🎯 Prompt Improver

Enhance your prompts using AI-powered optimization

\n\n

\n \n Enter your prompt\n \n \n

\n\n

\n \n Improve Prompt\n \n \n Clear\n \n

\n\n

Processing through workers...

\n\n

Improved Prompt:

\n \n

\n \n \n\n \n Copy to Clipboard\n \n

\n\n \n

\n\n \n\n",[],[185,200],[185],{"_104":211,"_95":212,"_156":213,"_158":-5,"_159":141,"_160":214,"_162":118,"_106":215,"_100":177,"_164":165,"_166":-5,"_167":22,"_168":-5,"_169":216,"_98":227},"01936344-f825-11ef-b176-569c3dd06744","shared","fba0c53a-f824-11ef-893a-569c3dd06744",26,["D",1741002329559],[217],{"_104":218,"_95":219,"_156":220,"_158":213,"_159":141,"_160":221,"_162":118,"_106":222,"_100":223,"_164":178,"_166":224,"_167":22,"_168":-5,"_169":225,"_98":226},"d1563ca2-8a63-11f0-8dad-0224a6c84d84","shared_utils.js","f90ee096-f823-11ef-ab78-569c3dd06744",80,["D",1757082176686],5,"// Shared utilities for the modular Prompt Improver system\n\nexport function formatPrompt(prompt) {\n // Clean and format the prompt\n return prompt\n .trim()\n .replace(/\\s+/g, ' ') // Normalize whitespace\n .replace(/\\n{3,}/g, '\\n\\n'); // Limit consecutive newlines\n}\n\nexport function validatePrompt(prompt) {\n if (!prompt || typeof prompt !== 'string') {\n return { valid: false, error: 'Prompt must be a non-empty string' };\n }\n \n if (prompt.length > 10000) {\n return { valid: false, error: 'Prompt exceeds maximum length of 10000 characters' };\n }\n \n if (prompt.trim().length === 0) {\n return { valid: false, error: 'Prompt cannot be empty or only whitespace' };\n }\n \n return { valid: true };\n}\n\nexport function truncatePrompt(prompt, maxLength = 100) {\n if (prompt.length <= maxLength) return prompt;\n return prompt.substring(0, maxLength) + '...';\n}\n\nexport function generateWorkerEndpoint(username, workerName) {\n return `https://api.val.town/v1/run/@${username}/prompt_improver_${workerName}`;\n}\n\nexport function parseValTownResponse(response) {\n // Parse Val Town API responses consistently\n if (!response) return null;\n \n if (typeof response === 'string') {\n return response;\n }\n \n if (response.result !== undefined) {\n return response.result;\n }\n \n if (response.data !== undefined) {\n return response.data;\n }\n \n return response;\n}\n\nexport function createWorkerHistory(step, workerName, prompt) {\n return {\n step,\n worker: workerName,\n prompt: truncatePrompt(prompt, 200),\n timestamp: new Date().toISOString(),\n };\n}\n\nexport function calculatePromptImprovement(original, improved) {\n // Calculate metrics about the improvement\n const originalWords = original.split(/\\s+/).length;\n const improvedWords = improved.split(/\\s+/).length;\n \n return {\n originalLength: original.length,\n improvedLength: improved.length,\n originalWords,\n improvedWords,\n compressionRatio: ((original.length - improved.length) / original.length * 100).toFixed(1),\n wordChange: improvedWords - originalWords,\n };\n}",[],[212,219],[212],{"_104":229,"_95":230,"_156":231,"_158":-5,"_159":141,"_160":232,"_162":118,"_106":233,"_100":32,"_164":165,"_166":-5,"_167":22,"_168":-5,"_169":234,"_98":262},"d0802db0-8a63-11f0-8d20-0224a6c84d84","workers","d0802e50-8a63-11f0-8d20-0224a6c84d84",56,["D",1757082175277],[235,244,253],{"_104":236,"_95":237,"_156":238,"_158":231,"_159":141,"_160":239,"_162":118,"_106":240,"_100":32,"_164":178,"_166":241,"_167":22,"_168":-5,"_169":242,"_98":243},"d1071c80-8a63-11f0-b5cc-0224a6c84d84","clarifier.ts","d1071e88-8a63-11f0-b5cc-0224a6c84d84",68,["D",1757082176094],"// Worker val for clarifying prompts\nimport { OpenAI } from \"https://esm.town/v/std/openai\";\n\nconst openai = new OpenAI();\n\nexport default async function clarifier(prompt: string): Promise {\n try {\n if (!prompt || typeof prompt !