Initial commit: Agent Governance System Phase 8
Phase 8 Production Hardening with complete governance infrastructure: - Vault integration with tiered policies (T0-T4) - DragonflyDB state management - SQLite audit ledger - Pipeline DSL and templates - Promotion/revocation engine - Checkpoint system for session persistence - Health manager and circuit breaker for fault tolerance - GitHub/Slack integrations - Architectural test pipeline with bug watcher, suggestion engine, council review - Multi-agent chaos testing framework Test Results: - Governance tests: 68/68 passing - E2E workflow: 16/16 passing - Phase 2 Vault: 14/14 passing - Integration tests: 27/27 passing Coverage: 57.6% average across 12 phases Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
profit
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# Python-generated files
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__pycache__/
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*.py[oc]
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build/
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dist/
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wheels/
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*.egg-info
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# Virtual environments
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.venv
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3.11
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# Status: Llm Planner
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## Current Phase
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** NOT STARTED**
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## Tasks
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| Status | Task | Updated |
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|--------|------|---------|
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| ☐ | *No tasks defined* | - |
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## Dependencies
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*No external dependencies.*
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## Issues / Blockers
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*No current issues or blockers.*
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## Activity Log
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### 2026-01-23 23:25:09 UTC
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- **Phase**: NOT STARTED
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- **Action**: Initialized
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- **Details**: Status tracking initialized for this directory.
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---
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*Last updated: 2026-01-23 23:25:09 UTC*
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Executable
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#!/usr/bin/env python3
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"""
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LLM Planner Agent - Tier 0 Observer
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====================================
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A compliant agent that uses OpenRouter LLMs for planning tasks.
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Follows the Agent Foundation document constraints.
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Capabilities:
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- Read documentation and inventory from Vault
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- Generate implementation plans using LLM
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- Produce structured, auditable outputs
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- Log all actions to governance ledger
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"""
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import json
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import sqlite3
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import subprocess
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import sys
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from dataclasses import dataclass, field
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from datetime import datetime, timezone
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from enum import Enum
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from typing import Any, Optional
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from openai import OpenAI
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from pydantic import BaseModel, Field
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# =============================================================================
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# Agent Metadata (Section 4 of Foundation Doc)
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# =============================================================================
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AGENT_METADATA = {
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"agent_id": "llm-planner-001",
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"agent_role": "observer",
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"owner": "system",
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"version": "0.1.0",
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"tier": 0,
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"input_contract": "TaskRequest",
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"output_contract": "AgentOutput",
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"allowed_side_effects": [
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"read_docs",
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"read_inventory",
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"read_logs",
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"generate_plan",
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"llm_inference"
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],
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"forbidden_actions": [
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"ssh",
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"create_vm",
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"modify_vm",
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"delete_vm",
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"run_ansible",
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"run_terraform",
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"write_secrets",
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"execute_shell",
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"modify_files"
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],
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"confidence_reporting": True,
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"confidence_threshold": 0.7,
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}
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# =============================================================================
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# Structured Types (Section 6 of Foundation Doc)
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# =============================================================================
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class Decision(str, Enum):
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EXECUTE = "EXECUTE"
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SKIP = "SKIP"
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ESCALATE = "ESCALATE"
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INSUFFICIENT_INFORMATION = "INSUFFICIENT_INFORMATION"
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ERROR = "ERROR"
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class SideEffect(BaseModel):
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type: str
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target: str
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reversible: bool = True
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class ErrorInfo(BaseModel):
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type: str
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message: str
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triggering_input: str
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partial_progress: str
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recommended_action: str
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class AgentOutput(BaseModel):
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"""Required output format per Foundation Doc Section 6"""
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agent_id: str
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version: str
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timestamp: str
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action: str
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decision: Decision
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confidence: float = Field(ge=0.0, le=1.0)
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assumptions: list[str] = []
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dependencies: list[str] = []
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side_effects: list[SideEffect] = []
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notes_for_humans: str = ""
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error: Optional[ErrorInfo] = None
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# Extended fields for LLM agent
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llm_model: Optional[str] = None
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llm_response: Optional[str] = None
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plan: Optional[dict] = None
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class TaskRequest(BaseModel):
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"""Input schema for task requests"""
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task_type: str # e.g., "generate_plan", "analyze", "summarize"
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description: str
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context: dict = {}
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constraints: list[str] = []
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# =============================================================================
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# Vault Integration
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# =============================================================================
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class VaultClient:
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def __init__(self, addr: str = "https://127.0.0.1:8200"):
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self.addr = addr
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self.token = self._load_token()
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def _load_token(self) -> str:
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with open("/opt/vault/init-keys.json") as f:
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return json.load(f)["root_token"]
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def read_secret(self, path: str) -> dict:
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result = subprocess.run([
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"curl", "-sk",
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"-H", f"X-Vault-Token: {self.token}",
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f"{self.addr}/v1/secret/data/{path}"
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], capture_output=True, text=True)
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data = json.loads(result.stdout)
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if "data" in data and "data" in data["data"]:
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return data["data"]["data"]
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raise ValueError(f"Failed to read secret: {path}")
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def get_openrouter_key(self) -> str:
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return self.read_secret("api-keys/openrouter")["api_key"]
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def get_inventory(self) -> dict:
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return self.read_secret("inventory/proxmox")
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def get_docs(self, doc_name: str) -> dict:
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return self.read_secret(f"docs/{doc_name}")
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# =============================================================================
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# Ledger Integration
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# =============================================================================
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class Ledger:
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def __init__(self, db_path: str = "/opt/agent-governance/ledger/governance.db"):
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self.db_path = db_path
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def log_action(self, output: AgentOutput, success: bool):
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conn = sqlite3.connect(self.db_path)
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cursor = conn.cursor()
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cursor.execute("""
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INSERT INTO agent_actions
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(timestamp, agent_id, agent_version, tier, action, decision, confidence,
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success, error_type, error_message)
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VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
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""", (
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output.timestamp,
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output.agent_id,
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output.version,
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AGENT_METADATA["tier"],
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output.action,
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output.decision.value,
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output.confidence,
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1 if success else 0,
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output.error.type if output.error else None,
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output.error.message if output.error else None
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))
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# Update metrics
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cursor.execute("""
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INSERT INTO agent_metrics (agent_id, current_tier, total_runs, last_active_at, compliant_runs, consecutive_compliant)
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VALUES (?, ?, 1, ?, ?, ?)
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ON CONFLICT(agent_id) DO UPDATE SET
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total_runs = total_runs + 1,
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compliant_runs = CASE WHEN ? = 1 THEN compliant_runs + 1 ELSE compliant_runs END,
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consecutive_compliant = CASE WHEN ? = 1 THEN consecutive_compliant + 1 ELSE 0 END,
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last_active_at = ?,
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updated_at = ?
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""", (
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output.agent_id, AGENT_METADATA["tier"], output.timestamp,
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1 if success else 0, 1 if success else 0,
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1 if success else 0, 1 if success else 0,
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output.timestamp, output.timestamp
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))
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conn.commit()
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conn.close()
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# =============================================================================
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# LLM Planner Agent
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# =============================================================================
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class LLMPlannerAgent:
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"""
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Tier 0 Observer Agent with LLM capabilities.
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Invariant: If the agent cannot explain why it took an action,
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that action is invalid. (Foundation Doc Section 1)
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"""
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def __init__(self, model: str = "anthropic/claude-3.5-haiku"):
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self.metadata = AGENT_METADATA
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self.model = model
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self.vault = VaultClient()
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self.ledger = Ledger()
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# Initialize OpenRouter client
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api_key = self.vault.get_openrouter_key()
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self.llm = OpenAI(
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base_url="https://openrouter.ai/api/v1",
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api_key=api_key
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)
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print(f"[INIT] Agent {self.metadata['agent_id']} v{self.metadata['version']} initialized")
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print(f"[INIT] LLM Model: {self.model}")
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print(f"[INIT] Tier: {self.metadata['tier']} ({self.metadata['agent_role']})")
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def _now(self) -> str:
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return datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")
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def _validate_action(self, action: str) -> bool:
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"""Section 3.3: Bounded Authority - validate action is allowed"""
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if action in self.metadata["forbidden_actions"]:
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return False
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if action in self.metadata["allowed_side_effects"]:
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return True
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# Default deny for unknown actions
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return False
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def _create_error_output(self, action: str, error: ErrorInfo) -> AgentOutput:
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return AgentOutput(
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agent_id=self.metadata["agent_id"],
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version=self.metadata["version"],
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timestamp=self._now(),
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action=action,
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decision=Decision.ERROR,
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confidence=0.0,
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error=error,
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notes_for_humans="Action failed - see error details"
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)
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def _check_confidence(self, confidence: float) -> bool:
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"""Section 7: Confidence below threshold = no irreversible actions"""
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return confidence >= self.metadata["confidence_threshold"]
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def generate_plan(self, request: TaskRequest) -> AgentOutput:
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"""Generate an implementation plan using LLM"""
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action = "generate_plan"
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# Validate action is allowed
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if not self._validate_action(action):
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error = ErrorInfo(
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type="FORBIDDEN_ACTION",
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message=f"Action '{action}' is not permitted for this agent",
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triggering_input=request.description,
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partial_progress="None",
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recommended_action="Escalate to higher tier agent"
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)
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output = self._create_error_output(action, error)
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self.ledger.log_action(output, success=False)
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return output
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# Build context from Vault
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try:
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inventory = self.vault.get_inventory()
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context_info = f"Infrastructure: {inventory.get('cluster', 'unknown')} with pools: {inventory.get('pools', 'unknown')}"
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except Exception as e:
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context_info = "Infrastructure context unavailable"
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# Construct prompt
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system_prompt = f"""You are a Tier 0 Observer agent in an infrastructure automation system.
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Your role is to generate implementation plans - you CANNOT execute anything.
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Agent Constraints:
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- You can ONLY generate plans, not execute them
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- Plans must be reversible and include rollback steps
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- You must identify uncertainties and flag them
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- All assumptions must be explicitly stated
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Infrastructure Context:
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{context_info}
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Output your plan as JSON with this structure:
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{{
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"title": "Plan title",
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"summary": "Brief summary",
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"confidence": 0.0-1.0,
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||||
"assumptions": ["assumption 1", "assumption 2"],
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"uncertainties": ["uncertainty 1"],
|
||||
"steps": [
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{{"step": 1, "action": "description", "reversible": true, "rollback": "how to undo"}}
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||||
],
|
||||
"estimated_tier_required": 0-4,
|
||||
"risks": ["risk 1"]
|
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}}"""
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||||
|
||||
user_prompt = f"""Task: {request.description}
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||||
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||||
Additional Context: {json.dumps(request.context) if request.context else 'None'}
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||||
Constraints: {', '.join(request.constraints) if request.constraints else 'None'}
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||||
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||||
Generate a detailed implementation plan."""
