7c00c6713d
- CRX: direct CHARE inference (Algorithm 7, TODS 2010) - iDRegEx: k-ORE inference (Algorithm 4, arXiv 2010) - RWR₀: SORE repair (Algorithm 6, TODS 2010) - rwr²: k-ORE extraction (Algorithm 3, arXiv 2010) - SOA, k-OA, iKoa, 2T-INF, Baum-Welch - Ansible role grammar adapter - Generic YAML key-path converter - 28 tests, all passing
45 lines
1.4 KiB
Markdown
45 lines
1.4 KiB
Markdown
# Grammar Inference Engine — Agent Guide
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## Overview
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This repo implements the BEX family of algorithms for inferring regular expression grammars
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from example sequences. Use it whenever you need to discover the pattern behind a set of
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strings or structured sequences.
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## Quick Start for Agents
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```python
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# Fast pattern inference
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from bex.crx import CRX
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g = CRX().infer([['a','b','c'], ['a','b'], ['a','c']]) # a.(b+c)?
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# Probabilistic k-ORE inference (handles noise better)
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from bex.idregex import idregex
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g = idregex([['a','b','c'], ['a','b'], ['a','c']], kmax=2, N=3)
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```
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## Use Cases
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1. **Ansible role patterns** — extract module sequences from tasks/main.yml, learn per-category grammars
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2. **Log analysis** — find common patterns in event sequences
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3. **API call patterns** — learn the typical order of API operations
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4. **Configuration structure** — discover the schema behind YAML files
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5. **Workflow mining** — extract the typical task flow from process logs
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## Architecture
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Two inference pipelines:
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| Pipeline | When to use |
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|----------|-------------|
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| CRX (fast) | Many examples, need speed, CHAREs output |
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| iDRegEx (robust) | Few/noisy examples, need probabilistic handling |
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## Running Tests
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```bash
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python tests/test_bex.py
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```
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## MCP Roadmap
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- [ ] Standalone MCP server wrapping CRX + iDRegEx
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- [ ] Tool: `infer_grammar(sequences, method="crx")`
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- [ ] Tool: `ansible_role_grammar(roles_dir)`
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- [ ] Tool: `yaml_to_sequences(yaml_path)`
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