Hi

\"\n});\n```\n\n## Val Town Utility Functions\n\nVal Town provides several utility functions to help with common project tasks.\n\n### Importing Utilities\n\nAlways import utilities with version pins to avoid breaking changes:\n\n```ts\nimport { parseProject, readFile, serveFile } from \"https://esm.town/v/std/utils@85-main/index.ts\";\n```\n\n### Available Utilities\n\n\n#### **serveFile** - Serve project files with proper content types\n\nFor example, in Hono:\n\n```ts\n// serve all files in frontend/ and shared/\napp.get(\"/frontend/*\", c => serveFile(c.req.path, import.meta.url));\napp.get(\"/shared/*\", c => serveFile(c.req.path, import.meta.url));\n```\n\n#### **readFile** - Read files from within the project:\n\n```ts\n// Read a file from the project\nconst fileContent = await readFile(\"/frontend/index.html\", import.meta.url);\n```\n\n#### **listFiles** - List all files in the project\n\n```ts\nconst files = await listFiles(import.meta.url);\n```\n\n#### **parseProject** - Extract information about the current project from import.meta.url\n\nThis is useful for including info for linking back to a val, ie in \"view source\" urls:\n\n```ts\nconst projectVal = parseProject(import.meta.url);\nconsole.log(projectVal.username); // Owner of the project\nconsole.log(projectVal.name); // Project name\nconsole.log(projectVal.version); // Version number\nconsole.log(projectVal.branch); // Branch name\nconsole.log(projectVal.links.self.project); // URL to the project page\n```\n\nHowever, it's *extremely importing* to note that `parseProject` and other Standard Library utilities ONLY RUN ON THE SERVER.\nIf you need access to this data on the client, run it in the server and pass it to the client by splicing it into the HTML page\nor by making an API request for it.\n\n## Val Town Platform Specifics\n\n- **Redirects:** Use `return new Response(null, { status: 302, headers: { Location: \"/place/to/redirect\" }})` instead of `Response.redirect` which is broken\n- **Images:** Avoid external images or base64 images. Use emojis, unicode symbols, or icon fonts/libraries instead\n- **AI Image:** To inline generate an AI image use: `

