Showing 2 open source projects for "wrestling"

View related business solutions
  • Powerful App Monitoring Without Surprise Bills Icon
    Powerful App Monitoring Without Surprise Bills

    AppSignal starts at $23/month with all features included. No overages, no hidden fees. 30-day free trial.

    Tired of monitoring tools that punish you for scaling? AppSignal offers transparent, predictable pricing with every feature unlocked on every plan. Track errors, monitor performance, detect anomalies, and manage logs across Ruby, Python, Node.js, and more. Trusted by developers since 2012 with free dev-to-dev support. No credit card required to start your 30-day trial.
    Try AppSignal Free
  • Try Google Cloud Risk-Free With $300 in Credit Icon
    Try Google Cloud Risk-Free With $300 in Credit

    No hidden charges. No surprise bills. Cancel anytime.

    Use your credit across every product. Compute, storage, AI, analytics. When it runs out, 20+ products stay free. You only pay when you choose to.
    Start Free
  • 1
    ChatTTS_colab

    ChatTTS_colab

    One-click deployment (including offline integration package)

    ChatTTS_colab is a wrapper project around the ChatTTS model that focuses on “one-click” deployment, especially in Google Colab. It provides an integrated offline bundle and scripts for Windows and macOS so users can run ChatTTS locally without wrestling with complex environment setup. The repository includes Colab notebooks that launch a Gradio-based web UI and expose streaming TTS, making it possible to listen to generated audio as it is produced. A distinctive feature is the “voice gacha” system, which batch-generates many distinct voice timbres and allows users to save the ones they like into a curated voice library. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    simpleaichat

    simpleaichat

    Python package for easily interfacing with chat apps

    ...The package emphasizes simplicity over heavy frameworks, making it ideal for scripts, notebooks, and small services that need LLMs without architectural lock-in. It supports structured responses and validation patterns so your app can reliably parse model outputs instead of wrestling with brittle free-text parsing. The project encourages clean separation between system prompts, user messages, and tool outputs to keep conversations predictable. With convenience helpers for logging, environment configuration, and retries, it reduces the friction of moving from a quick experiment to a reliable internal tool.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB