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README.md
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# 🐺 Wolf: Model Evaluation Backbone
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Wolf is a multi-model evaluation system for sovereign AI fleets. It automates the process of assigning coding tasks to different AI models, executing them, and scoring their performance based on real-world metrics like CI status, code quality, and PR effectiveness.
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## 🚀 Key Features
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- **Task Generator**: Automatically creates tasks from Gitea issues or task specifications.
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- **Agent Runner**: Executes tasks using various model providers (OpenRouter, Groq, Ollama, OpenAI, Anthropic).
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- **PR Creator**: Opens Pull Requests on Gitea with the agent's work.
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- **Evaluators**: Scores PRs on multiple dimensions:
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- CI test results.
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- Commit message quality.
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- Code quality vs. boilerplate.
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- Functionality and test inclusion.
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- PR description clarity.
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- **Leaderboard**: Tracks model performance over time and identifies "serverless-ready" models.
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## 📦 Installation
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Wolf is designed to be zero-dependency where possible, requiring only `stdlib` and `requests`.
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```bash
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pip install requests pyyaml
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```
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## 🛠️ Configuration
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Save your configuration to `~/.hermes/wolf-config.yaml`. See `wolf-config.yaml.example` for a template.
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## 🤖 Usage
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### Run Pending Tasks
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```bash
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python3 -m wolf.cli --run
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```
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### Evaluate Open PRs
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```bash
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python3 -m wolf.cli --evaluate
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```
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### Show Leaderboard
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```bash
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python3 -m wolf.cli --leaderboard
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```
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### Run as a Cron Job
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Add the following to your crontab to run Wolf every hour:
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```bash
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0 * * * * cd /path/to/wolf && python3 -m wolf.cli --run --evaluate >> ~/.hermes/wolf/cron.log 2>&1
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```
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## 🧪 Testing
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Run the test suite locally:
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```bash
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python3 -m unittest discover tests
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```
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---
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**"The strength of the pack is the wolf, and the strength of the wolf is the pack."**
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*— The Wolf Sovereign Core has spoken.*
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