Confident AI

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Confident AI is an open-source evaluation infrastructure for LLMs that enables developers to unit test and benchmark AI models with ease.
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Confident AI

Product Information

Updated:09/11/2024

What is Confident AI

Confident AI is a platform that provides tools and infrastructure for evaluating and testing large language models (LLMs). It offers DeepEval, an open-source Python framework that allows developers to write unit tests for LLMs in just a few lines of code. The platform aims to help AI developers build more robust and reliable language models by providing metrics, benchmarking capabilities, and a centralized environment for tracking evaluation results.

Key Features of Confident AI

Confident AI is an open-source evaluation platform for Large Language Models (LLMs) that enables companies to test, evaluate, and deploy their LLM implementations with confidence. It offers features like A/B testing, output evaluation against ground truths, output classification, reporting dashboards, and detailed monitoring. The platform aims to help AI engineers detect breaking changes, reduce time to production, and optimize LLM applications.
DeepEval Package: An open-source package allowing engineers to evaluate or 'unit test' their LLM applications' outputs in under 10 lines of code.
A/B Testing: Compare and choose the best LLM workflow to maximize enterprise ROI.
Ground Truth Evaluation: Define ground truths to ensure LLMs behave as expected and quantify outputs against benchmarks.
Output Classification: Discover recurring queries and responses to optimize for specific use cases.
Reporting Dashboard: Utilize report insights to trim LLM costs and latency over time.

Use Cases of Confident AI

LLM Application Development: AI engineers can use Confident AI to detect breaking changes and iterate faster on their LLM applications.
Enterprise LLM Deployment: Large companies can evaluate and justify putting their LLM solutions into production with confidence.
LLM Performance Optimization: Data scientists can use the platform to identify bottlenecks and areas for improvement in LLM workflows.
AI Model Compliance: Organizations can ensure their AI models behave as expected and meet regulatory requirements.

Pros

Open-source and simple to use
Comprehensive set of evaluation metrics
Centralized platform for LLM application assessment
Helps reduce time to production for LLM applications

Cons

May require some coding knowledge to fully utilize
Primarily focused on LLMs, may not be suitable for all types of AI models

How to Use Confident AI

Install DeepEval: Run 'pip install -U deepeval' to install the DeepEval library
Import required modules: Import assert_test, metrics, and LLMTestCase from deepeval
Create a test case: Create an LLMTestCase object with input and actual_output
Define evaluation metric: Create a metric object, e.g. HallucinationMetric, with desired parameters
Run assertion: Use assert_test() to evaluate the test case against the metric
Execute tests: Run 'deepeval test run test_file.py' to execute tests
View results: Check test results in console output
Log to Confident AI platform: Use @deepeval.log_hyperparameters decorator to log results to Confident AI
Analyze results: Log into Confident AI platform to view detailed analytics and insights

Confident AI FAQs

Confident AI is a company that provides open-source evaluation infrastructure for Large Language Models (LLMs). They offer DeepEval, a tool that allows developers to unit test LLMs in under 10 lines of code.

Analytics of Confident AI Website

Confident AI Traffic & Rankings
98.7K
Monthly Visits
#430300
Global Rank
#5457
Category Rank
Traffic Trends: Jun 2024-Oct 2024
Confident AI User Insights
00:02:08
Avg. Visit DTabsNavuration
2.16
Pages Per Visit
51.29%
User Bounce Rate
Top Regions of Confident AI

  1. US: 38.33%

  2. IN: 4.83%

  3. RU: 4.43%

  4. KR: 4.2%

  5. GB: 3.6%

  6. Others: 44.61%

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