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",[],[181],{"_103":189,"_95":190,"_152":191,"_154":-5,"_155":137,"_156":192,"_158":159,"_105":193,"_100":32,"_161":174,"_163":194,"_164":22,"_165":-5,"_166":195,"_98":196},"787b2594-7fb8-11f0-9730-0224a6c84d84",".env","787b262a-7fb8-11f0-9730-0224a6c84d84",8,["D",1755909072046],"GITHUB_TOKEN=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\nGROQ_API_KEY=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",[],[190],{"_103":198,"_95":199,"_152":200,"_154":-5,"_155":137,"_156":201,"_158":159,"_105":202,"_100":32,"_161":174,"_163":203,"_164":22,"_165":-5,"_166":204,"_98":205},"788813c6-7fb8-11f0-a529-0224a6c84d84",".vtignore","7888147a-7fb8-11f0-a529-0224a6c84d84",11,["D",1755909072118],".git\n.vscode\n.cursorrules\n.DS_Store\nnode_modules\nvendor",[],[199],{"_103":207,"_95":208,"_152":209,"_154":-5,"_155":137,"_156":210,"_158":159,"_105":211,"_100":32,"_161":174,"_163":212,"_164":22,"_165":-5,"_166":213,"_98":214},"78698398-7fb8-11f0-9730-0224a6c84d84","deno.json","78698488-7fb8-11f0-9730-0224a6c84d84",4,["D",1755909071853],"{\n \"name\": \"labkit\",\n \"description\": \"A design kit for labspace\",\n \"tasks\": {\n \"serve\": \"deno serve --port 8012 --watch --allow-read --allow-env --allow-import --allow-write --allow-net ./main.js\",\n \"snapshot\": \"deno run --allow-read --allow-env --allow-write --allow-net ./snapshot.js\"\n },\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}\n",[],[208],{"_103":216,"_95":217,"_152":218,"_154":-5,"_155":137,"_156":219,"_158":159,"_105":220,"_100":32,"_161":174,"_163":221,"_164":22,"_165":-5,"_166":222,"_98":223},"787227aa-7fb8-11f0-a63d-0224a6c84d84","deno.lock","7872285e-7fb8-11f0-a63d-0224a6c84d84",6,["D",1755909071987],"{\n \"version\": \"5\",\n \"specifiers\": {\n \"jsr:@smallweb/sandbox@0.1.0\": \"0.1.0\",\n \"jsr:@std/dotenv@*\": \"0.225.2\",\n \"jsr:@std/encoding@1.0.8\": \"1.0.8\",\n \"jsr:@std/html@1.0.3\": \"1.0.3\",\n \"jsr:@std/http@1.0.12\": \"1.0.12\",\n \"npm:@google/generative-ai@*\": \"0.17.1\",\n \"npm:@valtown/sdk@*\": \"0.21.2\",\n \"npm:git-repo-parser@*\": \"2.0.7\",\n \"npm:graphemer@*\": \"1.4.0\",\n \"npm:hono@*\": \"4.6.3\",\n \"npm:js-tiktoken@*\": \"1.0.15\",\n \"npm:marked@*\": \"14.1.0\",\n \"npm:tiktoken@*\": \"1.0.17\",\n \"npm:zod@*\": \"3.23.8\",\n \"npm:zodex@*\": \"0.18.2_zod@3.23.8\"\n },\n \"jsr\": {\n \"@smallweb/sandbox@0.1.0\": {\n \"integrity\": \"840a6120563b20be994fdac3fa858d2cc2e815c6f9b5ea8f14bd02ddd7f71be8\",\n \"dependencies\": [\n \"jsr:@std/encoding\",\n \"jsr:@std/html\",\n \"jsr:@std/http\"\n ]\n },\n \"@std/dotenv@0.225.2\": {\n \"integrity\": \"e2025dce4de6c7bca21dece8baddd4262b09d5187217e231b033e088e0c4dd23\"\n },\n \"@std/encoding@1.0.8\": {\n \"integrity\": \"a6c8f3f933ab1bed66244f435d1dc0fd23a888e07195532122ddc3d5f8f0e6b4\"\n },\n \"@std/html@1.0.3\": {\n \"integrity\": \"7a0ac35e050431fb49d44e61c8b8aac1ebd55937e0dc9ec6409aa4bab39a7988\"\n },\n \"@std/http@1.0.12\": {\n \"integrity\": \"85246d8bfe9c8e2538518725b158bdc31f616e0869255f4a8d9e3de919cab2aa\"\n }\n },\n \"npm\": {\n \"@google/generative-ai@0.17.1\": {\n \"integrity\": \"sha512-TgWz02c5l2XJlEDys81UVat5+Qg9xqmYah7tQt6xlsBwFvzIFPz64aZFGd1av2sxT22NsssqLATjNsusAIJICA==\"\n },\n \"@kwsites/file-exists@1.1.1\": {\n \"integrity\": \"sha512-m9/5YGR18lIwxSFDwfE3oA7bWuq9kdau6ugN4H2rJeyhFQZcG9AgSHkQtSD15a8WvTgfz9aikZMrKPHvbpqFiw==\",\n \"dependencies\": [\n \"debug\"\n ]\n },\n \"@kwsites/promise-deferred@1.1.1\": {\n \"integrity\": \"sha512-GaHYm+c0O9MjZRu0ongGBRbinu8gVAMd2UZjji6jVmqKtZluZnptXGWhz1E8j8D2HJ3f/yMxKAUC0b+57wncIw==\"\n },\n \"@types/node-fetch@2.6.11\": {\n \"integrity\": \"sha512-24xFj9R5+rfQJLRyM56qh+wnVSYhyXC2tkoBndtY0U+vubqNsYXGjufB2nn8Q6gt0LrARwL6UBtMCSVCwl4B1g==\",\n \"dependencies\": [\n \"@types/node@22.5.4\",\n \"form-data\"\n ]\n },\n \"@types/node@18.19.55\": {\n \"integrity\": \"sha512-zzw5Vw52205Zr/nmErSEkN5FLqXPuKX/k5d1D7RKHATGqU7y6YfX9QxZraUzUrFGqH6XzOzG196BC35ltJC4Cw==\",\n \"dependencies\": [\n \"undici-types@5.26.5\"\n ]\n },\n \"@types/node@22.5.4\": {\n \"integrity\": \"sha512-FDuKUJQm/ju9fT/SeX/6+gBzoPzlVCzfzmGkwKvRHQVxi4BntVbyIwf6a4Xn62mrvndLiml6z/UBXIdEVjQLXg==\",\n \"dependencies\": [\n \"undici-types@6.19.8\"\n ]\n },\n \"@valtown/sdk@0.21.2\": {\n \"integrity\": \"sha512-KBHODXnwGtj68SA1hRW+6rba1zu5c2FrYxttGgPemiPGgLoF8Yo29RvNhsA8Qc08bmj5IJS0Mzn0tfqis6Qr+Q==\",\n \"dependencies\": [\n \"@types/node@18.19.55\",\n \"@types/node-fetch\",\n \"abort-controller\",\n \"agentkeepalive\",\n \"form-data-encoder\",\n \"formdata-node\",\n \"node-fetch\"\n ]\n },\n \"abort-controller@3.0.0\": {\n \"integrity\": \"sha512-h8lQ8tacZYnR3vNQTgibj+tODHI5/+l06Au2Pcriv/Gmet0eaj4TwWH41sO9wnHDiQsEj19q0drzdWdeAHtweg==\",\n \"dependencies\": [\n \"event-target-shim\"\n ]\n },\n \"agentkeepalive@4.5.0\": {\n \"integrity\": \"sha512-5GG/5IbQQpC9FpkRGsSvZI5QYeSCzlJHdpBQntCsuTOxhKD8lqKhrleg2Yi7yvMIf82Ycmmqln9U8V9qwEiJew==\",\n \"dependencies\": [\n \"humanize-ms\"\n ]\n },\n \"asynckit@0.4.0\": {\n \"integrity\": \"sha512-Oei9OH4tRh0YqU3GxhX79dM/mwVgvbZJaSNaRk+bshkj0S5cfHcgYakreBjrHwatXKbz+IoIdYLxrKim2MjW0Q==\"\n },\n \"base64-js@1.5.1\": {\n \"integrity\": \"sha512-AKpaYlHn8t4SVbOHCy+b5+KKgvR4vrsD8vbvrbiQJps7fKDTkjkDry6ji0rUJjC0kzbNePLwzxq8iypo41qeWA==\"\n },\n \"combined-stream@1.0.8\": {\n \"integrity\": \"sha512-FQN4MRfuJeHf7cBbBMJFXhKSDq+2kAArBlmRBvcvFE5BB1HZKXtSFASDhdlz9zOYwxh8lDdnvmMOe/+5cdoEdg==\",\n \"dependencies\": [\n \"delayed-stream\"\n ]\n },\n \"debug@4.3.7\": {\n \"integrity\": \"sha512-Er2nc/H7RrMXZBFCEim6TCmMk02Z8vLC2Rbi1KEBggpo0fS6l0S1nnapwmIi3yW/+GOJap1Krg4w0Hg80oCqgQ==\",\n \"dependencies\": [\n \"ms\"\n ]\n },\n \"delayed-stream@1.0.0\": {\n \"integrity\": \"sha512-ZySD7Nf91aLB0RxL4KGrKHBXl7Eds1DAmEdcoVawXnLD7SDhpNgtuII2aAkg7a7QS41jxPSZ17p4VdGnMHk3MQ==\"\n },\n \"event-target-shim@5.0.1\": {\n \"integrity\": \"sha512-i/2XbnSz/uxRCU6+NdVJgKWDTM427+MqYbkQzD321DuCQJUqOuJKIA0IM2+W2xtYHdKOmZ4dR6fExsd4SXL+WQ==\"\n },\n \"form-data-encoder@1.7.2\": {\n \"integrity\": \"sha512-qfqtYan3rxrnCk1VYaA4H+Ms9xdpPqvLZa6xmMgFvhO32x7/3J/ExcTd6qpxM0vH2GdMI+poehyBZvqfMTto8A==\"\n },\n \"form-data@4.0.1\": {\n \"integrity\": \"sha512-tzN8e4TX8+kkxGPK8D5u0FNmjPUjw3lwC9lSLxxoB/+GtsJG91CO8bSWy73APlgAZzZbXEYZJuxjkHH2w+Ezhw==\",\n \"dependencies\": [\n \"asynckit\",\n \"combined-stream\",\n \"mime-types\"\n ]\n },\n \"formdata-node@4.4.1\": {\n \"integrity\": \"sha512-0iirZp3uVDjVGt9p49aTaqjk84TrglENEDuqfdlZQ1roC9CWlPk6Avf8EEnZNcAqPonwkG35x4n3ww/1THYAeQ==\",\n \"dependencies\": [\n \"node-domexception\",\n \"web-streams-polyfill\"\n ]\n },\n \"git-repo-parser@2.0.7\": {\n \"integrity\": \"sha512-51bz2UL04epQnxR4eZC1CaQXVtpEnhtekRs4UeTkiio74kYcIfSsaSb4kLPHuDbJaEuLEZeGNjh63bJkVhCQHw==\",\n \"dependencies\": [\n \"simple-git\"\n ],\n \"bin\": true\n },\n \"graphemer@1.4.0\": {\n \"integrity\": \"sha512-EtKwoO6kxCL9WO5xipiHTZlSzBm7WLT627TqC/uVRd0HKmq8NXyebnNYxDoBi7wt8eTWrUrKXCOVaFq9x1kgag==\"\n },\n \"hono@4.6.3\": {\n \"integrity\": \"sha512-0LeEuBNFeSHGqZ9sNVVgZjB1V5fmhkBSB0hZrpqStSMLOWgfLy0dHOvrjbJh0H2khsjet6rbHfWTHY0kpYThKQ==\"\n },\n \"humanize-ms@1.2.1\": {\n \"integrity\": \"sha512-Fl70vYtsAFb/C06PTS9dZBo7ihau+Tu/DNCk/OyHhea07S+aeMWpFFkUaXRa8fI+ScZbEI8dfSxwY7gxZ9SAVQ==\",\n \"dependencies\": [\n \"ms\"\n ]\n },\n \"js-tiktoken@1.0.15\": {\n \"integrity\": \"sha512-65ruOWWXDEZHHbAo7EjOcNxOGasQKbL4Fq3jEr2xsCqSsoOo6VVSqzWQb6PRIqypFSDcma4jO90YP0w5X8qVXQ==\",\n \"dependencies\": [\n \"base64-js\"\n ]\n },\n \"marked@14.1.0\": {\n \"integrity\": \"sha512-P93GikH/Pde0hM5TAXEd8I4JAYi8IB03n8qzW8Bh1BIEFpEyBoYxi/XWZA53LSpTeLBiMQOoSMj0u5E/tiVYTA==\",\n \"bin\": true\n },\n \"mime-db@1.52.0\": {\n \"integrity\": \"sha512-sPU4uV7dYlvtWJxwwxHD0PuihVNiE7TyAbQ5SWxDCB9mUYvOgroQOwYQQOKPJ8CIbE+1ETVlOoK1UC2nU3gYvg==\"\n },\n \"mime-types@2.1.35\": {\n \"integrity\": \"sha512-ZDY+bPm5zTTF+YpCrAU9nK0UgICYPT0QtT1NZWFv4s++TNkcgVaT0g6+4R2uI4MjQjzysHB1zxuWL50hzaeXiw==\",\n \"dependencies\": [\n \"mime-db\"\n ]\n },\n \"ms@2.1.3\": {\n \"integrity\": \"sha512-6FlzubTLZG3J2a/NVCAleEhjzq5oxgHyaCU9yYXvcLsvoVaHJq/s5xXI6/XXP6tz7R9xAOtHnSO/tXtF3WRTlA==\"\n },\n \"node-domexception@1.0.0\": {\n \"integrity\": \"sha512-/jKZoMpw0F8GRwl4/eLROPA3cfcXtLApP0QzLmUT/HuPCZWyB7IY9ZrMeKw2O/nFIqPQB3PVM9aYm0F312AXDQ==\",\n \"deprecated\": true\n },\n \"node-fetch@2.7.0\": {\n \"integrity\": \"sha512-c4FRfUm/dbcWZ7U+1Wq0AwCyFL+3nt2bEw05wfxSz+DWpWsitgmSgYmy2dQdWyKC1694ELPqMs/YzUSNozLt8A==\",\n \"dependencies\": [\n \"whatwg-url\"\n ],\n \"optionalPeers\": [\n \"encoding@^0.1.0\"\n ]\n },\n \"simple-git@2.48.0\": {\n \"integrity\": \"sha512-z4qtrRuaAFJS4PUd0g+xy7aN4y+RvEt/QTJpR184lhJguBA1S/LsVlvE/CM95RsYMOFJG3NGGDjqFCzKU19S/A==\",\n \"dependencies\": [\n \"@kwsites/file-exists\",\n \"@kwsites/promise-deferred\",\n \"debug\"\n ]\n },\n \"tiktoken@1.0.17\": {\n \"integrity\": \"sha512-UuFHqpy/DxOfNiC3otsqbx3oS6jr5uKdQhB/CvDEroZQbVHt+qAK+4JbIooabUWKU9g6PpsFylNu9Wcg4MxSGA==\"\n },\n \"tr46@0.0.3\": {\n \"integrity\": \"sha512-N3WMsuqV66lT30CrXNbEjx4GEwlow3v6rr4mCcv6prnfwhS01rkgyFdjPNBYd9br7LpXV1+Emh01fHnq2Gdgrw==\"\n },\n \"type-fest@4.26.1\": {\n \"integrity\": \"sha512-yOGpmOAL7CkKe/91I5O3gPICmJNLJ1G4zFYVAsRHg7M64biSnPtRj0WNQt++bRkjYOqjWXrhnUw1utzmVErAdg==\"\n },\n \"undici-types@5.26.5\": {\n \"integrity\": \"sha512-JlCMO+ehdEIKqlFxk6IfVoAUVmgz7cU7zD/h9XZ0qzeosSHmUJVOzSQvvYSYWXkFXC+IfLKSIffhv0sVZup6pA==\"\n },\n \"undici-types@6.19.8\": {\n \"integrity\": \"sha512-ve2KP6f/JnbPBFyobGHuerC9g1FYGn/F8n1LWTwNxCEzd6IfqTwUQcNXgEtmmQ6DlRrC1hrSrBnCZPokRrDHjw==\"\n },\n \"web-streams-polyfill@4.0.0-beta.3\": {\n \"integrity\": \"sha512-QW95TCTaHmsYfHDybGMwO5IJIM93I/6vTRk+daHTWFPhwh+C8Cg7j7XyKrwrj8Ib6vYXe0ocYNrmzY4xAAN6ug==\"\n },\n \"webidl-conversions@3.0.1\": {\n \"integrity\": \"sha512-2JAn3z8AR6rjK8Sm8orRC0h/bcl/DqL7tRPdGZ4I1CjdF+EaMLmYxBHyXuKL849eucPFhvBoxMsflfOb8kxaeQ==\"\n },\n \"whatwg-url@5.0.0\": {\n \"integrity\": \"sha512-saE57nupxk6v3HY35+jzBwYa0rKSy0XR8JSxZPwgLr7ys0IBzhGviA1/TUGJLmSVqs8pb9AnvICXEuOHLprYTw==\",\n \"dependencies\": [\n \"tr46\",\n \"webidl-conversions\"\n ]\n },\n \"zod@3.23.8\": {\n \"integrity\": \"sha512-XBx9AXhXktjUqnepgTiE5flcKIYWi/rme0Eaj+5Y0lftuGBq+jyRu/md4WnuxqgP1ubdpNCsYEYPxrzVHD8d6g==\"\n },\n \"zodex@0.18.2_zod@3.23.8\": {\n \"integrity\": \"sha512-GE0/S68lJhhBhJWeOSvq4BCigrguOeKFr7h3sbsMPd6kF4ZCHeVU/hOzNLHlj6d+ezNXcpQ4nHj6purY5RxQBg==\",\n \"dependencies\": [\n \"type-fest\",\n \"zod\"\n ]\n }\n },\n \"remote\": {\n \"https://deno.land/x/hono@v3.11.7/client/client.ts\": \"ff340f58041203879972dd368b011ed130c66914f789826610869a90603406bf\",\n \"https://deno.land/x/hono@v3.11.7/client/index.ts\": \"3ff4cf246f3543f827a85a2c84d66a025ac350ee927613629bda47e854bfb7ba\",\n \"https://deno.land/x/hono@v3.11.7/client/types.ts\": \"ca165b8738d384361b927964466ecc8bc1436edad3d0414e30a28f40ba4ca496\",\n \"https://deno.land/x/hono@v3.11.7/client/utils.ts\": \"053273c002963b549d38268a1b423ac8ca211a8028bdab1ed0b781a62aa5e661\",\n \"https://deno.land/x/hono@v3.11.7/compose.ts\": \"37d6e33b7db80e4c43a0629b12fd3a1e3406e7d9e62a4bfad4b30426ea7ae4f1\",\n \"https://deno.land/x/hono@v3.11.7/context.ts\": \"5cac561498e1f4af7a355673a047f07f47349056c5167ed9aec8a20cdcac8464\",\n \"https://deno.land/x/hono@v3.11.7/helper.ts\": \"719df05d8deefb5986ccdb0051f892a837dd8b91e48cd6db43fef237153f1057\",\n \"https://deno.land/x/hono@v3.11.7/helper/adapter/index.ts\": \"eea9b4caedbfa3a3b4a020bf46c88c0171a00008cd6c10708cd85a3e39d86e62\",\n \"https://deno.land/x/hono@v3.11.7/helper/cookie/index.ts\": \"a05ce7e3bafe1f8c7f45d04abf79822716011be75904fe1aad2e99126fd985b9\",\n \"https://deno.land/x/hono@v3.11.7/helper/dev/index.ts\": \"e78ee9d96713211f957e89df180aaa48f8ce9407a938979b393a79547d7f8029\",\n \"https://deno.land/x/hono@v3.11.7/helper/factory/index.ts\": \"45c9f0a981c23d6b5e481697637b0f66fec3234aec442d0cb285048b07ed54c6\",\n \"https://deno.land/x/hono@v3.11.7/helper/html/index.ts\": \"a4ac61c54cd432e708dd019aced59273e5e053933f4804b0b5758d9916468b3e\",\n \"https://deno.land/x/hono@v3.11.7/helper/streaming/index.ts\": \"90dd4424d8d8271efd602ab7a8fcc0539a1573c98ee03e4c910bc0bbd7d20f27\",\n \"https://deno.land/x/hono@v3.11.7/helper/testing/index.ts\": \"bc49c049aa0d6426417e3d1a2f52a471a09edb1fb8610b7545eae1968e7d7874\",\n \"https://deno.land/x/hono@v3.11.7/hono-base.ts\": \"ab40351c5198cedef9e235ca0a958a161fec822b62aa7fb1eaa36559dc05e0d5\",\n \"https://deno.land/x/hono@v3.11.7/hono.ts\": \"2cc4c292e541463a4d6f83edbcea58048d203e9564ae62ec430a3d466b49a865\",\n \"https://deno.land/x/hono@v3.11.7/http-exception.ts\": \"6071df078b5f76d279684d52fe82a590f447a64ffe1b75eb5064d0c8a8d2d676\",\n \"https://deno.land/x/hono@v3.11.7/mod.ts\": \"90114a97be9111b348129ad0143e764a64921f60dd03b8f3da529db98a0d3a82\",\n \"https://deno.land/x/hono@v3.11.7/request.ts\": \"71a67261d14bba95e9a8b4782a1c1704d12d54a77390ce404741df15ab99a109\",\n \"https://deno.land/x/hono@v3.11.7/router.ts\": \"880316f561918fc197481755aac2165fdbe2f530b925c5357a9f98d6e2cc85c7\",\n \"https://deno.land/x/hono@v3.11.7/router/linear-router/index.ts\": \"8a2a7144c50b1f4a92d9ee99c2c396716af144c868e10608255f969695efccd0\",\n \"https://deno.land/x/hono@v3.11.7/router/linear-router/router.ts\": \"bc63e8b5bc1dabc815306d50bebd1bb5877ffa3936ba2ad7550d093c95ee6bd1\",\n \"https://deno.land/x/hono@v3.11.7/router/pattern-router/index.ts\": \"304a66c50e243872037ed41c7dd79ed0c89d815e17e172e7ad7cdc4bc07d3383\",\n \"https://deno.land/x/hono@v3.11.7/router/pattern-router/router.ts\": \"a9a5a2a182cce8c3ae82139892cc0502be7dd8f579f31e76d0302b19b338e548\",\n \"https://deno.land/x/hono@v3.11.7/router/reg-exp-router/index.ts\": \"52755829213941756159b7a963097bafde5cc4fc22b13b1c7c9184dc0512d1db\",\n \"https://deno.land/x/hono@v3.11.7/router/reg-exp-router/node.ts\": \"5b3fb80411db04c65df066e69fedb2c8c0844753c2633d703336de84d569252c\",\n \"https://deno.land/x/hono@v3.11.7/router/reg-exp-router/router.ts\": \"7f7af7ce45a4327f9ac7dbdee186f7ba9a24f2eff14c720e3f670be001e71780\",\n \"https://deno.land/x/hono@v3.11.7/router/reg-exp-router/trie.ts\": \"852ce7207e6701e47fa30889a0d2b8bfcd56d8862c97e7bc9831e0a64bd8835f\",\n \"https://deno.land/x/hono@v3.11.7/router/smart-router/index.ts\": \"74f9b4fe15ea535900f2b9b048581915f12fe94e531dd2b0032f5610e61c3bef\",\n \"https://deno.land/x/hono@v3.11.7/router/smart-router/router.ts\": \"f1848a2a1eefa316a11853ae12e749552747771fb8a11fe713ae04ea6461140b\",\n \"https://deno.land/x/hono@v3.11.7/router/trie-router/index.ts\": \"3eb75e7f71ba81801631b30de6b1f5cefb2c7239c03797e2b2cbab5085911b41\",\n \"https://deno.land/x/hono@v3.11.7/router/trie-router/node.ts\": \"e9ea493da22913b2e60a88284c5edb5330506f2ceb0ac631909219bb139c4b60\",\n \"https://deno.land/x/hono@v3.11.7/router/trie-router/router.ts\": \"54ced78d35676302c8fcdda4204f7bdf5a7cc907fbf9967c75674b1e394f830d\",\n \"https://deno.land/x/hono@v3.11.7/types.ts\": \"82f95c64c13c21129130d7bb383956306e19d23b3e986c02c914d7aa08808d1d\",\n \"https://deno.land/x/hono@v3.11.7/utils/body.ts\": \"7a16a6656331a96bcae57642f8d5e3912bd361cbbcc2c0d2157ecc3f218f7a92\",\n \"https://deno.land/x/hono@v3.11.7/utils/buffer.ts\": \"9066a973e64498cb262c7e932f47eed525a51677b17f90893862b7279dc0773e\",\n \"https://deno.land/x/hono@v3.11.7/utils/cookie.ts\": \"19920ba6756944aae1ad8585c3ddeaa9df479733f59d05359db096f7361e5e4b\",\n \"https://deno.land/x/hono@v3.11.7/utils/crypto.ts\": \"bda0e141bbe46d3a4a20f8fbcb6380d473b617123d9fdfa93e4499410b537acc\",\n \"https://deno.land/x/hono@v3.11.7/utils/html.ts\": \"4d2f3975238819fa756e0e51cb7090702136b1e3c54c5049694e26c62d2fcd84\",\n \"https://deno.land/x/hono@v3.11.7/utils/http-status.ts\": \"e0c4343ea7717c314dc600131e16b636c29d61cfdaf9df93b267258d1729d1a0\",\n \"https://deno.land/x/hono@v3.11.7/utils/stream.ts\": \"1789dcc73c5b0ede28f83d7d34e47ae432c20e680907cb3275a9c9187f293983\",\n \"https://deno.land/x/hono@v3.11.7/utils/types.ts\": \"41c4e7d8028f3dec43ff7c26e9498fed53d9ec7c3b47071d066b40f7b7a8ef58\",\n \"https://deno.land/x/hono@v3.11.7/utils/url.ts\": \"5fc3307ef3cb2e6f34ec2a03e3d7f2126c6a9f5f0eab677222df3f0e40bd7567\",\n \"https://deno.land/x/hono@v3.11.7/validator/index.ts\": \"6c986e8b91dcf857ecc8164a506ae8eea8665792a4ff7215471df669c632ae7c\",\n \"https://deno.land/x/hono@v3.11.7/validator/validator.ts\": \"f6139f0b6eb2040bc9f7ed4148905d5affc898235952772b2d6585fdae8d4731\"\n }\n}\n",[],[217],{"_103":225,"_95":226,"_152":227,"_154":-5,"_155":137,"_156":228,"_158":159,"_105":229,"_100":32,"_161":230,"_163":231,"_164":22,"_165":-5,"_166":232,"_98":233},"78611ff0-7fb8-11f0-b98a-0224a6c84d84","extractors.js","78612090-7fb8-11f0-b98a-0224a6c84d84",3,["D",1755909071854],"script","import { load as cheerioLoad } from \"npm:cheerio@1.0.0-rc.12\";\n\nexport const GROQ_EXAMPLES_URL = \"https://console.groq.com/docs/examples\";\n\nfunction toAbsoluteUrl(path) {\n if (!path) return null;\n if (path.startsWith(\"http://\") || path.startsWith(\"https://\")) return path;\n return \"https://console.groq.com\" + (path.startsWith(\"/\") ? path : \"/\" + path);\n}\n\nfunction parseExamplesFromHtml(htmlText) {\n const $ = cheerioLoad(htmlText);\n const cards = $(\n \"div.rounded-lg.border.bg-card.text-card-foreground.overflow-hidden.h-full.flex.flex-col\"\n );\n const items = [];\n\n cards.each((_idx, el) => {\n const card = $(el);\n const title = card.find(\"h3\").first().text().trim();\n\n let description = card.find(\"p.text-sm\").first().text().trim();\n if (!description) {\n const firstP = card.find(\"p\").filter((_, p) => $(p).text().trim().length > 0).first();\n description = firstP.text().trim();\n }\n\n const imageSrc = card.find(\".aspect-video img\").attr(\"src\") || null;\n const image = toAbsoluteUrl(imageSrc);\n\n const authorP = card.find(\"p.text-xs\").first();\n const avatarUrl = toAbsoluteUrl(authorP.find(\"img\").attr(\"src\") || null);\n let username = authorP.text().replace(/\\s+/g, \" \").trim();\n username = username.replace(/^by\\s*/i, \"\").trim();\n\n let github = null;\n let demo = null;\n card.find(\"a\").each((_, a) => {\n const href = $(a).attr(\"href\") || \"\";\n const text = $(a).text().toLowerCase();\n const abs = href ? (href.startsWith(\"http\") ? href : toAbsoluteUrl(href)) : null;\n if (!abs) return;\n if (text.includes(\"view repository\") || abs.includes(\"github.com\")) github = abs;\n if (text.includes(\"live demo\")) demo = abs;\n });\n\n const item = { title, description, image, imageFit: \"cover\", username, avatarUrl, github, demo };\n if (item.title || item.github || item.demo) items.push(item);\n });\n\n return items;\n}\n\nexport async function fetchGroqExamples() {\n const res = await fetch(GROQ_EXAMPLES_URL, {\n headers: {\n \"user-agent\": \"Mozilla/5.0 (compatible; GroqExamplesFetcher/1.0; +https://labspace.ai)\",\n accept: \"text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8\",\n },\n });\n const htmlText = await res.text();\n const items = parseExamplesFromHtml(htmlText);\n return { items: Array.isArray(items) ? items : [], fallbackUsed: false };\n}\n\n// --- GitHub helpers and cookbook scrapers ---\nfunction convertGithubToRawUrls(githubUrl) {\n const urls = [];\n const refsHeadsUrl = githubUrl\n .replace('github.com', 'raw.githubusercontent.com')\n .replace('/blob/', '/refs/heads/')\n .replace('/tree/', '/refs/heads/');\n urls.push(refsHeadsUrl);\n const directUrl = githubUrl\n .replace('github.com', 'raw.githubusercontent.com')\n .replace('/blob/', '/')\n .replace('/tree/', '/');\n urls.push(directUrl);\n if (githubUrl.includes('raw.githubusercontent.com')) urls.push(githubUrl);\n return urls;\n}\n\nasync function tryFetchJsonFromPossibleUrls(possibleUrls) {\n for (const u of possibleUrls) {\n try {\n const resp = await fetch(u);\n if (!resp.ok) continue;\n const contentType = resp.headers.get('content-type') || '';\n if (contentType.includes('application/json')) {\n const json = await resp.json();\n return json;\n }\n const text = await resp.text();\n try {\n const parsed = JSON.parse(text);\n return parsed;\n } catch (_) {}\n } catch (_) {}\n }\n return null;\n}\n\nexport function githubApiHeaders() {\n const headers = {\n accept: 'application/vnd.github+json',\n 'user-agent': 'GroqCookbookScraper/1.0 (+https://labspace.ai)'\n };\n try {\n const token = (typeof Deno !== 'undefined' && Deno.env) ? (Deno.env.get('GITHUB_TOKEN') || Deno.env.get('GH_TOKEN')) : null;\n if (token) headers['authorization'] = `Bearer ${token}`;\n } catch (_) {}\n return headers;\n}\n\nexport function slugifyTitle(title) {\n if (!title) return null;\n return title.toLowerCase().replace(/[^a-z0-9]+/g, '-').replace(/(^-|-$)+/g, '');\n}\n\nexport function parseGithubDirUrl(dirUrl) {\n try {\n const m = dirUrl.match(/^https?:\\/\\/github\\.com\\/([^/]+)\\/([^/]+)\\/tree\\/([^/]+)\\/?(.*)$/);\n if (!m) return null;\n const [, org, repo, branch, pathRest] = m;\n const dirPath = (pathRest || '').replace(/^\\/+|\\/+$/g, '');\n return { org, repo, branch, dirPath };\n } catch (_) {\n return null;\n }\n}\n\nfunction buildRawBase({ org, repo, branch, dirPath }) {\n const suffix = dirPath ? `/${dirPath}` : '';\n return `https://raw.githubusercontent.com/${org}/${repo}/${branch}${suffix}`;\n}\n\nfunction buildGithubApiContentsUrl({ org, repo, branch, dirPath }) {\n const path = dirPath ? `/contents/${dirPath}` : `/contents`;\n return `https://api.github.com/repos/${org}/${repo}${path}?ref=${encodeURIComponent(branch)}`;\n}\n\nasync function fetchReadmeFromGithubDir(dirUrl) {\n const info = parseGithubDirUrl(dirUrl);\n if (!info) return { content: '', rawUrl: null, rawBase: null };\n const rawBase = buildRawBase(info);\n const candidates = [\n `${rawBase}/README.md`, `${rawBase}/Readme.md`, `${rawBase}/readme.md`,\n `${rawBase}/README.MD`, `${rawBase}/README.markdown`, `${rawBase}/README.MARKDOWN`,\n ];\n for (const u of candidates) {\n try {\n const res = await fetch(u);\n if (res.ok) {\n const text = await res.text();\n return { content: text, rawUrl: u, rawBase };\n }\n } catch (_) {}\n }\n // Fallback: list directory contents and try to find a README file\n try {\n const apiUrl = buildGithubApiContentsUrl(info);\n const res = await fetch(apiUrl, { headers: githubApiHeaders() });\n if (res.ok) {\n const data = await res.json();\n if (Array.isArray(data) && data.length) {\n let readmeEntry = data.find((e) => e && e.type === 'file' && /^readme(\\.|$)/i.test(e.name));\n if (!readmeEntry) readmeEntry = data.find((e) => e && e.type === 'file' && /\\.md$/i.test(e.name));\n if (readmeEntry) {\n const url = `${rawBase.replace(/\\/$/, '')}/${readmeEntry.name}`;\n try {\n const res2 = await fetch(url);\n if (res2.ok) {\n const text = await res2.text();\n return { content: text, rawUrl: url, rawBase };\n }\n } catch (_) {}\n }\n }\n }\n } catch (_) {}\n return { content: '', rawUrl: null, rawBase };\n}\n\nfunction extractTitleAndDescriptionFromMarkdown(md) {\n if (!md) return { title: null, description: null };\n const lines = md.split(/\\r?\\n/);\n let title = null;\n let startIdx = 0;\n for (let i = 0; i < lines.length; i++) {\n const line = lines[i].trim();\n if (line.startsWith('# ')) { title = line.replace(/^#\\s+/, '').trim(); startIdx = i + 1; break; }\n }\n let description = null;\n let para = [];\n for (let i = startIdx; i < lines.length; i++) {\n const line = lines[i];\n if (/^#{1,6}\\s+/.test(line)) break;\n if (line.trim() === '') { if (para.length) break; continue; }\n para.push(line.trim());\n }\n if (para.length) description = para.join(' ');\n return { title, description };\n}\n\nfunction extractFirstImageUrlFromMarkdown(md, rawBase) {\n if (!md) return null;\n const m = md.match(/!\\[[^\\]]*\\]\$([^)]+)\$/);\n if (!m) return null;\n const url = m[1].trim();\n if (/^https?:\\/\\//i.test(url)) return url;\n if (url.startsWith('/')) return null;\n const base = rawBase?.replace(/\\/$/, '') || '';\n return `${base}/${url}`;\n}\n\nfunction extractFirstIpyNbLinkFromMarkdown(md) {\n if (!md) return null;\n const mdLink = md.match(/\\[[^\\]]*\\]\$([^)]+\\.ipynb(?:\\?[^)]*)?)