== \"string\") {\n return prompt;\n }\n\n const response = await openai.chat.completions.create({\n model: \"gpt-4o-mini\",\n max_tokens: 1000,\n temperature: 0.3,\n messages: [\n {\n role: \"system\",\n content: `You are a prompt clarification specialist. Your role is to:\n1. Identify vague or ambiguous parts of prompts\n2. Add specific details where needed\n3. Define unclear terms\n4. Make implicit requirements explicit\n5. Ensure the prompt has clear objectives\n\nOnly return the clarified prompt, nothing else. If the prompt is already clear, return it unchanged.`,\n },\n {\n role: \"user\",\n content: `Clarify this prompt: ${prompt}`,\n },\n ],\n });\n\n return response.choices[0].message.content || prompt;\n } catch (error) {\n console.error(\"Clarifier error:\", error);\n return prompt;\n }\n}",[],[230,237],{"_104":245,"_95":246,"_156":247,"_158":231,"_159":141,"_160":248,"_162":118,"_106":249,"_100":32,"_164":178,"_166":250,"_167":22,"_168":-5,"_169":251,"_98":252},"d0f9fa8c-8a63-11f0-b0c5-0224a6c84d84","condenser.ts","d0f9fb2c-8a63-11f0-b0c5-0224a6c84d84",66,["D",1757082176086],"// Worker val for condensing prompts\nimport { OpenAI } from \"https://esm.town/v/std/openai\";\n\nconst openai = new OpenAI();\n\nexport default async function condenser(prompt: string): Promise {\n try {\n if (!prompt || typeof prompt !== \"string\") {\n return prompt;\n }\n\n const response = await openai.chat.completions.create({\n model: \"gpt-4o-mini\",\n max_tokens: 800,\n temperature: 0.2,\n messages: [\n {\n role: \"system\",\n content: `You are a prompt condensation specialist. Your role is to:\n1. Remove redundant information\n2. Eliminate unnecessary words\n3. Combine related ideas\n4. Keep essential context and requirements\n5. Make the prompt more concise while maintaining clarity\n\nOnly return the condensed prompt, nothing else. If the prompt is already concise, return it unchanged.`,\n },\n {\n role: \"user\",\n content: `Condense this prompt: ${prompt}`,\n },\n ],\n });\n\n return response.choices[0].message.content || prompt;\n } catch (error) {\n console.error(\"Condenser error:\", error);\n return prompt;\n }\n}",[],[230,246],{"_104":254,"_95":255,"_156":256,"_158":231,"_159":141,"_160":257,"_162":118,"_106":258,"_100":32,"_164":178,"_166":259,"_167":22,"_168":-5,"_169":260,"_98":261},"d1035104-8a63-11f0-9574-0224a6c84d84","includer.ts","d10351d6-8a63-11f0-9574-0224a6c84d84",67,["D",1757082176146],"// Worker val for adding missing details to prompts\nimport { OpenAI } from \"https://esm.town/v/std/openai\";\n\nconst openai = new OpenAI();\n\nexport default async function includer(prompt: string): Promise {\n try {\n if (!prompt || typeof prompt !== \"string\") {\n return prompt;\n }\n\n const response = await openai.chat.completions.create({\n model: \"gpt-4o-mini\",\n max_tokens: 1200,\n temperature: 0.4,\n messages: [\n {\n role: \"system\",\n content: `You are a prompt enhancement specialist. Your role is to:\n1. Add helpful context that might be missing\n2. Include relevant examples when appropriate\n3. Add format specifications if output format is unclear\n4. Include edge cases or constraints that should be considered\n5. Add any industry-standard practices or conventions\n\nOnly return the enhanced prompt, nothing else. If the prompt is already comprehensive, return it unchanged.`,\n },\n {\n role: \"user\",\n content: `Enhance this prompt with missing details: ${prompt}`,\n },\n ],\n });\n\n return response.choices[0].message.content || prompt;\n } catch (error) {\n console.error(\"Includer error:\", error);\n return prompt;\n }\n}",[],[230,255],[230],{"_104":264,"_95":265,"_156":266,"_158":-5,"_159":141,"_160":267,"_162":22,"_106":268,"_100":32,"_164":269,"_166":270,"_167":22,"_168":-5,"_169":271,"_98":272},"d135dd2c-8a63-11f0-8360-0224a6c84d84",".vtignore","d135ddd6-8a63-11f0-8360-0224a6c84d84",75,["D",1757082176477],"file",".git\n.vscode\n.cursorrules\n.DS_Store\nnode_modules\nvendor",[],[265],{"_104":274,"_95":275,"_156":276,"_158":-5,"_159":141,"_160":277,"_162":118,"_106":278,"_100":32,"_164":269,"_166":279,"_167":22,"_168":-5,"_169":280,"_98":281},"d13c51a2-8a63-11f0-b285-0224a6c84d84","DEPLOY.md","d13c5260-8a63-11f0-b285-0224a6c84d84",76,["D",1757082176485],"# Val Town Projects Deployment Guide\n\nThis project uses Val Town Projects architecture for modular deployment.