cascade-lattice 0.5.5

Universal AI provenance layer — cryptographic receipts for every call, with HOLD inference halt protocol

Cascade Lattice

Universal AI provenance layer — cryptographic receipts for every call, with HOLD inference halt protocol

Installation

pip install cascade-lattice

With optional dependencies:

pip install cascade-lattice[torch]  # PyTorch integration
pip install cascade-lattice[all]    # All integrations

Quick Start

from cascade import Monitor

# Create a monitor for your component
monitor = Monitor("training_loop")

# Observe events (parses logs, extracts metrics)
event = monitor.observe("Epoch 5: loss=0.0234, accuracy=0.9812")
print(event.data)  # {'loss': 0.0234, 'accuracy': 0.9812, ...}

# Get metrics summary
print(monitor.metrics.summary())

Features

• Universal Observation — Monitor training, inference, system logs, API calls
• Cryptographic Receipts — Every observation gets a verifiable hash chain
• HOLD Protocol — Inference halt capability for safety-critical applications
• Tape Storage — JSONL event streams for replay and analysis
• Provider Patches — Drop-in monitoring for OpenAI, Anthropic, LiteLLM, Ollama

CLI Usage

cascade --help              # Show all commands
cascade stats               # Lattice statistics
cascade list -n 20          # Recent observations
cascade watch               # Live observation feed
cascade fingerprint model/  # Fingerprint a model
cascade pii scan.log        # Scan for PII

Tape Utilities

from cascade.viz import load_tape_file, find_latest_tape, list_tape_files

# Find and load tape files
latest = find_latest_tape("./logs")
events = load_tape_file(latest)

for event in events:
    print(event['event']['event_type'], event['event']['data'])

License

MIT