AdalFlow
AdalFlow lets you compose, run, and automatically optimize LLM pipelines in pure Python.
- •You need a repeatable LLM workflow (prompt → model → post‑processing) that you can version‑control.
- •You want the library to automatically tune prompts or model parameters for cost or quality targets.
- •You prefer a single Python dependency instead of stitching together LangChain, PromptLayer, etc.
python demo.py # runs the script above and prints a concise, LLM‑generated answer
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Works after you add credentials — the setup agent will ask you for them.
mkdir -p ~/.claude/skills/adalflow && curl -fsSL https://workflowstacks.com/api/skills/adalflow/claude-skill -o ~/.claude/skills/adalflow/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
AdalFlow is a large Python project (~59k lines across 278 code files, plus 55 test files). Setup is light: installs like a normal app. Reading the code is optional. Last commit 4 months ago, MIT license, has a test suite.
- 1README.mdStart here — what it does and how to install it
- 2pyproject.tomlDependencies and the commands it exposes
- 3adalflow/README.mdInside adalflow/ — the main logic begins here
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Works after you add credentials — the setup agent will ask you for them.
mkdir -p ~/.claude/skills/adalflow && curl -fsSL https://workflowstacks.com/api/skills/adalflow/claude-skill -o ~/.claude/skills/adalflow/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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