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Evaluation Infrastructure for LLMs.
Companies of all sizes use Confident AI to justify why their LLM deserves to be in production.
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import pytest
from deepeval.evaluator import assert_test
from deepeval.metrics import HallucinationMetric
from deepeval.test_case import LLMTestCase
def test_example();
test_case = LLMTestCase(input="...", actual_output="...")
metric = HallucinationMetric(minimum_score=0.7)
assert_test(test_case, [metric])
> pip install -U deepeval
> deepeval test run test_chatbot.py
✓ Test Run Completed.
✓ 1/1 test case(s) passing.
Open-source and simple to use.
We offer a generous free tier and anyone can get started in under 10 lines of code.
2.4x
Less time to production
No more time wasted on fixing breaking changes.
12+
Metrics available
We offer plenty of open-source metrics for you to plug and use.
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17k
Evaluations completed
Users evaluate by writing and executing test cases in python.
100%
Sleep better at night
Our users sleep better knowing their LLM is behaving as expected.
Judge your LLM application on one, centralized platform.
Deploy LLM solutions with confidence, ensuring substantial benefits and address any weaknesses in your LLM implementation.
Define ground truths to ensure your LLM is behaving as expected
Supply ground truths as benchmarks to evaluate your LLM outputs. Evaluate performance against expected outputs to pinpoint areas for iterations.
Advanced diff tracking to iterate towards the optimal LLM stack
From altering prompt templates to selecting the right knowledge bases – we guide you towards the optimal configurations for your specific use case.
Comprehensive analytics to identify areas of focus
Utilize out-of-the-box observability to identify and evaluate use cases that bring the most ROI for your enterprise.
Powerful features to productionize LLMs with confidence.
A/B testing
Compare and choose the best LLM workflow to maximize your enterprise ROI.
Evaluation
Quantify and benchmark your LLM outputs against expected ground truths.
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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.
Dataset generation
Automatically generate expected queries and responses for evaluation.
Detailed monitoring
Identify bottlenecks in your LLM workflows for targeted iteration and improvement.
Book a demo today.
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