Description
Agenta addresses the inherent unpredictability of LLMs by providing a structured approach to LLM application development. It serves as a single source of truth for AI teams, moving them from scattered workflows to organized processes that adhere to LLMOps best practices. The platform centralizes prompts, evaluations, and traces, fostering collaboration among Product Managers, Developers, and Domain Experts.
Key capabilities include a unified playground for comparing prompts and models side-by-side, with complete version history for prompts. Agenta is model-agnostic, allowing users to leverage models from any provider without vendor lock-in. The evaluation tools replace guesswork with evidence, offering automated evaluation, integration of any evaluator (including LLM-as-a-judge and custom code), and the ability to evaluate full traces, examining each intermediate step in an agent's reasoning.
Observability features allow debugging of AI systems, tracing every request to pinpoint failure points, and annotating traces with team feedback or user input. Monitoring production systems with live, online evaluations helps detect regressions. Agenta facilitates collaboration by bringing different team roles into a unified workflow, enabling safe prompt editing and experimentation for domain experts through a dedicated UI, and empowering product managers to run evaluations directly.
The platform offers full API and UI parity, integrating programmatic and UI workflows. It seamlessly integrates with popular frameworks like LangChain and LlamaIndex, as well as models from OpenAI and other providers. Agenta aims to help teams ship reliable agents faster by streamlining prompt engineering, evaluation, and deployment processes.
Agenta's Core Features
Open-source LLMOps platform
Integrated prompt management
Automated evaluation tools
Observability for LLM apps
Unified playground for prompt and model comparison
Complete prompt version history
Model-agnostic architecture
Trace evaluation for intermediate steps
Human evaluation integration
Production monitoring and regression detection
Collaborative workflow for AI teams
UI for domain expert prompt experimentation
Seamless integration with frameworks like LangChain and LlamaIndex
Full API and UI parity
How to use Agenta?
Configure: Set up your LLM application environment and integrate Agenta.
Iterate: Experiment with prompts and models in the unified playground.
Evaluate: Create systematic evaluations to track results and validate changes.
Monitor: Observe production systems and detect regressions with live evaluations.
Collaborate: Bring your team into the workflow for shared prompt management and debugging.
Agenta's Use Cases
- Prompt Engineering
- LLM Evaluation
- Debugging LLM Apps
- Production Monitoring
- Team Collaboration
- LLMOps Best Practices
