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Paweł Kędzia
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Enhance README with linked component sections and revised headings; add radlab-ml-utils to install_requires in setup.py.
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README.md

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@@ -12,18 +12,23 @@ a ready‑made image in your own infrastructure.
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and optional Prometheus metrics.
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- **llm_router_lib** is a Python SDK that wraps the API with typed request/response models, automatic retries, token
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handling and a rich exception hierarchy, letting developers focus on application logic rather than raw HTTP calls.
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- **llm_router_web** offers ready‑to‑use Flask UIs – an anonymizer UI that masks sensitive data and a configuration
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- [**llm_router_web**](https://github.com/radlab-dev-group/llm-router-web) offers ready‑to‑use Flask UIs – an anonymizer
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UI that masks sensitive data and a configuration
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manager for model/user settings – demonstrating how to consume the router from a browser.
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- **llm_router_plugins** (e.g., the **fast_masker** plugin) deliver a rule‑based text anonymisation engine with
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- [**llm_router_plugins**](https://github.com/radlab-dev-group/llm-router-plugins) (e.g., the **fast_masker** plugin)
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deliver a rule‑based text anonymisation engine with
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a comprehensive set of Polish‑specific masking rules (emails, IPs, URLs, phone numbers, PESEL, NIP, KRS, REGON,
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monetary amounts, dates, etc.) and an extensible architecture for custom rules and validators.
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- [**llm_router_services**](https://github.com/radlab-dev-group/llm-router-services) provides HTTP services that
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implement the core functionality used by the LLM‑Router’s plugin system. The services expose guardrail and masking
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capabilities through Flask applications.
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All components run on Python 3.10+ using `virtualenv` and require only the listed dependencies, making the suite easy to
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install, extend, and deploy in both development and production environments.
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---
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### ✨ Key Features
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## ✨ Key Features
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| Feature | Description |
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|-------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------|
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#### Base requirements
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> **Prerequisite**: `radlab-ml-utils`
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>
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> This project uses the
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> [radlab-ml-utils](https://github.com/radlab-dev-group/ml-utils)
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> library for machine learning utilities
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> (e.g., experiment/result logging with Weights & Biases/wandb).
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> Install it before working with ML-related parts:
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>
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> ```bash
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> pip install git+https://github.com/radlab-dev-group/ml-utils.git
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> ```
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>
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> For more options and details, see the library README:
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> https://github.com/radlab-dev-group/ml-utils
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```shell script
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python3 -m venv .venv
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source .venv/bin/activate
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LLM_ROUTER_MINIMUM=1 python3 -m llm_router_api.rest_api
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```
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### 📦 Docker
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## 📦 Docker
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Run the container with the default configuration:
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---
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### Configuration (via environment)
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## 🛠️ Configuration (via environment)
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A full list of environment variables is available at the link
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[.env list](llm_router_api/README.md#environment-variables)
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## 🛠️ Development
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## 🔧 Development
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- **Python**3.10+ (project is tested on 3.10.6)
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- All dependencies are listed in `requirements.txt`. Install them inside the virtualenv.

setup.py

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exclude=("tests", "docs"),
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),
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python_requires=">=3.10",
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install_requires=requirements_lib + [
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"llm-router-lib @ git+https://github.com/radlab-dev-group/llm-router-lib",
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install_requires=requirements_lib
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+ [
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"radlab-ml-utils @ git+https://github.com/radlab-dev-group/ml-utils",
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"llm-router-plugins @ git+https://github.com/radlab-dev-group/llm-router-plugins",
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],
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extras_require=extras,

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