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Google Fonts

Sébastien Merour
publié le 27/03/2020 à 17h47 | modifé le 25/04/2020 à 16h54
Catégorie : Front-End | Commentaires (81357)
Google Fonts
Description

Google Fonts est une service d'hébergement de polices de caractères créé en 2010. Ce service, créé par Google, permet d'afficher des polices de caractères spécifiques sur un site web, grâce à un fichier CSS disponible sur le site de Google Fonts. Les développeurs peuvent faire appel à ce fichier CSS en mode "embed", ou bien en téléchargeant le fichier CSS pour l'intégrer ensuite en local sur le site. Il est préférable de l'utiliser en mode "embed" pour ne pas ralentir l'affichage du site.

Fonctionnalités
Police d'écriture
Année de création
2010
Licence
SIL Open Font License 1.1 / Apache License
Langage
CSS
Liens
Aux dernières nouvelles
960 polices de caractères gratuites. Polices populaires : Open Sans, Roboto, Lato, Slabo, Oswald and Lobster.
81357 Commentaire(s)
  1. user
    Guytow
    15/10/2026 à 18h38  commentaire modifé
    The overall feel of the post was professional without being stuffy, and a look at gildedgrovecommercegallery kept that approachable expertise going, finding the right register for technical content is hard but this site has clearly figured out how to sound knowledgeable without slipping into that distant lecturing tone that loses readers in droves every time.
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    Domenicalads
    15/10/2026 à 18h37  commentaire modifé
    Came back to this an hour later to reread a specific section, and a quick visit to waveharborcommercehub also drew a second look, content that pulls you back rather than letting you move on permanently is the kind I want to fill my browser bookmarks with in 2026 and beyond as the open internet evolves.
  3. user
    AI_Engineer_jary
    15/10/2026 à 18h37  commentaire modifé
    An AI feature should have a defined response when one dependency becomes unavailable. Repeating the same request can amplify load and still return no useful result. An AI reliability design should separate retryable failures from conditions that require a user message or manual path. Decide which functions can continue without generation. Search results may remain available while summarization is paused, and a draft action can wait instead of executing with missing data. https://ai-software-development.net A production AI workflow also needs timeouts, bounded retries and circuit breaking outside the model. Recovery tests have two jobs. They must verify that queued work is not duplicated and that users can tell whether an action completed.
  4. user
    AI_Engineer_jary
    15/10/2026 à 18h36  commentaire modifé
    An AI agent should earn its control loop. If a workflow always follows the same sequence, ordinary application code is easier to test and less expensive to supervise. The AI agent development scope should identify which state changes the next action and which actions remain forbidden. Use https://ai-software-development.net as the plain service reference. agentic workflow engineering is the BBCode form for related discussion. Define tool permissions before prompts: read-only access, approval-required actions and blocked operations need separate treatment. The agent also needs a stop condition when tools fail or state becomes ambiguous. Without those boundaries, adding more autonomy expands the failure surface instead of improving the workflow.
  5. user
    AI_Dev_jary
    15/10/2026 à 18h35  commentaire modifé
    Some organizations have plenty of documents but no reliable way to identify their current version. That is a data governance problem before it is an AI problem. AI readiness assessment can frame the investigation, but it cannot replace ownership of the source material. Pause discovery when key data cannot be accessed, the target action has no accountable owner or a failed output has no safe destination. AI discovery readiness describes the broader service context. The plain reference is https://ai-software-development.net for systems that strip markup. Resume only after the workflow has a baseline, an escalation route and a clear definition of an acceptable result. Those conditions make later model comparisons meaningful instead of cosmetic.
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