DeepEval

DeepEval

Confident AI
Vizcab Eval

Vizcab Eval

Vizcab
+
+

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About

DeepEval is a simple-to-use, open source LLM evaluation framework, for evaluating and testing large-language model systems. It is similar to Pytest but specialized for unit testing LLM outputs. DeepEval incorporates the latest research to evaluate LLM outputs based on metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., which uses LLMs and various other NLP models that run locally on your machine for evaluation. Whether your application is implemented via RAG or fine-tuning, LangChain, or LlamaIndex, DeepEval has you covered. With it, you can easily determine the optimal hyperparameters to improve your RAG pipeline, prevent prompt drifting, or even transition from OpenAI to hosting your own Llama2 with confidence. The framework supports synthetic dataset generation with advanced evolution techniques and integrates seamlessly with popular frameworks, allowing for efficient benchmarking and optimization of LLM systems.

About

Vizcab Eval is the solution to allow you to produce reliable, robust building ACV studies and percussive in one minimum time. Import your DPGF-type measurements and your RSET in a few clicks. Complete your entry using our research panel by keyword. Automatically associate your components and make simple corrections with our alert system. View results globally or in batches in real-time in the form of tables and graphs and validate compliance with thresholds. Identify at a glance the most impactful cards of your project, and bring efficient optimizations. Choose the most virtuous products with our scoring system of FDES. Work together and exchange easily with our fashion collaborative. Export your results in the form of graphs, and study reports according to your needs. Recover one RSEE export from your study to Excel format. You import your data directly into Vizcab Eval, and your components are automatically associated with plugs.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Professional users interested in a tool to evaluate, test, and optimize their LLM applications

Audience

Companies searching for a solution to calculate, visualize, and optimize their environmental impact

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Confident AI
United States
docs.confident-ai.com

Company Information

Vizcab
France
vizcab.io/vizcab-eval

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Categories

Categories

Integrations

Hugging Face
KitchenAI
LangChain
Llama 2
LlamaIndex
Microsoft Excel
OpenAI
Opik
Ragas
XML

Integrations

Hugging Face
KitchenAI
LangChain
Llama 2
LlamaIndex
Microsoft Excel
OpenAI
Opik
Ragas
XML
Claim DeepEval and update features and information
Claim DeepEval and update features and information
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Claim Vizcab Eval and update features and information