Fud AI: Open-Source Calorie Tracker with Photo Logging and BYOK Support

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Fud AI is a newly launched open-source nutrition tracking app available on both iOS and Android, released under the MIT license. The app allows users to log meals by snapping a photo, with AI estimating calories and macronutrients automatically. Additional input methods include barcode scanning, voice entry, manual input, and saved meals. Users can bring their own Gemini or OpenRouter API key, or opt into a paid Fud AI Plus tier that includes an AI coach, weight and body-fat tracking, and BMR calculation. The project's source code has been made publicly available on GitHub as part of a build-in-public initiative.

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Developer Moves Code Repos to Codeberg After GitHub Silently Flagged Account as Spam

A freelance developer discovered on July 2 that GitHub had silently flagged their account as spam since June 18, making all public repositories return 404 errors to anyone not logged in as the account owner. The developer only learned of the outage when an AI agent followed a source-code link without an active session and hit a dead end — nearly two weeks after the flag was applied. GitHub support confirmed the flag was a mistake and removed it on July 3, but by then the developer had already migrated all repositories to Codeberg, a non-profit-run platform, with full commit history intact. The incident coincided with a potential client inquiry, and the developer suspects the broken links may have contributed to the lead going silent, though this cannot be confirmed. In response, the developer has added logged-out visibility checks for all external links to their monthly site audit, noting that standard uptime scanners do not catch this class of silent failure.

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ProgrammingHacker News ·

Apocketlypse

Article URL: https://0dd.company/galleries/triumph/1.html Comments URL: https://news.ycombinator.com/item?id=48792352 Points: 3 # Comments: 0

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ProgrammingDEV Community ·

Anthropic launches OIDC gateway to replace per-developer Claude Code credentials

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ProgrammingDEV Community ·

How the MOD-97 Algorithm Validates IBANs and Catches Typos Before Transfers

Every IBAN contains two check digits immediately after the country code, computed using the MOD-97 algorithm (ISO 7064), which allows banks and software to detect transcription errors before a payment is processed. To validate an IBAN, the number is normalized, rotated so the country code and check digits move to the end, letters are converted to two-digit numbers, and the resulting large integer is divided by 97. A remainder of exactly 1 confirms the IBAN is internally consistent; any other result indicates an error in the number. Importantly, passing this check only verifies the number's internal integrity and correct length — it does not confirm that the bank account actually exists, which requires a separate directory lookup. Developers can implement the validation in Python using arbitrary-precision integers, with an added per-country length check recommended for production use.

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