\n\n## Prerequisites\n\n1. **Val Town CLI installed**:\n ```bash\n npm install -g @valtown/cli\n ```\n\n2. **Authenticate with Val Town**:\n ```bash\n vt auth\n ```\n\n3. **Environment Variables**:\n - `OPENAI_API_KEY` - Your OpenAI API key\n - `VAL_TOWN_API_KEY` - Automatically provided by Val Town\n\n## Project Structure\n\n```\nPrompt_Improver/\n├── index.http.ts # Main HTTP handler\n├── val.json # Project configuration\n├── workers/\n│ ├── clarifier.ts # Clarification worker\n│ ├── condenser.ts # Condensation worker\n│ └── includer.ts # Enhancement worker\n├── frontend/\n│ ├── index.html # Frontend UI\n│ └── ...\n├── backend/\n│ ├── backend_logic.js # Orchestration logic\n│ └── ...\n├── shared/\n│ └── shared_utils.js # Shared utilities\n└── README.md\n```\n\n## Deployment Commands\n\n### 1. Deploy the Project\n\nFrom the project root directory:\n\n```bash\ncd /home/toowired/Prompt_Improver\nvt push\n```\n\nThis will:\n- Deploy the entire project as a Val Town Project\n- Create the main HTTP endpoint\n- Bundle all workers, frontend, and backend code\n- Set up proper routing and imports\n\n### 2. Check Deployment Status\n\n```bash\nvt status\n```\n\n### 3. View Logs\n\n```bash\nvt logs\n```\n\n### 4. Development Mode (Optional)\n\nFor local development:\n\n```bash\nvt dev\n```\n\n## Access Your Application\n\nAfter deployment, your application will be available at:\n```\nhttps://[username]-prompt-improver.web.val.run\n```\n\n## API Endpoints\n\n- `GET /` - Frontend interface\n- `POST /api/improve` - Improve prompt endpoint\n- `GET /health` - Health check\n- `GET /api/test-workers` - Test all workers\n\n## Configuration Details\n\nThe `val.json` file configures:\n- Entry point: `index.http.ts`\n- Project type: HTTP\n- Dependencies: Hono, OpenAI, Val Town utils\n- Environment variables required\n- Public visibility\n\n## Benefits of This Approach\n\n1. **Single Deployment**: One `vt push` deploys everything\n2. **Local Workers**: All workers run in the same context (fast)\n3. **Relative Imports**: Clean import paths within the project\n4. **File Serving**: Frontend files served directly from project\n5. **Version Control**: Entire project versioned together\n\n## Troubleshooting\n\n### Authentication Issues\n```bash\nvt auth --reset\n```\n\n### Push Failures\nCheck that:\n- You're in the correct directory\n- `val.json` is valid JSON\n- All imports use correct relative paths\n\n### Runtime Errors\n```bash\nvt logs --tail\n```\n\n## Environment Variables\n\nSet in Val Town dashboard:\n1. Go to your val's settings\n2. Add `OPENAI_API_KEY`\n3. `VAL_TOWN_API_KEY` is automatically provided\n\n## Project Updates\n\nTo update the deployed project:\n```bash\nvt push\n```\n\nThis will update the existing deployment with your changes.\n\n## Local Testing\n\nBefore deployment, test locally:\n```bash\nvt dev\n```\n\nVisit `http://localhost:3000` to test the application.\n\n## File Organization\n\n- **Frontend files** in `/frontend/` are served via `serveFile()`\n- **Workers** are imported directly as TypeScript modules \n- **Shared utilities** available to all components\n- **Backend logic** handles orchestration\n\nThis architecture provides the benefits of modular design while keeping everything in a single deployable project.",[],[275],{"_104":283,"_95":284,"_156":285,"_158":-5,"_159":141,"_160":286,"_162":118,"_106":287,"_100":32,"_164":269,"_166":288,"_167":22,"_168":-5,"_169":289,"_98":290},"d1461c78-8a63-11f0-b0c5-0224a6c84d84","README.md","d1461d40-8a63-11f0-b0c5-0224a6c84d84",78,["D",1757082176573],"# Prompt Improver - Val Town Application\n\nAn AI-powered prompt optimization tool built on Val Town that iteratively improves prompts using multiple specialized AI workers.