EDSL: AI-Powered Research

Expected Parrot Domain-Specific Language (EDSL) is an open-source Python package for conducting AI-powered research.

EDSL is developed by Expected Parrot and available under the MIT License.

This page provides documentation, tutorials and demo notebooks for the EDSL package and the Coop: a platform for creating, storing and sharing AI research. The contents are organized into key sections to help you get started.

Researchers

Are you using EDSL for a research project? We’d love to hear about your experience!

Send us an email at info@expectedparrot.com and we’ll provide credits to run your project or a gift card for your time.

Introduction

  • Overview: An overview of the purpose, concepts and goals of the EDSL package.

  • Whitepaper: A whitepaper about the EDSL package (in progress).

  • Citation: How to cite the package in your work.

  • Papers: Research papers and articles that use or cite EDSL.

Technical Setup

  • Installation: Instructions for installing the EDSL package.

  • Coop: Create, store and share research on the Expected Parrot server.

  • API Keys: Instructions for storing API keys to use EDSL locally (optional).

Getting Started

Core Concepts

  • Questions: Learn about different question types and applications.

  • Scenarios: Explore how questions can be dynamically parameterized for tasks like data labeling.

  • Surveys: Construct surveys with rules and conditions.

  • Agents: Design AI agents with relevant traits to respond to surveys.

  • Language Models: Select language models to generate results.

Working with Results

Coop

Coop is a platform for creating, storing and sharing EDSL content and AI-based research.

  • Coop: Learn how to create, store and share content at the Coop.

  • Survey Builder: An interface for launching hybrid human-AI surveys.

  • File Store: Store and share files for use in EDSL projects.

  • Remote Inference: Run surveys on the Expected Parrot server.

  • Remote Caching: Automatically store survey results and API calls on the Expected Parrot server.

  • Notebooks: Instructions for posting .ipynb files to the Coop.

Importing Data

  • Conjure: Automatically import other survey data into EDSL to:

    • Clean and analyze your data

    • Create AI agents for respondents and conduct follow-on interviews

    • Extend your results with new questions and surveys

    • Store and share your data on the Coop

How-to Guides

Examples of special methods and use cases for EDSL, including:

  • Data labeling

  • Data cleaning

  • Analyzing survey results

  • Adding data to surveys from CSVs, PDFs, images and other sources

  • Conducting agent conversations

  • Converting surveys into EDSL

  • Cognitive testing

Notebooks

Templates and example code for using EDSL to conduct different kinds of research. We’re happy to create a new notebook for your use case!

Developers

Information about additional functionality for developers.