LoopGain
An open-source cost controller for AI agent loops that stops loops when converged and rolls back before degradation.
LoopGain
What is LoopGain?
LoopGain vs Similar AI Tools
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How to use LoopGain?
- 1Install LoopGain via pip: pip install loopgain
- 2Import and create a LoopGain instance with a target_error.
- 3In your iterative loop, call lg.observe(errors, output=output) and lg.should_continue().
- 4After termination, access lg.result for best output and savings metrics.
LoopGain Key Features
- Real-time loop gain measurement with smoothed Aβ bands
- Best-so-far rollback on oscillation or divergence
- Pre-built adapters for LangGraph, CrewAI, AutoGen, LangChain, OpenAI Agents, and Claude Agent SDK
- Pure Python, no runtime dependencies
- Opt-in telemetry with self-hostable dashboard
LoopGain Use Cases
- Verify-revise loops
- Refinement loops
- Tool-use retry chains
- RAG with self-correction
- Code generation with linter/test feedback
LoopGain Pricing & Free Credits
LoopGain currently operates on a Free model.
This tool is completely free to use
LoopGain Pros & Cons
Pros
- Reduces API spend by up to 92.8% in benchmarks
- Preserves output quality with best-so-far rollback
- Works with any iterative AI loop with a measurable error signal
- Open source and framework-agnostic
Cons
- Requires a meaningful error signal; quality depends on verifier
- Detects convergence, not correctness – may stop on a plateau
- Alpha software; API may break before 1.0
What is LoopGain best for?
- Developers building AI agent loops who want to minimize token waste without sacrificing quality
LoopGain FAQ
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