Confident AI Howto

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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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Profile of Confident AI
Overview
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What is Confident AI
Features of Confident AI & Use Cases

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.

Confident AI Monthly Traffic Trends

Confident AI saw a 34.1% increase in traffic, reaching 140K visits. The moderate growth may be attributed to the increasing focus on AI evaluation and the product's robust feature set, including 14 metrics for LLM experiments and human feedback integration. Additionally, the entry of DeepSeek into the market and the narrowing performance gap between U.S. and Chinese AI models could be driving interest in comprehensive evaluation tools.

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