`\n- **Storage:** DO NOT use the Deno KV module for storage\n- **Browser APIs:** DO NOT use the `alert()`, `prompt()`, or `confirm()` methods\n- **Weather Data:** Use open-meteo for weather data (doesn't require API keys) unless otherwise specified\n- **View Source:** Add a view source link by importing & using `import.meta.url.replace(\"ems.sh\", \"val.town)\"` (or passing this data to the client) and include `target=\"_top\"` attribute\n- **Error Debugging:** Add `` to HTML to capture client-side errors\n- **Error Handling:** Only use try...catch when there's a clear local resolution; Avoid catches that merely log or return 500s. Let errors bubble up with full context\n- **Environment Variables:** Use `Deno.env.get('keyname')` when you need to, but generally prefer APIs that don't require keys\n- **Imports:** Use `https://esm.sh` for npm and Deno dependencies to ensure compatibility on server and browser\n- **Storage Strategy:** Only use backend storage if explicitly required; prefer simple static client-side sites\n- **React Configuration:** When using React libraries, pin versions with `?deps=react@18.2.0,react-dom@18.2.0` and start the file with `/** @jsxImportSource https://esm.sh/react@18.2.0 */`\n- Ensure all React dependencies and sub-dependencies are pinned to the same version\n- **Styling:** Default to using TailwindCSS via `` unless otherwise specified\n\n## Project Structure and Design Patterns\n\n### Recommended Directory Structure\n```\n├── backend/\n│ ├── database/\n│ │ ├── migrations.ts # Schema definitions\n│ │ ├── queries.ts # DB query functions\n│ │ └── README.md\n│ └── routes/ # Route modules\n│ ├── [route].ts\n│ └── static.ts # Static file serving\n│ ├── index.ts # Main entry point\n│ └── README.md\n├── frontend/\n│ ├── components/\n│ │ ├── App.tsx\n│ │ └── [Component].tsx\n│ ├── favicon.svg\n│ ├── index.html # Main HTML template\n│ ├── index.tsx # Frontend JS entry point\n│ ├── README.md\n│ └── style.css\n├── README.md\n└── shared/\n ├── README.md\n └── utils.ts # Shared types and functions\n```\n\n### Backend (Hono) Best Practices\n\n- Hono is the recommended API framework\n- Main entry point should be `backend/index.ts`\n- **Static asset serving:** Use the utility functions to read and serve project files:\n ```ts\n import { readFile, serveFile } from \"https://esm.town/v/std/utils@85-main/index.ts\";\n \n // serve all files in frontend/ and shared/\n app.get(\"/frontend/*\", c => serveFile(c.req.path, import.meta.url));\n app.get(\"/shared/*\", c => serveFile(c.req.path, import.meta.url));\n \n // For index.html, often you'll want to bootstrap with initial data\n app.get(\"/\", async c => {\n let html = await readFile(\"/frontend/index.html\", import.meta.url);\n \n // Inject data to avoid extra round-trips\n const initialData = await fetchInitialData();\n const dataScript = ``;\n \n html = html.replace(\"\", `${dataScript}`);\n return c.html(html);\n });\n ```\n- Create RESTful API routes for CRUD operations\n- Always include this snippet at the top-level Hono app to re-throwing errors to see full stack traces:\n ```ts\n // Unwrap Hono errors to see original error details\n app.onError((err, c) => {\n throw err;\n });\n ```\n\n### Database Patterns\n- Run migrations on startup or comment out for performance\n- Change table names when modifying schemas rather than altering\n- Export clear query functions with proper TypeScript typing\n\n## Common Gotchas and Solutions\n\n1. **Environment Limitations:** \n - Val Town runs on Deno in a serverless context, not Node.js\n - Code in `shared/` must work in both frontend and backend environments\n - Cannot use `Deno` keyword in shared code\n - Use `https://esm.sh` for imports that work in both environments\n\n2. **SQLite Peculiarities:**\n - Limited support for ALTER TABLE operations\n - Create new tables with updated schemas and copy data when needed\n - Always run table creation before querying\n\n3. **React Configuration:**\n - All React dependencies must be pinned to 18.2.0\n - Always include `@jsxImportSource https://esm.sh/react@18.2.0` at the top of React files\n - Rendering issues often come from mismatched React versions\n\n4. **File Handling:**\n - Val Town only supports text files, not binary\n - Use the provided utilities to read files across branches and forks\n - For files in the project, use `readFile` helpers\n\n5. **API Design:**\n - `fetch` handler is the entry point for HTTP vals\n - Run the Hono app with `export default app.fetch // This is the entry point for HTTP vals`\n\n",[],[199],{"_105":207,"_97":208,"_161":209,"_163":-5,"_164":146,"_165":210,"_167":119,"_107":211,"_101":33,"_169":183,"_171":212,"_172":22,"_173":-5,"_174":213,"_100":214},"cbab981c-8ecb-11f0-9255-0224a6c84d84","README.md","cbab98a8-8ecb-11f0-9255-0224a6c84d84",5,["D",1757566639422],"# Food Calorie Tracker - Val Town Version\n\nA web-based food calorie tracker that estimates calories using AI and logs them to Notion.