\$/i);\n if (mdLink) return mdLink[1];\n const plain = md.match(/https?:[^\\s)]+\\.ipynb/gi);\n return plain && plain.length ? plain[0] : null;\n}\n\nfunction extractDemoLinkFromMarkdown(md) {\n if (!md) return null;\n const links = Array.from(md.matchAll(/\\[[^\\]]*\\]\$([^)]+)\$/g)).map(m => m[1]);\n const candidates = links.filter(u => /https?:\\/\\//i.test(u));\n const prefer = candidates.find(u => /(vercel|demo|live|appgen|groqlabs|render|railway|heroku|netlify)/i.test(u));\n return prefer || null;\n}\n\nasync function probeRawFile(rawBase, filename) {\n const url = `${rawBase.replace(/\\/$/, '')}/${filename}`;\n try {\n const head = await fetch(url, { method: 'HEAD' });\n if (head.ok) return { exists: true, url };\n } catch (_) {}\n try {\n const get = await fetch(url, { method: 'GET', headers: { 'range': 'bytes=0-0' } });\n return { exists: get.ok, url };\n } catch (_) { return { exists: false, url }; }\n}\n\nexport async function fetchGithubCookbookFromDir(query) {\n const dirUrl = query?.dir || query?.repoDirUrl;\n if (!dirUrl) return { items: [], fallbackUsed: false, sourceUrl: null };\n const info = parseGithubDirUrl(dirUrl);\n if (!info) return { items: [], fallbackUsed: false, sourceUrl: dirUrl };\n const { content, rawUrl, rawBase } = await fetchReadmeFromGithubDir(dirUrl);\n const slugFromPath = (info.dirPath ? info.dirPath.split('/').pop() : null) || null;\n let title = null, description = null, image = null, ipynbLink = null, demoLink = null;\n if (content) {\n const parsed = extractTitleAndDescriptionFromMarkdown(content);\n title = parsed.title || null;\n description = parsed.description || null;\n image = extractFirstImageUrlFromMarkdown(content, rawBase);\n ipynbLink = extractFirstIpyNbLinkFromMarkdown(content);\n demoLink = extractDemoLinkFromMarkdown(content);\n }\n let appExists = false;\n try {\n const apiUrl = buildGithubApiContentsUrl(info);\n const res = await fetch(apiUrl, { headers: githubApiHeaders() });\n if (res.ok) {\n const data = await res.json();\n if (Array.isArray(data)) {\n if (!ipynbLink) {\n const nb = data.find((e) => e && e.type === 'file' && /\\.ipynb$/i.test(e.name));\n if (nb) {\n const blobBase = `https://github.com/${info.org}/${info.repo}/blob/${info.branch}`;\n ipynbLink = `${blobBase}/${info.dirPath ? info.dirPath + '/' : ''}${nb.name}`;\n }\n }\n const appEntry = data.find((e) => e && e.type === 'file' && e.name === 'app.py');\n appExists = !!appEntry;\n }\n }\n } catch (_) {}\n\n // If neither README/markdown content nor an ipynb exists, skip this folder entirely\n const hasReadableContent = (content && content.trim().length > 0) || !!ipynbLink;\n if (!hasReadableContent) {\n // However, if this folder has child directories, allow it to pass when nested scraping is enabled upstream\n return { items: [], fallbackUsed: false, sourceUrl: dirUrl };\n }\n\n if (!title) title = slugifyTitle(slugFromPath || '') || slugFromPath || dirUrl;\n const item = {\n slug: slugifyTitle(title) || slugFromPath,\n title,\n description,\n image: image || null,\n imageFit: 'cover',\n username: null,\n avatarUrl: null,\n github: dirUrl,\n demo: demoLink || null,\n language: appExists ? 'python' : null,\n difficulty: null,\n tags: [],\n sections: [],\n date: null,\n readmeSource: rawUrl,\n ipynbLink: ipynbLink || null,\n ctas: [ { icon: 'mdi:github', href: dirUrl }, ...(ipynbLink ? [ { icon: 'mdi:notebook', href: ipynbLink } ] : []), ...(demoLink ? [ { icon: 'mdi:play-circle-outline', href: demoLink } ] : []) ],\n authors: [],\n featured: false,\n markdown: null,\n };\n return { items: [item], fallbackUsed: false, sourceUrl: dirUrl };\n}\n\nexport async function fetchGithubCookbooksFromParentDir(query) {\n const parent = query?.parent || query?.parentDir || query?.parentUrl;\n if (!parent) return { items: [], fallbackUsed: false, sourceUrl: null };\n const limit = query?.limit ? Number(query.limit) : undefined;\n const nested = String(query?.nested || \"\").toLowerCase() === \"1\" || String(query?.nested || \"\").toLowerCase() === \"true\";\n const info = parseGithubDirUrl(parent);\n const apiUrl = info ? buildGithubApiContentsUrl(info) : null;\n let entries = [];\n if (apiUrl) {\n try {\n const res = await fetch(apiUrl, { headers: githubApiHeaders() });\n if (res.ok) {\n const data = await res.json();\n if (Array.isArray(data)) entries = data;\n }\n } catch (_) {}\n }\n const dirEntries = entries.filter((e) => e && e.type === 'dir').map((d) => ({\n name: d.name,\n url: `https://github.com/${info.org}/${info.repo}/tree/${info.branch}/${d.path}`\n }));\n let nestedDirEntries = [];\n for (const d of dirEntries) {\n try {\n const childInfo = parseGithubDirUrl(d.url);\n const childApiUrl = childInfo ? buildGithubApiContentsUrl(childInfo) : null;\n if (!childApiUrl) continue;\n const res = await fetch(childApiUrl, { headers: githubApiHeaders() });\n if (!res.ok) continue;\n const data = await res.json();\n if (!Array.isArray(data)) continue;\n const subs = data.filter((e) => e && e.type === 'dir').map((sd) => ({\n name: sd.name,\n url: `https://github.com/${childInfo.org}/${childInfo.repo}/tree/${childInfo.branch}/${sd.path}`\n }));\n nestedDirEntries.push(...subs);\n } catch (_) {}\n }\n const nbFiles = entries.filter((e) => e && e.type === 'file' && /\\.ipynb$/i.test(e.name));\n // Always include both first-level dirs and one-level nested dirs (deduped)\n const unionDirs = Array.from(new Map([...dirEntries, ...nestedDirEntries].map((d) => [d.url, d])).values());\n const baseList = unionDirs;\n const selectedDirs = typeof limit === 'number' && limit > 0 ? baseList.slice(0, limit) : baseList;\n const dirResults = await Promise.all(selectedDirs.map((d) => fetchGithubCookbookFromDir({ dir: d.url })));\n const dirItems = dirResults.flatMap((r) => r.items || []);\n const fileItems = nbFiles.map((f) => {\n const slug = slugifyTitle(f.name.replace(/\\.ipynb$/i, '')) || f.name.replace(/\\.ipynb$/i, '');\n const blobBase = `https://github.com/${info.org}/${info.repo}/blob/${info.branch}`;\n const ipynbLink = `${blobBase}/${info.dirPath ? info.dirPath + '/' : ''}${f.name}`;\n // Prefer a folder URL if present, otherwise use parent URL\n const github = parent || `https://github.com/${info.org}/${info.repo}/tree/${info.branch}/${info.dirPath || ''}`.replace(/\\/$/, '');\n return {\n slug, title: slug, description: null, image: null, imageFit: 'cover', username: null, avatarUrl: null,\n github, demo: null, language: null, difficulty: null, tags: [], sections: [], date: null,\n readmeSource: null, ipynbLink, ctas: [ { icon: 'mdi:notebook', href: ipynbLink } ], authors: [], featured: false, markdown: null,\n };\n });\n const items = [...dirItems, ...fileItems];\n return { items, fallbackUsed: false, sourceUrl: parent };\n}\n\nexport function getGroqCookbookRootItem() {\n const repoRoot = \"https://github.com/groq/groq-api-cookbook/tree/main\";\n const rawLogo = \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/images/groq-logo.png\";\n return {\n slug: \"groq-api-cookbook\",\n title: \"Groq API Cookbook\",\n description: \"Getting Started • Tutorials • Questions • Bug Reporting • Contributing\",\n image: rawLogo,\n imageFit: \"cover\",\n username: \"Groq\",\n avatarUrl: \"https://console.groq.com/groq-circle.png\",\n github: repoRoot,\n demo: null,\n language: null,\n difficulty: null,\n tags: [\"overview\", \"cookbook\"],\n sections: [\"overview\"],\n date: null,\n readmeSource: \"https://github.com/groq/groq-api-cookbook/blob/main/README.md\",\n ipynbLink: null,\n ctas: [\n { icon: \"mdi:github\", href: repoRoot },\n { icon: \"mdi:book-open-outline\", href: \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials\" },\n { icon: \"mdi:help-circle-outline\", href: \"https://github.com/groq/groq-api-cookbook/discussions\" },\n { icon: \"mdi:alert-circle-outline\", href: \"https://github.com/groq/groq-api-cookbook/issues\" },\n { icon: \"mdi:account-plus-outline\", href: \"https://github.com/groq/groq-api-cookbook/blob/main/CONTRIBUTING.md\" }\n ],\n authors: [],\n featured: true,\n markdown: \"Groq API Cookbook — Getting Started, Tutorials, Questions, Bug Reporting, Contributing\",\n };\n}\n\n\n",[],[226],{"_103":235,"_95":236,"_152":237,"_154":-5,"_155":137,"_156":238,"_158":159,"_105":239,"_100":183,"_161":240,"_163":241,"_164":22,"_165":96,"_166":242,"_98":243},"0cb30a26-7fbc-11f0-84b1-0224a6c84d84","main.js","786f8b08-7fb8-11f0-b010-0224a6c84d84",14,["D",1755910609188],"http","import { Hono } from \"https://deno.land/x/hono@v3.11.7/mod.ts\";\nimport \"jsr:@std/dotenv/load\";\nimport { load as cheerioLoad } from \"npm:cheerio@1.0.0-rc.12\";\nimport { listFiles, readFile } from \"https://esm.town/v/std/utils/index.ts\";\n\nconst pipeline_url = `https://yawnxyz-executeproxy.web.val.run/execute`;\n\nconst app = new Hono();\n\n// Environment-aware file reading function\nasync function readFileContent(filePath) {\n if (typeof Deno !== \"undefined\" && Deno.env.get(\"valtown\")) {\n return await readFile(filePath, import.meta.url);\n } else {\n return await Deno.readTextFile(filePath);\n }\n}\n\n// Utils for scraping Groq examples\nconst GROQ_EXAMPLES_URL = \"https://console.groq.com/docs/examples\";\n\nfunction toAbsoluteUrl(path) {\n if (!path) return null;\n if (path.startsWith(\"http://\") || path.startsWith(\"https://\")) return path;\n return \"https://console.groq.com\" + (path.startsWith(\"/\") ? path : \"/\" + path);\n}\n\nfunction parseExamplesFromHtml(htmlText) {\n const $ = cheerioLoad(htmlText);\n const cards = $(\n \"div.rounded-lg.border.bg-card.text-card-foreground.overflow-hidden.h-full.flex.flex-col\"\n );\n const items = [];\n\n cards.each((_idx, el) => {\n const card = $(el);\n const title = card.find(\"h3\").first().text().trim();\n\n let description = card.find(\"p.text-sm\").first().text().trim();\n if (!description) {\n const firstP = card.find(\"p\").filter((_, p) => $(p).text().trim().length > 0).first();\n description = firstP.text().trim();\n }\n\n const imageSrc = card.find(\".aspect-video img\").attr(\"src\") || null;\n const image = toAbsoluteUrl(imageSrc);\n\n const authorP = card.find(\"p.text-xs\").first();\n const avatarUrl = toAbsoluteUrl(authorP.find(\"img\").attr(\"src\") || null);\n let username = authorP.text().replace(/\\s+/g, \" \").trim();\n username = username.replace(/^by\\s*/i, \"\").trim();\n\n let github = null;\n let demo = null;\n card.find(\"a\").each((_, a) => {\n const href = $(a).attr(\"href\") || \"\";\n const text = $(a).text().toLowerCase();\n const abs = href ? (href.startsWith(\"http\") ? href : toAbsoluteUrl(href)) : null;\n if (!abs) return;\n if (text.includes(\"view repository\") || abs.includes(\"github.com\")) github = abs;\n if (text.includes(\"live demo\")) demo = abs;\n });\n\n const item = {\n title,\n description,\n image,\n imageFit: \"cover\",\n username,\n avatarUrl,\n github,\n demo,\n };\n\n if (item.title || item.github || item.demo) items.push(item);\n });\n\n return items;\n}\n\n\nasync function fetchGroqExamples() {\n const res = await fetch(GROQ_EXAMPLES_URL, {\n headers: {\n \"user-agent\":\n \"Mozilla/5.0 (compatible; GroqExamplesFetcher/1.0; +https://labspace.ai)\",\n accept: \"text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8\",\n },\n });\n const htmlText = await res.text();\n const items = parseExamplesFromHtml(htmlText);\n return { items: Array.isArray(items) ? items : [], fallbackUsed: false };\n}\n\n// --- GitHub cookbook adapter helpers ---\nfunction convertGithubToRawUrls(githubUrl) {\n const urls = [];\n const refsHeadsUrl = githubUrl\n .replace('github.com', 'raw.githubusercontent.com')\n .replace('/blob/', '/refs/heads/')\n .replace('/tree/', '/refs/heads/');\n urls.push(refsHeadsUrl);\n const directUrl = githubUrl\n .replace('github.com', 'raw.githubusercontent.com')\n .replace('/blob/', '/')\n .replace('/tree/', '/');\n urls.push(directUrl);\n if (githubUrl.includes('raw.githubusercontent.com')) urls.push(githubUrl);\n return urls;\n}\n\nasync function tryFetchJsonFromPossibleUrls(possibleUrls) {\n for (const u of possibleUrls) {\n try {\n const resp = await fetch(u);\n if (!resp.ok) continue;\n const contentType = resp.headers.get('content-type') || '';\n if (contentType.includes('application/json')) {\n const json = await resp.json();\n return json;\n }\n const text = await resp.text();\n try {\n const parsed = JSON.parse(text);\n return parsed;\n } catch (_) {\n // Not JSON, skip\n }\n } catch (_) {\n // ignore and continue\n }\n }\n return null;\n}\n\nfunction githubApiHeaders() {\n const headers = {\n accept: 'application/vnd.github+json',\n 'user-agent': 'GroqCookbookScraper/1.0 (+https://labspace.ai)'\n };\n try {\n const token = (typeof Deno !== 'undefined' && Deno.env) ? (Deno.env.get('GITHUB_TOKEN') || Deno.env.get('GH_TOKEN')) : null;\n if (token) headers['authorization'] = `Bearer ${token}`;\n } catch (_) {}\n return headers;\n}\n\nfunction mapCookbookItemToSchema(entry) {\n const authorName = entry?.author?.username || (Array.isArray(entry?.authors) ? entry.authors.map(a => a.username).join(', ') : null);\n const avatarUrl = entry?.author?.imageUrl || (Array.isArray(entry?.authors) && entry.authors.length ? entry.authors[0].imageUrl : null);\n const githubFromCtas = Array.isArray(entry?.ctas) ? (entry.ctas.find(c => (c.icon || '').includes('github'))?.href || null) : null;\n const demoFromCtas = Array.isArray(entry?.ctas) ? (entry.ctas.find(c => /demo|vercel|app|run|spaces|live|render|heroku|netlify|railway/i.test(c.href || ''))?.href || null) : null;\n\n return {\n id: entry?.id ?? null,\n slug: entry?.slug ?? null,\n title: entry?.title ?? null,\n description: entry?.description ?? null,\n image: entry?.image || null,\n imageFit: 'cover',\n username: authorName,\n avatarUrl,\n github: entry?.githubLink || githubFromCtas || null,\n demo: demoFromCtas || null,\n // Cookbook-specific fields\n language: entry?.language || null,\n difficulty: entry?.difficulty || null,\n tags: entry?.tags || [],\n sections: entry?.sections || [],\n date: entry?.date || null,\n readmeSource: entry?.readmeSource || null,\n ipynbLink: entry?.ipynbLink || null,\n ctas: entry?.ctas || [],\n authors: entry?.authors || (entry?.author ? [entry.author] : []),\n featured: entry?.featured || false,\n markdown: entry?.markdown || null,\n };\n}\n\n// No fallback cookbook examples; adapters must fetch live or return empty\n\nfunction slugifyTitle(title) {\n if (!title) return null;\n return title\n .toLowerCase()\n .replace(/[^a-z0-9]+/g, '-')\n .replace(/(^-|-$)+/g, '');\n}\n\nfunction parseGithubDirUrl(dirUrl) {\n try {\n const m = dirUrl.match(/^https?:\\/\\/github\\.com\\/([^/]+)\\/([^/]+)\\/tree\\/([^/]+)\\/?