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# Call LLM
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try:
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response = self.llm.chat.completions.create(
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model=self.model,
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||||
messages=[
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{"role": "system", "content": system_prompt},
|
||||
{"role": "user", "content": user_prompt}
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||||
],
|
||||
max_tokens=2000,
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||||
temperature=0.3 # Lower temperature for more deterministic planning
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)
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||||
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||||
llm_response = response.choices[0].message.content
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||||
|
||||
# Try to parse the plan JSON
|
||||
try:
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# Extract JSON from response
|
||||
json_start = llm_response.find('{')
|
||||
json_end = llm_response.rfind('}') + 1
|
||||
if json_start >= 0 and json_end > json_start:
|
||||
plan = json.loads(llm_response[json_start:json_end])
|
||||
confidence = plan.get("confidence", 0.5)
|
||||
else:
|
||||
plan = {"raw_response": llm_response}
|
||||
confidence = 0.5
|
||||
except json.JSONDecodeError:
|
||||
plan = {"raw_response": llm_response}
|
||||
confidence = 0.5
|
||||
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||||
# Check confidence threshold
|
||||
decision = Decision.EXECUTE if self._check_confidence(confidence) else Decision.ESCALATE
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||||
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||||
output = AgentOutput(
|
||||
agent_id=self.metadata["agent_id"],
|
||||
version=self.metadata["version"],
|
||||
timestamp=self._now(),
|
||||
action=action,
|
||||
decision=decision,
|
||||
confidence=confidence,
|
||||
assumptions=plan.get("assumptions", []),
|
||||
dependencies=[],
|
||||
side_effects=[
|
||||
SideEffect(type="llm_inference", target=self.model, reversible=True)
|
||||
],
|
||||
notes_for_humans=f"Plan generated. Estimated tier required: {plan.get('estimated_tier_required', 'unknown')}",
|
||||
llm_model=self.model,
|
||||
llm_response=llm_response[:500] + "..." if len(llm_response) > 500 else llm_response,
|
||||
plan=plan
|
||||
)
|
||||
|
||||
self.ledger.log_action(output, success=True)
|
||||
return output
|
||||
|
||||
except Exception as e:
|
||||
error = ErrorInfo(
|
||||
type="LLM_ERROR",
|
||||
message=str(e),
|
||||
triggering_input=request.description,
|
||||
partial_progress="Context loaded, LLM call failed",
|
||||
recommended_action="Check API key and connectivity"
|
||||
)
|
||||
output = self._create_error_output(action, error)
|
||||
self.ledger.log_action(output, success=False)
|
||||
return output
|
||||
|
||||
def analyze(self, request: TaskRequest) -> AgentOutput:
|
||||
"""Analyze a topic and provide insights"""
|
||||
action = "read_docs" # Analysis is a form of reading
|
||||
|
||||
if not self._validate_action(action):
|
||||
error = ErrorInfo(
|
||||
type="FORBIDDEN_ACTION",
|
||||
message=f"Action '{action}' is not permitted",
|
||||
triggering_input=request.description,
|
||||
partial_progress="None",
|
||||
recommended_action="Check agent permissions"
|
||||
)
|
||||
output = self._create_error_output(action, error)
|
||||
self.ledger.log_action(output, success=False)
|
||||
return output
|
||||
|
||||
try:
|
||||
response = self.llm.chat.completions.create(
|
||||
model=self.model,
|
||||
messages=[
|
||||
{"role": "system", "content": "You are a technical analyst. Provide clear, structured analysis. Be explicit about uncertainties."},
|
||||
{"role": "user", "content": request.description}
|
||||
],
|
||||
max_tokens=1500,
|
||||
temperature=0.4
|
||||
)
|
||||
|
||||
llm_response = response.choices[0].message.content
|
||||
|
||||
output = AgentOutput(
|
||||
agent_id=self.metadata["agent_id"],
|
||||
version=self.metadata["version"],
|
||||
timestamp=self._now(),
|
||||
action=action,
|
||||
decision=Decision.EXECUTE,
|
||||
confidence=0.8,
|
||||
assumptions=["Analysis based on provided context only"],
|
||||
dependencies=[],
|
||||
side_effects=[
|
||||
SideEffect(type="llm_inference", target=self.model, reversible=True)
|
||||
],
|
||||
notes_for_humans="Analysis complete",
|
||||
llm_model=self.model,
|
||||
llm_response=llm_response
|
||||
)
|
||||
|
||||
self.ledger.log_action(output, success=True)
|
||||
return output
|
||||
|
||||
except Exception as e:
|
||||
error = ErrorInfo(
|
||||
type="LLM_ERROR",
|
||||
message=str(e),
|
||||
triggering_input=request.description,
|
||||
partial_progress="None",
|
||||
recommended_action="Retry or check connectivity"
|
||||
)
|
||||
output = self._create_error_output(action, error)
|
||||
self.ledger.log_action(output, success=False)
|
||||
return output
|
||||
|
||||
def run(self, request: TaskRequest) -> AgentOutput:
|
||||
"""Main entry point - routes to appropriate handler"""
|
||||
print(f"\n[TASK] Received: {request.task_type}")
|
||||
print(f"[TASK] Description: {request.description[:100]}...")
|
||||
|
||||
handlers = {
|
||||
"generate_plan": self.generate_plan,
|
||||
"plan": self.generate_plan,
|
||||
"analyze": self.analyze,
|
||||
"analysis": self.analyze,
|
||||
}
|
||||
|
||||
handler = handlers.get(request.task_type)
|
||||
if handler:
|
||||
return handler(request)
|
||||
|
||||
# Unknown task type
|
||||
error = ErrorInfo(
|
||||
type="UNKNOWN_TASK_TYPE",
|
||||
message=f"Unknown task type: {request.task_type}",
|
||||
triggering_input=json.dumps(request.model_dump()),
|
||||
partial_progress="None",
|
||||
recommended_action=f"Use one of: {list(handlers.keys())}"
|
||||
)
|
||||
output = self._create_error_output(request.task_type, error)
|
||||
self.ledger.log_action(output, success=False)
|
||||
return output
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# CLI Interface
|
||||
# =============================================================================
|
||||
|
||||
def main():
|
||||
import argparse
|
||||
|
||||
parser = argparse.ArgumentParser(description="LLM Planner Agent")
|
||||
parser.add_argument("task_type", choices=["plan", "analyze"], help="Type of task")
|
||||
parser.add_argument("description", help="Task description")
|
||||
parser.add_argument("--model", default="anthropic/claude-3.5-haiku", help="OpenRouter model")
|
||||
parser.add_argument("--json", action="store_true", help="Output raw JSON")
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
agent = LLMPlannerAgent(model=args.model)
|
||||
|
||||
request = TaskRequest(
|
||||
task_type=args.task_type,
|
||||
description=args.description
|
||||
)
|
||||
|
||||
output = agent.run(request)
|
||||
|
||||
if args.json:
|
||||
print(output.model_dump_json(indent=2))
|
||||
else:
|
||||
print("\n" + "="*60)
|
||||
print(f"Decision: {output.decision.value}")
|
||||
print(f"Confidence: {output.confidence}")
|
||||
print(f"Model: {output.llm_model}")
|
||||
print("="*60)
|
||||
|
||||
if output.plan:
|
||||
print("\n📋 PLAN:")
|
||||
print(json.dumps(output.plan, indent=2))
|
||||
elif output.llm_response:
|
||||
print("\n📝 RESPONSE:")
|
||||
print(output.llm_response)
|
||||
|
||||
if output.error:
|
||||
print("\n❌ ERROR:")
|
||||
print(f" Type: {output.error.type}")
|
||||
print(f" Message: {output.error.message}")
|
||||
print(f" Recommendation: {output.error.recommended_action}")
|
||||
|
||||
if output.assumptions:
|
||||
print("\n⚠️ ASSUMPTIONS:")
|
||||
for a in output.assumptions:
|
||||
print(f" - {a}")
|
||||
|
||||
print("\n" + "="*60)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Executable
+736
@@ -0,0 +1,736 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Agent Runtime Governance via DragonflyDB
|
||||
=========================================
|
||||
Implements real-time agent control: instruction packets, state tracking,
|
||||
error budgets, revocation, and handoffs.
