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Description
DeepEval offers an intuitive open-source framework designed for the assessment and testing of large language model systems, similar to what Pytest does but tailored specifically for evaluating LLM outputs. It leverages cutting-edge research to measure various performance metrics, including G-Eval, hallucinations, answer relevancy, and RAGAS, utilizing LLMs and a range of other NLP models that operate directly on your local machine. This tool is versatile enough to support applications developed through methods like RAG, fine-tuning, LangChain, or LlamaIndex. By using DeepEval, you can systematically explore the best hyperparameters to enhance your RAG workflow, mitigate prompt drift, or confidently shift from OpenAI services to self-hosting your Llama2 model. Additionally, the framework features capabilities for synthetic dataset creation using advanced evolutionary techniques and integrates smoothly with well-known frameworks, making it an essential asset for efficient benchmarking and optimization of LLM systems. Its comprehensive nature ensures that developers can maximize the potential of their LLM applications across various contexts.
Description
Evalship assists engineering teams in assessing LLM-driven software by conducting evaluation-suite audits and reviewing pull requests. It meticulously examines scorers and judges for potential errors, spots areas lacking coverage, and highlights evaluations that might yield incorrect outcomes, all while presenting findings complete with code references and recommendations for improvements. The setup process aids a coding agent in configuring GitHub Actions and initiating a setup pull request. For subsequent pull requests, evalship analyzes the outcomes in relation to the default branch, identifying regressions, flaky evaluations, and any modifications to prompts or model calls that lack evaluation coverage, alongside offering a merge-gating status check. It processes results from various supported test runners and LLM evaluation platforms. Evaluations are executed within the customer’s GitHub Actions environment using their specific model API keys, while evalship focuses on reviewing these results rather than carrying out the evaluations itself. In addition to these features, teams can access their evaluation history and obtain weekly performance reports to track progress and improvements over time. This comprehensive approach ensures that software quality remains a top priority throughout the development lifecycle.
API Access
Has API
No
API Access
Has API
Yes
Screenshots View All
No images available
Integrations
Braintrust
No
GitHub Actions
No
Hugging Face
Yes
Jest
No
KitchenAI
Yes
LangChain
Yes
LangSmith
No
Langfuse
No
Llama 2
Yes
LlamaIndex
Yes
Integrations
Braintrust
Yes
GitHub Actions
Yes
Hugging Face
No
Jest
Yes
KitchenAI
No
LangChain
No
LangSmith
Yes
Langfuse
Yes
Llama 2
No
LlamaIndex
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
$7.60/month
The Team plan is $7.60 per month during the launch offer, 60% off its $19 monthly price for the next 9 accounts. It includes 3 users and 2 private repositories. Additional users cost $2 per month each, and additional repositories cost $10 per month each. A 7-day free trial is offered. Public repositories are free.
Free Trial
Yes
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Confident AI
Country
United States
Website
docs.confident-ai.com
Vendor Details
Company Name
Garm Tech B.V.
Founded
2026
Country
Netherlands
Website
evalship.com