\n\n## Features\n\n- 🍎 Web interface for entering food descriptions\n- 🤖 AI-powered calorie estimation using OpenAI GPT-4o\n- 📊 Automatic logging to Notion database\n- 🎨 Clean, responsive UI with TailwindCSS\n\n## Setup\n\n### Environment Variables\n\nSet these environment variables in your Val Town account:\n\n- `NOTION_OAUTH_TOKEN` - Your Notion OAuth token\n- `OPENAI_API_KEY` - Your OpenAI API key (handled by Val Town's OpenAI integration)\n\n### Notion Database\n\nYour Notion database should have these properties:\n- **Name** (Title) - Food name\n- **Calories** (Number) - Calorie count\n- **Date** (Date) - Entry date (auto-populated)\n\nUpdate the `notionFoodDbId` in `notion.ts` with your database ID.\n\n## Usage\n\n1. Visit the HTTP endpoint URL for your Val Town\n2. Enter a food description (e.g., \"RT Rotisserie bowl with chicken and beet tahini sauce\")\n3. Click \"Estimate Calories & Log\"\n4. View the AI's calorie estimate and confirmation of Notion logging\n\n## Architecture\n\n- `main.http.ts` - HTTP trigger with web interface and AI integration\n- `notion.ts` - Notion API integration for logging food entries\n- Uses Val Town's OpenAI integration for GPT-4o access\n- Responsive web UI built with TailwindCSS\n\n## Migration from Original\n\nThis version has been migrated from a Bun CLI script to a Val Town HTTP trigger:\n\n- ✅ Uses Val Town's OpenAI integration instead of direct OpenAI SDK\n- ✅ Environment variables use `Deno.env.get()` instead of `process.env`\n- ✅ ESM imports from `https://esm.sh` for compatibility\n- ✅ Web interface instead of CLI\n- ✅ HTTP trigger following Val Town conventions\n",[],[208],{"_105":216,"_97":217,"_161":218,"_163":-5,"_164":146,"_165":219,"_167":119,"_107":220,"_101":33,"_169":183,"_171":221,"_172":22,"_173":-5,"_174":222,"_100":223},"cba33c80-8ecb-11f0-aef3-0224a6c84d84","deno.json","cba33d3e-8ecb-11f0-aef3-0224a6c84d84",3,["D",1757566639425],"{\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}",[],[217],{"_105":225,"_97":226,"_161":117,"_163":-5,"_164":146,"_165":102,"_167":22,"_107":227,"_101":192,"_169":228,"_171":229,"_172":22,"_173":-5,"_174":230,"_100":231},"273c8910-8ed7-11f0-94fb-0224a6c84d84","main.http.ts",["D",1757571517569],"http","import { OpenAI } from \"https://esm.town/v/std/openai\";\nimport { logFood } from \"./notion.ts\";\nimport { searchFood, getNutrition, type SearchResult, type NutritionResult } from \"./usda.ts\";\nimport { BrowserUseClient } from \"https://esm.sh/browser-use-sdk@latest\";\n\nconst openai = new OpenAI();\nconst browserUse = new BrowserUseClient({\n apiKey: Deno.env.get('BROWSER_USE_API_KEY')\n});\n\nconst SYSTEM_PROMPT = `I'm working on my weight loss journey and want to log all the foods that I eat and my weight on specific days. So everything is tracked in Notion right now. So all I need you to do is generally if I give you a picture of food and a description, I want you to like estimate the calories for that food and then add it to the food database via the log_food tool. If I give you like a specific restaurant and a dish, I want you to use your agent mode to go find the restaurant and the ingredients in that dish and then add it as a more accurate estimate. If I give you a barcode or like a processed food, then you should like go online and find the food database. And then try and figure out the calories from there. So always try to get the best estimate for food. If I ask you to log my weight, I'll give you a weight and then just log it for that day. In Notion, the create times are automatically added. So all you need to do is add an entry.\n\nWhen estimating calories, use web search strategically:\n\n1. **Restaurant items**: Search \"[restaurant name] [dish name] nutrition facts\" or \"[restaurant name] [dish name] calories\"\n\n2. **Packaged foods**: Search \"[brand] [product name] nutrition label\" or \"[UPC/barcode] nutrition facts\"\n\n3. **Generic dishes**: Search \"[dish name] average calories per serving\" or \"[main ingredient] calories per [portion size]\"\n\n4. **Verification**: If your estimate seems off, search \"typical calories [food type]\" to cross-reference\n\nAlways search BEFORE making your final estimate. Use multiple searches if the first doesn't provide clear nutritional data. Look for official restaurant websites, nutrition databases (USDA, MyFitnessPal), or product labels.\n\nYou have access to the USDA FoodData Central database through the usda_food function. PREFER using this tool to get exact nutrition data before falling back to web search and estimation. The USDA database contains over 900,000 foods including branded products and restaurant items with precise calorie and macro information.`;\n\nasync function searchDoorDash(restaurant: string, dish: string): Promise {\n try {\n const task = await browserUse.tasks.createTask({\n task: `Search DoorDash for \"${restaurant}\" and find the menu item \"${dish}\". Extract the calories, ingredients, and nutritional information if available. If exact match not found, find the closest similar item. Return the information in JSON format with: restaurant, dish_name, calories, ingredients, and any other nutritional info available.`,\n llm: \"gpt-4o\"\n });\n\n const result = await task.complete();\n return JSON.stringify({\n action: \"doordash_search\",\n result: result.output,\n message: `Found DoorDash info for ${restaurant} - ${dish}`\n });\n } catch (error) {\n return JSON.stringify({\n error: `DoorDash search failed: ${error.message}`,\n fallback: \"Use USDA database or web search instead\"\n });\n }\n}\n\nasync function handleToolCall(toolCall: any): Promise {\n const { name, arguments: args } = toolCall.function;\n \n if (name === \"doordash_search\") {\n try {\n const params = JSON.parse(args);\n const { restaurant, dish } = params;\n \n if (!restaurant || !dish) {\n throw new Error(\"Both restaurant and dish are required for DoorDash search\");\n }\n \n return await searchDoorDash(restaurant, dish);\n } catch (error) {\n return JSON.stringify({\n error: `DoorDash search failed: ${error.message}`,\n fallback: \"Use USDA database or web search instead\"\n });\n }\n } else if (name === \"usda_food\") {\n try {\n const params = JSON.parse(args);\n const { action, query, fdcId, portionIndex } = params;\n \n if (action === \"search\") {\n if (!query) throw new Error(\"query is required for search action\");\n const results = await searchFood(query);\n return JSON.stringify({ \n action: \"search\",\n results: results.slice(0, 5), // Limit to top 5 results\n message: `Found ${results.length} foods matching \"${query}\"`\n });\n } else if (action === \"get\") {\n if (!fdcId) throw new Error(\"fdcId is required for get action\");\n const nutrition = await getNutrition(fdcId, portionIndex);\n return JSON.stringify({\n action: \"get\",\n nutrition,\n message: `Nutrition data for ${nutrition.serving}: ${nutrition.calories} kcal`\n });\n } else {\n throw new Error(`Unknown action: ${action}`);\n }\n } catch (error) {\n return JSON.stringify({\n error: `USDA lookup failed: ${error.message}`,\n fallback: \"Use web search or estimation instead\"\n });\n }\n }\n \n return JSON.stringify({ error: `Unknown tool: ${name}` });\n}\n\nasync function estimateCalories(food: string) {\n const messages = [\n {\n role: \"system\" as const,\n content: SYSTEM_PROMPT\n },\n {\n role: \"user\" as const,\n content: `Estimate calories for: ${food}\n\nUse detailed reasoning to break down the ingredients, portion sizes, and cooking methods. If this is from a specific restaurant, search for nutritional information online. Consider: 1) Ingredient analysis 2) Portion size estimation 3) Cooking method impact 4) Restaurant-specific data if available.