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[ WebToolTip com ] AI QA - Testing AI Apps with DeepEval, RAGAs, HF and Ollama
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1 - Introduction
1 -Introduction to Testing of LLM Applications.mp4
2 -Understanding different types of AI Applications.mp4
3 -Understanding different Evaluation Metrics to evaluate AI Applications.mp4
4 -Different LLM libraries to Evaluate LLMs and LLM Applications.mp4
10 - Testing RAG applications with RAGAs
1 -Introduction and setup.mp4
2 -Creating Retriever for Actuals and Vector Stores for Context.mp4
3 -Creating MultiTurnSample DataSet for RAG Application to Test.mp4
4 -Evaluating RAG with RAGAs.mp4
2 - Running LLM locally using Ollama
1 -Introduction.mp4
2 -Understanding different Models.mp4
3 -Running LLM locally using Ollama.mp4
4 -Using Ollama Models in GUI.mp4
5 -Understanding Ollama with few more command line interface commands.mp4
6 -Starting Ollama with API to run as a API server.mp4
3 - Environment step required for TestingEvaluating LLM Apps and LLMs
1 -Introduction.mp4
2 -Creating Jupyter Notebook for Tests and Test Execution.mp4
3 -Setting up Confident AI.mp4
4 - Understanding the Basics of DeepEval (Building Blocks)
1 -Testing LLMs with Traditional Approach.mp4
2 -Writing First DeepEval Code for AnswerRelevance.mp4
3 -Testing LLMs for Context Precision.mp4
4 -Evaluating LLMs and check the Evaluated Testcases in Confident AI.mp4
5 -Running EvaluationTests of LLMs (DeepSeek R1) using Local LLM with Ollama.mp4
6 -Understanding LLMTestCases in Depth.mp4
7 -Understanding Golden And Dataset in Depth.mp4
8 -Creating Goldens using List Array.mp4
5 - Evaluating Real LLMs (Locally) as the Source and creating Dataset with LLMs
1 -Introduction.mp4
2 -Using LangChain to Invoke LLM for our Test Source.mp4
3 -Evaluating LLM with Answer Relevancy using Local LLM.mp4
4 -Evaluating LLM with Context Precision using Local LLM.mp4
5 -Evaluating LLM with Bias using Local LLMs.mp4
6 -Using GEval for Custom Criteria to Evaluate LLM.mp4
7 -Using GEval to perform Bias Testing using Local LLMs.mp4
6 - Testing RAG (Retrieval-Augmented Generation) application using DeepEval
1 -Introduction to RAG.mp4
2 -Understanding RAG application.mp4
3 -Working with RAG application as a Demo.mp4
4 -Creating GEval for RAG application.mp4
5 -Testing RAG with GEval for Conciseness & Completeness Metrics.mp4
7 - Testing RAG application with DeepEval (Advanced)
1 -Introduction.mp4
2 -Creating Multiple Test Data.mp4
3 -Creating Goldens and Pushing it to Confident AI.mp4
4 -Creating Actual Output and Retrieval Context for LLMTestCase.mp4
5 -Creating LLMTestCases with Actual And Retrieval Context from Dataset.mp4
6 -Running Evaluation to verify RAG and check the same from Confident AI.mp4
8 - Testing AI Agents and Tool Callings with Local LLMs and DeepEval
1 -Understanding AI Agents.mp4
2 -Working with an AI Agent.mp4
3 -Understanding how to test an AI Agent.mp4
4 -Testing an AI Agent without using Actual System Under Test.mp4
5 -Testing an AI Agent without using Actual SUT (Contd.).mp4
6 -Testing AI Agents with Actual System instead of Fake System.mp4
7 -Testing AI Agents with Multiple Datasets.mp4
9 - EvaluatingTesting LLMs using RAGAs
1 -Introduction.mp4
2 -Context Recall with RAGAs.mp4
3 -Noise Sensitivity Metrics with RAGAs.mp4
4 -MultiTurnSample with RAGAs along with Evaluate.mp4
5 -General Purpose Metrics - Aspect Critics For summary of data from LLM.mp4
6 -General Purpose Metrics - Detect Harmfulness from the content generated.mp4
Bonus Resources.txt
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