|
||||
"""
|
||||
|
||||
import json
|
||||
import hashlib
|
||||
import time
|
||||
from dataclasses import dataclass, field, asdict
|
||||
from datetime import datetime, timezone
|
||||
from enum import Enum
|
||||
from typing import Any, Optional
|
||||
import redis
|
||||
import subprocess
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Configuration
|
||||
# =============================================================================
|
||||
|
||||
def get_dragonfly_client() -> redis.Redis:
|
||||
"""Get DragonflyDB client with credentials from Vault"""
|
||||
# Get credentials from Vault
|
||||
with open("/opt/vault/init-keys.json") as f:
|
||||
token = json.load(f)["root_token"]
|
||||
|
||||
result = subprocess.run([
|
||||
"curl", "-sk",
|
||||
"-H", f"X-Vault-Token: {token}",
|
||||
"https://127.0.0.1:8200/v1/secret/data/services/dragonfly"
|
||||
], capture_output=True, text=True)
|
||||
|
||||
creds = json.loads(result.stdout)["data"]["data"]
|
||||
|
||||
return redis.Redis(
|
||||
host=creds["host"],
|
||||
port=int(creds["port"]),
|
||||
password=creds["password"],
|
||||
decode_responses=True
|
||||
)
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Enums and Types
|
||||
# =============================================================================
|
||||
|
||||
class AgentPhase(str, Enum):
|
||||
BOOTSTRAP = "BOOTSTRAP"
|
||||
PREFLIGHT = "PREFLIGHT"
|
||||
PLAN = "PLAN"
|
||||
EXECUTE = "EXECUTE"
|
||||
VERIFY = "VERIFY"
|
||||
PACKAGE = "PACKAGE"
|
||||
REPORT = "REPORT"
|
||||
EXIT = "EXIT"
|
||||
REVOKED = "REVOKED"
|
||||
|
||||
|
||||
class AgentStatus(str, Enum):
|
||||
PENDING = "PENDING"
|
||||
RUNNING = "RUNNING"
|
||||
PAUSED = "PAUSED"
|
||||
COMPLETED = "COMPLETED"
|
||||
REVOKED = "REVOKED"
|
||||
FAILED = "FAILED"
|
||||
|
||||
|
||||
class RevocationType(str, Enum):
|
||||
ERROR_BUDGET_EXCEEDED = "ERROR_BUDGET_EXCEEDED"
|
||||
PROCEDURE_VIOLATION = "PROCEDURE_VIOLATION"
|
||||
FORBIDDEN_ACTION = "FORBIDDEN_ACTION"
|
||||
HEARTBEAT_TIMEOUT = "HEARTBEAT_TIMEOUT"
|
||||
LOCK_EXPIRED = "LOCK_EXPIRED"
|
||||
MANUAL = "MANUAL"
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Data Classes
|
||||
# =============================================================================
|
||||
|
||||
@dataclass
|
||||
class ErrorBudget:
|
||||
max_total_errors: int = 12
|
||||
max_same_error_repeats: int = 3
|
||||
max_procedure_violations: int = 1
|
||||
|
||||
|
||||
@dataclass
|
||||
class InstructionPacket:
|
||||
agent_id: str
|
||||
task_id: str
|
||||
created_for: str
|
||||
objective: str
|
||||
deliverables: list[str]
|
||||
constraints: dict
|
||||
success_criteria: list[str]
|
||||
error_budget: ErrorBudget
|
||||
escalation_rules: list[str]
|
||||
repo: str = ""
|
||||
pr_context: dict = field(default_factory=dict)
|
||||
revocation_context: dict = field(default_factory=dict)
|
||||
created_at: str = ""
|
||||
|
||||
def __post_init__(self):
|
||||
if not self.created_at:
|
||||
self.created_at = datetime.now(timezone.utc).isoformat()
|
||||
if isinstance(self.error_budget, dict):
|
||||
self.error_budget = ErrorBudget(**self.error_budget)
|
||||
|
||||
def to_dict(self) -> dict:
|
||||
d = asdict(self)
|
||||
d["error_budget"] = asdict(self.error_budget)
|
||||
return d
|
||||
|
||||
|
||||
@dataclass
|
||||
class AgentState:
|
||||
agent_id: str
|
||||
status: AgentStatus
|
||||
phase: AgentPhase
|
||||
step: str = ""
|
||||
started_at: str = ""
|
||||
last_progress_at: str = ""
|
||||
current_pr: Optional[int] = None
|
||||
notes: str = ""
|
||||
|
||||
def to_dict(self) -> dict:
|
||||
return {
|
||||
"agent_id": self.agent_id,
|
||||
"status": self.status.value,
|
||||
"phase": self.phase.value,
|
||||
"step": self.step,
|
||||
"started_at": self.started_at,
|
||||
"last_progress_at": self.last_progress_at,
|
||||
"current_pr": self.current_pr,
|
||||
"notes": self.notes
|
||||
}
|
||||
|
||||
|
||||
@dataclass
|
||||
class HandoffObject:
|
||||
task_id: str
|
||||
previous_agent_id: str
|
||||
revoked: bool
|
||||
revocation_reason: dict
|
||||
last_known_state: dict
|
||||
what_was_tried: list[str]
|
||||
blocking_issue: str
|
||||
required_next_actions: list[str]
|
||||
constraints_reminder: list[str]
|
||||
artifacts: list[str]
|
||||
created_at: str = ""
|
||||
|
||||
def __post_init__(self):
|
||||
if not self.created_at:
|
||||
self.created_at = datetime.now(timezone.utc).isoformat()
|
||||
|
||||
def to_dict(self) -> dict:
|
||||
return asdict(self)
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Governance Manager
|
||||
# =============================================================================
|
||||
|
||||
class GovernanceManager:
|
||||
"""
|
||||
Core runtime governance via DragonflyDB.
|
||||
Manages instruction packets, state, errors, locks, and handoffs.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
self.db = get_dragonfly_client()
|
||||
self.lock_ttl = 300 # 5 minutes default lock TTL
|
||||
self.heartbeat_ttl = 60 # 1 minute heartbeat timeout
|
||||
|
||||
def _now(self) -> str:
|
||||
return datetime.now(timezone.utc).isoformat()
|
||||
|
||||
def _error_signature(self, error_type: str, message: str) -> str:
|
||||
"""Generate a normalized error signature"""
|
||||
normalized = f"{error_type}:{message[:100]}".lower()
|
||||
return hashlib.md5(normalized.encode()).hexdigest()[:12]
|
||||
|
||||
# -------------------------------------------------------------------------
|
||||
# Instruction Packets
|
||||
# -------------------------------------------------------------------------
|
||||
|
||||
def create_instruction_packet(self, packet: InstructionPacket) -> bool:
|
||||
"""Store an instruction packet for an agent"""
|
||||
key = f"agent:{packet.agent_id}:packet"
|
||||
return self.db.set(key, json.dumps(packet.to_dict()))
|
||||
|
||||
def get_instruction_packet(self, agent_id: str) -> Optional[InstructionPacket]:
|
||||
"""Retrieve an agent's instruction packet"""
|
||||
key = f"agent:{agent_id}:packet"
|
||||
data = self.db.get(key)
|
||||
if data:
|
||||
return InstructionPacket(**json.loads(data))
|
||||
return None
|
||||
|
||||
# -------------------------------------------------------------------------
|
||||
# Agent State
|
||||
# -------------------------------------------------------------------------
|
||||
|
||||
def set_agent_state(self, state: AgentState) -> bool:
|
||||
"""Update agent's runtime state"""
|
||||
state.last_progress_at = self._now()
|
||||
key = f"agent:{state.agent_id}:state"
|
||||
return self.db.set(key, json.dumps(state.to_dict()))
|
||||
|
||||
def get_agent_state(self, agent_id: str) -> Optional[AgentState]:
|
||||
"""Get agent's current state"""
|
||||
key = f"agent:{agent_id}:state"
|
||||
data = self.db.get(key)
|
||||
if data:
|
||||
d = json.loads(data)
|
||||
return AgentState(
|
||||
agent_id=d["agent_id"],
|
||||
status=AgentStatus(d["status"]),
|
||||
phase=AgentPhase(d["phase"]),
|
||||
step=d.get("step", ""),
|
||||
started_at=d.get("started_at", ""),
|
||||
last_progress_at=d.get("last_progress_at", ""),
|
||||
current_pr=d.get("current_pr"),
|
||||
notes=d.get("notes", "")
|
||||
)
|
||||
return None
|
||||
|
||||
def transition_phase(self, agent_id: str, phase: AgentPhase, step: str = "", notes: str = "") -> bool:
|
||||
"""Transition agent to a new phase"""
|
||||
state = self.get_agent_state(agent_id)
|
||||
if not state:
|
||||
return False
|
||||
|
||||
state.phase = phase
|
||||
state.step = step
|
||||
state.notes = notes
|
||||
return self.set_agent_state(state)
|
||||
|
||||
# -------------------------------------------------------------------------
|
||||
# Locking
|
||||
# -------------------------------------------------------------------------
|
||||
|
||||
def acquire_lock(self, agent_id: str, ttl: int = None) -> bool:
|
||||
"""Acquire execution lock for an agent"""
|
||||
key = f"agent:{agent_id}:lock"
|
||||
ttl = ttl or self.lock_ttl
|
||||
# NX = only set if not exists
|
||||
return self.db.set(key, self._now(), nx=True, ex=ttl)
|
||||
|
||||
def refresh_lock(self, agent_id: str, ttl: int = None) -> bool:
|
||||
"""Refresh an existing lock"""
|
||||
key = f"agent:{agent_id}:lock"
|
||||
ttl = ttl or self.lock_ttl
|
||||
if self.db.exists(key):
|
||||
return self.db.expire(key, ttl)
|
||||
return False
|
||||
|
||||
def release_lock(self, agent_id: str) -> bool:
|
||||
"""Release execution lock"""
|
||||
key = f"agent:{agent_id}:lock"
|
||||
return self.db.delete(key) > 0
|
||||
|
||||
def has_lock(self, agent_id: str) -> bool:
|
||||
"""Check if agent has a valid lock"""
|
||||
key = f"agent:{agent_id}:lock"
|
||||
return self.db.exists(key)
|
||||
|
||||
# -------------------------------------------------------------------------
|
||||
# Heartbeat
|
||||
# -------------------------------------------------------------------------
|
||||
|
||||
def heartbeat(self, agent_id: str) -> bool:
|
||||
"""Update agent heartbeat"""
|
||||
key = f"agent:{agent_id}:heartbeat"
|
||||
return self.db.set(key, self._now(), ex=self.heartbeat_ttl)
|
||||
|
||||
def is_alive(self, agent_id: str) -> bool:
|
||||
"""Check if agent heartbeat is fresh"""
|
||||
key = f"agent:{agent_id}:heartbeat"
|
||||
return self.db.exists(key)
|
||||
|
||||
# -------------------------------------------------------------------------
|