\n\nPlease provide your response in this exact format:\n1. First, provide the calorie estimate: \"Food Name: XXX calories\"\n2. Then provide your detailed reasoning\n3. Finally, provide just the food name and calorie number in this JSON format: {\"food\": \"Food Name\", \"calories\": 123}`\n }\n ];\n\n let completion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages,\n tools: [\n {\n type: \"function\",\n function: {\n name: \"doordash_search\",\n description: \"Search DoorDash for restaurant menu items and extract nutritional information\",\n parameters: {\n type: \"object\",\n properties: {\n restaurant: {\n type: \"string\",\n description: \"Name of the restaurant (e.g., 'McDonald's', 'Chipotle', 'RT Rotisserie')\"\n },\n dish: {\n type: \"string\", \n description: \"Name of the dish or menu item (e.g., 'Big Mac', 'Burrito Bowl', 'Rotisserie Bowl')\"\n }\n },\n required: [\"restaurant\", \"dish\"]\n }\n }\n },\n {\n type: \"function\",\n function: {\n name: \"usda_food\",\n description: \"Look up nutrition data from USDA FoodData Central database with over 900k foods\",\n parameters: {\n type: \"object\",\n properties: {\n action: {\n type: \"string\",\n enum: [\"search\", \"get\"],\n description: \"Use 'search' to find foods by name, 'get' to retrieve detailed nutrition for a specific food\"\n },\n query: {\n type: \"string\", \n description: \"Free-text food search query (required for action=search)\"\n },\n fdcId: {\n type: \"integer\",\n description: \"Food Data Central ID (required for action=get)\"\n },\n portionIndex: {\n type: \"integer\",\n description: \"Optional serving size index for action=get (default: 0)\"\n }\n },\n required: [\"action\"]\n }\n }\n }\n ],\n max_tokens: 1000,\n });\n\n // Handle tool calls\n while (completion.choices[0]?.message?.tool_calls) {\n const message = completion.choices[0].message;\n messages.push(message);\n \n // Execute all tool calls\n for (const toolCall of message.tool_calls) {\n const result = await handleToolCall(toolCall);\n messages.push({\n role: \"tool\" as const,\n content: result,\n tool_call_id: toolCall.id\n });\n }\n \n // Get next response\n completion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages,\n tools: [\n {\n type: \"function\",\n function: {\n name: \"doordash_search\",\n description: \"Search DoorDash for restaurant menu items and extract nutritional information\",\n parameters: {\n type: \"object\",\n properties: {\n restaurant: {\n type: \"string\",\n description: \"Name of the restaurant (e.g., 'McDonald's', 'Chipotle', 'RT Rotisserie')\"\n },\n dish: {\n type: \"string\", \n description: \"Name of the dish or menu item (e.g., 'Big Mac', 'Burrito Bowl', 'Rotisserie Bowl')\"\n }\n },\n required: [\"restaurant\", \"dish\"]\n }\n }\n },\n {\n type: \"function\",\n function: {\n name: \"usda_food\",\n description: \"Look up nutrition data from USDA FoodData Central database with over 900k foods\",\n parameters: {\n type: \"object\",\n properties: {\n action: {\n type: \"string\",\n enum: [\"search\", \"get\"],\n description: \"Use 'search' to find foods by name, 'get' to retrieve detailed nutrition for a specific food\"\n },\n query: {\n type: \"string\", \n description: \"Free-text food search query (required for action=search)\"\n },\n fdcId: {\n type: \"integer\",\n description: \"Food Data Central ID (required for action=get)\"\n },\n portionIndex: {\n type: \"integer\",\n description: \"Optional serving size index for action=get (default: 0)\"\n }\n },\n required: [\"action\"]\n }\n }\n }\n ],\n max_tokens: 1000,\n });\n }\n\n const response = completion.choices[0]?.message?.content || \"\";\n \n // Extract JSON from response for logging\n const jsonMatch = response.match(/\\{[^}]*\"food\"[^}]*\"calories\"[^}]*\\}/);\n if (jsonMatch) {\n try {\n const foodData = JSON.parse(jsonMatch[0]);\n const success = await logFood(foodData.food, foodData.calories);\n \n return {\n response: response.replace(jsonMatch[0], '').trim(),\n logged: success,\n foodData\n };\n } catch (error) {\n console.error(\"Failed to parse JSON:\", error);\n return {\n response,\n logged: false,\n error: \"Failed to parse food data\"\n };\n }\n }\n \n return {\n response,\n logged: false,\n error: \"No food data found in response\"\n };\n}\n\nfunction wantsJson(req: Request): boolean {\n const url = new URL(req.url);\n const acceptHeader = req.headers.get(\"accept\") || \"\";\n \n return url.searchParams.has(\"json\") || \n acceptHeader.includes(\"application/json\") ||\n !acceptHeader.includes(\"text/html\");\n}\n\nexport default async function(req: Request) {\n if (req.method === \"GET\") {\n if (wantsJson(req)) {\n return Response.json({\n message: \"Food Calorie Tracker API\",\n usage: \"POST with 'food' parameter to estimate calories\"\n });\n }\n \n return new Response(`\n \n \n Food Calorie Tracker\n \n \n \n