\n\n## Features\n\n- **Multi-stage Optimization**: Uses three specialized workers (Clarifier, Condenser, Includer) to improve prompts\n- **Iterative Refinement**: Processes prompts through multiple cycles until optimal results are achieved\n- **Final Organization**: Applies a final organization pass to structure the improved prompt\n- **Modern UI**: Clean, responsive interface built with TailwindCSS\n- **Val Town Integration**: Fully compatible with Val Town's serverless platform\n\n## Architecture\n\nThe application consists of:\n\n1. **Main HTTP Handler** (`backend/index.http.ts`): Serves the frontend and API endpoint\n2. **Worker Functions**: Three specialized prompt improvement functions\n - **Clarifier**: Makes prompts clearer and more specific\n - **Condenser**: Removes redundancy while maintaining meaning\n - **Includer**: Adds missing context and relevant details\n3. **Frontend**: Single-page application with real-time prompt improvement\n\n## Deployment to Val Town\n\n### Prerequisites\n\n- Val Town account (paid subscription recommended for API features)\n- OpenAI API key configured in Val Town environment variables\n\n### Step 1: Deploy the Main Val\n\n1. Go to [Val Town](https://val.town)\n2. Create a new HTTP val named `prompt_improver`\n3. Copy the contents of `backend/index.http.ts` to your val\n4. Save and deploy\n\n### Step 2: Configure Environment Variables\n\nIn your Val Town settings, ensure you have:\n- `OPENAI_API_KEY` - Your OpenAI API key\n- `valtown` or `VAL_TOWN_API_KEY` - Automatically set by Val Town\n\n### Step 3: Access Your Application\n\nYour application will be available at:\n```\nhttps://[your-username]-prompt-improver.web.val.run\n```\n\n## API Usage\n\n### Endpoint\n```\nPOST https://[your-username]-prompt-improver.web.val.run/api/improve\n```\n\n### Request Body\n```json\n{\n \"prompt\": \"Your prompt to improve\"\n}\n```\n\n### Response\n```json\n{\n \"result\": \"The improved prompt\",\n \"steps\": 5,\n \"history\": [\n {\n \"step\": 1,\n \"worker\": \"Clarifier\",\n \"prompt\": \"Clarified version...\"\n }\n ]\n}\n```\n\n## Local Development\n\n### Using Deno\n\n1. Install [Deno](https://deno.land/)\n2. Run the application:\n ```bash\n deno run --allow-net --allow-env backend/index.http.ts\n ```\n3. Open http://localhost:8000\n\n### Environment Variables\n\nCreate a `.env` file:\n```\nOPENAI_API_KEY=your_openai_api_key\nVAL_TOWN_API_KEY=your_valtown_api_key\n```\n\n## How It Works\n\n1. **Input**: User provides a prompt to improve\n2. **Processing**: The prompt goes through multiple optimization cycles:\n - Each cycle applies three workers in sequence (Clarifier → Condenser → Includer)\n - Process continues until the prompt stabilizes or reaches maximum iterations\n3. **Organization**: A final pass organizes the improved prompt for clarity\n4. **Output**: Returns the optimized prompt with processing statistics\n\n## Configuration\n\n### Maximum Steps\nThe `MAX_STEPS` constant in the backend controls the maximum number of optimization cycles (default: 10).\n\n### AI Model\nThe application uses OpenAI's `gpt-4o-mini` model by default. You can change this in the worker functions.\n\n### Temperature Settings\nEach worker has different temperature settings optimized for its task:\n- Clarifier: 0.3 (more focused)\n- Condenser: 0.2 (very focused)\n- Includer: 0.4 (slightly creative)\n- Organizer: 0 (deterministic)\n\n## Troubleshooting\n\n### Common Issues\n\n1. **\"Failed to improve prompt\" error**\n - Check your OpenAI API key is correctly configured\n - Ensure you have API credits available\n - Check Val Town logs for detailed error messages\n\n2. **Val not found errors**\n - Ensure the val is deployed with the correct name\n - Check that your Val Town account has the necessary permissions\n\n3. **CORS errors**\n - The application includes CORS headers by default\n - If issues persist, check your browser's security settings\n\n### Debugging\n\nEnable detailed logging by checking the Val Town logs:\n1. Go to your val's page on Val Town\n2. Click on the \"Logs\" tab\n3. Review any error messages or console outputs\n\n## Contributing\n\nFeel free to fork this project and submit improvements. Key areas for enhancement:\n- Additional worker types\n- Support for different AI models\n- Batch processing capabilities\n- Prompt history and favorites\n\n## License\n\nMIT License - Feel free to use and modify as needed.