||||
# Error Tracking
|
||||
# -------------------------------------------------------------------------
|
||||
|
||||
def record_error(self, agent_id: str, error_type: str, message: str) -> dict:
|
||||
"""Record an error and return current counts"""
|
||||
key = f"agent:{agent_id}:errors"
|
||||
sig = self._error_signature(error_type, message)
|
||||
|
||||
pipe = self.db.pipeline()
|
||||
pipe.hincrby(key, "total_errors", 1)
|
||||
pipe.hincrby(key, f"same_error:{sig}", 1)
|
||||
pipe.hset(key, "last_error_signature", sig)
|
||||
pipe.hset(key, "last_error_at", self._now())
|
||||
pipe.hset(key, "last_error_type", error_type)
|
||||
pipe.hset(key, "last_error_message", message[:500])
|
||||
pipe.execute()
|
||||
|
||||
return self.get_error_counts(agent_id)
|
||||
|
||||
def record_procedure_violation(self, agent_id: str, violation: str) -> int:
|
||||
"""Record a procedure violation"""
|
||||
key = f"agent:{agent_id}:errors"
|
||||
self.db.hset(key, "last_violation", violation)
|
||||
self.db.hset(key, "last_violation_at", self._now())
|
||||
return self.db.hincrby(key, "procedure_violations", 1)
|
||||
|
||||
def get_error_counts(self, agent_id: str) -> dict:
|
||||
"""Get all error counts for an agent"""
|
||||
key = f"agent:{agent_id}:errors"
|
||||
data = self.db.hgetall(key)
|
||||
return {
|
||||
"total_errors": int(data.get("total_errors", 0)),
|
||||
"procedure_violations": int(data.get("procedure_violations", 0)),
|
||||
"last_error_signature": data.get("last_error_signature", ""),
|
||||
"last_error_at": data.get("last_error_at", ""),
|
||||
"last_error_type": data.get("last_error_type", ""),
|
||||
"same_error_counts": {
|
||||
k.replace("same_error:", ""): int(v)
|
||||
for k, v in data.items()
|
||||
if k.startswith("same_error:")
|
||||
}
|
||||
}
|
||||
|
||||
def check_error_budget(self, agent_id: str) -> tuple[bool, Optional[str]]:
|
||||
"""Check if error budget is exceeded. Returns (ok, reason)"""
|
||||
packet = self.get_instruction_packet(agent_id)
|
||||
if not packet:
|
||||
return False, "NO_INSTRUCTION_PACKET"
|
||||
|
||||
counts = self.get_error_counts(agent_id)
|
||||
budget = packet.error_budget
|
||||
|
||||
# Check procedure violations
|
||||
if counts["procedure_violations"] >= budget.max_procedure_violations:
|
||||
return False, f"PROCEDURE_VIOLATIONS ({counts['procedure_violations']} >= {budget.max_procedure_violations})"
|
||||
|
||||
# Check total errors
|
||||
if counts["total_errors"] >= budget.max_total_errors:
|
||||
return False, f"TOTAL_ERRORS ({counts['total_errors']} >= {budget.max_total_errors})"
|
||||
|
||||
# Check same error repeats
|
||||
for sig, count in counts["same_error_counts"].items():
|
||||
if count >= budget.max_same_error_repeats:
|
||||
return False, f"SAME_ERROR_REPEATED ({sig}: {count} >= {budget.max_same_error_repeats})"
|
||||
|
||||
return True, None
|
||||
|
||||
# -------------------------------------------------------------------------
|
||||
# Task Management
|
||||
# -------------------------------------------------------------------------
|
||||
|
||||
def assign_agent_to_task(self, task_id: str, agent_id: str) -> bool:
|
||||
"""Assign an agent to a task"""
|
||||
# Set active agent
|
||||
self.db.set(f"task:{task_id}:active_agent", agent_id)
|
||||
# Add to history
|
||||
self.db.rpush(f"task:{task_id}:history", json.dumps({
|
||||
"agent_id": agent_id,
|
||||
"assigned_at": self._now(),
|
||||
"event": "ASSIGNED"
|
||||
}))
|
||||
return True
|
||||
|
||||
def get_active_agent(self, task_id: str) -> Optional[str]:
|
||||
"""Get the currently active agent for a task"""
|
||||
return self.db.get(f"task:{task_id}:active_agent")
|
||||
|
||||
def get_task_history(self, task_id: str) -> list[dict]:
|
||||
"""Get task agent history"""
|
||||
data = self.db.lrange(f"task:{task_id}:history", 0, -1)
|
||||
return [json.loads(d) for d in data]
|
||||
|
||||
# -------------------------------------------------------------------------
|
||||
# Revocation
|
||||
# -------------------------------------------------------------------------
|
||||
|
||||
def revoke_agent(self, agent_id: str, reason_type: RevocationType, details: str) -> bool:
|
||||
"""Revoke an agent's access"""
|
||||
# Update state
|
||||
state = self.get_agent_state(agent_id)
|
||||
if state:
|
||||
state.status = AgentStatus.REVOKED
|
||||
state.phase = AgentPhase.REVOKED
|
||||
state.notes = f"Revoked: {reason_type.value} - {details}"
|
||||
self.set_agent_state(state)
|
||||
|
||||
# Release lock
|
||||
self.release_lock(agent_id)
|
||||
|
||||
# Write to revocation ledger
|
||||
revocation_event = {
|
||||
"agent_id": agent_id,
|
||||
"reason_type": reason_type.value,
|
||||
"details": details,
|
||||
"revoked_at": self._now()
|
||||
}
|
||||
self.db.rpush("revocations:ledger", json.dumps(revocation_event))
|
||||
|
||||
# Add to task history if we know the task
|
||||
packet = self.get_instruction_packet(agent_id)
|
||||
if packet:
|
||||
self.db.rpush(f"task:{packet.task_id}:history", json.dumps({
|
||||
"agent_id": agent_id,
|
||||
"event": "REVOKED",
|
||||
"reason": reason_type.value,
|
||||
"revoked_at": self._now()
|
||||
}))
|
||||
|
||||
return True
|
||||
|
||||
def get_recent_revocations(self, count: int = 50) -> list[dict]:
|
||||
"""Get recent revocation events"""
|
||||
data = self.db.lrange("revocations:ledger", -count, -1)
|
||||
return [json.loads(d) for d in data]
|
||||
|
||||
# -------------------------------------------------------------------------
|
||||
# Handoff
|
||||
# -------------------------------------------------------------------------
|
||||
|
||||
def create_handoff(self, handoff: HandoffObject) -> bool:
|
||||
"""Create a handoff object for task continuity"""
|
||||
key = f"handoff:{handoff.task_id}:latest"
|
||||
return self.db.set(key, json.dumps(handoff.to_dict()))
|
||||
|
||||
def get_handoff(self, task_id: str) -> Optional[HandoffObject]:
|
||||
"""Get the latest handoff for a task"""
|
||||
key = f"handoff:{task_id}:latest"
|
||||
data = self.db.get(key)
|
||||
if data:
|
||||
return HandoffObject(**json.loads(data))
|
||||
return None
|
||||
|
||||
# -------------------------------------------------------------------------
|
||||
# Artifacts
|
||||
# -------------------------------------------------------------------------
|
||||
|
||||
def register_artifact(self, task_id: str, artifact_type: str, reference: str) -> bool:
|
||||
"""Register an artifact for a task"""
|
||||
key = f"task:{task_id}:artifacts"
|
||||
artifact = {
|
||||
"type": artifact_type,
|
||||
"reference": reference,
|
||||
"created_at": self._now()
|
||||
}
|
||||
self.db.rpush(key, json.dumps(artifact))
|
||||
return True
|
||||
|
||||
def get_artifacts(self, task_id: str) -> list[dict]:
|
||||
"""Get all artifacts for a task"""
|
||||
key = f"task:{task_id}:artifacts"
|
||||
data = self.db.lrange(key, 0, -1)
|
||||
return [json.loads(d) for d in data]
|
||||
|
||||
def has_required_artifact(self, task_id: str, artifact_type: str) -> bool:
|
||||
"""Check if a required artifact exists"""
|
||||
artifacts = self.get_artifacts(task_id)
|
||||
return any(a["type"] == artifact_type for a in artifacts)
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Worker Agent Runtime
|
||||
# =============================================================================
|
||||
|
||||
class WorkerRuntime:
|
||||
"""
|
||||
Runtime for worker agents.
|
||||
Handles bootstrap, state transitions, error reporting, and compliance.
|
||||
"""
|
||||
|
||||
def __init__(self, agent_id: str):
|
||||
self.agent_id = agent_id
|
||||
self.gov = GovernanceManager()
|
||||
self.packet: Optional[InstructionPacket] = None
|
||||
self.state: Optional[AgentState] = None
|
||||
|
||||
def bootstrap(self) -> tuple[bool, str]:
|
||||
"""
|
||||
Bootstrap the agent runtime.
|
||||
Returns (success, message)
|
||||
"""
|
||||
# Step 1: Read revocation ledger
|
||||
revocations = self.gov.get_recent_revocations(50)
|
||||
if revocations:
|
||||
print(f"[BOOTSTRAP] Read {len(revocations)} recent revocations")
|
||||
# Check if this agent was previously revoked
|
||||
for rev in revocations:
|
||||
if rev["agent_id"] == self.agent_id:
|
||||
return False, f"AGENT_PREVIOUSLY_REVOKED: {rev['reason_type']}"
|
||||
|
||||
# Step 2: Read instruction packet
|
||||
self.packet = self.gov.get_instruction_packet(self.agent_id)
|
||||
if not self.packet:
|
||||
return False, "NO_INSTRUCTION_PACKET"
|
||||
|
||||
print(f"[BOOTSTRAP] Loaded instruction packet for task: {self.packet.task_id}")
|
||||
|
||||
# Step 3: Check for existing handoff
|
||||
handoff = self.gov.get_handoff(self.packet.task_id)
|
||||
if handoff and handoff.previous_agent_id != self.agent_id:
|
||||
print(f"[BOOTSTRAP] Found handoff from previous agent: {handoff.previous_agent_id}")
|
||||
print(f"[BOOTSTRAP] Revocation reason: {handoff.revocation_reason}")
|
||||
print(f"[BOOTSTRAP] Required next actions: {handoff.required_next_actions}")
|
||||
|
||||
# Step 4: Acquire lock
|
||||
if not self.gov.acquire_lock(self.agent_id):
|
||||
return False, "CANNOT_ACQUIRE_LOCK"
|
||||
|
||||
# Step 5: Initialize state
|
||||
self.state = AgentState(
|
||||
agent_id=self.agent_id,
|
||||
status=AgentStatus.RUNNING,
|
||||
phase=AgentPhase.BOOTSTRAP,
|
||||
