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Introduction

  • Overview
  • Whitepaper
  • Citation
  • Papers

Getting Started

  • Starter Tutorial
  • Installation
  • API Keys
  • Colab Setup
  • Credits

Core Concepts

  • Questions
  • Scenarios
  • Surveys
  • Agents
  • Prompts
  • Language Models

Working with Results

  • Results
  • Caching LLM Calls
  • Exceptions & Debugging
  • Token usage
  • Survey logic checklist

Coop

  • Coop
  • Notebooks
  • Colab Notebooks
  • Remote Inference
  • Remote Caching
  • File Store

How-to Guides

  • Intro to EDSL
  • Estimating costs
  • Analyzing a transcript
  • Updating agent traits
  • Save & load objects
  • Data labeling
  • Data cleaning
  • Simulate a feedback survey
  • Using PDFs in a survey
  • Using images in a survey
  • Using Wikipedia tables in a survey
  • Using data with surveys: FileStore
  • Adding metadata to survey results
  • Creating question variants
  • Skip logic & scenarios
  • Agent dynamic traits
  • Importing agents
  • Batching results
  • Cognitive testing & creating new methods

Notebooks

  • Calculating next token probabilities
  • Analyzing customer service calls
  • Analyzing course evaluations
  • Concept induction
  • Simulate a qualitative interview
  • Launch an interview
  • NPS survey in EDSL
  • Data labeling agents
  • Using EDSL to sense check data
  • Simulating randomness
  • Testing model training data
  • Comparing model responses
  • Evaluating job posts
  • Cognitive testing & LLM biases
  • Exploring real world survey contexts
  • Exploring free text responses
  • Creating a digital twin
  • Stylized content
  • Google Form -> EDSL
  • Using EDSL for AI polling
  • Working with CES data in EDSL

Developers

  • Contributing
  • Jobs
  • Interviews
  • Answers
  • Enums
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