Skip to content
Logo LogoRagas
⌘ K
Logo LogoRagas
  • 🚀 Get Started
    • Installation
    • Generate a Synthetic Test Set
    • Evaluating Using Your Test Set
    • Monitor Your RAG in Production
  • 📚 Core Concepts
    • Metrics-Driven Development
    • Metrics
      • Faithfulness
      • Answer Relevance
      • Context Precision
      • Context utilization
      • Context Recall
      • Context entities recall
      • Noise Sensitivity
      • Answer semantic similarity
      • Answer Correctness
      • Aspect Critique
      • Domain Specific Evaluation
      • Summarization Score
    • Prompt Objects
    • Automatic prompt Adaptation
    • Synthetic Test Data generation
    • Utilizing User Feedback
  • 🛠️ How-to Guides
    • Customizations
      • Bring Your Own LLMs and Embeddings
      • Using Ragas Critic Model instead of GPT-4
      • Max Workers, Timeouts, Retries and more with RunConfig
      • Using Azure OpenAI
      • Using Amazon Bedrock
      • Vertex AI
    • Applications
      • Building HF Dataset with your own Data
      • Understand Cost and Usage of Operations
      • Compare Embeddings for retriever
      • Compare LLMs using Ragas Evaluations
      • Write custom prompts with ragas
      • Automatic language adaptation
      • Explainability through Logging and tracing
      • Adding to your CI pipeline with Pytest
    • Integrations
      • LlamaIndex
      • Langchain
      • Langsmith
      • Phoenix (Arize)
      • Langfuse
      • Athina AI
      • Zeno
      • Tonic Validate
      • Haystack
      • OpenLayer
      • Helicone
  • 📖 References
    • Evaluation
    • Metrics
    • RunConfig
    • Integrations
  • ❤️ Community
Ragas
/
📖 References

📖 References¶

Reference documents for the ragas package.

  • Evaluation
    • evaluate()
    • Result
  • Metrics
    • AnswerCorrectness
      • AnswerCorrectness.name
      • AnswerCorrectness.weights
      • AnswerCorrectness.answer_similarity
      • AnswerCorrectness.adapt()
      • AnswerCorrectness.init()
      • AnswerCorrectness.save()
    • AnswerRelevancy
      • AnswerRelevancy.name
      • AnswerRelevancy.strictness
      • AnswerRelevancy.embeddings
      • AnswerRelevancy.adapt()
      • AnswerRelevancy.save()
    • AnswerSimilarity
      • AnswerSimilarity.name
      • AnswerSimilarity.model_name
      • AnswerSimilarity.threshold
    • AspectCritique
      • AspectCritique.name
      • AspectCritique.definition
      • AspectCritique.strictness
      • AspectCritique.llm
      • AspectCritique.adapt()
      • AspectCritique.save()
    • ContextEntityRecall
      • ContextEntityRecall.name
      • ContextEntityRecall.batch_size
      • ContextEntityRecall.save()
    • ContextPrecision
      • ContextPrecision.name
      • ContextPrecision.evaluation_mode
      • ContextPrecision.context_precision_prompt
      • ContextPrecision.adapt()
      • ContextPrecision.save()
    • ContextRecall
      • ContextRecall.name
      • ContextRecall.adapt()
      • ContextRecall.save()
    • ContextUtilization
    • Faithfulness
      • Faithfulness.adapt()
      • Faithfulness.save()
    • FaithulnesswithHHEM
    • LabelledRubricsScore
      • LabelledRubricsScore.adapt()
      • LabelledRubricsScore.save()
    • NoiseSensitivity
      • NoiseSensitivity.adapt()
      • NoiseSensitivity.save()
    • ReferenceFreeRubricsScore
    • SummarizationScore
      • SummarizationScore.adapt()
  • RunConfig
    • rng
  • Integrations
Helicone
Evaluation

© 2023, ExplodingGradients Built with Sphinx 6.2.1