edsl
Active·★ 510·MIT·Updated 2026-10-27
★ Trending
EDSL simplifies computational social science and market research using AI. It enables designing and running surveys and experiments with numerous AI agents and large language models, providing replicable results with built-in analysis and collaboration tools.
edsl sits in the Multi-Agent category, so it is usually better judged by workflow fit, deployment style, and team needs than by isolated features alone. Based on the available metadata, it leans most clearly toward Declarative design for consistent results. A representative use case is Conducting computational social science research with AI. The listed license is MIT. GitHub stars are currently 507. Relevant tags include AI, LLM.
#AI#LLM#Python#Social Science#Survey Research#Web Browsing#Coding
01
Features
01Declarative design for consistent results
02Parameterized prompts for dynamic data import
03Design AI agent personas for diverse responses
04Simplified access to and comparison of LLMs
05Piping & skip-logic for rich data labeling flows
02
Why choose it
+Declarative design for consistent results
+Parameterized prompts for dynamic data import
+Conducting computational social science research with AI
+Supports 4 platforms or runtime environments.
03
Trade-offs
!The final decision should still be made through side-by-side comparison with similar tools.
04
Compatibility
Expected Parrot Server
Native
Verified via docs
Large Language Models (LLMs)
Supported
Verified via docs
OpenAI GPT
Supported
Verified via docs
Google Gemini
Supported
Verified via docs
05
Quick start
1
$ pip install edsl
06
Use cases
↳Conducting computational social science research with AI
↳Designing and running AI-powered surveys and experiments
↳Performing complex data labeling and research tasks
07
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