Agenta

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Agenta is an open source platform that streamlines the development monitoring and evaluation of applications powered by large language models by leveraging AI to enable collaborative prompt engineering systematic prompt versioning robust A/B testing and in depth observability Agenta allows users to easily experiment with and compare outputs from over 50 LLMs track performance and costs integrate user feedback and conduct detailed tracing and debugging It supports frameworks like LangChain and LlamaIndex and even allows for testing with image inputs and advanced agent workflows making it ideal for engineers product teams and researchers who want to accelerate LLM app iteration ensure reliability and optimize model performance through seamless collaborative workflows and data driven insights.

Agenta is a platform designed for building, deploying, and monitoring AI agents and LLM applications. It provides tools for developers and teams to streamline the development lifecycle, from initial prototyping to production deployment and ongoing evaluation. The platform supports a wide range of use cases, including agent orchestration, workflow automation, and real-time monitoring of AI-driven applications.

Key features include automated online evaluation of LLM outputs, allowing users to monitor for issues such as hallucinations or off-brand responses as they occur. Evaluations can be configured with custom prompts and sampling rates, and results are accessible through a centralized dashboard. The platform supports multiple evaluation models, including OpenAI and Anthropic, and provides detailed error handling and score calculation for both automated and human evaluations. Users can export evaluation results and integrate problematic cases into test sets for continuous improvement.

Agenta offers advanced observability, with real-time tracking of cost, latency, and call volume for deployed applications. It integrates with Litellm to automatically trace LLM calls and propagate cost and token usage data. The platform also supports flexible configuration of evaluators, including the ability to define expected answer columns and set advanced evaluation parameters. Additional features include improved SDK performance, comprehensive documentation, and support for large output handling in evaluation views.

The platform is suitable for teams looking to build reliable, scalable AI agents and LLM applications with robust monitoring, evaluation, and integration capabilities.

This description was generated by AI (artificial intelligence). AI can make mistakes. Check important info.

Website: agenta.ai

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Agenta

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