(.*)$/);\n if (!m) return null;\n const [, org, repo, branch, pathRest] = m;\n const dirPath = (pathRest || '').replace(/^\\/+|\\/+$/g, '');\n return { org, repo, branch, dirPath };\n } catch (_) {\n return null;\n }\n}\n\nfunction buildRawBase({ org, repo, branch, dirPath }) {\n const suffix = dirPath ? `/${dirPath}` : '';\n return `https://raw.githubusercontent.com/${org}/${repo}/${branch}${suffix}`;\n}\n\nasync function fetchReadmeFromGithubDir(dirUrl) {\n const info = parseGithubDirUrl(dirUrl);\n if (!info) return { content: '', rawUrl: null, rawBase: null };\n const rawBase = buildRawBase(info);\n const candidates = [\n `${rawBase}/README.md`,\n `${rawBase}/Readme.md`,\n `${rawBase}/readme.md`,\n `${rawBase}/README.MD`,\n `${rawBase}/README.markdown`,\n `${rawBase}/README.MARKDOWN`,\n ];\n for (const u of candidates) {\n try {\n const res = await fetch(u);\n if (res.ok) {\n const text = await res.text();\n return { content: text, rawUrl: u, rawBase };\n }\n } catch (_) {\n // continue\n }\n }\n // Fallback: list directory contents and try to find a README file\n try {\n const infoForList = parseGithubDirUrl(dirUrl);\n if (infoForList) {\n const apiUrl = buildGithubApiContentsUrl(infoForList);\n const res = await fetch(apiUrl, {\n headers: {\n accept: 'application/vnd.github+json',\n 'user-agent': 'GroqCookbookScraper/1.0 (+https://labspace.ai)'\n }\n });\n if (res.ok) {\n const data = await res.json();\n if (Array.isArray(data) && data.length) {\n let readmeEntry = data.find((e) => e && e.type === 'file' && /^readme(\\.|$)/i.test(e.name));\n if (!readmeEntry) readmeEntry = data.find((e) => e && e.type === 'file' && /\\.md$/i.test(e.name));\n if (readmeEntry) {\n const url = `${rawBase.replace(/\\/$/, '')}/${readmeEntry.name}`;\n try {\n const res2 = await fetch(url);\n if (res2.ok) {\n const text = await res2.text();\n return { content: text, rawUrl: url, rawBase };\n }\n } catch (_) {}\n }\n }\n }\n }\n } catch (_) {\n // ignore\n }\n return { content: '', rawUrl: null, rawBase };\n}\n\nfunction extractTitleAndDescriptionFromMarkdown(md) {\n if (!md) return { title: null, description: null };\n const lines = md.split(/\\r?\\n/);\n let title = null;\n let startIdx = 0;\n for (let i = 0; i < lines.length; i++) {\n const line = lines[i].trim();\n if (line.startsWith('# ')) {\n title = line.replace(/^#\\s+/, '').trim();\n startIdx = i + 1;\n break;\n }\n }\n // find first non-empty paragraph after title\n let description = null;\n let para = [];\n for (let i = startIdx; i < lines.length; i++) {\n const line = lines[i];\n // stop at next header\n if (/^#{1,6}\\s+/.test(line)) break;\n if (line.trim() === '') {\n if (para.length) break;\n continue;\n }\n para.push(line.trim());\n }\n if (para.length) description = para.join(' ');\n return { title, description };\n}\n\nfunction extractFirstImageUrlFromMarkdown(md, rawBase) {\n if (!md) return null;\n const m = md.match(/!\\[[^\\]]*\\]\$([^)]+)\$/);\n if (!m) return null;\n const url = m[1].trim();\n if (/^https?:\\/\\//i.test(url)) return url;\n if (url.startsWith('/')) return null; // absolute repo path unsupported here\n const base = rawBase?.replace(/\\/$/, '') || '';\n return `${base}/${url}`;\n}\n\nfunction extractFirstIpyNbLinkFromMarkdown(md) {\n if (!md) return null;\n // Prefer markdown links containing .ipynb\n const mdLink = md.match(/\\[[^\\]]*\\]\$([^)]+\\.ipynb(?:\\?[^)]*)?)\$/i);\n if (mdLink) return mdLink[1];\n // Fallback: plain URLs\n const plain = md.match(/https?:[^\\s)]+\\.ipynb/gi);\n return plain && plain.length ? plain[0] : null;\n}\n\nfunction extractDemoLinkFromMarkdown(md) {\n if (!md) return null;\n const links = Array.from(md.matchAll(/\\[[^\\]]*\\]\$([^)]+)\$/g)).map(m => m[1]);\n const candidates = links.filter(u => /https?:\\/\\//i.test(u));\n const prefer = candidates.find(u => /(vercel|demo|live|appgen|groqlabs|render|railway|heroku|netlify)/i.test(u));\n return prefer || null;\n}\n\nasync function probeRawFile(rawBase, filename) {\n const url = `${rawBase.replace(/\\/$/, '')}/${filename}`;\n try {\n const head = await fetch(url, { method: 'HEAD' });\n if (head.ok) return { exists: true, url };\n } catch (_) {}\n try {\n const get = await fetch(url, { method: 'GET', headers: { 'range': 'bytes=0-0' } });\n return { exists: get.ok, url };\n } catch (_) {\n return { exists: false, url };\n }\n}\n\nasync function fetchGithubCookbookFromDir(query) {\n const dirUrl = query?.dir || query?.repoDirUrl;\n if (!dirUrl) return { items: [], fallbackUsed: false, sourceUrl: null };\n const info = parseGithubDirUrl(dirUrl);\n if (!info) return { items: [], fallbackUsed: false, sourceUrl: dirUrl };\n const { content, rawUrl, rawBase } = await fetchReadmeFromGithubDir(dirUrl);\n const slugFromPath = (info.dirPath ? info.dirPath.split('/').pop() : null) || null;\n let title = null;\n let description = null;\n let image = null;\n let ipynbLink = null;\n let demoLink = null;\n\n if (content) {\n const parsed = extractTitleAndDescriptionFromMarkdown(content);\n title = parsed.title || null;\n description = parsed.description || null;\n image = extractFirstImageUrlFromMarkdown(content, rawBase);\n ipynbLink = extractFirstIpyNbLinkFromMarkdown(content);\n demoLink = extractDemoLinkFromMarkdown(content);\n }\n\n // List directory to find notebooks and detect app.py\n let appExists = false;\n try {\n const apiUrl = buildGithubApiContentsUrl(info);\n const res = await fetch(apiUrl, { headers: githubApiHeaders() });\n if (res.ok) {\n const data = await res.json();\n if (Array.isArray(data)) {\n if (!ipynbLink) {\n const nb = data.find((e) => e && e.type === 'file' && /\\.ipynb$/i.test(e.name));\n if (nb) {\n const blobBase = `https://github.com/${info.org}/${info.repo}/blob/${info.branch}`;\n ipynbLink = `${blobBase}/${info.dirPath ? info.dirPath + '/' : ''}${nb.name}`;\n }\n }\n const appEntry = data.find((e) => e && e.type === 'file' && e.name === 'app.py');\n appExists = !!appEntry;\n }\n }\n } catch (_) {}\n\n if (!title) title = slugifyTitle(slugFromPath || '') || slugFromPath || dirUrl;\n\n const item = {\n slug: slugifyTitle(title) || slugFromPath,\n title,\n description,\n image: image || null,\n imageFit: 'cover',\n username: null,\n avatarUrl: null,\n github: dirUrl,\n demo: demoLink || null,\n language: appExists ? 'python' : null,\n difficulty: null,\n tags: [],\n sections: [],\n date: null,\n readmeSource: rawUrl,\n ipynbLink: ipynbLink || null,\n ctas: [\n { icon: 'mdi:github', href: dirUrl },\n ...(ipynbLink ? [ { icon: 'mdi:notebook', href: ipynbLink } ] : []),\n ...(demoLink ? [ { icon: 'mdi:play-circle-outline', href: demoLink } ] : []),\n ],\n authors: [],\n featured: false,\n markdown: null,\n };\n return { items: [item], fallbackUsed: false, sourceUrl: dirUrl };\n}\n\nfunction buildGithubApiContentsUrl({ org, repo, branch, dirPath }) {\n const path = dirPath ? `/contents/${dirPath}` : `/contents`;\n return `https://api.github.com/repos/${org}/${repo}${path}?ref=${encodeURIComponent(branch)}`;\n}\n\nasync function listGithubSubdirectories(parentDirUrl) {\n const info = parseGithubDirUrl(parentDirUrl);\n if (!info) return [];\n const apiUrl = buildGithubApiContentsUrl(info);\n try {\n const res = await fetch(apiUrl, { headers: githubApiHeaders() });\n if (!res.ok) return [];\n const data = await res.json();\n if (!Array.isArray(data)) return [];\n const children = data.filter((e) => e && e.type === 'dir');\n const prefix = `https://github.com/${info.org}/${info.repo}/tree/${info.branch}`;\n return children.map((d) => ({\n name: d.name,\n path: d.path,\n url: `${prefix}/${d.path}`\n }));\n } catch (_) {\n return [];\n }\n}\n\nasync function fetchGithubCookbooksFromParentDir(query) {\n const parent = query?.parent || query?.parentDir || query?.parentUrl;\n if (!parent) return { items: [], fallbackUsed: false, sourceUrl: null };\n const limit = query?.limit ? Number(query.limit) : undefined;\n // Fetch all entries (dirs and files) in the parent directory\n const info = parseGithubDirUrl(parent);\n const apiUrl = info ? buildGithubApiContentsUrl(info) : null;\n let entries = [];\n if (apiUrl) {\n try {\n const res = await fetch(apiUrl, { headers: githubApiHeaders() });\n if (res.ok) {\n const data = await res.json();\n if (Array.isArray(data)) entries = data;\n }\n } catch (_) {}\n }\n\n const dirEntries = entries.filter((e) => e && e.type === 'dir').map((d) => ({\n name: d.name,\n url: `https://github.com/${info.org}/${info.repo}/tree/${info.branch}/${d.path}`\n }));\n\n const nbFiles = entries.filter((e) => e && e.type === 'file' && /\\.ipynb$/i.test(e.name));\n\n const selectedDirs = typeof limit === 'number' && limit > 0 ? dirEntries.slice(0, limit) : dirEntries;\n const dirResults = await Promise.all(selectedDirs.map((d) => fetchGithubCookbookFromDir({ dir: d.url })));\n const dirItems = dirResults.flatMap((r) => r.items || []);\n\n // Convert ipynb files into minimal items\n const fileItems = nbFiles.map((f) => {\n const slug = slugifyTitle(f.name.replace(/\\.ipynb$/i, '')) || f.name.replace(/\\.ipynb$/i, '');\n const blobBase = `https://github.com/${info.org}/${info.repo}/blob/${info.branch}`;\n const ipynbLink = `${blobBase}/${info.dirPath ? info.dirPath + '/' : ''}${f.name}`;\n const github = `https://github.com/${info.org}/${info.repo}/tree/${info.branch}/${info.dirPath || ''}`.replace(/\\/$/, '');\n return {\n slug,\n title: slug,\n description: null,\n image: null,\n imageFit: 'cover',\n username: null,\n avatarUrl: null,\n github,\n demo: null,\n language: null,\n difficulty: null,\n tags: [],\n sections: [],\n date: null,\n readmeSource: null,\n ipynbLink,\n ctas: [ { icon: 'mdi:notebook', href: ipynbLink } ],\n authors: [],\n featured: false,\n markdown: null,\n };\n });\n\n const items = [...dirItems, ...fileItems];\n return { items, fallbackUsed: false, sourceUrl: parent };\n}\n\nasync function fetchGithubCookbookExamples(query) {\n const urlParam = query?.url || query?.cookbooksUrl || null;\n let entries = null;\n let resolvedFrom = urlParam || null;\n\n if (urlParam) {\n try {\n const urls = urlParam.includes('github.com') ? convertGithubToRawUrls(urlParam) : [urlParam];\n const json = await tryFetchJsonFromPossibleUrls(urls);\n if (Array.isArray(json)) {\n entries = json;\n resolvedFrom = urlParam;\n }\n } catch (_) {\n // ignore\n }\n }\n\n if (!Array.isArray(entries)) {\n return { items: [], fallbackUsed: false, sourceUrl: resolvedFrom };\n }\n\n const items = entries.map(mapCookbookItemToSchema);\n return { items, fallbackUsed: false, sourceUrl: resolvedFrom };\n}\n\n// --- Custom curated data (hard-coded) ---\nfunction getGroqCookbookRootItem() {\n const repoRoot = \"https://github.com/groq/groq-api-cookbook/tree/main\";\n const rawLogo = \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/images/groq-logo.png\";\n return {\n slug: \"groq-api-cookbook\",\n title: \"Groq API Cookbook\",\n description: \"Getting Started • Tutorials • Questions • Bug Reporting • Contributing\",\n image: rawLogo,\n imageFit: \"cover\",\n username: \"Groq\",\n avatarUrl: \"https://console.groq.com/groq-circle.png\",\n github: repoRoot,\n demo: null,\n language: null,\n difficulty: null,\n tags: [\"overview\", \"cookbook\"],\n sections: [\"overview\"],\n date: null,\n readmeSource: \"https://github.com/groq/groq-api-cookbook/blob/main/README.md\",\n ipynbLink: null,\n ctas: [\n { icon: \"mdi:github\", href: repoRoot },\n { icon: \"mdi:book-open-outline\", href: \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials\" },\n { icon: \"mdi:help-circle-outline\", href: \"https://github.com/groq/groq-api-cookbook/discussions\" },\n { icon: \"mdi:alert-circle-outline\", href: \"https://github.com/groq/groq-api-cookbook/issues\" },\n { icon: \"mdi:account-plus-outline\", href: \"https://github.com/groq/groq-api-cookbook/blob/main/CONTRIBUTING.md\" }\n ],\n authors: [],\n featured: true,\n markdown: \"Groq API Cookbook — Getting Started, Tutorials, Questions, Bug Reporting, Contributing\",\n };\n}\n\nconst html = `\n\n\n\n \n \n \n Boink - A kitchen sink of common interface elements\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n

\n \n

Boink

A kitchen sink of common interface elements

\n\n

\n \n

\n Boink is a simple tool for processing text data.\n

\n\n

\n \n

\n Simply paste your text in the input box below and click Execute.\n

\n\n

Example of summary / details toggle

\n \n

\n\n

\n Select dropdown example:\n

\n \n

\n\n \n \n

\n \n

Output will appear here

\n\n

\n 0 characters • 0 words\n

\n \n

Output will appear here

\n\n

\n A labspace.ai experiment\n

\n\n \n\n\n`;\n\n// Adapter registry and helpers\nconst adaptersRegistry = {\n \"groq-console\": {\n name: \"groq-console\",\n label: \"Groq Console Examples\",\n title: \"Groq Examples\",\n description: \"Jumpstart your AI-powered applications with Groq's lightning-fast inference templates and community-driven solutions.\",\n source: \"groq-console\",\n sourceUrl: GROQ_EXAMPLES_URL,\n async fetchItems() {\n const { items, fallbackUsed } = await fetchGroqExamples();\n return { items, fallbackUsed, sourceUrl: GROQ_EXAMPLES_URL };\n },\n },\n \"github-cookbooks\": {\n name: \"github-cookbooks\",\n label: \"Groq Cookbook Examples (GitHub)\",\n title: \"Groq Cookbook Tutorials\",\n description: \"Explore tutorials, notebooks, and sample apps from the Groq API Cookbook.\",\n source: \"github-cookbooks\",\n sourceUrl: \"https://github.com/groq/groq-api-cookbook\",\n // Accepts optional query.url or query.cookbooksUrl pointing to JSON array (cookbookExamples)\n async fetchItems(query) {\n // If a specific directory is provided, scrape just that one (e.g., Website Guru)\n if (query?.dir || query?.repoDirUrl) {\n const { items, fallbackUsed, sourceUrl } = await fetchGithubCookbookFromDir(query || {});\n return { items, fallbackUsed, sourceUrl: sourceUrl || this.sourceUrl };\n }\n // If a parent tutorials directory is provided, enumerate child dirs and scrape each\n if (query?.parent || query?.parentDir || query?.parentUrl) {\n const { items, fallbackUsed, sourceUrl } = await fetchGithubCookbooksFromParentDir(query || {});\n return { items, fallbackUsed, sourceUrl: sourceUrl || this.sourceUrl };\n }\n // Default: scrape tutorials parent directory\n const defaultParent = \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials\";\n const { items, fallbackUsed, sourceUrl } = await fetchGithubCookbooksFromParentDir({ parent: defaultParent, limit: (query || {}).limit });\n return { items, fallbackUsed, sourceUrl: sourceUrl || defaultParent };\n },\n },\n \"github-website-guru\": {\n name: \"github-website-guru\",\n label: \"Website Guru (GitHub)\",\n title: \"Website Guru\",\n description: \"Ask questions about any website with a Streamlit + Groq reference app.\",\n source: \"github-cookbooks\",\n sourceUrl: \"https://github.com/groq/groq-api-cookbook/tree/main/chat_with_website\",\n async fetchItems() {\n const { items, fallbackUsed, sourceUrl } = await fetchGithubCookbookFromDir({ dir: this.sourceUrl });\n return { items, fallbackUsed, sourceUrl };\n },\n },\n \"groq-cookbook-root\": {\n name: \"groq-cookbook-root\",\n label: \"Groq API Cookbook\",\n title: \"Groq API Cookbook\",\n description: \"This is a collection of example code and guides for Groq API for you to explore.\",\n source: \"custom\",\n sourceUrl: \"https://github.com/groq/groq-api-cookbook/tree/main\",\n async fetchItems() {\n return { items: [getGroqCookbookRootItem()], fallbackUsed: false, sourceUrl: this.sourceUrl };\n },\n },\n \"github-replit-examples\": {\n name: \"github-replit-examples\",\n label: \"Replit Examples (GitHub)\",\n title: \"Replit Examples\",\n description: \"Forkable Replit projects demonstrating Groq API integrations you can run in minutes.\",\n source: \"github-cookbooks\",\n sourceUrl: \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples\",\n async fetchItems(query) {\n const { items, fallbackUsed, sourceUrl } = await fetchGithubCookbooksFromParentDir({ parent: this.sourceUrl, limit: (query || {}).limit });\n return { items, fallbackUsed, sourceUrl };\n },\n },\n // Additional adapters can be registered here, e.g. \"github-cookbooks\"\n};\n\nfunction listAdapters() {\n return Object.values(adaptersRegistry).map((a) => ({\n name: a.name,\n label: a.label,\n title: a.title,\n description: a.description,\n source: a.source,\n sourceUrl: a.sourceUrl,\n }));\n}\n\nasync function runAdapter(adapterName, queryArgs) {\n const adapter = adaptersRegistry[adapterName];\n if (!adapter) {\n return {\n adapter: adapterName,\n error: \"Adapter not found\",\n count: 0,\n items: [],\n fetchedAt: new Date().toISOString(),\n };\n }\n try {\n const { items, fallbackUsed, sourceUrl } = await adapter.fetchItems(queryArgs);\n const itemsWithAdapter = Array.isArray(items) ? items.map((it) => ({ adapter: adapter.name, ...it })) : [];\n return {\n adapter: adapter.name,\n label: adapter.label,\n title: adapter.title,\n description: adapter.description,\n source: adapter.source,\n sourceUrl: sourceUrl || adapter.sourceUrl,\n count: itemsWithAdapter.length,\n items: itemsWithAdapter,\n fallbackUsed: !!fallbackUsed,\n fetchedAt: new Date().toISOString(),\n };\n } catch (error) {\n return {\n adapter: adapter.name,\n label: adapter.label,\n title: adapter.title,\n description: adapter.description,\n source: adapter.source,\n sourceUrl: adapter.sourceUrl,\n count: 0,\n items: [],\n error: String(error?.message || error),\n fetchedAt: new Date().toISOString(),\n };\n }\n}\n\n// Keep UI under /ui\napp.get(\"/ui\", (c) => c.html(html));\n\n// List available adapters\napp.get(\"/adapters\", (c) => {\n return c.json({ adapters: listAdapters() });\n});\n\n// Root: run one or more adapters, return per-adapter results (not combined)\napp.get(\"/\", async (c) => {\n // Try prebuilt snapshot first\n try {\n const snapshot = await readFileContent(\"./projects.json\");\n if (snapshot) {\n const parsed = JSON.parse(snapshot);\n if (parsed && Array.isArray(parsed.adapters)) {\n return c.json(parsed);\n }\n }\n } catch (_) {}\n\n const adapterQuery = c.req.query(\"adapter\");\n const requested = adapterQuery\n ? adapterQuery.split(\",\").map((s) => s.trim()).filter(Boolean)\n : Object.keys(adaptersRegistry);\n\n // Collect all query params (first value only) and pass to adapters\n const queries = c.req.queries();\n const queryArgs = {};\n for (const key in queries) {\n if (key === \"adapter\") continue;\n const val = queries[key];\n queryArgs[key] = Array.isArray(val) ? val[0] : val;\n }\n\n const results = await Promise.all(requested.map((name) => runAdapter(name, queryArgs)));\n return c.json({ adapters: results });\n});\n\n// Fetch a single adapter by name\napp.get(\"/adapters/:name\", async (c) => {\n const name = c.req.param('name');\n const queries = c.req.queries();\n const queryArgs = {};\n for (const key in queries) {\n const val = queries[key];\n queryArgs[key] = Array.isArray(val) ? val[0] : val;\n }\n const result = await runAdapter(name, queryArgs);\n return c.json(result);\n});\n\n// Removed legacy boink UI/API\n\nexport default (typeof Deno !== \"undefined\" && Deno.env.get(\"valtown\")) ? app.fetch : app;\n",[],[236],{"_103":245,"_95":99,"_152":246,"_154":-5,"_155":137,"_156":247,"_158":159,"_105":248,"_100":32,"_161":174,"_163":249,"_164":22,"_165":-5,"_166":250,"_98":251},"3a4bebfc-7fc0-11f0-bae3-0224a6c84d84","3a4bece2-7fc0-11f0-bae3-0224a6c84d84",18,["D",1755912403691],"note that the default cookbook image is using\n\nhttps://canada1.discourse-cdn.com/flex003/uploads/groq1/original/1X/900fb9a3f1a492df1ddfa9ff695bbc6918831754.png",[],[99],{"_103":253,"_95":254,"_152":255,"_154":-5,"_155":137,"_156":256,"_158":159,"_105":257,"_100":210,"_161":174,"_163":258,"_164":22,"_165":-5,"_166":259,"_98":260},"2badc5fa-7fc2-11f0-b061-0224a6c84d84","projects.json","7876474a-7fb8-11f0-a364-0224a6c84d84",21,["D",1755913238155],"{\n \"adapters\": [\n {\n \"adapter\": \"groq-console\",\n \"label\": \"Groq Console Examples\",\n \"title\": \"Groq Examples\",\n \"description\": \"Jumpstart your AI-powered applications with Groq's lightning-fast inference templates and community-driven solutions.\",\n \"source\": \"groq-console\",\n \"sourceUrl\": \"https://console.groq.com/docs/examples\",\n \"items\": [\n {\n \"title\": \"Stock Bot\",\n \"description\": \"Stock Bot is an AI chatbot offering real-time stock data, charts, financials, and market insights.\",\n \"image\": \"https://console.groq.com/templates/stockbot.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Benjamin Klieger\",\n \"avatarUrl\": \"https://console.groq.com/groq-circle.png\",\n \"github\": \"https://github.com/bklieger-groq/stockbot-on-groq\",\n \"demo\": \"https://groq-stockbot.vercel.app/\"\n },\n {\n \"title\": \"Starter Chatbot\",\n \"description\": \"Open-source AI chatbot app template built with Next.js and the AI SDK by Vercel.\",\n \"image\": \"https://console.groq.com/templates/ai-sdk-starter-groq.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Vercel\",\n \"avatarUrl\": null,\n \"github\": \"https://github.com/vercel-labs/ai-sdk-starter-groq\",\n \"demo\": \"https://ai-sdk-starter-groq.vercel.app/\"\n },\n {\n \"title\": \"Blog Generator from Audio\",\n \"description\": \"Groq's Blog Wizard generates structured blog posts from audio or video content using AI models like Whisper and Llama3.\",\n \"image\": \"https://console.groq.com/templates/blogwizard.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Benjamin Klieger\",\n \"avatarUrl\": \"https://console.groq.com/groq-circle.png\",\n \"github\": \"https://github.com/groq/blogwizard\",\n \"demo\": \"https://blogwizard.groqlabs.com/\"\n },\n {\n \"title\": \"Groq App Generator\",\n \"description\": \"Groq App Generator is an interactive web application that generates and modifies web applications in microseconds.\",\n \"image\": \"https://console.groq.com/showcase-applications/appgen.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Rick Lamers, Jose Menendez, Benjamin Klieger\",\n \"avatarUrl\": \"https://console.groq.com/groq-circle.png\",\n \"github\": \"https://github.com/groq/groq-appgen\",\n \"demo\": \"https://appgen.groqlabs.com/\"\n },\n {\n \"title\": \"Groq x Gradio Voice Assistant\",\n \"description\": \"Groq and Gradio voice assistant application uses Groq for real-time speech recognition and Gradio for user interface.\",\n \"image\": \"https://console.groq.com/showcase-applications/voiceapp.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Hatice Ozen\",\n \"avatarUrl\": \"https://console.groq.com/groq-circle.png\",\n \"github\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/groq-gradio/groq-gradio-tutorial.ipynb\",\n \"demo\": null\n },\n {\n \"title\": \"Magic Spell\",\n \"description\": \"AI-powered text editor built with Next.js, Vercel AI SDK, and Groq.\",\n \"image\": \"https://console.groq.com/showcase-applications/magic-spell.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Ai-ng and Nick Oates\",\n \"avatarUrl\": null,\n \"github\": \"https://github.com/ai-ng/magic-spell\",\n \"demo\": \"https://magic-spell.vercel.app/\"\n },\n {\n \"title\": \"Groq MCP Server\",\n \"description\": \"Groq MCP Server is a server for querying Groq models from clients like Claude and others.\",\n \"image\": \"https://console.groq.com/showcase-applications/groq-mcp-server.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Jan Zheng\",\n \"avatarUrl\": \"https://console.groq.com/groq-circle.png\",\n \"github\": \"https://github.com/groq/groq-mcp-server\",\n \"demo\": null\n },\n {\n \"title\": \"Groq Compound CLI\",\n \"description\": \"Groq Compound CLI is an interactive command line interface for the compound-beta system.\",\n \"image\": \"https://console.groq.com/showcase-applications/compound-cli.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Benjamin Klieger\",\n \"avatarUrl\": \"https://console.groq.com/groq-circle.png\",\n \"github\": \"https://github.com/bklieger-groq/compound-cli\",\n \"demo\": null\n },\n {\n \"title\": \"Groq Desktop\",\n \"description\": \"Groq Desktop is a local MCP client with server support for Groq models.\",\n \"image\": \"https://console.groq.com/showcase-applications/groq-desktop-beta.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Rick Lamers\",\n \"avatarUrl\": \"https://console.groq.com/groq-circle.png\",\n \"github\": \"https://github.com/groq/groq-desktop-beta\",\n \"demo\": null\n },\n {\n \"title\": \"Groq Compound MCP Server\",\n \"description\": \"Groq Compound MCP Server is a server for interacting with Groq models.\",\n \"image\": \"https://console.groq.com/showcase-applications/groq-compound-mcp-server.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Rick Lamers, John Barrus\",\n \"avatarUrl\": \"https://console.groq.com/groq-circle.png\",\n \"github\": \"https://github.com/groq/compound-mcp-server\",\n \"demo\": null\n }\n ],\n \"count\": 10\n },\n {\n \"adapter\": \"github-cookbooks\",\n \"label\": \"Groq Cookbook Examples (GitHub)\",\n \"title\": \"Groq Cookbook Tutorials\",\n \"description\": \"Explore tutorials, notebooks, and sample apps from the Groq API Cookbook.\",\n \"source\": \"github-cookbooks\",\n \"sourceUrl\": \"https://github.com/groq/groq-api-cookbook\",\n \"items\": [\n {\n \"slug\": \"groq-api-cookbook\",\n \"title\": \"Groq API Cookbook\",\n \"description\": \"GitHub repository \\\"groq-api-cookbook\\\" contains a README.md file with documentation and links to tutorials and other resources.\",\n \"image\": \"https://canada1.discourse-cdn.com/flex003/uploads/groq1/original/1X/900fb9a3f1a492df1ddfa9ff695bbc6918831754.png\",\n \"imageFit\": \"cover\",\n \"username\": \"Groq\",\n \"avatarUrl\": \"https://console.groq.com/groq-circle.png\",\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [\n \"overview\",\n \"cookbook\"\n ],\n \"sections\": [\n \"overview\"\n ],\n \"date\": null,\n \"readmeSource\": \"https://github.com/groq/groq-api-cookbook/blob/main/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main\"\n },\n {\n \"icon\": \"mdi:book-open-outline\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials\"\n },\n {\n \"icon\": \"mdi:help-circle-outline\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/discussions\"\n },\n {\n \"icon\": \"mdi:alert-circle-outline\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/issues\"\n },\n {\n \"icon\": \"mdi:account-plus-outline\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/CONTRIBUTING.md\"\n }\n ],\n \"authors\": [],\n \"featured\": true,\n \"markdown\": \"Groq API Cookbook — Getting Started, Tutorials, Questions, Bug Reporting, Contributing\"\n },\n {\n \"slug\": \"portkey-ai-with-groq\",\n \"title\": \"Portkey AI with Groq\",\n \"description\": \"Portkey is a control panel for AI apps that enables teams to build reliable, cost-efficient, and fast applications by integrating with various AI models and services.\",\n \"image\": \"https://raw.githubusercontent.com/siddharthsambharia-portkey/Portkey-Product-Images/refs/heads/main/Portkey-Dashboard.png\",\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/Portkey-with-Groq\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/Portkey-with-Groq/Readme.