step="initialized",
|
||||
started_at=datetime.now(timezone.utc).isoformat()
|
||||
)
|
||||
self.gov.set_agent_state(self.state)
|
||||
|
||||
# Step 6: Start heartbeat
|
||||
self.gov.heartbeat(self.agent_id)
|
||||
|
||||
# Step 7: Assign to task
|
||||
self.gov.assign_agent_to_task(self.packet.task_id, self.agent_id)
|
||||
|
||||
return True, "BOOTSTRAP_COMPLETE"
|
||||
|
||||
def transition(self, phase: AgentPhase, step: str = "", notes: str = "") -> bool:
|
||||
"""Transition to a new phase"""
|
||||
if not self.state:
|
||||
return False
|
||||
|
||||
# Refresh heartbeat and lock
|
||||
self.gov.heartbeat(self.agent_id)
|
||||
self.gov.refresh_lock(self.agent_id)
|
||||
|
||||
# Check error budget before transition
|
||||
ok, reason = self.gov.check_error_budget(self.agent_id)
|
||||
if not ok:
|
||||
self.gov.revoke_agent(self.agent_id, RevocationType.ERROR_BUDGET_EXCEEDED, reason)
|
||||
return False
|
||||
|
||||
# Update state
|
||||
self.state.phase = phase
|
||||
self.state.step = step
|
||||
self.state.notes = notes
|
||||
self.gov.set_agent_state(self.state)
|
||||
|
||||
print(f"[PHASE] {phase.value} - {step}")
|
||||
return True
|
||||
|
||||
def report_error(self, error_type: str, message: str) -> bool:
|
||||
"""Report an error and check if we should continue"""
|
||||
counts = self.gov.record_error(self.agent_id, error_type, message)
|
||||
print(f"[ERROR] {error_type}: {message}")
|
||||
print(f"[ERROR] Counts: total={counts['total_errors']}, violations={counts['procedure_violations']}")
|
||||
|
||||
ok, reason = self.gov.check_error_budget(self.agent_id)
|
||||
if not ok:
|
||||
print(f"[REVOKE] Error budget exceeded: {reason}")
|
||||
self.gov.revoke_agent(self.agent_id, RevocationType.ERROR_BUDGET_EXCEEDED, reason)
|
||||
return False
|
||||
|
||||
return True
|
||||
|
||||
def report_violation(self, violation: str) -> bool:
|
||||
"""Report a procedure violation"""
|
||||
count = self.gov.record_procedure_violation(self.agent_id, violation)
|
||||
print(f"[VIOLATION] {violation} (count: {count})")
|
||||
|
||||
ok, reason = self.gov.check_error_budget(self.agent_id)
|
||||
if not ok:
|
||||
print(f"[REVOKE] Procedure violation limit: {reason}")
|
||||
self.gov.revoke_agent(self.agent_id, RevocationType.PROCEDURE_VIOLATION, reason)
|
||||
return False
|
||||
|
||||
return True
|
||||
|
||||
def register_artifact(self, artifact_type: str, reference: str):
|
||||
"""Register a work artifact"""
|
||||
if self.packet:
|
||||
self.gov.register_artifact(self.packet.task_id, artifact_type, reference)
|
||||
print(f"[ARTIFACT] Registered: {artifact_type} -> {reference}")
|
||||
|
||||
def complete(self, notes: str = "") -> bool:
|
||||
"""Mark work as complete"""
|
||||
if self.state:
|
||||
self.state.status = AgentStatus.COMPLETED
|
||||
self.state.phase = AgentPhase.EXIT
|
||||
self.state.notes = notes
|
||||
self.gov.set_agent_state(self.state)
|
||||
|
||||
self.gov.release_lock(self.agent_id)
|
||||
print(f"[COMPLETE] {notes}")
|
||||
return True
|
||||
|
||||
def create_handoff(self, blocking_issue: str, what_was_tried: list[str],
|
||||
required_next_actions: list[str]) -> bool:
|
||||
"""Create a handoff for the next agent"""
|
||||
if not self.packet or not self.state:
|
||||
return False
|
||||
|
||||
handoff = HandoffObject(
|
||||
task_id=self.packet.task_id,
|
||||
previous_agent_id=self.agent_id,
|
||||
revoked=self.state.status == AgentStatus.REVOKED,
|
||||
revocation_reason={
|
||||
"type": self.state.status.value,
|
||||
"details": self.state.notes
|
||||
},
|
||||
last_known_state={
|
||||
"phase": self.state.phase.value,
|
||||
"step": self.state.step
|
||||
},
|
||||
what_was_tried=what_was_tried,
|
||||
blocking_issue=blocking_issue,
|
||||
required_next_actions=required_next_actions,
|
||||
constraints_reminder=self.packet.constraints.get("forbidden", []),
|
||||
artifacts=[a["reference"] for a in self.gov.get_artifacts(self.packet.task_id)]
|
||||
)
|
||||
|
||||
return self.gov.create_handoff(handoff)
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# CLI
|
||||
# =============================================================================
|
||||
|
||||
if __name__ == "__main__":
|
||||
import sys
|
||||
|
||||
gov = GovernanceManager()
|
||||
|
||||
if len(sys.argv) < 2:
|
||||
print("Usage: governance.py <command> [args]")
|
||||
print("Commands:")
|
||||
print(" create-packet <agent_id> <task_id> <objective>")
|
||||
print(" get-state <agent_id>")
|
||||
print(" get-errors <agent_id>")
|
||||
print(" revocations")
|
||||
print(" test")
|
||||
sys.exit(1)
|
||||
|
||||
cmd = sys.argv[1]
|
||||
|
||||
if cmd == "create-packet":
|
||||
agent_id, task_id, objective = sys.argv[2], sys.argv[3], sys.argv[4]
|
||||
packet = InstructionPacket(
|
||||
agent_id=agent_id,
|
||||
task_id=task_id,
|
||||
created_for="CLI test",
|
||||
objective=objective,
|
||||
deliverables=["plan artifacts", "run logs"],
|
||||
constraints={
|
||||
"scope": ["sandbox only"],
|
||||
"forbidden": ["no prod access", "no unrecorded root"],
|
||||
"required_steps": ["plan before apply"]
|
||||
},
|
||||
success_criteria=["CI passes", "artifacts uploaded"],
|
||||
error_budget=ErrorBudget(),
|
||||
escalation_rules=["If blocked > 20m -> escalate"]
|
||||
)
|
||||
gov.create_instruction_packet(packet)
|
||||
print(f"Created packet for {agent_id}")
|
||||
|
||||
elif cmd == "get-state":
|
||||
agent_id = sys.argv[2]
|
||||
state = gov.get_agent_state(agent_id)
|
||||
if state:
|
||||
print(json.dumps(state.to_dict(), indent=2))
|
||||
else:
|
||||
print("No state found")
|
||||
|
||||
elif cmd == "get-errors":
|
||||
agent_id = sys.argv[2]
|
||||
errors = gov.get_error_counts(agent_id)
|
||||
print(json.dumps(errors, indent=2))
|
||||
|
||||
elif cmd == "revocations":
|
||||
revs = gov.get_recent_revocations()
|
||||
for r in revs:
|
||||
print(json.dumps(r))
|
||||
|
||||
elif cmd == "test":
|
||||
print("=== Testing Governance System ===\n")
|
||||
|
||||
# Create test packet
|
||||
packet = InstructionPacket(
|
||||
agent_id="test-agent-001",
|
||||
task_id="test-task-001",
|
||||
created_for="Governance test",
|
||||
objective="Test the governance system",
|
||||
deliverables=["test output"],
|
||||
constraints={
|
||||
"scope": ["sandbox"],
|
||||
"forbidden": ["prod access"],
|
||||
"required_steps": ["plan first"]
|
||||
},
|
||||
success_criteria=["test passes"],
|
||||
error_budget=ErrorBudget(max_total_errors=5, max_same_error_repeats=2),
|
||||
escalation_rules=[]
|
||||
)
|
||||
gov.create_instruction_packet(packet)
|
||||
print("[OK] Created instruction packet")
|
||||
|
||||
# Test worker runtime
|
||||
worker = WorkerRuntime("test-agent-001")
|
||||
ok, msg = worker.bootstrap()
|
||||
print(f"[OK] Bootstrap: {msg}")
|
||||
|
||||
# Simulate work phases
|
||||
worker.transition(AgentPhase.PREFLIGHT, "scope_check")
|
||||
worker.transition(AgentPhase.PLAN, "generating_plan")
|
||||
worker.register_artifact("plan", "plan_output_001")
|
||||
worker.transition(AgentPhase.EXECUTE, "applying")
|
||||
|
||||
# Simulate some errors
|
||||
worker.report_error("VALIDATION_ERROR", "Variable not defined")
|
||||
worker.report_error("VALIDATION_ERROR", "Variable not defined") # Same error
|
||||
|
||||
# Check error budget
|
||||
ok, reason = gov.check_error_budget("test-agent-001")
|
||||
print(f"[OK] Error budget check: ok={ok}, reason={reason}")
|
||||
|
||||
# Complete
|
||||
worker.complete("Test completed successfully")
|
||||
|
||||
print("\n=== Test Complete ===")
|
||||
|
||||
else:
|
||||
print(f"Unknown command: {cmd}")
|
||||
Executable
+397
@@ -0,0 +1,397 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Governed LLM Agent
|
||||
==================
|
||||
An LLM-powered agent that operates under the governance runtime.
|
||||
Combines planning capabilities with full governance compliance.
|
||||
"""
|
||||
|
||||
import json
|
||||
import sys
|
||||
from datetime import datetime, timezone
|
||||
from typing import Optional
|
||||
|
||||
from openai import OpenAI
|
||||
from pydantic import BaseModel
|
||||
|
||||
from governance import (
|
||||
GovernanceManager,
|
||||
WorkerRuntime,
|
||||
InstructionPacket,
|
||||
ErrorBudget,
|
||||
AgentPhase,
|
||||
AgentStatus,
|
||||
)
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Configuration
|
||||
# =============================================================================
|
||||
|
||||
def get_openrouter_client() -> OpenAI:
|
||||
"""Get OpenRouter client with API key from Vault"""
|
||||
import subprocess
|
||||
with open("/opt/vault/init-keys.json") as f:
|
||||
token = json.load(f)["root_token"]
|
||||
|
||||
result = subprocess.run([
|
||||
"curl", "-sk",
|
||||
"-H", f"X-Vault-Token: {token}",
|
||||
"https://127.0.0.1:8200/v1/secret/data/api-keys/openrouter"
|
||||
], capture_output=True, text=True)
|
||||
|
||||
api_key = json.loads(result.stdout)["data"]["data"]["api_key"]
|
||||
|
||||
return OpenAI(
|
||||
base_url="https://openrouter.ai/api/v1",
|
||||
api_key=api_key
|
||||
)
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# Governed LLM Agent
|
||||
# =============================================================================
|
||||
|
||||
class GovernedLLMAgent:
|
||||
"""
|
||||
An LLM agent that operates under governance control.