🍎 Food Calorie Tracker

\n \n \n `, {\n headers: { \"Content-Type\": \"text/html\" }\n });\n }\n\n if (req.method === \"POST\") {\n let food: string;\n \n // Handle both form data and JSON requests\n const contentType = req.headers.get(\"content-type\") || \"\";\n if (contentType.includes(\"application/json\")) {\n const json = await req.json();\n food = json.food;\n } else {\n const formData = await req.formData();\n food = formData.get(\"food\") as string;\n }\n\n if (!food) {\n const error = { error: \"Food description is required\" };\n return wantsJson(req) \n ? Response.json(error, { status: 400 })\n : new Response(\"Food description is required\", { status: 400 });\n }\n\n try {\n const result = await estimateCalories(food);\n \n if (wantsJson(req)) {\n return Response.json({\n success: result.logged,\n food: result.foodData?.food,\n calories: result.foodData?.calories,\n message: result.response,\n error: result.error\n });\n }\n \n return new Response(`\n \n \n Calorie Estimate Result\n \n \n \n

📊 Calorie Estimate

\n \n ${result.logged ? \n '

✅ Successfully logged to Notion!

' : \n '

❌ Failed to log to Notion

'\n }\n \n

${result.response}

\n \n ${result.foodData ? \n `

Logged Data:

