Scorecard AI Docs home pagelight logodark logo
  • About Us
  • Blog
  • Introduction
    • Overview
    • Quickstart
    • What Is Scorecard?
    • The LLM Developer's Journey
    • Technical System Overview
    Features
    • Projects
    • Prompt Management
    • Tracing
    • Privacy By Design
    • Automated Scoring
    • Best In Class Metrics
    • Logging
    • Testset Management
    • A/B Comparison
    • AI Guardrails
    • Run Inspection
    • AI Proxy
    How To Use Scorecard
    • Guides
    • Cookbooks
    • RAG: Retrieval Augmented Generation
    • CI/CD With GitHub Actions
    • Contact
    • Sign In
    Scorecard AI Docs home pagelight logodark logo
    • Contact
    • Sign In
    • Sign In
    Guides
    API Reference
    Glossary
    Changelog
    Guides
    API Reference
    Glossary
    Changelog
    How To Use Scorecard

    Cookbooks

    Welcome to the Scorecard Cookbooks. Here you’ll find code and guides for accomplishing common tasks with the Scorecard API and SDKs.

    To run these examples, you’ll need a Scorecard account and associated API key (create an account here).

    Most code examples are written in Python, though the concepts can be applied in any language.

    ​
    Scorecard Recipes

    E2E Text Extraction and Vector Search Python Demo

    End-to-end example of text extraction and vector search using Python.

    Anthropic Retrieval Augmented Generation (RAG) Example

    Implementation of RAG with Anthropic models.

    Create a Testset with Custom Schema

    Guide on setting up a Testset using Scorecard’s SDK.

    Multi-Message Prompt using Scorecard SDK

    Learn how to structure multi-message prompts with Scorecard.

    Prompt with Custom Variables using Scorecard SDK

    Customize prompts dynamically using Scorecard SDK.

    Heuristic Scoring Example - Exact String Match

    Example of using heuristic scoring for evaluations.

    Tracing with Scorecard - Python Demo

    Learn how to implement tracing in Python with Scorecard.

    Tracing with Scorecard - Node Demo

    Implement tracing in Node.js with Scorecard.

    Prompt Management Example

    Efficiently manage and version prompts with Scorecard.

    Using Second-Party Metrics from MLflow

    Integrate MLflow metrics with Scorecard.

    Using Second-Party Metrics from RAGAS

    Leverage RAGAS metrics within Scorecard.

    Was this page helpful?

    Suggest editsRaise issue
    Previous
    RAG: Retrieval Augmented GenerationRetrieval Augmented Generation (RAG) is the use of retrieval methods (e.g. via search and vector stores) to provide generative models with additional context, or *grounding*.
    Next
    websitegithublinkedin
    Powered by Mintlify