lemony-ai/cascadeflow

Cascading runtime for AI agents. Optimize cost, latency, quality, and policy decisions inside the agent loop.

66
/ 100
Established

This is a tool for developers building AI agent applications who need to optimize the performance and cost of their agent's decision-making process. It takes your existing AI agent code and allows you to define policies that dynamically select the best AI model for each step, considering factors like cost, speed, and quality. AI application developers, machine learning engineers, and MLOps professionals are the primary users.

294 stars. Available on PyPI.

Use this if you are developing AI agent applications and want to reduce operational costs, improve response times, and maintain high quality by intelligently managing which AI models your agent uses at each step.

Not ideal if you are an end-user of an AI application or if you only need high-level monitoring of AI API calls without needing to influence in-process agent decisions.

AI agent development MLOps AI cost optimization AI application performance AI model orchestration
Maintenance 10 / 25
Adoption 10 / 25
Maturity 22 / 25
Community 24 / 25

How are scores calculated?

Stars

294

Forks

96

Language

Python

License

MIT

Last pushed

Mar 12, 2026

Commits (30d)

0

Dependencies

3

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