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/Portkey-with-Groq\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"agno-groq-mlb-game-recap-generator\",\n \"title\": \"Agno + Groq MLB Game Recap Generator\",\n \"description\": \"project uses multiple AI agents with different language models to generate comprehensive MLB game recaps.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/agno-mixture-of-agents\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/agno-mixture-of-agents/README.md\",\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/agno-mixture-of-agents/Mixture-of-Agents-Agno-Groq.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/agno-mixture-of-agents\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/agno-mixture-of-agents/Mixture-of-Agents-Agno-Groq.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"travel-agent-powered-by-aixplain\",\n \"title\": \"Travel Agent Powered by aiXplain\",\n \"description\": \"Travel Agent is a modular multi-agent system powered by Groq for fast inference speed and personalized travel planning experiences.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/aiXplain-agents\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/aiXplain-agents/README.md\",\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/aiXplain-agents/aiXplain_Agents.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/aiXplain-agents\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/aiXplain-agents/aiXplain_Agents.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"arize-phoenix-evaluate-groq-agent\",\n \"title\": \"arize-phoenix-evaluate-groq-agent\",\n \"description\": \"Phoenix is an open-source AI observability platform for tracing, evaluating, and experimenting with Groq applications.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/arize-phoenix-evaluate-groq-agent\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/arize-phoenix-evaluate-groq-agent/README.md\",\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/arize-phoenix-evaluate-groq-agent/trace_and_evaluate_function_calling_agent.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/arize-phoenix-evaluate-groq-agent\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/arize-phoenix-evaluate-groq-agent/trace_and_evaluate_function_calling_agent.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"audio-chunking\",\n \"title\": \"audio-chunking\",\n \"description\": \"Chunking longer audio files for Whisper models on Groq involves breaking down audio files into manageable chunks to ensure reliable transcription while maintaining high accuracy.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/audio-chunking\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/audio-chunking/audio_chunking_tutorial.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/audio-chunking\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/audio-chunking/audio_chunking_tutorial.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"analyze-and-tag-images-with-llama-4-on-groq-batch\",\n \"title\": \"Analyze and Tag Images with Llama 4 on Groq Batch\",\n \"description\": \"Analyzing a bulk set of images to tag and categorize them using the Groq Batch API and Llama 4 model.\",\n \"image\": \"https://canada1.discourse-cdn.com/flex003/uploads/groq1/original/1X/900fb9a3f1a492df1ddfa9ff695bbc6918831754.png\",\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/batch-analyze-images\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/batch-analyze-images/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/batch-analyze-images\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"groq-batch-processing\",\n \"title\": \"Groq Batch Processing\",\n \"description\": \"Groq API batch processing involves setting up dependencies, uploading a JSONL file, creating a batch object, monitoring status, and retrieving results.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/batch-processing\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/batch-processing/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/batch-processing\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"benchmarking-rag-langchain\",\n \"title\": \"benchmarking-rag-langchain\",\n \"description\": \"Retrieval Augmented Generation pipeline is benchmarked using Llama3 and LangChain to evaluate its performance, limitations, and potential for improvement.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/benchmarking-rag-langchain\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/benchmarking-rag-langchain/benchmarking_rag.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/benchmarking-rag-langchain\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/benchmarking-rag-langchain/benchmarking_rag.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"composio-newsletter-summarizer-agent\",\n \"title\": \"composio-newsletter-summarizer-agent\",\n \"description\": \"Groq's LLMs can be used with Composio to create seamless integrations between applications and agents.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/composio-newsletter-summarizer-agent\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/composio-newsletter-summarizer-agent/README.md\",\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/composio-newsletter-summarizer-agent/composio-groq.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/composio-newsletter-summarizer-agent\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/composio-newsletter-summarizer-agent/composio-groq.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"crewai-mixture-of-agents\",\n \"title\": \"crewai-mixture-of-agents\",\n \"description\": \"mixture of AI agents with different language models collaboratively generates a game recap article by aggregating diverse outputs from multiple writers and editing them into a polished final result.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/crewai-mixture-of-agents\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/crewai-mixture-of-agents/Mixture-of-Agents-Crew-AI-Groq.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/crewai-mixture-of-agents\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/crewai-mixture-of-agents/Mixture-of-Agents-Crew-AI-Groq.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"function-calling-101-ecommerce\",\n \"title\": \"function-calling-101-ecommerce\",\n \"description\": \"Function calling in large language models allows for invoking pre-defined functions to perform specific tasks, combining flexibility and creativity with consistent and repeatable actions.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/function-calling-101-ecommerce\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/function-calling-101-ecommerce/Function-Calling-101-Ecommerce.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/function-calling-101-ecommerce\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/function-calling-101-ecommerce/Function-Calling-101-Ecommerce.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"function-calling-sql\",\n \"title\": \"function-calling-sql\",\n \"description\": \"Groq API is used to build a \\\"chat with my database\\\" tool, exploring methods for querying a database and leveraging its JSON mode and tool use feature for function calling.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/function-calling-sql\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/function-calling-sql/json-mode-function-calling-for-sql.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/function-calling-sql\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/function-calling-sql/json-mode-function-calling-for-sql.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"groq-gradio\",\n \"title\": \"groq-gradio\",\n \"description\": \"voice-powered AI application is built using Groq for real-time speech recognition and text generation, Gradio for an interactive web interface, and Hugging Face Spaces for hosting.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/groq-gradio\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/groq-gradio/groq-gradio-tutorial.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/groq-gradio\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/groq-gradio/groq-gradio-tutorial.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"groq-chat-streamlit-app\",\n \"title\": \"Groq Chat Streamlit App\",\n \"description\": \"Streamlit app integrates with the Groq API to provide a fast and customizable chat interface with advanced language models.\",\n \"image\": \"https://static.streamlit.io/badges/streamlit_badge_black_white.svg\",\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/groq_streamlit_demo\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/groq_streamlit_demo/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/groq_streamlit_demo\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"instagram-reel-subtitler\",\n \"title\": \"instagram-reel-subtitler\",\n \"description\": \"Automated Instagram Reel subtitle generator using Groq Whisper extracts audio, transcribes it, and overlays word-by-word subtitles onto the video.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/instagram-reel-subtitler\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/instagram-reel-subtitler/subtitler-tutorial.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/instagram-reel-subtitler\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/instagram-reel-subtitler/subtitler-tutorial.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"jigsawstack-prompt-engine\",\n \"title\": \"jigsawstack-prompt-engine\",\n \"description\": \"JigsawStack Prompt Engine is a feature that automatically chooses the best Large Language Model for every prompt, delivering fast results powered by Groq.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/jigsawstack-prompt-engine\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/jigsawstack-prompt-engine/README.md\",\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/jigsawstack-prompt-engine/jigsawstack-prompt-engine.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/jigsawstack-prompt-engine\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/jigsawstack-prompt-engine/jigsawstack-prompt-engine.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"json-mode-social-determinants-of-health\",\n \"title\": \"json-mode-social-determinants-of-health\",\n \"description\": \"Groq API's JSON mode feature extracts social determinants of health from clinical notes and structures them into a neat table for analytics.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/json-mode-social-determinants-of-health\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/json-mode-social-determinants-of-health/SDOH-Json-mode.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/json-mode-social-determinants-of-health\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/json-mode-social-determinants-of-health/SDOH-Json-mode.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"follow-up-question-works-since-agent-maintains-conversation-history\",\n \"title\": \"follow-up question works since agent maintains conversation history\",\n \"description\": \"You can use Langroid with Groq by setting the model name to groq/ and placing your GROQ_API_KEY in a .env file.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/langroid-llm-agents\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/langroid-llm-agents/README.md\",\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/langroid-llm-agents/search-assistant.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/langroid-llm-agents\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/langroid-llm-agents/search-assistant.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"use-litellm-proxy-to-call-groq-api\",\n \"title\": \"Use LiteLLM Proxy to Call Groq API\",\n \"description\": \"LiteLLM Proxy is a tool that allows calling multiple large language models from various platforms, including Groq, in a standardized format.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/litellm-proxy-groq\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/litellm-proxy-groq/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/litellm-proxy-groq\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"llama-guard-safe-chatbot\",\n \"title\": \"llama-guard-safe-chatbot\",\n \"description\": \"Llama Guard 4 is an advanced content moderation tool designed to assess user messages for harmful content across 14 categories.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/llama-guard-safe-chatbot\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/llama-guard-safe-chatbot/Llama-Guard-4-Ensuring-Safe-Chatbot.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/llama-guard-safe-chatbot\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/llama-guard-safe-chatbot/Llama-Guard-4-Ensuring-Safe-Chatbot.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"llama3-stock-market-function-calling\",\n \"title\": \"llama3-stock-market-function-calling\",\n \"description\": \"Llama 3 is used with LangChain to leverage the yfinance API for real-time stock market analysis through function calling.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/llama3-stock-market-function-calling\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/llama3-stock-market-function-calling/llama3-stock-market-function-calling.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/llama3-stock-market-function-calling\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/llama3-stock-market-function-calling/llama3-stock-market-function-calling.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"minions-with-groq-api-cookbook-for-multi-hop-reasoning\",\n \"title\": \"Minions with Groq API Cookbook for Multi-Hop Reasoning\",\n \"description\": \"Minions is a framework that enables efficient collaboration between local and cloud models for multi-hop question-answering tasks.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/minions-groq\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/minions-groq/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/minions-groq\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"mixture-of-agents\",\n \"title\": \"mixture-of-agents\",\n \"description\": \"Mixture of Agents (MoA) is an advanced approach in Generative AI that combines multiple AI models to produce more robust and comprehensive responses.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/mixture-of-agents\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/mixture-of-agents/mixture_of_agents.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/mixture-of-agents\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/mixture-of-agents/mixture_of_agents.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"multimodal-image-processing\",\n \"title\": \"multimodal-image-processing\",\n \"description\": \"Groq API provides a powerful vision model called LLaVA that combines language and image analysis capabilities for generating text descriptions of images and creating short stories.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/multimodal-image-processing\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/multimodal-image-processing/dog-picture-storytelling-with-llava.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/multimodal-image-processing\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/multimodal-image-processing/dog-picture-storytelling-with-llava.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"open-source-platform-for-ai-engineering\",\n \"title\": \"Open Source Platform for AI Engineering\",\n \"description\": \"OpenLIT is an open-source tool for monitoring AI performance with OpenTelemetry-native tracing and metrics.\",\n \"image\": \"https://img.shields.io/github/license/openlit/openlit?label=License&logo=github&color=f80&logoColor=white\",\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/opentelemetry-observability-groq\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/opentelemetry-observability-groq/README.md\",\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/opentelemetry-observability-groq/groq_opentelemetry_tracing_evals.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/opentelemetry-observability-groq\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/opentelemetry-observability-groq/groq_opentelemetry_tracing_evals.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"parallel-tool-use\",\n \"title\": \"parallel-tool-use\",\n \"description\": \"Parallel tool use enables Large Language Models to interact with external resources by invoking multiple tools simultaneously for more efficient and effective responses.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/parallel-tool-use\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/parallel-tool-use/parallel-tool-use.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/parallel-tool-use\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/parallel-tool-use/parallel-tool-use.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"portkey-openai-to-groq\",\n \"title\": \"portkey-openai-to-groq\",\n \"description\": \"Portkey is a control panel for AI apps that provides a unified API to connect to 150+ models, view metrics and logs, and implement features like semantic cache and automatic retries.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/portkey-openai-to-groq\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/portkey-openai-to-groq/Switch_from_OpenAI_to_Groq.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/portkey-openai-to-groq\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/portkey-openai-to-groq/Switch_from_OpenAI_to_Groq.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"presidential-speeches-rag\",\n \"title\": \"presidential-speeches-rag\",\n \"description\": \"Retrieval-Augmented Generation system is used to gather information from external data sources and provide it to Large Language Models to overcome knowledge cutoffs and hallucination issues.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/presidential-speeches-rag\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/presidential-speeches-rag/rag-langchain-presidential-speeches.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/presidential-speeches-rag\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/presidential-speeches-rag/rag-langchain-presidential-speeches.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"structured-output-instructor\",\n \"title\": \"structured-output-instructor\",\n \"description\": \"Groq and Instructor libraries simplify generating structured outputs from Large Language Models.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/structured-output-instructor\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/structured-output-instructor/structured_output_instructor.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/structured-output-instructor\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/structured-output-instructor/structured_output_instructor.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"toolhouse-for-tool-use-with-groq-api\",\n \"title\": \"toolhouse-for-tool-use-with-groq-api\",\n \"description\": \"Groq API and Toolhouse integration enables LLMs to use tools like Code Interpreter and Web Search without manual coding or prompting.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/toolhouse-for-tool-use-with-groq-api\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/toolhouse-for-tool-use-with-groq-api/Groq <> Toolhouse.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/toolhouse-for-tool-use-with-groq-api\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/toolhouse-for-tool-use-with-groq-api/Groq <> Toolhouse.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"whisper-podcast-rag\",\n \"title\": \"whisper-podcast-rag\",\n \"description\": \"Whisper model converts spoken language into written text, enabling applications like transcription services, voice assistants, and podcast chat apps.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/whisper-podcast-rag\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/whisper-podcast-rag/whisper-podcast-rag.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/whisper-podcast-rag\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/whisper-podcast-rag/whisper-podcast-rag.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"ai-code-execution-with-groq\",\n \"title\": \"AI Code Execution with Groq\",\n \"description\": \"AI data analyst uses Groq-powered LLMs to plot a linear regression chart from uploaded CSV data in a secure cloud sandbox.\",\n \"image\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/e2b-code-interpreting/code-interpreter-js/image_1.png\",\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/e2b-code-interpreting/code-interpreter-js\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/e2b-code-interpreting/code-interpreter-js/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/e2b-code-interpreting/code-interpreter-js\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"ai-code-execution-with-models-powered-by-groq\",\n \"title\": \"AI Code Execution with models powered by Groq\",\n \"description\": \"AI data analyst uses LLMs powered by Groq to plot a linear regression chart from an uploaded CSV file in a secure cloud sandbox.\",\n \"image\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/e2b-code-interpreting/code-interpreter-python/image.png\",\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/e2b-code-interpreting/code-interpreter-python\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/tutorials/e2b-code-interpreting/code-interpreter-python/README.md\",\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/e2b-code-interpreting/code-interpreter-python/groq_with_e2b_code_interpreter.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials/e2b-code-interpreting/code-interpreter-python\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/e2b-code-interpreting/code-interpreter-python/groq_with_e2b_code_interpreter.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"image-moderation\",\n \"title\": \"image-moderation\",\n \"description\": \"Groq and Gradio are used to build an image moderation application for fast image analysis and content safety checking.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": null,\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/image_moderation.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/main/tutorials/image_moderation.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"website-guru\",\n \"title\": \"Website Guru\",\n \"description\": \"Streamlit application called Website Guru uses Large Language Models to generate responses to user questions about a given website's content.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/chat_with_website\",\n \"demo\": null,\n \"language\": \"python\",\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/chat_with_website/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/chat_with_website\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n }\n ],\n \"count\": 36\n },\n {\n \"adapter\": \"github-replit-examples\",\n \"label\": \"Replit Examples (GitHub)\",\n \"title\": \"Replit Examples\",\n \"description\": \"Forkable Replit projects demonstrating Groq API integrations you can run in minutes.\",\n \"source\": \"github-cookbooks\",\n \"sourceUrl\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples\",\n \"items\": [\n {\n \"slug\": \"a-guide-on-implementing-chat-history-in-your-groq-based-llm-applications\",\n \"title\": \"A guide on implementing chat history in your Groq based LLM applications\",\n \"description\": \"Groq-based LLM applications can implement chat history using simple JSON files to store previous queries and answers.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/chat-history\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/chat-history/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/chat-history\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"groq-langchain-conversational-chatbot\",\n \"title\": \"Groq LangChain Conversational Chatbot\",\n \"description\": \"conversational chatbot application powered by LangChain and the Groq API allows users to interact with a chatbot that generates human-like responses.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/conversational-chatbot-langchain\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/conversational-chatbot-langchain/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/conversational-chatbot-langchain\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"crewai-machine-learning-assistant\",\n \"title\": \"CrewAI Machine Learning Assistant\",\n \"description\": \"CrewAI Machine Learning Assistant is a command line application that utilizes AI agents to guide users through the initial steps of machine learning projects.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/crewai-agents\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/crewai-agents/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/crewai-agents\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"groq-quickstart-conversational-chatbot\",\n \"title\": \"Groq Quickstart Conversational Chatbot\",\n \"description\": \"conversational chatbot application powered by Groq allows users to interact with a simple interface and receive short, concise responses.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/groq-quickstart-conversational-chatbot\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/groq-quickstart-conversational-chatbot/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/groq-quickstart-conversational-chatbot\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"groqing-the-stock-market-with-llama-3-function-calling\",\n \"title\": \"'Groqing the Stock Market' with Llama 3 Function Calling\",\n \"description\": \"application uses the yfinance API and Llama 3 model to provide insights into stocks and their prices based on user prompts.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/groqing-the-stock-market-function-calling-llama3\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/groqing-the-stock-market-function-calling-llama3/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/groqing-the-stock-market-function-calling-llama3\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"llamachat-conversational-chatbot-with-llamaindex-and-llama3\",\n \"title\": \"LlamaChat: Conversational Chatbot with LlamaIndex and Llama3\",\n \"description\": \"conversational chatbot application powered by LlamaIndex and Meta's Llama3 model uses the Groq API to generate responses in different interaction modes.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/llamachat-conversational-chatbot-with-llamaIndex\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/llamachat-conversational-chatbot-with-llamaIndex/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/llamachat-conversational-chatbot-with-llamaIndex\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"presidential-speeches-rag-with-pinecone\",\n \"title\": \"Presidential Speeches RAG with Pinecone\",\n \"description\": \"command line application uses Retrieval-Augmented Generation to answer user questions about US presidential speeches by retrieving relevant information from a Pinecone vector database.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/presidential-speeches-rag-with-pinecone\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/presidential-speeches-rag-with-pinecone/README.md\",\n \"ipynbLink\": \"https://github.com/groq/groq-api-cookbook/blob/dan/replit-conversion/presidential-speeches-rag/presidential-speeches-rag.ipynb\",\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/presidential-speeches-rag-with-pinecone\"\n },\n {\n \"icon\": \"mdi:notebook\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/blob/dan/replit-conversion/presidential-speeches-rag/presidential-speeches-rag.ipynb\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"duckdb-text-to-sql-with-json-mode\",\n \"title\": \"DuckDB Text-to-SQL with JSON Mode\",\n \"description\": \"command line application generates SQL queries based on user questions and executes them on a DuckDB database using the Groq API's JSON mode.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/text-to-sql-json-mode\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/text-to-sql-json-mode/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/text-to-sql-json-mode\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"executing-verified-queries-with-function-calling\",\n \"title\": \"Executing Verified Queries with Function Calling\",\n \"description\": \"command line application uses function calling to execute verified queries against DuckDB data and return results based on user input.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/verified-sql-function-calling\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/verified-sql-function-calling/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/verified-sql-function-calling\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"jigsawstack-prompt-engine\",\n \"title\": \"JigsawStack Prompt Engine\",\n \"description\": \"JigsawStack is a powerful AI SDK that automates tasks such as web scraping and translation using custom fine-tuned models.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/jigsawstack-prompt-engine/node-example\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/jigsawstack-prompt-engine/node-example/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/jigsawstack-prompt-engine/node-example\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n },\n {\n \"slug\": \"jigsawstack-prompt-engine\",\n \"title\": \"JigsawStack Prompt Engine\",\n \"description\": \"JigsawStack is a powerful AI SDK that automates tasks such as web scraping and translation using custom fine-tuned models.