Process Synthesis Engine

1. Input Domain Knowledge

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2. Query the Model

Awaiting process model extraction...

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\n\n\n\n`;\n}\n\n// --- MAIN APPLICATION LOGIC (Hono Router) ---\nconst app = new Hono();\n\n// Serves the main HTML page.\napp.get(\"/\", (c) => {\n const sourceUrl = `https://${new URL(c.req.url).hostname}/`;\n return c.html(generateHtml(sourceUrl));\n});\n\n// Endpoint for extracting the structured process model from text.\napp.post(\"/extract\", async (c) => {\n const openai = new OpenAI();\n try {\n const { domainKnowledge } = await c.req.json();\n\n if (!domainKnowledge || typeof domainKnowledge !== \"string\") {\n return c.json({ error: \"Invalid 'domainKnowledge' provided.\" }, 400);\n }\n\n const initialCompletion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [\n { role: \"system\", content: KNOWLEDGE_EXTRACTOR_PROMPT },\n { role: \"user\", content: domainKnowledge },\n ],\n response_format: { type: \"json_object\" },\n });\n\n const rawContent = initialCompletion.choices[0].message.content;\n let jsonContent = extractJson(rawContent);\n let parsed: ExtractedKnowledge;\n\n try {\n // First attempt to parse the AI's response.\n parsed = JSON.parse(jsonContent);\n } catch (parseError) {\n // If parsing fails, initiate the self-correction mechanism.\n console.log(\n \"Initial JSON parsing failed. Attempting self-correction with AI.\",\n );\n\n const correctionCompletion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [\n { role: \"system\", content: JSON_CORRECTOR_PROMPT },\n { role: \"user\", content: jsonContent }, // Feed the malformed JSON back to the AI.\n ],\n response_format: { type: \"json_object\" },\n });\n\n const correctedRawContent =\n correctionCompletion.choices[0].message.content;\n const correctedJsonContent = extractJson(correctedRawContent);\n parsed = JSON.parse(correctedJsonContent); // Second attempt to parse.\n }\n\n // Final validation of the (potentially corrected) structure.\n if (\n !parsed.processTitle || !Array.isArray(parsed.entities) ||\n !Array.isArray(parsed.rules)\n ) {\n throw new Error(\n \"The AI model returned a malformed or incomplete JSON structure, even after correction.\",\n );\n }\n\n return c.json(parsed);\n } catch (error) {\n console.error(\"Unrecoverable Extraction Error:\", error);\n return c.json(\n { error: error.message || \"An internal error occurred.\" },\n 500,\n );\n }\n});\n\n// Endpoint for answering questions based on the extracted model.\napp.post(\"/query\", async (c) => {\n try {\n const openai = new OpenAI();\n const { knowledge, question } = await c.req.json();\n\n if (!knowledge || !question || typeof question !== \"string\") {\n return c.json(\n { error: \"Invalid 'knowledge' or 'question' provided.\" },\n 400,\n );\n }\n\n const completion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [\n { role: \"system\", content: PROCESS_QA_PROMPT },\n {\n role: \"user\",\n content: `Knowledge: ${\n JSON.stringify(knowledge)\n }\\n\\nQuestion: \"${question}\"`,\n },\n ],\n response_format: { type: \"json_object\" },\n });\n\n const rawContent = completion.choices[0].message.content;\n const jsonContent = extractJson(rawContent);\n const parsed = JSON.parse(jsonContent);\n\n if (!parsed.answer || !parsed.justification) {\n throw new Error(\n \"The AI model returned a malformed JSON structure for the query.\",\n );\n }\n\n return c.json(parsed);\n } catch (error) {\n console.error(\"Query Error:\", error);\n return c.json(\n { error: error.message || \"An internal error occurred.\" },\n 500,\n );\n }\n});\n\nexport default app.fetch;","deleted","label",[98],"permalink","https://www.val.town/x/realtime/process/code/main.ts","extension","actionData","errors"]