Persistent AI Journey

Connecting to journey stream...

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\n\n \n\n`;\n}\n\nexport default async function(req: Request) {\n const url = new URL(req.url);\n const action = url.searchParams.get(\"action\");\n\n if (req.method === \"POST\" && action === \"getJourney\") {\n try {\n const after_id = parseInt(url.searchParams.get(\"after_id\") || \"0\", 10);\n\n const { rows: nextJourneyRows } = await sqlite.execute({\n sql: \"SELECT id, journey_data FROM journeys WHERE id > ? ORDER BY id ASC LIMIT 1\",\n args: [after_id],\n });\n const nextJourneyRow = nextJourneyRows[0];\n\n // *** THIS IS THE FIX ***\n // This single, robust check validates the entire structure of the row from the database.\n if (\n nextJourneyRow\n && typeof nextJourneyRow === \"object\"\n && \"id\" in nextJourneyRow\n && \"journey_data\" in nextJourneyRow\n && typeof nextJourneyRow.journey_data === \"string\"\n ) {\n const parsed = JSON.parse(nextJourneyRow.journey_data);\n return new Response(\n JSON.stringify({\n id: nextJourneyRow.id,\n journey: parsed.journey,\n }),\n { headers: { \"Content-Type\": \"application/json\" } },\n );\n } else if (nextJourneyRow) {\n // If the row exists but is malformed, log it and let the code proceed\n // to generate a new journey, effectively self-healing.\n console.error(\"Found a corrupt or malformed row in the database:\", nextJourneyRow);\n }\n\n const { rows: lastGenRows } = await sqlite.execute(\"SELECT created_at FROM journeys ORDER BY id DESC LIMIT 1\");\n const lastGen = lastGenRows[0];\n\n const thirtySeconds = 30 * 1000;\n const now = Date.now();\n\n if (lastGen && (now - (lastGen.created_at as number) < thirtySeconds)) {\n return new Response(\n JSON.stringify({\n status: \"wait\",\n retry_after: thirtySeconds - (now - (lastGen.created_at as number)),\n }),\n { headers: { \"Content-Type\": \"application/json\" } },\n );\n }\n\n const openai = new OpenAI();\n const completion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [\n { role: \"system\", content: JOURNEY_GENERATOR_PROMPT },\n { role: \"user\", content: \"Generate a new visual conceptual journey based on the provided context.\" },\n ],\n temperature: 0.9,\n response_format: { type: \"json_object\" },\n });\n\n const journeyData = completion.choices[0].message.content;\n const parsedData = JSON.parse(journeyData);\n if (!parsedData.journey) throw new Error(\"AI response did not contain 'journey' key.\");\n\n const { lastInsertRowid } = await sqlite.execute({\n sql: \"INSERT INTO journeys (journey_data, created_at) VALUES (?, ?)\",\n args: [journeyData, now],\n });\n\n const { rows: countRows } = await sqlite.execute(\"SELECT COUNT(*) as count FROM journeys\");\n const count = Number(countRows[0]?.count || 0);\n\n if (count > 10) {\n await sqlite.execute({\n sql: `DELETE FROM journeys WHERE id IN (SELECT id FROM journeys ORDER BY created_at ASC LIMIT ?)`,\n args: [count - 10],\n });\n }\n\n return new Response(\n JSON.stringify({\n id: lastInsertRowid,\n journey: parsedData.journey,\n }),\n { headers: { \"Content-Type\": \"application/json\" } },\n );\n } catch (error) {\n console.error(\"AI Journey Handler Error:\", error);\n return new Response(\n JSON.stringify({ error: `The AI failed to generate or retrieve the journey. Details: ${error.message}` }),\n {\n status: 500,\n headers: { \"Content-Type\": \"application/json\" },\n },\n );\n }\n }\n\n const sourceUrl = `https://${url.hostname}${url.pathname}`;\n return new Response(generateHtml(sourceUrl), { headers: { \"Content-Type\": \"text/html\" } });\n}","deleted","label",[98],"permalink","https://www.val.town/x/join/wordstream/code/main.tsx","extension","actionData","errors"]