Showing 2 open source projects for "token"

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  • MongoDB Atlas runs apps anywhere Icon
    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

    MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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  • $300 Free Credits to Build on Google Cloud Icon
    $300 Free Credits to Build on Google Cloud

    New to Google Cloud? Get $300 in credits to explore Compute Engine, BigQuery, Cloud Run, Gemini Enterprise Agent Platform, and more.

    Start your next project with $300 in free Google Cloud credit. Spin up VMs, run containers, query petabytes in BigQuery, or build agents with Gemini Enterprise Agent Platform. Once your credits are used, keep building with 20+ always-free tier products including Compute Engine, Cloud Storage, GKE, and Cloud Run functions. No commitment required—just sign up and start building.
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    LLM Gateway

    LLM Gateway

    Route, manage, and analyze your LLM requests across multiple providers

    LLM Gateway is an open-source middleware that consolidates interactions with multiple LLM providers—such as OpenAI, Anthropic, Google Vertex AI—behind a single, unified API compatible with OpenAI's spec. Designed for both self-hosted and cloud use, it enables developers to route requests dynamically, secure and manage API keys, monitor token usage and costs, and analyze performance metrics. With optional UI, telemetry, and Docker deployment, it's ideal for teams aiming to centralize LLM orchestration and gain visibility into AI usage.
    Downloads: 4 This Week
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    LangDB AI Gateway

    LangDB AI Gateway

    Govern, secure, and optimize your AI traffic

    AI Gateway is a high-performance, open-source API gateway optimized for managing and monitoring LLM traffic at scale. Developed by the LangDB team, AI Gateway acts as an intermediary between clients and backend LLMs, providing advanced features like caching, rate limiting, prompt management, and observability. It helps teams secure and optimize their LLM deployments, whether using local models or external APIs like OpenAI or Anthropic. With native support for multi-tenant environments and...
    Downloads: 0 This Week
    Last Update:
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