🤖 Val Town TDD Generator

\n \n {error && (\n

\n Error: {error}\n

\n )}\n {implementationResult && (\n

Generated Implementation

\n            {JSON.stringify(implementationResult, null, 2)}\n

\n )}\n

\n );\n}\n\nwindow.initClient = function() {\n const rootElement = document.getElementById(\"root\");\n if (rootElement) {\n const root = createRoot(rootElement);\n root.render();\n }\n};\n\nif (typeof document !== \"undefined\") {\n window.initClient();\n}\n\nexport default async function server(request: Request): Promise {\n // Handle GET requests by serving the HTML\n if (request.method === 'GET') {\n return new Response(`\n \n \n \n \n \n Val Town TDD Generator\n \n \n \n

\n \n \n \n \n \n `, {\n headers: {\n 'Content-Type': 'text/html',\n 'Access-Control-Allow-Origin': '*'\n }\n });\n }\n\n // CORS handling\n if (request.method === 'OPTIONS') {\n return new Response(null, {\n headers: {\n 'Access-Control-Allow-Origin': '*',\n 'Access-Control-Allow-Methods': 'POST, GET, OPTIONS',\n 'Access-Control-Allow-Headers': 'Content-Type, Accept',\n 'Access-Control-Max-Age': '86400'\n }\n });\n }\n\n // Ensure POST request\n if (request.method !== 'POST') {\n return new Response('Method Not Allowed', { \n status: 405,\n headers: {\n 'Access-Control-Allow-Origin': '*',\n 'Content-Type': 'text/plain'\n }\n });\n }\n\n try {\n // Dynamic imports for SQLite and OpenAI\n const [{ sqlite }, { OpenAI }] = await Promise.all([\n import(\"https://esm.town/v/stevekrouse/sqlite\"),\n import(\"https://esm.town/v/std/openai\")\n ]);\n\n const openai = new OpenAI();\n const SPECIFICATIONS_TABLE = \"val_town_agent_specifications\";\n const IMPLEMENTATIONS_TABLE = \"val_town_agent_implementations\";\n\n // Create implementations table if not exists\n await sqlite.execute(`\n CREATE TABLE IF NOT EXISTS ${IMPLEMENTATIONS_TABLE} (\n id TEXT PRIMARY KEY,\n spec_id TEXT,\n tool_name TEXT,\n test_code TEXT,\n implementation_code TEXT,\n size_bytes INTEGER,\n status TEXT DEFAULT 'pending',\n created_at DATETIME DEFAULT CURRENT_TIMESTAMP\n )\n `);\n\n // Parse request body\n const { specId } = await request.json();\n\n if (!specId) {\n throw new Error('Specification ID is required');\n }\n\n // Retrieve specification details\n const specResult = await sqlite.execute(`\n SELECT * FROM ${SPECIFICATIONS_TABLE} WHERE id = ?\n `, [specId]);\n\n if (specResult.rows.length === 0) {\n throw new Error(`Specification with ID ${specId} not found`);\n }\n\n const specification = specResult.rows[0];\n const scenarios = JSON.parse(specification.scenarios);\n\n // TDD Generator Prompt (GPT-4o-mini)\n const tddPrompt = `You are a Test-Driven Development expert creating a Unix-style tool. \nIMPORTANT: Generate a JSON response with implementation details.\n\nTool Context:\n- Name: ${specification.tool_name}\n- Feature: ${specification.feature}\n\nScenarios to Cover:\n${scenarios.map(scenario => \n `- ${scenario.description}\n Given: ${scenario.given}\n When: ${scenario.when}\n Then: ${scenario.then}`\n).join('\\n')}\n\nTASK: \n1. Generate a TypeScript implementation for the tool\n2. Create comprehensive unit and integration tests\n3. Ensure the implementation is under 15KB\n4. Follow Unix philosophy: do one thing well\n5. Use functional programming principles\n6. Provide clear, concise, and efficient code\n7. MUST return a valid JSON object with implementation details\n\nRespond STRICTLY in this JSON format:\n{\n \"implementation_code\": \"string (TypeScript code)\",\n \"test_code\": \"string (Jest/Deno test code)\",\n \"size_bytes\": number\n}\n\nEnsure the response is a valid JSON object that can be parsed directly.`;\n\n // Generate implementation using GPT-4o-mini\n const completion = await openai.chat.completions.create({\n messages: [\n { \n role: \"user\", \n content: tddPrompt \n }\n ],\n model: \"gpt-4o-mini\",\n response_format: { type: \"json_object\" }\n });\n\n // Parse the response\n const implementationData = JSON.parse(completion.choices[0].message.content);\n const implementationId = nanoid();\n\n // Validate implementation size\n const implementationSizeBytes = new TextEncoder().encode(\n implementationData.implementation_code + \n implementationData.test_code\n ).length;\n\n if (implementationSizeBytes > 15 * 1024) {\n throw new Error(`Implementation exceeds 15KB limit: ${implementationSizeBytes} bytes`);\n }\n\n // Store implementation in SQLite\n await sqlite.execute(`\n INSERT INTO ${IMPLEMENTATIONS_TABLE} \n (id, spec_id, tool_name, test_code, implementation_code, size_bytes, status) \n VALUES (?, ?, ?, ?, ?, ?, 'completed')\n `, [\n implementationId, \n specId, \n specification.tool_name,\n implementationData.test_code,\n implementationData.implementation_code,\n implementationSizeBytes\n ]);\n\n return new Response(JSON.stringify({\n implementationId,\n specId,\n ...implementationData,\n size_bytes: implementationSizeBytes\n }), {\n headers: {\n 'Content-Type': 'application/json',\n 'Access-Control-Allow-Origin': '*'\n }\n });\n } catch (error) {\n console.error('TDD Generator Error:', error);\n\n return new Response(JSON.stringify({ \n error: 'TDD Generator Failed', \n details: error.toString(),\n stack: error.stack\n }), { \n status: 500,\n headers: {\n 'Content-Type': 'application/json',\n 'Access-Control-Allow-Origin': '*'\n }\n });\n }\n}\n\nconst css = `\nbody {\n font-family: system-ui, sans-serif;\n line-height: 1.6;\n background-color: #f4f4f4;\n margin: 0;\n padding: 0;\n}\n#root {\n max-width: 800px;\n margin: 0 auto;\n padding: 20px;\n}\ninput {\n width: 100%;\n padding: 10px;\n margin-bottom: 10px;\n border: 1px solid #ddd;\n border-radius: 4px;\n}\nbutton {\n background-color: #4CAF50;\n color: white;\n padding: 10px 15px;\n border: none;\n border-radius: 4px;\n cursor: pointer;\n transition: background-color 0.3s;\n}\nbutton:hover {\n background-color: #45a049;\n}\nbutton:disabled {\n background-color: #cccccc;\n cursor: not-allowed;\n}\npre {\n white-space: pre-wrap;\n word-wrap: break-word;\n}\n`;","deleted","label",[125],"3f634a0c-2798-11f0-9d52-569c3dd06744","README.md","3f634a8e-2798-11f0-9d52-569c3dd06744",1,["D",1731970165610],"# LLM-Safe Fork of @std/sqlite\n\nWe found that LLMs have trouble with the inputs and outputs of our @std/sqlite method.\n\n1. It expects the input to be `(sql: string, args: any[])` but it's `{ sql: string, args: any[] }`\n2. 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