New Show Hacker News story: Show HN: Pezzo – Open-Source LLMOps Plaform Tailored for Developers
Show HN: Pezzo – Open-Source LLMOps Plaform Tailored for Developers
5 by arielwein | 0 comments on Hacker News.
Hello HN, Introducing Pezzo – a developer-centric LLMOps platform designed to streamline Generative AI integrations. As Generative AI gains traction, we've observed a gap in tools catering to product teams and developers. Most are oriented toward ML/AI experts. That's why we created Pezzo - fully open-source under Apache 2.0. GitHub: https://ift.tt/YkFTf7x Why Pezzo? - Centralized Prompt Management: Think email templates but for prompts. Design, test, and publish prompts without undergoing an extensive release cycle. - Observability & Insights: Comprehensive dashboards that offer insights into cost metrics, AI provider expenses, success/error rates, and anomaly detection. Be in control of your AI operations. - Efficient Request Caching: Out-of-the-box caching reduces costs and redundancy. Especially valuable during local development with repetitive LLM requests. Future Roadmap: We're working on issue auto-suggestions, continuous prompt improvements, cost optimization, and security threat flagging, among other features. If you'd like to try it out, we've made our Cloud version available: https://pezzo.ai . Note: It runs the identical code as our open-source version! Additionally, we're always looking for contributors, so if you're interested - we'd love to hear from you.
5 by arielwein | 0 comments on Hacker News.
Hello HN, Introducing Pezzo – a developer-centric LLMOps platform designed to streamline Generative AI integrations. As Generative AI gains traction, we've observed a gap in tools catering to product teams and developers. Most are oriented toward ML/AI experts. That's why we created Pezzo - fully open-source under Apache 2.0. GitHub: https://ift.tt/YkFTf7x Why Pezzo? - Centralized Prompt Management: Think email templates but for prompts. Design, test, and publish prompts without undergoing an extensive release cycle. - Observability & Insights: Comprehensive dashboards that offer insights into cost metrics, AI provider expenses, success/error rates, and anomaly detection. Be in control of your AI operations. - Efficient Request Caching: Out-of-the-box caching reduces costs and redundancy. Especially valuable during local development with repetitive LLM requests. Future Roadmap: We're working on issue auto-suggestions, continuous prompt improvements, cost optimization, and security threat flagging, among other features. If you'd like to try it out, we've made our Cloud version available: https://pezzo.ai . Note: It runs the identical code as our open-source version! Additionally, we're always looking for contributors, so if you're interested - we'd love to hear from you.
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