Air quality API examples & templates
Use these vals as a playground to view and fork Air quality API examples and templates on Val Town. Run any example below or find templates that can be used as a pre-built solution.
simplescraper
aiEmailAssistant
Email
Email AI Assistant Chat with your favorite AI via email (with PDF attachment support) What It Does This script allows you to: Send emails to OpenAI. The text will be treated as the prompt Parse PDF attachments and include their contents in the AI's analysis. Get response directly to your inbox. Setup guide Copy this Val and save it as an Email Val (choose Val type in top-right corner of editor) Add your OpenAI API key to line 8 (or use an environment variable: https://docs.val.town/reference/environment-variables/) Copy the email address of the Val (click 3 dots in top-right > Copy > Copy email address) Write your email, include any attachments, and send it to the Val email address. The AI will respond after a few seconds.
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martinbowling
emailValHandlerNo
Email
Email AI Assistant Chat with your favorite AI via email (with enhanced attachment and content support) What It Does This advanced email AI assistant allows you to: Send emails to an AI for comprehensive analysis and responses Automatically transform your queries into structured research objectives Parse and analyze various types of content: PDF attachments Image attachments (using GPT-4 Vision) Website content from links in your email Get detailed, context-aware responses directly to your inbox Setup Guide Copy this Val and save it as an Email Val (choose Val type in the top-right corner of the editor) Set up the required environment variables: OPENAI_API_KEY: Your OpenAI API key MD_API_KEY: Your API key for the markdown extraction service You can set these using Val Town's environment variables: https://docs.val.town/reference/environment-variables/ Copy the email address of the Val (click 3 dots in top-right > Copy > Copy email address) Compose your email: Write your query or request in the email body Attach any relevant PDFs or images Include links to websites you want analyzed Send it to the Val email address Wait for the AI's response, which will arrive in your inbox shortly How to Use Effectively Be clear and specific in your queries Provide context when necessary Utilize attachments and links to give the AI more information to work with The AI will transform your query into a structured research objective, so even simple questions may yield comprehensive answers Supported File Types and Limitations PDFs: Text content will be extracted and analyzed Images: Will be analyzed using GPT-4 Vision API Websites: Content will be extracted and converted to markdown for analysis Other file types are not currently supported and will be ignored Note: There may be size limitations for attachments and processing times may vary based on the complexity of the content. The AI uses advanced prompt transformation to enhance your queries, providing more detailed and structured responses. This process helps in generating comprehensive and relevant answers to your questions.
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JamesAndrew
codecommenter
HTTP
Code Commenter Code Commenter is a web application that automatically adds concise and useful comments to your code using OpenAI's language model. It supports JavaScript, TypeScript, and C# languages. Features Two-panel interface: Input code on the left, view commented code on the right Language selection: Choose between JavaScript, TypeScript, and C# Syntax highlighting: Commented code is displayed with proper syntax highlighting Loading indicator: A spinner animation shows when the AI is processing your code Responsive design: The app adjusts to fit various screen sizes How It Works The user pastes their code into the left panel The user selects the appropriate language from the dropdown menu When the "Add Comments" button is clicked, the code is sent to the server The server uses OpenAI's API to generate comments for the code The commented code is returned and displayed in the right panel with syntax highlighting Technology Stack Frontend: React: For building the user interface Prism.js: For syntax highlighting Backend: Deno: Runtime environment Val Town: Hosting platform OpenAI API: For generating code comments Usage Open the application in your web browser Paste your code into the left panel Select the appropriate language from the dropdown menu Click the "Add Comments" button Wait for the AI to process your code (a spinner will indicate that it's working) View the commented code in the right panel Limitations The maximum length of code that can be processed is limited by the OpenAI API's token limit The quality of comments may vary depending on the complexity of the code and the AI model's capabilities Internet connection is required to use the application Privacy Considerations Please note that the code you submit is sent to OpenAI's servers for processing. Do not submit sensitive or proprietary code that you don't want to be processed by a third-party service. Future Improvements Add support for more programming languages Implement user authentication for personalized experiences Add the ability to save and share commented code snippets Improve error handling and user feedback Feedback and Contributions This project is hosted on Val Town. If you have any suggestions, bug reports, or want to contribute to the project, please contact the Val Town team or the val's creator.
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