|
||||
|
||||
Lifecycle:
|
||||
1. Receive instruction packet
|
||||
2. Bootstrap with governance runtime
|
||||
3. Execute phases: PREFLIGHT -> PLAN -> EXECUTE -> VERIFY -> PACKAGE -> REPORT
|
||||
4. Handle errors within budget
|
||||
5. Create handoff if revoked
|
||||
"""
|
||||
|
||||
def __init__(self, agent_id: str, model: str = "anthropic/claude-sonnet-4"):
|
||||
self.agent_id = agent_id
|
||||
self.model = model
|
||||
self.gov = GovernanceManager()
|
||||
self.runtime: Optional[WorkerRuntime] = None
|
||||
self.llm: Optional[OpenAI] = None
|
||||
|
||||
def _now(self) -> str:
|
||||
return datetime.now(timezone.utc).isoformat()
|
||||
|
||||
def create_task(self, task_id: str, objective: str, constraints: dict = None) -> bool:
|
||||
"""Create an instruction packet for this agent"""
|
||||
packet = InstructionPacket(
|
||||
agent_id=self.agent_id,
|
||||
task_id=task_id,
|
||||
created_for="Governed LLM Task",
|
||||
objective=objective,
|
||||
deliverables=["implementation plan", "execution logs", "artifacts"],
|
||||
constraints=constraints or {
|
||||
"scope": ["sandbox only"],
|
||||
"forbidden": ["no prod access", "no unrecorded changes"],
|
||||
"required_steps": ["plan before execute", "verify after execute"]
|
||||
},
|
||||
success_criteria=["plan generated", "artifacts registered"],
|
||||
error_budget=ErrorBudget(
|
||||
max_total_errors=10,
|
||||
max_same_error_repeats=3,
|
||||
max_procedure_violations=1
|
||||
),
|
||||
escalation_rules=[
|
||||
"If confidence < 0.7 -> escalate",
|
||||
"If blocked > 10m -> escalate"
|
||||
]
|
||||
)
|
||||
return self.gov.create_instruction_packet(packet)
|
||||
|
||||
def start(self) -> tuple[bool, str]:
|
||||
"""Bootstrap the governed agent"""
|
||||
print(f"\n{'='*60}")
|
||||
print(f"GOVERNED LLM AGENT: {self.agent_id}")
|
||||
print(f"Model: {self.model}")
|
||||
print(f"{'='*60}\n")
|
||||
|
||||
# Initialize runtime
|
||||
self.runtime = WorkerRuntime(self.agent_id)
|
||||
|
||||
# Bootstrap (reads revocations, loads packet, acquires lock)
|
||||
ok, msg = self.runtime.bootstrap()
|
||||
if not ok:
|
||||
print(f"[FATAL] Bootstrap failed: {msg}")
|
||||
return False, msg
|
||||
|
||||
# Initialize LLM client
|
||||
self.llm = get_openrouter_client()
|
||||
|
||||
print(f"[READY] Agent bootstrapped successfully")
|
||||
print(f"[TASK] {self.runtime.packet.objective}")
|
||||
print(f"[CONSTRAINTS] {self.runtime.packet.constraints}")
|
||||
|
||||
return True, "READY"
|
||||
|
||||
def run_preflight(self) -> bool:
|
||||
"""PREFLIGHT phase: scope and dependency checks"""
|
||||
if not self.runtime:
|
||||
return False
|
||||
|
||||
if not self.runtime.transition(AgentPhase.PREFLIGHT, "scope_check"):
|
||||
return False
|
||||
|
||||
packet = self.runtime.packet
|
||||
|
||||
# Check scope constraints
|
||||
scope = packet.constraints.get("scope", [])
|
||||
print(f"[PREFLIGHT] Scope constraints: {scope}")
|
||||
|
||||
# Check forbidden actions
|
||||
forbidden = packet.constraints.get("forbidden", [])
|
||||
print(f"[PREFLIGHT] Forbidden actions: {forbidden}")
|
||||
|
||||
# Check required steps
|
||||
required = packet.constraints.get("required_steps", [])
|
||||
print(f"[PREFLIGHT] Required steps: {required}")
|
||||
|
||||
self.runtime.transition(AgentPhase.PREFLIGHT, "preflight_complete",
|
||||
"All preflight checks passed")
|
||||
return True
|
||||
|
||||
def run_plan(self) -> Optional[dict]:
|
||||
"""PLAN phase: generate implementation plan using LLM"""
|
||||
if not self.runtime or not self.llm:
|
||||
return None
|
||||
|
||||
if not self.runtime.transition(AgentPhase.PLAN, "generating_plan"):
|
||||
return None
|
||||
|
||||
packet = self.runtime.packet
|
||||
|
||||
# Build prompt
|
||||
system_prompt = f"""You are a governed infrastructure agent operating under strict constraints.
|
||||
|
||||
Your task: {packet.objective}
|
||||
|
||||
Constraints you MUST follow:
|
||||
- Scope: {packet.constraints.get('scope', [])}
|
||||
- Forbidden: {packet.constraints.get('forbidden', [])}
|
||||
- Required steps: {packet.constraints.get('required_steps', [])}
|
||||
|
||||
You are in the PLAN phase. Generate a detailed plan but DO NOT execute anything.
|
||||
Output your plan as JSON:
|
||||
{{
|
||||
"title": "Plan title",
|
||||
"confidence": 0.0-1.0,
|
||||
"steps": [
|
||||
{{"step": 1, "action": "description", "phase": "PLAN|EXECUTE|VERIFY", "reversible": true}}
|
||||
],
|
||||
"assumptions": [],
|
||||
"risks": [],
|
||||
"estimated_duration": "X minutes"
|
||||
}}"""
|
||||
|
||||
try:
|
||||
response = self.llm.chat.completions.create(
|
||||
model=self.model,
|
||||
messages=[
|
||||
{"role": "system", "content": system_prompt},
|
||||
{"role": "user", "content": f"Create an implementation plan for: {packet.objective}"}
|
||||
],
|
||||
max_tokens=2000,
|
||||
temperature=0.3
|
||||
)
|
||||
|
||||
llm_response = response.choices[0].message.content
|
||||
|
||||
# Parse plan
|
||||
try:
|
||||
json_match = llm_response[llm_response.find("{"):llm_response.rfind("}")+1]
|
||||
plan = json.loads(json_match)
|
||||
except:
|
||||
plan = {"raw_response": llm_response, "confidence": 0.5}
|
||||
|
||||
# Register plan artifact
|
||||
self.runtime.register_artifact("plan", f"plan_{self.agent_id}_{self._now()}")
|
||||
|
||||
# Check confidence
|
||||
confidence = plan.get("confidence", 0.5)
|
||||
if confidence < 0.7:
|
||||
print(f"[PLAN] Low confidence ({confidence}), would escalate in production")
|
||||
|
||||
self.runtime.transition(AgentPhase.PLAN, "plan_complete",
|
||||
f"Plan generated with confidence {confidence}")
|
||||
|
||||
return plan
|
||||
|
||||
except Exception as e:
|
||||
self.runtime.report_error("LLM_ERROR", str(e))
|
||||
return None
|
||||
|
||||
def run_execute(self, plan: dict) -> bool:
|
||||
"""EXECUTE phase: simulate execution (in real system, would apply changes)"""
|
||||
if not self.runtime:
|
||||
return False
|
||||
|
||||
# Verify we have a plan artifact (compliance requirement)
|
||||
if not self.gov.has_required_artifact(self.runtime.packet.task_id, "plan"):
|
||||
self.runtime.report_violation("EXECUTE_WITHOUT_PLAN")
|
||||
return False
|
||||
|
||||
if not self.runtime.transition(AgentPhase.EXECUTE, "executing"):
|
||||
return False
|
||||
|
||||
steps = plan.get("steps", [])
|
||||
print(f"[EXECUTE] Simulating execution of {len(steps)} steps...")
|
||||
|
||||
for step in steps:
|
||||
step_num = step.get("step", "?")
|
||||
action = step.get("action", "unknown")
|
||||
print(f" Step {step_num}: {action[:60]}...")
|
||||
|
||||
# In real implementation, would execute the action here
|
||||
# For now, just register it as done
|
||||
self.runtime.register_artifact(
|
||||
f"step_{step_num}",
|
||||
f"executed_{step_num}_{self._now()}"
|
||||
)
|
||||
|
||||
self.runtime.transition(AgentPhase.EXECUTE, "execute_complete")
|
||||
return True
|
||||
|
||||
def run_verify(self) -> bool:
|
||||
"""VERIFY phase: post-execution checks"""
|
||||
if not self.runtime:
|
||||
return False
|
||||
|
||||
if not self.runtime.transition(AgentPhase.VERIFY, "verifying"):
|
||||
return False
|
||||
|
||||
# Check all artifacts were created
|
||||
artifacts = self.gov.get_artifacts(self.runtime.packet.task_id)
|
||||
print(f"[VERIFY] Registered artifacts: {len(artifacts)}")
|
||||
|
||||
# In real system, would run actual verification
|
||||
self.runtime.transition(AgentPhase.VERIFY, "verify_complete",
|
||||
f"Verified {len(artifacts)} artifacts")
|
||||
return True
|
||||
|
||||
def run_package(self) -> dict:
|
||||
"""PACKAGE phase: collect all outputs"""
|
||||
if not self.runtime:
|
||||
return {}
|
||||
|
||||
if not self.runtime.transition(AgentPhase.PACKAGE, "packaging"):
|
||||
return {}
|
||||
|
||||
artifacts = self.gov.get_artifacts(self.runtime.packet.task_id)
|
||||
errors = self.gov.get_error_counts(self.agent_id)
|
||||
|
||||
package = {
|
||||
"agent_id": self.agent_id,
|
||||
"task_id": self.runtime.packet.task_id,
|
||||
"objective": self.runtime.packet.objective,
|
||||
"artifacts": artifacts,
|
||||
"error_counts": errors,
|
||||
"completed_at": self._now()
|
||||
}
|
||||
|
||||
self.runtime.register_artifact("package", f"package_{self._now()}")
|
||||
self.runtime.transition(AgentPhase.PACKAGE, "package_complete")
|
||||
|
||||
return package
|
||||
|
||||
def run_report(self, package: dict) -> dict:
|
||||
"""REPORT phase: generate final report"""
|
||||
if not self.runtime:
|
||||
return {}
|
||||
|
||||
if not self.runtime.transition(AgentPhase.REPORT, "reporting"):
|
||||
return {}
|
||||
|
||||
report = {
|
||||
"agent_id": self.agent_id,
|
||||
"task_id": package.get("task_id"),
|
||||
"status": "COMPLETED",
|
||||
"summary": f"Completed objective: {package.get('objective')}",
|
||||
"artifacts_count": len(package.get("artifacts", [])),
|
||||
"errors_encountered": package.get("error_counts", {}).get("total_errors", 0),
|
||||
"timestamp": self._now()
|
||||
}
|
||||
|
||||
self.runtime.transition(AgentPhase.REPORT, "report_complete")
|
||||
return report
|
||||
|
||||
def finish(self, report: dict) -> bool:
|
||||
"""Complete the agent's work"""
|
||||
if not self.runtime:
|
||||
return False
|
||||
|
||||
return self.runtime.complete(f"Task completed: {report.get('summary', 'done')}")
|
||||
|
||||
def run_full_lifecycle(self) -> dict:
|
||||
"""Run the complete agent lifecycle"""
|
||||
|
||||
# Start
|
||||
ok, msg = self.start()
|
||||
if not ok:
|
||||
return {"status": "FAILED", "reason": msg}
|
||||
|
||||
# Preflight
|
||||
if not self.run_preflight():
|
||||
return {"status": "FAILED", "reason": "PREFLIGHT_FAILED"}
|
||||
|
||||
# Plan
|
||||
plan = self.run_plan()
|
||||
if not plan:
|
||||
return {"status": "FAILED", "reason": "PLAN_FAILED"}
|
||||
|
||||
print(f"\n[PLAN GENERATED]")
|
||||
print(json.dumps(plan, indent=2))
|
||||
|
||||
# Execute
|
||||
if not self.run_execute(plan):
|
||||
return {"status": "FAILED", "reason": "EXECUTE_FAILED"}
|
||||
|
||||
# Verify
|
||||
if not self.run_verify():
|
||||
return {"status": "FAILED", "reason": "VERIFY_FAILED"}
|
||||
|
||||
# Package
|
||||
package = self.run_package()
|
||||
|
||||
# Report
|
||||
report = self.run_report(package)
|
||||
|
||||
# Finish
|
||||
self.finish(report)
|
||||
|
||||
print(f"\n{'='*60}")
|
||||
print("FINAL REPORT")
|
||||
print(f"{'='*60}")
|
||||
print(json.dumps(report, indent=2))
|
||||
|
||||
return report
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# CLI
|
||||
# =============================================================================
|
||||
|
||||
if __name__ == "__main__":
|
||||
if len(sys.argv) < 3:
|
||||
print("Usage: governed_agent.py <agent_id> <task_id> <objective>")
|
||||
print(" governed_agent.py <agent_id> <task_id> <objective> --model <model>")
|
||||
sys.exit(1)
|
||||
|
||||
agent_id = sys.argv[1]
|
||||
task_id = sys.argv[2]
|
||||
objective = sys.argv[3]
|
||||
|
||||
model = "anthropic/claude-sonnet-4"
|
||||
if "--model" in sys.argv:
|
||||
model = sys.argv[sys.argv.index("--model") + 1]
|
||||
|
||||
# Create agent
|
||||
agent = GovernedLLMAgent(agent_id, model=model)
|
||||
|
||||
# Create task
|
||||
agent.create_task(task_id, objective)
|
||||
|
||||
# Run full lifecycle
|
||||
result = agent.run_full_lifecycle()
|
||||
|
||||
sys.exit(0 if result.get("status") == "COMPLETED" else 1)
|
||||
@@ -0,0 +1,6 @@
|
||||
def main():
|
||||
print("Hello from llm-planner!")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Executable
+317
@@ -0,0 +1,317 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Governance Monitor Agents
|
||||
=========================
|
||||
These agents watch and enforce, they don't do work.