Food: ${result.foodData.food}

Calories: ${result.foodData.calories}

` : ''\n }\n \n \n ← Back to Tracker\n \n

\n \n \n `, {\n headers: { \"Content-Type\": \"text/html\" }\n });\n } catch (error) {\n const errorMsg = `Error: ${error.message}`;\n return wantsJson(req)\n ? Response.json({ error: errorMsg }, { status: 500 })\n : new Response(errorMsg, { status: 500 });\n }\n }\n\n return new Response(\"Method not allowed\", { status: 405 });\n}\n",[],[226],{"_105":233,"_97":234,"_161":235,"_163":-5,"_164":146,"_165":236,"_167":119,"_107":237,"_101":33,"_169":238,"_171":239,"_172":22,"_173":-5,"_174":240,"_100":241},"cbd1ba1a-8ecb-11f0-9b83-0224a6c84d84","notion.ts","cbd1bace-8ecb-11f0-9b83-0224a6c84d84",8,["D",1757566639423],"script","import { Client } from \"https://esm.sh/@notionhq/client\";\n\nconst notion = new Client({ auth: Deno.env.get(\"NOTION_OAUTH_TOKEN\") });\n\nconst notionFoodDbId = \"2645a80474df80699a56d85fe03a6c69\";\n\nexport async function logFood(food: string, calories: number) {\n try {\n await notion.pages.create({\n parent: { database_id: notionFoodDbId },\n properties: {\n Name: {\n title: [{ text: { content: food } }],\n },\n Calories: {\n number: calories,\n },\n },\n });\n return true;\n } catch (error) {\n console.error(\"Failed to log food to Notion:\", error);\n return false;\n }\n}\n",[],[234],{"_105":243,"_97":244,"_161":245,"_163":-5,"_164":146,"_165":246,"_167":119,"_107":247,"_101":33,"_169":238,"_171":248,"_172":22,"_173":-5,"_174":249,"_100":250},"d310332a-8ed4-11f0-a0cf-0224a6c84d84","test_usda.ts","d3103406-8ed4-11f0-a0cf-0224a6c84d84",13,["D",1757570517369],"import { searchFood, getNutrition } from \"./usda.ts\";\n\nasync function test() {\n try {\n console.log(\"Testing USDA search...\");\n const results = await searchFood(\"banana\");\n console.log(\"Search results:\", results.slice(0, 3));\n \n if (results.length > 0) {\n console.log(\"\\nTesting nutrition lookup...\");\n const nutrition = await getNutrition(results[0].fdcId);\n console.log(\"Nutrition:\", nutrition);\n }\n } catch (error) {\n console.error(\"Error:\", error.message);\n }\n}\n\ntest();\n",[],[244],{"_105":252,"_97":253,"_161":254,"_163":-5,"_164":146,"_165":255,"_167":119,"_107":256,"_101":33,"_169":238,"_171":257,"_172":22,"_173":-5,"_174":258,"_100":259},"8ebc1194-8ed4-11f0-bb42-0224a6c84d84","usda.ts","8ebc122a-8ed4-11f0-bb42-0224a6c84d84",10,["D",1757570402732],"export interface Nutrients {\n calories: number; // kcal\n protein: number; // g\n carbs: number; // g\n fat: number; // g\n fiber?: number; // g\n sugar?: number; // g\n}\n\nexport interface SearchResult {\n fdcId: number;\n description: string;\n dataType: 'Branded' | 'Survey (FNDDS)' | 'SR Legacy' | 'Foundation';\n caloriesPer100g?: number;\n}\n\nexport interface NutritionResult extends Nutrients {\n serving: string;\n fdcId: number;\n}\n\nconst API_BASE = 'https://api.nal.usda.gov/fdc/v1';\n\n// Nutrient IDs from USDA database\nconst NUTRIENT_IDS = {\n calories: 208, // Energy (kcal)\n protein: 203, // Protein\n carbs: 205, // Carbohydrate, by difference\n fat: 204, // Total lipid (fat)\n fiber: 291, // Fiber, total dietary\n sugar: 269, // Sugars, total including NLEA\n};\n\nfunction getApiKey(): string {\n const key = Deno.env.get('USDA_FDC_KEY');\n if (!key) {\n throw new Error('USDA_FDC_KEY environment variable is required. Get one from https://api.data.gov/signup/');\n }\n return key;\n}\n\nasync function makeRequest(endpoint: string, params: Record = {}): Promise {\n const apiKey = getApiKey();\n const url = new URL(`${API_BASE}${endpoint}`);\n url.searchParams.set('api_key', apiKey);\n \n Object.entries(params).forEach(([key, value]) => {\n url.searchParams.set(key, value);\n });\n\n let retries = 3;\n while (retries > 0) {\n try {\n const response = await fetch(url.toString());\n \n if (response.status === 429) {\n // Rate limit hit, wait and retry\n await new Promise(resolve => setTimeout(resolve, 1000 * (4 - retries)));\n retries--;\n continue;\n }\n \n if (!response.ok) {\n throw new Error(`USDA API error: ${response.status} ${response.statusText}`);\n }\n \n return await response.json();\n } catch (error) {\n retries--;\n if (retries === 0) throw error;\n await new Promise(resolve => setTimeout(resolve, 1000));\n }\n }\n}\n\nexport async function searchFood(query: string, maxResults = 10): Promise {\n if (!query.trim()) {\n throw new Error('Search query cannot be empty');\n }\n\n const data = await makeRequest('/foods/search', {\n query: query.trim(),\n pageSize: maxResults.toString(),\n });\n\n if (!data.foods || !Array.isArray(data.foods)) {\n return [];\n }\n\n return data.foods.map((food: any) => {\n // Extract calories per 100g if available\n let caloriesPer100g: number | undefined;\n if (food.foodNutrients) {\n const calorieNutrient = food.foodNutrients.find(\n (n: any) => n.nutrientNumber === NUTRIENT_IDS.calories.toString()\n );\n if (calorieNutrient && typeof calorieNutrient.value === 'number') {\n caloriesPer100g = Math.round(calorieNutrient.value);\n }\n }\n\n return {\n fdcId: food.fdcId,\n description: food.description || 'Unknown food',\n dataType: food.dataType || 'Unknown',\n caloriesPer100g,\n };\n });\n}\n\nexport async function getNutrition(fdcId: number, portionIndex?: number): Promise {\n const data = await makeRequest(`/food/${fdcId}`, {\n format: 'full'\n });\n\n if (!data) {\n throw new Error(`No food found with ID ${fdcId}`);\n }\n\n // Extract nutrients\n const nutrients: Partial = {};\n const foodNutrients = data.foodNutrients || [];\n\n Object.entries(NUTRIENT_IDS).forEach(([name, id]) => {\n const nutrient = foodNutrients.find((n: any) => n.nutrient?.number === id.toString());\n if (nutrient && typeof nutrient.amount === 'number') {\n (nutrients as any)[name] = nutrient.amount;\n }\n });\n\n // Default missing values\n const finalNutrients: Nutrients = {\n calories: nutrients.calories || 0,\n protein: nutrients.protein || 0,\n carbs: nutrients.carbs || 0,\n fat: nutrients.fat || 0,\n fiber: nutrients.fiber,\n sugar: nutrients.sugar,\n };\n\n // Determine portion/serving\n let serving = '100 g';\n let scalingFactor = 1;\n\n if (data.foodPortions && Array.isArray(data.foodPortions) && data.foodPortions.length > 0) {\n const portionIdx = portionIndex ?? 0;\n const portion = data.foodPortions[portionIdx];\n \n if (portion) {\n serving = `${portion.amount || 1} ${portion.modifier || portion.measureUnit?.name || 'serving'}`;\n \n // Scale nutrients based on gram weight\n if (portion.gramWeight && portion.gramWeight !== 100) {\n scalingFactor = portion.gramWeight / 100;\n }\n }\n } else if (data.servingSize && data.servingSizeUnit) {\n // For branded foods, use serving size info\n serving = `${data.servingSize} ${data.servingSizeUnit}`;\n \n // If we have household serving info, try to get gram weight\n if (data.householdServingFullText) {\n serving = data.householdServingFullText;\n }\n }\n\n // Apply scaling\n if (scalingFactor !== 1) {\n Object.keys(finalNutrients).forEach(key => {\n const value = (finalNutrients as any)[key];\n if (typeof value === 'number') {\n (finalNutrients as any)[key] = Math.round(value * scalingFactor * 10) / 10;\n }\n });\n }\n\n return {\n ...finalNutrients,\n serving,\n fdcId,\n };\n}\n\n// Helper function for testing\nexport async function findAndGetNutrition(query: string): Promise {\n 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tanishqkancharla

food-tracker