPrompt = finalUserPrompt.replace(\n new RegExp(`\\\\{\\\\{\\\\s${key}\\\\s\\\\}\\\\}`, \"g\"),\n String(value),\n );\n }\n\n let strategicGuidance = \"\";\n if (clarifications && Object.keys(clarifications).length > 0) {\n const guidancePoints = Object.entries(clarifications).map(([q, a]) =>\n `- Q: ${q}\\n - A: ${a}`\n ).join(\"\\n\");\n strategicGuidance = `# USER'S STRATEGIC GUIDANCE\\n${guidancePoints}\\n---\\n`;\n }\n\n const systemPromptWithContext =\n `# YOUR CONTEXT\\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}# YOUR TASK BRIEFING\\n${finalUserPrompt}`;\n\n try {\n const openai = new OpenAI();\n const agentStream = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [{ role: \"system\", content: systemPromptWithContext }, {\n role: \"user\",\n content: \"Proceed with the task.\",\n }],\n stream: true,\n });\n\n return streamText(c, async (stream) => {\n for await (const part of agentStream) {\n const content = part.choices[0]?.delta?.content || \"\";\n if (content) await stream.write(content);\n }\n });\n } catch (e) {\n return c.body(\"AI execution failed.\", 500);\n }\n});\n\napp.post(\"/api/format-html\", async (c: Context) => {\n const { raw_text } = await c.req.json();\n if (!raw_text) return c.json({ error: \"raw_text is required\" }, 400);\n try {\n const openai = new OpenAI();\n const htmlCompletion = await openai.chat.completions.create({\n model: \"gpt-4o-mini\", // Using a faster model for simple formatting\n messages: [{ role: \"system\", content: HTML_FORMATTER_SYSTEM_PROMPT }, {\n role: \"user\",\n content: raw_text,\n }],\n });\n const htmlOutput = htmlCompletion.choices[0].message.content;\n return c.json({ output: htmlOutput });\n } catch (e) {\n return c.json({ error: `Formatting failed: ${e.message}` }, 500);\n }\n});\n\n// --- EXPORT THE VAL ---\nexport default app.fetch;","deleted","label","agentive",[98],"permalink","https://www.val.town/x/join/Agentive/code/main.tsx","extension","actionData","errors"]