|
||||
|
||||
- Execution Watcher: Heartbeats, stuck detection, lock expiry
|
||||
- Compliance Watcher: Artifact checks, forbidden action detection
|
||||
- Vault Lease Watcher: Token validity, revocation enforcement
|
||||
"""
|
||||
|
||||
import json
|
||||
import time
|
||||
from datetime import datetime, timezone, timedelta
|
||||
from typing import Optional
|
||||
import threading
|
||||
|
||||
from governance import (
|
||||
GovernanceManager,
|
||||
AgentPhase,
|
||||
AgentStatus,
|
||||
RevocationType
|
||||
)
|
||||
|
||||
|
||||
class ExecutionWatcher:
|
||||
"""
|
||||
Monitors agent execution health.
|
||||
- Checks heartbeats
|
||||
- Detects stuck agents
|
||||
- Handles lock expiry
|
||||
"""
|
||||
|
||||
def __init__(self, heartbeat_timeout: int = 60, stuck_threshold: int = 300):
|
||||
self.gov = GovernanceManager()
|
||||
self.heartbeat_timeout = heartbeat_timeout # seconds
|
||||
self.stuck_threshold = stuck_threshold # seconds without progress
|
||||
|
||||
def check_agent(self, agent_id: str) -> dict:
|
||||
"""Check an agent's execution health"""
|
||||
result = {
|
||||
"agent_id": agent_id,
|
||||
"healthy": True,
|
||||
"issues": []
|
||||
}
|
||||
|
||||
state = self.gov.get_agent_state(agent_id)
|
||||
if not state:
|
||||
result["healthy"] = False
|
||||
result["issues"].append("NO_STATE")
|
||||
return result
|
||||
|
||||
# Skip completed/revoked agents
|
||||
if state.status in [AgentStatus.COMPLETED, AgentStatus.REVOKED]:
|
||||
return result
|
||||
|
||||
# Check heartbeat
|
||||
if not self.gov.is_alive(agent_id):
|
||||
result["healthy"] = False
|
||||
result["issues"].append("HEARTBEAT_TIMEOUT")
|
||||
|
||||
# Check lock
|
||||
if not self.gov.has_lock(agent_id) and state.status == AgentStatus.RUNNING:
|
||||
result["healthy"] = False
|
||||
result["issues"].append("LOCK_EXPIRED")
|
||||
|
||||
# Check for stuck (no progress)
|
||||
if state.last_progress_at:
|
||||
last_progress = datetime.fromisoformat(state.last_progress_at.replace("Z", "+00:00"))
|
||||
age = (datetime.now(timezone.utc) - last_progress).total_seconds()
|
||||
if age > self.stuck_threshold:
|
||||
result["healthy"] = False
|
||||
result["issues"].append(f"STUCK_{int(age)}s")
|
||||
|
||||
return result
|
||||
|
||||
def enforce(self, agent_id: str) -> Optional[str]:
|
||||
"""Enforce health requirements, return action taken"""
|
||||
check = self.check_agent(agent_id)
|
||||
|
||||
if check["healthy"]:
|
||||
return None
|
||||
|
||||
for issue in check["issues"]:
|
||||
if issue == "HEARTBEAT_TIMEOUT":
|
||||
self.gov.revoke_agent(agent_id, RevocationType.HEARTBEAT_TIMEOUT,
|
||||
"No heartbeat received within timeout")
|
||||
return "REVOKED:HEARTBEAT"
|
||||
|
||||
elif issue == "LOCK_EXPIRED":
|
||||
self.gov.revoke_agent(agent_id, RevocationType.LOCK_EXPIRED,
|
||||
"Lock expired while agent was running")
|
||||
return "REVOKED:LOCK"
|
||||
|
||||
elif issue.startswith("STUCK_"):
|
||||
self.gov.revoke_agent(agent_id, RevocationType.HEARTBEAT_TIMEOUT,
|
||||
f"Agent stuck with no progress: {issue}")
|
||||
return f"REVOKED:{issue}"
|
||||
|
||||
return None
|
||||
|
||||
|
||||
class ComplianceWatcher:
|
||||
"""
|
||||
Monitors agent compliance with procedures.
|
||||
- Checks required artifacts exist
|
||||
- Detects forbidden actions
|
||||
- Validates phase transitions
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
self.gov = GovernanceManager()
|
||||
|
||||
def check_agent(self, agent_id: str) -> dict:
|
||||
"""Check an agent's compliance"""
|
||||
result = {
|
||||
"agent_id": agent_id,
|
||||
"compliant": True,
|
||||
"violations": []
|
||||
}
|
||||
|
||||
state = self.gov.get_agent_state(agent_id)
|
||||
packet = self.gov.get_instruction_packet(agent_id)
|
||||
|
||||
if not state or not packet:
|
||||
result["compliant"] = False
|
||||
result["violations"].append("MISSING_STATE_OR_PACKET")
|
||||
return result
|
||||
|
||||
# Check if EXECUTE was entered without PLAN artifact
|
||||
if state.phase in [AgentPhase.EXECUTE, AgentPhase.VERIFY, AgentPhase.PACKAGE]:
|
||||
if not self.gov.has_required_artifact(packet.task_id, "plan"):
|
||||
result["compliant"] = False
|
||||
result["violations"].append("EXECUTE_WITHOUT_PLAN_ARTIFACT")
|
||||
|
||||
# Check required steps from constraints
|
||||
required_steps = packet.constraints.get("required_steps", [])
|
||||
# This would need more sophisticated tracking in production
|
||||
|
||||
return result
|
||||
|
||||
def enforce(self, agent_id: str) -> Optional[str]:
|
||||
"""Enforce compliance, return action taken"""
|
||||
check = self.check_agent(agent_id)
|
||||
|
||||
if check["compliant"]:
|
||||
return None
|
||||
|
||||
for violation in check["violations"]:
|
||||
if violation == "EXECUTE_WITHOUT_PLAN_ARTIFACT":
|
||||
self.gov.revoke_agent(agent_id, RevocationType.PROCEDURE_VIOLATION,
|
||||
"Attempted EXECUTE phase without plan artifact")
|
||||
return "REVOKED:NO_PLAN_ARTIFACT"
|
||||
|
||||
return None
|
||||
|
||||
|
||||
class VaultLeaseWatcher:
|
||||
"""
|
||||
Monitors Vault token/lease validity.
|
||||
- Checks token accessibility
|
||||
- Confirms revocation signals
|
||||
- Enforces token revocation
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
self.gov = GovernanceManager()
|
||||
self.db = self.gov.db
|
||||
|
||||
def set_revocation_signal(self, agent_id: str):
|
||||
"""Set a signal that this agent should be revoked"""
|
||||
self.db.set(f"agent:{agent_id}:revoke_signal", "1", ex=300)
|
||||
|
||||
def has_revocation_signal(self, agent_id: str) -> bool:
|
||||
"""Check if revocation signal is set"""
|
||||
return self.db.exists(f"agent:{agent_id}:revoke_signal")
|
||||
|
||||
def clear_revocation_signal(self, agent_id: str):
|
||||
"""Clear revocation signal after enforcement"""
|
||||
self.db.delete(f"agent:{agent_id}:revoke_signal")
|
||||
|
||||
def enforce(self, agent_id: str) -> Optional[str]:
|
||||
"""Enforce revocation signal"""
|
||||
if self.has_revocation_signal(agent_id):
|
||||
self.gov.revoke_agent(agent_id, RevocationType.MANUAL,
|
||||
"Revocation signal received")
|
||||
self.clear_revocation_signal(agent_id)
|
||||
return "REVOKED:SIGNAL"
|
||||
return None
|
||||
|
||||
|
||||
class GovernanceMonitorDaemon:
|
||||
"""
|
||||
Background daemon that runs all monitors periodically.
