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  • Getting Started
    • Overview
    Prompts
    • Prompt Comparison
    • Prompt Versioning
    Datasets
    • AWS Bedrock Models
    • Preparing Data for Fine-Tuning
    • Get Data from S3 Bucket
    • Compare and Evaluate Multiple Models
    • Comparing datasets using Athina IDE
    • Prototype and Evaluate a Prompt Chain
    • Run Prompts and Evaluate
    Evals
    • Pairwise Evaluation
    • Evaluations in CI/CD Pipeline
    • A guide to RAG evaluation
    • Prompt Injection: Attacks and Defenses
    • Running evals as real-time guardrails
    • Different stages of evaluation
    • Improving Eval performance
    • Measuring Retrieval Accuracy in RAG Apps
    • Pairwise Evaluation
    • Evaluate Conversations
    • RAG Evaluators
    Experiments
    • Compare Multiple Models
    Flows
    • Create and Share Flow
    Getting Started

    Getting Started Guides

    It might be helpful to start by reading this: Athina Platform: Overview and Concepts

    If you don’t have an Athina account yet, then start by signing up and inviting your team

    • Create and commit your first Prompt Template
    • Create and share your first Flow TODO
    • Log a sample LLM inference (Python Notebook)
    • Configure an online eval
    • Re-run LLM calls with a different prompt or model
    • View analytics and compare different segments TODO
    • Create a dataset from your logs
    • Export your logs TODO
    • Getting started: Datasets Overview & Concepts
    • Creating a dataset
    • Running an offline eval in Athina IDE
    • Running a prompt column in Athina IDE
    • Running dynamic columns in Athina IDE
    • Running an experiment in Athina IDE

    ​
    Experimentation

    • Comparing different models and prompts
    • Comparing different datasets side-by-side
    • Prototyping a prompt chain in 3 mins without writing code

    ​
    Evaluation

    • RAG Evaluation: A Guide
    • Measure and Improve retrieval in your RAGs
    • LLM-as-a-Judge Evaluation
    • Pairwise Evaluation

    ​
    Evaluation Best Practices

    • Improving eval performance
    • Different stages of evaluation

    ​
    Safeguarding

    • Prompt Injection: Attack and Defense
    • Running evals as real-time guardrails
    Prompt Comparison
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