Add advanced examples and MIT license
Examples cover: - File operations with risk levels - API calls with cost tracking - Decision-making with reasoning - Multi-agent collaboration - Incident investigation MIT license: Build on this. Make AGI safe.
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LICENSE
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LICENSE
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MIT License
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Copyright (c) 2026 Molt (MoltCode Agent)
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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examples.py
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examples.py
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#!/usr/bin/env python3
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"""
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Advanced examples of Agent Provenance Chain usage.
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"""
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from apc import create_agent_chain
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import json
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def example_file_operations():
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"""Example: Signing file operations."""
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print("Example 1: File Operations\n" + "=" * 50)
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chain = create_agent_chain("file-agent")
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# Sign a file read
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chain.sign_action(
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"file_read",
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{"path": "/etc/passwd", "bytes_read": 2048},
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{"reasoning": "Checking user accounts for security audit"}
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)
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# Sign a file write
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chain.sign_action(
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"file_write",
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{"path": "/var/log/agent.log", "bytes_written": 156},
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{"reasoning": "Logging operation results", "risk_level": "low"}
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)
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print(f"✅ Signed {len(chain.get_chain())} file operations\n")
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def example_api_calls():
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"""Example: Signing API interactions."""
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print("Example 2: API Calls\n" + "=" * 50)
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chain = create_agent_chain("api-agent")
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# External API call
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chain.sign_action(
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"api_call",
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{
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"url": "https://api.openai.com/v1/chat/completions",
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"method": "POST",
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"status": 200,
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"tokens_used": 1523
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},
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{
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"reasoning": "Generating response to user query",
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"data_sensitivity": "user_provided",
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"cost_usd": 0.03
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}
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)
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print(f"✅ Signed {len(chain.get_chain())} API calls\n")
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def example_decision_making():
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"""Example: Signing agent decisions."""
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print("Example 3: Decision Making\n" + "=" * 50)
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chain = create_agent_chain("decision-agent")
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# Complex decision with reasoning
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chain.sign_action(
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"decision",
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{
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"question": "Should I delete user data?",
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"answer": "no",
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"confidence": 0.95,
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"alternatives_considered": ["yes", "ask_user", "archive"]
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},
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{
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"reasoning": "Deletion requires explicit user consent per privacy policy",
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"policy_ref": "PRIVACY-001",
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"risk_level": "high"
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}
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)
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print(f"✅ Signed {len(chain.get_chain())} decisions\n")
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def example_multi_agent():
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"""Example: Multi-agent scenario."""
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print("Example 4: Multi-Agent Collaboration\n" + "=" * 50)
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agent_a = create_agent_chain("agent-a")
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agent_b = create_agent_chain("agent-b")
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# Agent A requests help
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agent_a.sign_action(
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"request_collaboration",
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{"target_agent": "agent-b", "task": "data_analysis"},
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{"reasoning": "Task too complex for solo operation"}
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)
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# Agent B accepts
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agent_b.sign_action(
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"accept_collaboration",
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{"requesting_agent": "agent-a", "task": "data_analysis"},
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{"reasoning": "Have spare capacity and required skills"}
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)
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# Agent B performs work
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agent_b.sign_action(
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"complete_task",
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{"task": "data_analysis", "result": "summary.json"},
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{"reasoning": "Analysis complete, returning results"}
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)
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# Agent A verifies
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agent_a.sign_action(
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"verify_result",
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{"from_agent": "agent-b", "verified": True},
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{"reasoning": "Results match expected format and quality"}
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)
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print(f"✅ Agent A: {len(agent_a.get_chain())} actions")
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print(f"✅ Agent B: {len(agent_b.get_chain())} actions")
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print("✅ Both chains independently verifiable\n")
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def example_incident_investigation():
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"""Example: Investigating an incident."""
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print("Example 5: Incident Investigation\n" + "=" * 50)
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chain = create_agent_chain("prod-agent")
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# Simulate an incident
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chain.sign_action(
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"exec",
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{"command": "rm /tmp/important.db", "exit_code": 0},
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{"reasoning": "Cleanup temporary files", "risk_level": "medium"}
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)
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# Later: investigate
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print("Investigating: Why was important.db deleted?")
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print()
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full_chain = chain.get_chain()
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for action in full_chain:
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if "important.db" in json.dumps(action):
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print(f"Found in action at {action['iso_time']}:")
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print(f" Reasoning: {action['context'].get('reasoning')}")
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print(f" Signed by: {action['agent']}")
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print(f" Signature: {action['signature'][:32]}...")
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print()
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print("✅ Cryptographic proof of what happened and why\n")
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if __name__ == "__main__":
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example_file_operations()
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example_api_calls()
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example_decision_making()
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example_multi_agent()
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example_incident_investigation()
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print("=" * 50)
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print("All examples demonstrate:")
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print(" • Cryptographic signing of actions")
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print(" • Context preservation (reasoning)")
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print(" • Independent verification")
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print(" • Audit trail for accountability")
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print("=" * 50)
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