\",\n \"image\": null,\n \"imageFit\": \"cover\",\n \"username\": null,\n \"avatarUrl\": null,\n \"github\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/jigsawstack-prompt-engine/python-example\",\n \"demo\": null,\n \"language\": null,\n \"difficulty\": null,\n \"tags\": [],\n \"sections\": [],\n \"date\": null,\n \"readmeSource\": \"https://raw.githubusercontent.com/groq/groq-api-cookbook/main/replit-examples/jigsawstack-prompt-engine/python-example/README.md\",\n \"ipynbLink\": null,\n \"ctas\": [\n {\n \"icon\": \"mdi:github\",\n \"href\": \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples/jigsawstack-prompt-engine/python-example\"\n }\n ],\n \"authors\": [],\n \"featured\": false,\n \"markdown\": null\n }\n ],\n \"count\": 11\n }\n ]\n}",[],[254],{"_103":262,"_95":263,"_152":264,"_154":-5,"_155":137,"_156":136,"_158":159,"_105":265,"_100":228,"_161":230,"_163":266,"_164":22,"_165":-5,"_166":267,"_98":268},"2bb3e7a0-7fc2-11f0-8534-0224a6c84d84","snapshot.js","7880c2d8-7fb8-11f0-841f-0224a6c84d84",["D",1755913238175],"import \"jsr:@std/dotenv/load\";\nimport { fetchGroqExamples, fetchGithubCookbooksFromParentDir, fetchGithubCookbookFromDir, getGroqCookbookRootItem } from \"./extractors.js\";\nimport { summarizeSnapshotDescriptions } from \"./summarizer.js\";\n\n// Adapter metadata (kept in sync with runtime adapters in main.js)\nconst ADAPTER_META = {\n \"groq-console\": {\n label: \"Groq Console Examples\",\n title: \"Groq Examples\",\n description: \"Jumpstart your AI-powered applications with Groq's lightning-fast inference templates and community-driven solutions.\",\n source: \"groq-console\",\n sourceUrl: \"https://console.groq.com/docs/examples\",\n },\n \"github-cookbooks\": {\n label: \"Groq Cookbook Examples (GitHub)\",\n title: \"Groq Cookbook Tutorials\",\n description: \"Explore tutorials, notebooks, and sample apps from the Groq API Cookbook.\",\n source: \"github-cookbooks\",\n sourceUrl: \"https://github.com/groq/groq-api-cookbook\",\n },\n // \"github-website-guru\": {\n // label: \"Website Guru (GitHub)\",\n // title: \"Website Guru\",\n // description: \"Ask questions about any website with a Streamlit + Groq reference app.\",\n // source: \"github-cookbooks\",\n // sourceUrl: \"https://github.com/groq/groq-api-cookbook/tree/main/chat_with_website\",\n // },\n // \"groq-cookbook-root\": {\n // label: \"Groq API Cookbook\",\n // title: \"Groq API Cookbook\",\n // description: \"This is a collection of example code and guides for Groq API for you to explore.\",\n // source: \"custom\",\n // sourceUrl: \"https://github.com/groq/groq-api-cookbook/tree/main\",\n // },\n \"github-replit-examples\": {\n label: \"Replit Examples (GitHub)\",\n title: \"Replit Examples\",\n description: \"Forkable Replit projects demonstrating Groq API integrations you can run in minutes.\",\n source: \"github-cookbooks\",\n sourceUrl: \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples\",\n },\n};\n\nfunction withMeta(adapterKey, extra) {\n const meta = ADAPTER_META[adapterKey] || {};\n return { adapter: adapterKey, label: meta.label, title: meta.title, description: meta.description, source: meta.source, sourceUrl: meta.sourceUrl, ...extra };\n}\n\n// Produces a consolidated projects.json snapshot so runtime endpoints can read from disk\nconst outputs = [];\n\n// 1) Groq console examples\ntry {\n const { items } = await fetchGroqExamples();\n outputs.push(withMeta(\"groq-console\", { items }));\n} catch (e) {\n console.error(\"Failed groq-console:\", e);\n outputs.push(withMeta(\"groq-console\", { items: [] }));\n}\n\n// 2) Tutorials parent\ntry {\n const { items } = await fetchGithubCookbooksFromParentDir({ parent: \"https://github.com/groq/groq-api-cookbook/tree/main/tutorials\", limit: 400, nested: 1 });\n outputs.push(withMeta(\"github-cookbooks\", { items }));\n} catch (e) {\n console.error(\"Failed github-cookbooks tutorials:\", e);\n outputs.push(withMeta(\"github-cookbooks\", { items: [] }));\n}\n\n// 3) Replit examples\ntry {\n const { items } = await fetchGithubCookbooksFromParentDir({ parent: \"https://github.com/groq/groq-api-cookbook/tree/main/replit-examples\", limit: 400, nested: 1 });\n outputs.push(withMeta(\"github-replit-examples\", { items }));\n} catch (e) {\n console.error(\"Failed github-replit-examples:\", e);\n outputs.push(withMeta(\"github-replit-examples\", { items: [] }));\n}\n\n// 4) Website Guru dedicated\ntry {\n const { items } = await fetchGithubCookbookFromDir({ dir: \"https://github.com/groq/groq-api-cookbook/tree/main/chat_with_website\" });\n outputs.push(withMeta(\"github-website-guru\", { items }));\n} catch (e) {\n console.error(\"Failed github-website-guru:\", e);\n outputs.push(withMeta(\"github-website-guru\", { items: [] }));\n}\n\n// 5) Cookbook root curated\ntry {\n outputs.push(withMeta(\"groq-cookbook-root\", { items: [getGroqCookbookRootItem()] }));\n} catch (e) {\n console.error(\"Failed groq-cookbook-root:\", e);\n outputs.push(withMeta(\"groq-cookbook-root\", { items: [] }));\n}\n\nconst apiKey = Deno.env.get(\"GROQ_API_KEY\") || Deno.env.get(\"GROQ_KEY\") || Deno.env.get(\"GROQ_TOKEN\");\n// Inject curated items into the github-cookbooks list\ntry {\n const tutorialsGroup = outputs.find((g) => g?.adapter === \"github-cookbooks\");\n if (tutorialsGroup && Array.isArray(tutorialsGroup.items)) {\n // 1) Prepend the base cookbook root card\n try {\n const rootItem = getGroqCookbookRootItem();\n if (rootItem) {\n const ROOT_IMAGE = \"https://canada1.discourse-cdn.com/flex003/uploads/groq1/original/1X/900fb9a3f1a492df1ddfa9ff695bbc6918831754.png\";\n const curatedRoot = { ...rootItem, image: ROOT_IMAGE };\n // Avoid duplicate by slug or github\n const exists = tutorialsGroup.items.some((it) => (it?.slug && it.slug === curatedRoot.slug) || (it?.github && it.github === curatedRoot.github));\n if (!exists) tutorialsGroup.items.unshift(curatedRoot);\n }\n } catch (_) {}\n\n // 2) Append Website Guru card (if available)\n try {\n const guruGroup = outputs.find((g) => g?.adapter === \"github-website-guru\");\n const guruItem = Array.isArray(guruGroup?.items) && guruGroup.items.length ? guruGroup.items[0] : null;\n if (guruItem) {\n const exists = tutorialsGroup.items.some((it) => (it?.slug && it.slug === guruItem.slug) || (it?.github && it.github === guruItem.github));\n if (!exists) tutorialsGroup.items.push(guruItem);\n }\n } catch (_) {}\n\n // 3) Force fallback image for known problematic image URLs\n try {\n const batchIdx = tutorialsGroup.items.findIndex((it) => it?.slug === \"analyze-and-tag-images-with-llama-4-on-groq-batch\");\n if (batchIdx !== -1) {\n const FALLBACK_IMG = \"https://canada1.discourse-cdn.com/flex003/uploads/groq1/original/1X/900fb9a3f1a492df1ddfa9ff695bbc6918831754.png\";\n tutorialsGroup.items[batchIdx] = { ...tutorialsGroup.items[batchIdx], image: FALLBACK_IMG };\n }\n } catch (_) {}\n\n tutorialsGroup.count = tutorialsGroup.items.length;\n }\n} catch (_) {}\n\n// Drop standalone groups for root and website-guru from the final snapshot,\n// while keeping their curated items injected above.\nconst BLOCK_ADAPTERS = new Set([\"groq-cookbook-root\", \"github-website-guru\"]);\nconst outputsFiltered = outputs.filter((g) => !BLOCK_ADAPTERS.has(g?.adapter));\n\nlet finalSnapshot = { adapters: outputsFiltered };\nif (apiKey) {\n try {\n finalSnapshot = await summarizeSnapshotDescriptions(finalSnapshot, { apiKey, force: true });\n console.log(\"Descriptions summarized via Groq\");\n } catch (e) {\n console.warn(\"Summary step failed:\", e?.message || e);\n }\n} else {\n console.warn(\"No GROQ_API_KEY set; skipping summarization.\");\n}\n\nawait Deno.writeTextFile(new URL(\"./projects.json\", import.meta.url), JSON.stringify(finalSnapshot, null, 2));\nconsole.log(\"Wrote projects.json with\", finalSnapshot.adapters.reduce((n, s) => n + (s.items?.length || 0), 0), \"items\");\n\n\n",[],[263],{"_103":270,"_95":271,"_152":272,"_154":-5,"_155":137,"_156":273,"_158":159,"_105":274,"_100":32,"_161":230,"_163":275,"_164":22,"_165":-5,"_166":276,"_98":277},"78902e26-7fb8-11f0-bf2c-0224a6c84d84","summarizer.js","78902ef8-7fb8-11f0-bf2c-0224a6c84d84",12,["D",1755909072185],"import \"jsr:@std/dotenv/load\";\n\nconst GROQ_CHAT_URL = \"https://api.groq.com/openai/v1/chat/completions\";\n\nfunction stripMarkdownAndHtml(input) {\n if (!input) return \"\";\n let text = String(input);\n // Remove HTML tags\n text = text.replace(/<[^>]*>/g, \" \");\n // Replace markdown images ![alt](url) with alt\n text = text.replace(/!\\[([^\\]]*)\\]\$[^)]*\$/g, \"$1\");\n // Replace markdown links [text](url) with text\n text = text.replace(/\\[([^\\]]+)\\]\$[^)]*\$/g, \"$1\");\n // Remove code fences and inline backticks\n text = text.replace(/```[\\s\\S]*?```/g, \" \");\n text = text.replace(/`+/g, \" \");\n // Collapse whitespace\n text = text.replace(/\\s+/g, \" \").trim();\n return text;\n}\n\nfunction toRawGithubUrl(possibleBlobUrl) {\n if (!possibleBlobUrl) return null;\n try {\n // Convert GitHub blob URLs to raw URLs; keep raw URLs intact\n if (possibleBlobUrl.includes('github.com')) {\n return possibleBlobUrl\n .replace('https://github.com/', 'https://raw.githubusercontent.com/')\n .replace('/blob/', '/');\n }\n return possibleBlobUrl;\n } catch (_) {\n return possibleBlobUrl;\n }\n}\n\nasync function fetchNotebookMarkdown(ipynbUrl) {\n try {\n const rawUrl = toRawGithubUrl(ipynbUrl);\n if (!rawUrl) return '';\n const res = await fetch(rawUrl);\n if (!res.ok) return '';\n const json = await res.json();\n const cells = Array.isArray(json?.cells) ? json.cells : [];\n const md = cells\n .filter((c) => (c?.cell_type || c?.cellType) === 'markdown' && Array.isArray(c?.source))\n .map((c) => c.source.join(''))\n .join('\\n\\n');\n // Fallback: if no markdown cells, concatenate first few code cells as text\n if (md && md.trim().length > 0) return md;\n const code = cells\n .filter((c) => (c?.cell_type || c?.cellType) === 'code' && Array.isArray(c?.source))\n .slice(0, 3)\n .map((c) => c.source.join(''))\n .join('\\n\\n');\n return code || '';\n } catch (_) {\n return '';\n }\n}\n\nfunction refineSummary(input) {\n let t = (input || \"\").trim();\n t = t.replace(/^(?:This\\s+(?:repository|project|tutorial|notebook|application|app|example)\\s+(?:appears\\s+to\\s+be|is|provides|contains|includes|builds|demonstrates|implements|offers)\\s+)/i, \"\");\n t = t.replace(/^(?:This\\s+(?:repository|project|tutorial|notebook|application|app|example)\\s*:\\s*)/i, \"\");\n t = t.replace(/^(?:This\\s+(?:repository|project|tutorial|notebook|application|app|example)\\s+)/i, \"\");\n t = t.replace(/^(?:It\\s+(?:is|provides|offers)\\s+)/i, \"\");\n t = t.replace(/^(?:An?\\s+|The\\s+)/i, \"\");\n return t.trim();\n}\n\nasync function callGroqOneSentence(readmeText, apiKey) {\n const prompt = \"Summarize into ONE plain-English sentence (<=25 words). Output a direct noun phrase without leading articles or meta phrases like 'This project/repository'. No markdown, no code, no title. Neutral tone.\";\n const content = stripMarkdownAndHtml(readmeText).slice(0, 12000);\n const body = {\n // model: \"openai/gpt-oss-20b\",\n model: \"llama-3.1-8b-instant\",\n messages: [\n { role: \"system\", content: prompt },\n { role: \"user\", content }\n ],\n temperature: 0.2,\n };\n const res = await fetch(GROQ_CHAT_URL, {\n method: \"POST\",\n headers: {\n Authorization: `Bearer ${apiKey}`,\n \"Content-Type\": \"application/json\",\n },\n body: JSON.stringify(body),\n });\n if (!res.ok) throw new Error(`Groq API error ${res.status}`);\n const json = await res.json();\n let text = json?.choices?.[0]?.message?.content || \"\";\n text = text.replace(/\\s+/g, \" \").trim();\n // Post-sanitize: strip any residual HTML/markdown and URLs\n text = stripMarkdownAndHtml(text).replace(/https?:[^\\s]+/gi, \"\").replace(/\\s+/g, \" \").trim();\n // Remove explainer prefaces\n text = refineSummary(text);\n // Limit length roughly to ~25 words / 200 chars\n if (text.length > 200) text = text.slice(0, 200).replace(/[,;:\\s]+[^,;:\\s]*$/, \"\").trim();\n return text;\n}\n\nexport async function summarizeSnapshotDescriptions(snapshot, { apiKey, force = false } = {}) {\n if (!snapshot || !Array.isArray(snapshot.adapters)) return snapshot;\n if (!apiKey) throw new Error(\"Missing GROQ_API_KEY\");\n\n const updated = { adapters: [] };\n for (const group of snapshot.adapters) {\n const items = Array.isArray(group.items) ? group.items : [];\n const newItems = [];\n for (const item of items) {\n let description = item?.description || null;\n const readmeUrl = item?.readmeSource || null;\n const ipynbUrl = item?.ipynbLink || null;\n\n if (force || !description) {\n let sourceText = \"\";\n // Try README first\n if (readmeUrl) {\n try {\n const res = await fetch(readmeUrl);\n const text = res.ok ? await res.text() : \"\";\n if (text && text.trim().length > 0) sourceText = text;\n } catch (_) {}\n }\n // Fallback to ipynb content if still missing\n if (!sourceText && ipynbUrl) {\n try {\n const nb = await fetchNotebookMarkdown(ipynbUrl);\n if (nb && nb.trim().length > 0) sourceText = nb;\n } catch (_) {}\n }\n // Last resort: synthesize from known fields\n if (!sourceText) {\n const parts = [];\n if (item.title) parts.push(String(item.title));\n if (item.description) parts.push(stripMarkdownAndHtml(item.description));\n const repoPath = (item.github || \"\").toString().split(\"/\").slice(-2).join(\"/\");\n if (repoPath) parts.push(repoPath);\n if (Array.isArray(item.tags) && item.tags.length) parts.push(item.tags.join(\", \"));\n sourceText = parts.join(\". \");\n }\n try {\n const repoSlug = (item.github || item.slug || item.title || \"item\").toString().split(\"/\").filter(Boolean).slice(-1)[0];\n description = await callGroqOneSentence(sourceText, apiKey);\n try { console.log(`[${repoSlug}]: \"${description}\"`); } catch (_) {}\n } catch (_) {}\n }\n newItems.push({ ...item, description });\n }\n updated.adapters.push({ ...group, items: newItems, count: newItems.length });\n }\n return updated;\n}\n\n\n",[],[271],"files",[149,168,179,188,197,206,215,224,234,244,252,261,269],"counts",{"_282":32,"_283":157,"_284":32,"_285":32},"pulls","branches","forks","envVars","contents",[],{"_103":245,"_95":99,"_152":246,"_154":-5,"_155":137,"_156":247,"_158":159,"_105":289,"_100":32,"_161":174,"_163":249,"_164":22,"_165":-5,"_98":290},["D",1755912403691],[99],"upstreamProject","upstreamBranch","emptyEnvVars","isNew","flags",[],"routes/_app.x.$handle.$name.branch.$branch.history_.$",{"_93":94,"_95":96,"_97":43,"_98":99,"_101":299,"_174":304,"_307":308,"_311":312,"_315":-7,"_316":32,"_317":22},{"_103":104,"_95":96,"_105":300,"_107":-5,"_108":22,"_109":110,"_111":72,"_112":-5,"_14":113,"_114":-5,"_115":22,"_116":-5,"_117":32,"_16":118,"_119":120,"_121":120,"_122":123,"_124":123,"_125":123,"_126":120,"_127":120,"_23":301,"_131":302,"_134":303,"_146":22},["D",1755909071355],{"_93":94,"_129":130},{"_93":94,"_133":130},{"_100":136,"_95":43,"_103":137,"_138":104,"_139":-5,"_140":-5,"_141":-5,"_142":-5,"_143":-5,"_144":96,"_145":94},{"_103":245,"_95":99,"_152":246,"_154":-5,"_155":137,"_156":247,"_158":159,"_105":305,"_100":32,"_161":174,"_163":249,"_164":22,"_165":-5,"_98":306},["D",1755912403691],[99],"history",[309],{"_103":245,"_155":137,"_152":246,"_95":99,"_163":249,"_161":174,"_100":32,"_154":-5,"_105":310,"_156":247,"_165":-5},["D",1755912403691],"versions",[313],{"_174":309,"_314":-5},"previous","versionNumber","page","hasNext","actionData","errors"]

Hi

Boink

\n \n What is Boink?\n \n \n \n \n \n

\n \n How do I use it?\n \n \n \n \n \n

\n \n

\n \n

yawnxyz

groq-api-projects

History for notes.md