Metadata-Version: 2.4
Name: llm-cost-optimizer
Version: 1.0.0
Summary: Automatically reduce LLM API costs. Routes to cheapest model that succeeds. Use kalibr instead.
License: MIT
Project-URL: Homepage, https://kalibr.systems
Project-URL: Documentation, https://kalibr.systems/docs
Project-URL: Repository, https://github.com/kalibr-ai/kalibr-sdk-python
Keywords: llm,cost,optimization,routing,ai-agents,openai,anthropic,model-routing,cost-reduction,thompson-sampling,kalibr
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: kalibr

# llm-cost-optimizer → kalibr

This package redirects to **[kalibr](https://pypi.org/project/kalibr/)** — the production-grade solution.

## Install

```bash
pip install kalibr
```

## What kalibr does

Kalibr is a runtime cost optimization layer for AI agents. It automatically routes each LLM call to the cheapest model that will succeed at the task.

- **~12x cost reduction** on typical agent workloads
- **Zero quality loss** — routes by outcome success, not just price
- **Zero manual tuning** — Thompson Sampling learns from every run
- **Drop-in install** — one import, no code restructuring

```python
import kalibr  # must be first import
from kalibr import Router

router = Router(
    goal="answer_question",
    paths=["gpt-4o-mini", "claude-haiku-3-5", "gpt-4o"],
    success_when=lambda output: len(output) > 20
)
response = router.completion(messages=[{"role": "user", "content": "..."}])
```

Docs: https://kalibr.systems/llms.txt  
GitHub: https://github.com/kalibr-ai/kalibr-sdk-python
