The Reflective Chamber

A private space for thoughtful inquiry into the substance of your daily thoughts.

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Your Reflection

\n Your Entry:\n

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\n\n\n\n`;\n}\n\n// --- API & ROUTING LOGIC ---\n\nconst app = new Hono();\n\n// Middleware for database initialization on all routes.\n// This guarantees the database is ready before any handler logic runs.\napp.use(\"*\", async (c, next) => {\n await initializeDatabase();\n await next();\n});\n\n// Middleware for CORS, allowing the frontend to call the API.\napp.use(\n \"/api/*\",\n cors({\n origin: \"*\", // In a real application, restrict this to the specific val's domain.\n allowMethods: [\"POST\", \"GET\", \"OPTIONS\"],\n }),\n);\n\n/**\n * Utility to extract a JSON object from a string that may contain surrounding text.\n * @param {string} str - The string possibly containing a JSON object.\n * @returns {object} The parsed JSON object.\n * @throws {Error} If no valid JSON object is found.\n */\nfunction extractJson(str) {\n const match = str.match(/\\{.*\\}/s);\n if (!match) {\n throw new Error(\"AI response did not contain a valid JSON object.\");\n }\n try {\n return JSON.parse(match[0]);\n }\n catch (e) {\n console.error(\"Failed to parse extracted JSON:\", e);\n throw new Error(\"AI response contained malformed JSON.\");\n }\n}\n\n// API endpoint to analyze an entry and provide guidance.\napp.post(\"/api/reframe\", async (c) => {\n const { entry_text } = await c.req.json();\n const openai = new OpenAI();\n\n if (!entry_text || typeof entry_text !== \"string\") {\n return c.json({ error: \"A valid 'entry_text' is required.\" }, 400);\n }\n\n try {\n // Step 1: Analyze the entry for cognitive distortions.\n const analysisCompletion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [\n { role: \"system\", content: ANALYZE_ENTRY_PROMPT },\n { role: \"user\", content: entry_text },\n ],\n temperature: 0.2,\n response_format: { type: \"json_object\" },\n });\n\n const analysisResult = extractJson(analysisCompletion.choices[0].message.content);\n const { identified_distortion } = analysisResult;\n console.log(\"AI Analysis:\", analysisResult); // For debugging purposes.\n\n // Step 2: Generate a Socratic question based on the analysis.\n const guidanceCompletion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [\n { role: \"system\", content: GENERATE_GUIDANCE_PROMPT },\n {\n role: \"user\",\n content:\n `The user's entry is: \"${entry_text}\". The identified distortion is: \"${identified_distortion}\". Please formulate a guidance question.`,\n },\n ],\n temperature: 0.7,\n response_format: { type: \"json_object\" },\n });\n\n const guidanceResult = extractJson(guidanceCompletion.choices[0].message.content);\n\n // Persist the entry for potential future use (e.g., user history).\n const entryId = crypto.randomUUID();\n await sqlite.execute({\n sql: `INSERT INTO journal_entries (id, created_at, entry_text, identified_distortion)\n VALUES (:id, :created_at, :entry_text, :identified_distortion)`,\n args: {\n id: entryId,\n created_at: new Date().toISOString(),\n entry_text: entry_text,\n identified_distortion: identified_distortion,\n },\n });\n\n return c.json(guidanceResult);\n }\n catch (error) {\n console.error(\"Reframe endpoint error:\", error);\n return c.json({ error: \"The AI partner is currently unavailable to respond.\" }, 500);\n }\n});\n\n// Main request handler for serving the HTML application.\nexport default async function(req: Request) {\n const url = new URL(req.url);\n\n // Route API requests to Hono.\n if (url.pathname.startsWith(\"/api/\")) {\n return app.fetch(req);\n }\n\n // Handle the root request to serve the UI.\n try {\n const openai = new OpenAI();\n let affirmations = [\n \"A moment of insight is preparing to bloom.\",\n \"Your thoughts are worthy of gentle examination.\",\n \"Clarity is gathering just beyond the horizon.\",\n \"Space is being made for a new perspective.\",\n \"The process of reflection is its own reward.\",\n ];\n\n try {\n // Attempt to fetch fresh affirmations, but have defaults as a fallback.\n const completion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [{ role: \"system\", content: AFFIRMATION_PROMPT }],\n response_format: { type: \"json_object\" },\n });\n const result = extractJson(completion.choices[0].message.content);\n if (result.affirmations && Array.isArray(result.affirmations) && result.affirmations.length > 0) {\n affirmations = result.affirmations;\n }\n }\n catch (e) {\n console.warn(\"Could not fetch fresh affirmations from AI, using defaults:\", e.message);\n }\n\n // Ensure the base URL passed to the client has a trailing slash for correct relative fetch paths.\n const sourceUrl = `https://${url.hostname}${url.pathname}`.replace(/\\/?$/, \"/\");\n return new Response(generateHtml(sourceUrl, affirmations), { headers: { \"Content-Type\": \"text/html\" } });\n }\n catch (error) {\n console.error(\"Main handler error:\", error);\n return new Response(\"The application could not be started.\", { status: 500 });\n }\n}","deleted","label",[98],"permalink","https://www.val.town/x/join/socratic/code/main.tsx","extension","actionData","errors"]