\n\n## Support\n\nFor issues or questions:\n- Create an issue in this repository\n- Contact through Val Town community forums\n- Check Val Town documentation at https://docs.val.town",[],[284],{"_104":292,"_95":293,"_156":294,"_158":-5,"_159":141,"_160":295,"_162":118,"_106":296,"_100":32,"_164":269,"_166":297,"_167":22,"_168":-5,"_169":298,"_98":299},"d0c78480-8a63-11f0-b64d-0224a6c84d84","deno.json","d0c78566-8a63-11f0-b64d-0224a6c84d84",59,["D",1757082175757],"{\n \"$schema\": \"https://raw.githubusercontent.com/denoland/deno/348900b8b79f4a434cab4c74b3bc8d4d2fa8ee74/cli/schemas/config-file.v1.json\",\n \"lock\": false,\n \"compilerOptions\": {\n \"noImplicitAny\": false,\n \"strict\": false,\n \"types\": [\n \"https://www.val.town/types/valtown.d.ts\"\n ],\n \"lib\": [\n \"dom\",\n \"dom.iterable\",\n \"dom.asynciterable\",\n \"deno.ns\",\n \"deno.unstable\"\n ]\n },\n \"lint\": {\n \"files\": {\n \"include\": [\n \"deno:/https/esm.town/**/*\"\n ]\n },\n \"rules\": {\n \"exclude\": [\n \"no-explicit-any\"\n ]\n }\n },\n \"node_modules_dir\": false,\n \"experimental\": {\n \"unstable-node-globals\": true,\n \"unstable-temporal\": true,\n \"unstable-worker-options\": true,\n \"unstable-sloppy-imports\": true\n }\n}",[],[293],{"_104":301,"_95":302,"_156":116,"_158":-5,"_159":141,"_160":303,"_162":22,"_106":304,"_100":177,"_164":205,"_166":305,"_167":22,"_168":-5,"_169":306,"_98":307},"4ac822d4-8a65-11f0-ab5a-0224a6c84d84","index.http.ts",101,["D",1757082809932],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport { Hono } from \"https://esm.sh/hono@4\";\nimport { cors } from \"https://esm.sh/hono@4/cors\";\nimport { readFile, serveFile } from \"https://esm.town/v/std/utils@85-main/index.ts\";\nimport { improvePromptBackend } from \"./backend/backend_logic.js\";\nimport { formatPrompt, validatePrompt } from \"./shared/shared_utils.js\";\n\nconst app = new Hono();\n\n// Enable CORS\napp.use(\"/*\", cors());\n\n// Serve frontend files\napp.get(\"/frontend/*\", c => serveFile(c.req.path, import.meta.url));\napp.get(\"/shared/*\", c => serveFile(c.req.path, import.meta.url));\n\n// Main page - serve the frontend\napp.get(\"/\", async (c) => {\n try {\n const html = await readFile(\"/frontend/index.html\", import.meta.url);\n return c.html(html);\n } catch (error) {\n console.error(\"Error reading frontend file:\", error);\n return c.html(\"

Frontend not found

\", 404);\n }\n});\n\n// API endpoint for improving prompts\napp.post(\"/api/improve\", async (c) => {\n try {\n const body = await c.req.json();\n const { prompt } = body;\n\n // Validate prompt\n const validation = validatePrompt(prompt);\n if (!validation.valid) {\n return c.json({\n error: validation.error,\n }, 400);\n }\n\n // Format the prompt\n const formattedPrompt = formatPrompt(prompt);\n \n // Use the existing backend infrastructure\n const result = await improvePromptBackend(formattedPrompt);\n\n return c.json({\n original: prompt,\n ...result,\n });\n\n } catch (error) {\n console.error(\"Error processing request:\", error);\n return c.json({\n error: \"Internal server error\",\n message: error.message || \"An unexpected error occurred\",\n }, 500);\n }\n});\n\n// Health check\napp.get(\"/health\", (c) => {\n return c.json({\n status: \"healthy\",\n project: \"Prompt Improver\",\n version: \"2.0.0\",\n architecture: \"Val Town Projects\",\n workers: [\"clarifier\", 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