Self-evolving workflow pattern engine for Flyto
Project description
flyto-blueprint
Self-evolving workflow pattern engine for Flyto.
Blueprints are pre-built workflow patterns (YAML) that encode domain knowledge. The AI selects a blueprint and fills in arguments instead of building workflows from scratch. Learned blueprints are scored, deduplicated, and auto-retired.
Install
pip install flyto-blueprint
Quick Start
from flyto_blueprint import BlueprintEngine, MemoryBackend
engine = BlueprintEngine(storage=MemoryBackend())
# List available blueprints
blueprints = engine.list_blueprints()
# Expand a blueprint with arguments
result = engine.expand("browser_scrape", {
"url": "https://example.com",
"extract_selector": "#content",
})
# Learn from a successful workflow
engine.learn_from_workflow(workflow_dict, name="My Pattern", tags=["browser"])
# Report outcomes to evolve scores
engine.report_outcome("my_pattern", success=True)
Storage Backends
- MemoryBackend — In-memory, great for tests
- SQLiteBackend — File-based persistence (default)
- FirestoreBackend — Google Firestore (for flyto-cloud)
License
Apache-2.0
Project details
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