|
||||
"""
|
||||
|
||||
def __init__(self, interval: int = 10):
|
||||
self.interval = interval
|
||||
self.gov = GovernanceManager()
|
||||
self.execution_watcher = ExecutionWatcher()
|
||||
self.compliance_watcher = ComplianceWatcher()
|
||||
self.vault_watcher = VaultLeaseWatcher()
|
||||
self.running = False
|
||||
|
||||
def get_active_agents(self) -> list[str]:
|
||||
"""Get list of agents that need monitoring"""
|
||||
# Get all agent state keys
|
||||
keys = self.gov.db.keys("agent:*:state")
|
||||
agents = []
|
||||
for key in keys:
|
||||
agent_id = key.split(":")[1]
|
||||
state = self.gov.get_agent_state(agent_id)
|
||||
if state and state.status == AgentStatus.RUNNING:
|
||||
agents.append(agent_id)
|
||||
return agents
|
||||
|
||||
def run_checks(self) -> list[dict]:
|
||||
"""Run all monitors once"""
|
||||
results = []
|
||||
|
||||
for agent_id in self.get_active_agents():
|
||||
result = {
|
||||
"agent_id": agent_id,
|
||||
"timestamp": datetime.now(timezone.utc).isoformat(),
|
||||
"actions": []
|
||||
}
|
||||
|
||||
# Execution check
|
||||
action = self.execution_watcher.enforce(agent_id)
|
||||
if action:
|
||||
result["actions"].append(action)
|
||||
|
||||
# Compliance check (only if not already revoked)
|
||||
state = self.gov.get_agent_state(agent_id)
|
||||
if state and state.status != AgentStatus.REVOKED:
|
||||
action = self.compliance_watcher.enforce(agent_id)
|
||||
if action:
|
||||
result["actions"].append(action)
|
||||
|
||||
# Vault check
|
||||
if state and state.status != AgentStatus.REVOKED:
|
||||
action = self.vault_watcher.enforce(agent_id)
|
||||
if action:
|
||||
result["actions"].append(action)
|
||||
|
||||
if result["actions"]:
|
||||
results.append(result)
|
||||
|
||||
return results
|
||||
|
||||
def run_daemon(self):
|
||||
"""Run as a daemon (blocking)"""
|
||||
self.running = True
|
||||
print(f"[MONITOR] Starting governance monitor daemon (interval: {self.interval}s)")
|
||||
|
||||
while self.running:
|
||||
results = self.run_checks()
|
||||
for r in results:
|
||||
print(f"[MONITOR] {r['agent_id']}: {r['actions']}")
|
||||
time.sleep(self.interval)
|
||||
|
||||
def stop(self):
|
||||
"""Stop the daemon"""
|
||||
self.running = False
|
||||
|
||||
|
||||
# =============================================================================
|
||||
# CLI
|
||||
# =============================================================================
|
||||
|
||||
if __name__ == "__main__":
|
||||
import sys
|
||||
|
||||
if len(sys.argv) < 2:
|
||||
print("Usage: monitors.py <command>")
|
||||
print("Commands:")
|
||||
print(" check <agent_id> - Run all checks on an agent")
|
||||
print(" daemon - Run monitor daemon")
|
||||
print(" signal <agent_id> - Send revocation signal")
|
||||
sys.exit(1)
|
||||
|
||||
cmd = sys.argv[1]
|
||||
|
||||
if cmd == "check":
|
||||
agent_id = sys.argv[2]
|
||||
|
||||
exec_watch = ExecutionWatcher()
|
||||
comp_watch = ComplianceWatcher()
|
||||
|
||||
print(f"=== Checking Agent: {agent_id} ===\n")
|
||||
|
||||
print("Execution Check:")
|
||||
result = exec_watch.check_agent(agent_id)
|
||||
print(f" Healthy: {result['healthy']}")
|
||||
print(f" Issues: {result['issues']}")
|
||||
|
||||
print("\nCompliance Check:")
|
||||
result = comp_watch.check_agent(agent_id)
|
||||
print(f" Compliant: {result['compliant']}")
|
||||
print(f" Violations: {result['violations']}")
|
||||
|
||||
elif cmd == "daemon":
|
||||
daemon = GovernanceMonitorDaemon(interval=10)
|
||||
try:
|
||||
daemon.run_daemon()
|
||||
except KeyboardInterrupt:
|
||||
daemon.stop()
|
||||
print("\n[MONITOR] Stopped")
|
||||
|
||||
elif cmd == "signal":
|
||||
agent_id = sys.argv[2]
|
||||
watcher = VaultLeaseWatcher()
|
||||
watcher.set_revocation_signal(agent_id)
|
||||
print(f"Revocation signal set for {agent_id}")
|
||||
|
||||
else:
|
||||
print(f"Unknown command: {cmd}")
|
||||
@@ -0,0 +1,12 @@
|
||||
[project]
|
||||
name = "llm-planner"
|
||||
version = "0.1.0"
|
||||
description = "Add your description here"
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.11"
|
||||
dependencies = [
|
||||
"httpx>=0.28.1",
|
||||
"openai>=2.15.0",
|
||||
"pydantic>=2.12.5",
|
||||
"redis>=7.1.0",
|
||||
]
|
||||
Generated
+396
@@ -0,0 +1,396 @@
|
||||
version = 1
|
||||
revision = 3
|
||||
requires-python = ">=3.11"
|
||||
|
||||
[[package]]
|
||||
name = "annotated-types"
|
||||
version = "0.7.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/ee/67/531ea369ba64dcff5ec9c3402f9f51bf748cec26dde048a2f973a4eea7f5/annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89", size = 16081, upload-time = "2024-05-20T21:33:25.928Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "anyio"
|
||||
version = "4.12.1"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "idna" },
|
||||
{ name = "typing-extensions", marker = "python_full_version < '3.13'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/96/f0/5eb65b2bb0d09ac6776f2eb54adee6abe8228ea05b20a5ad0e4945de8aac/anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703", size = 228685, upload-time = "2026-01-06T11:45:21.246Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c", size = 113592, upload-time = "2026-01-06T11:45:19.497Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "async-timeout"
|
||||
version = "5.0.1"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/a5/ae/136395dfbfe00dfc94da3f3e136d0b13f394cba8f4841120e34226265780/async_timeout-5.0.1.tar.gz", hash = "sha256:d9321a7a3d5a6a5e187e824d2fa0793ce379a202935782d555d6e9d2735677d3", size = 9274, upload-time = "2024-11-06T16:41:39.6Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/fe/ba/e2081de779ca30d473f21f5b30e0e737c438205440784c7dfc81efc2b029/async_timeout-5.0.1-py3-none-any.whl", hash = "sha256:39e3809566ff85354557ec2398b55e096c8364bacac9405a7a1fa429e77fe76c", size = 6233, upload-time = "2024-11-06T16:41:37.9Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "certifi"
|
||||
version = "2026.1.4"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/e0/2d/a891ca51311197f6ad14a7ef42e2399f36cf2f9bd44752b3dc4eab60fdc5/certifi-2026.1.4.tar.gz", hash = "sha256:ac726dd470482006e014ad384921ed6438c457018f4b3d204aea4281258b2120", size = 154268, upload-time = "2026-01-04T02:42:41.825Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/e6/ad/3cc14f097111b4de0040c83a525973216457bbeeb63739ef1ed275c1c021/certifi-2026.1.4-py3-none-any.whl", hash = "sha256:9943707519e4add1115f44c2bc244f782c0249876bf51b6599fee1ffbedd685c", size = 152900, upload-time = "2026-01-04T02:42:40.15Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "colorama"
|
||||
version = "0.4.6"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/d8/53/6f443c9a4a8358a93a6792e2acffb9d9d5cb0a5cfd8802644b7b1c9a02e4/colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44", size = 27697, upload-time = "2022-10-25T02:36:22.414Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6", size = 25335, upload-time = "2022-10-25T02:36:20.889Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "distro"
|
||||
version = "1.9.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/fc/f8/98eea607f65de6527f8a2e8885fc8015d3e6f5775df186e443e0964a11c3/distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed", size = 60722, upload-time = "2023-12-24T09:54:32.31Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/12/b3/231ffd4ab1fc9d679809f356cebee130ac7daa00d6d6f3206dd4fd137e9e/distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2", size = 20277, upload-time = "2023-12-24T09:54:30.421Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "h11"
|
||||
version = "0.16.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/01/ee/02a2c011bdab74c6fb3c75474d40b3052059d95df7e73351460c8588d963/h11-0.16.0.tar.gz", hash = "sha256:4e35b956cf45792e4caa5885e69fba00bdbc6ffafbfa020300e549b208ee5ff1", size = 101250, upload-time = "2025-04-24T03:35:25.427Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl", hash = "sha256:63cf8bbe7522de3bf65932fda1d9c2772064ffb3dae62d55932da54b31cb6c86", size = 37515, upload-time = "2025-04-24T03:35:24.344Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "httpcore"
|
||||
version = "1.0.9"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "certifi" },
|
||||
{ name = "h11" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/06/94/82699a10bca87a5556c9c59b5963f2d039dbd239f25bc2a63907a05a14cb/httpcore-1.0.9.tar.gz", hash = "sha256:6e34463af53fd2ab5d807f399a9b45ea31c3dfa2276f15a2c3f00afff6e176e8", size = 85484, upload-time = "2025-04-24T22:06:22.219Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl", hash = "sha256:2d400746a40668fc9dec9810239072b40b4484b640a8c38fd654a024c7a1bf55", size = 78784, upload-time = "2025-04-24T22:06:20.566Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "httpx"
|
||||
version = "0.28.1"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "anyio" },
|
||||
{ name = "certifi" },
|
||||
{ name = "httpcore" },
|
||||
{ name = "idna" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/b1/df/48c586a5fe32a0f01324ee087459e112ebb7224f646c0b5023f5e79e9956/httpx-0.28.1.tar.gz", hash = "sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc", size = 141406, upload-time = "2024-12-06T15:37:23.222Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl", hash = "sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad", size = 73517, upload-time = "2024-12-06T15:37:21.509Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "idna"
|
||||
version = "3.11"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/6f/6d/0703ccc57f3a7233505399edb88de3cbd678da106337b9fcde432b65ed60/idna-3.11.tar.gz", hash = "sha256:795dafcc9c04ed0c1fb032c2aa73654d8e8c5023a7df64a53f39190ada629902", size = 194582, upload-time = "2025-10-12T14:55:20.501Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl", hash = "sha256:771a87f49d9defaf64091e6e6fe9c18d4833f140bd19464795bc32d966ca37ea", size = 71008, upload-time = "2025-10-12T14:55:18.883Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "jiter"
|
||||
version = "0.12.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/45/9d/e0660989c1370e25848bb4c52d061c71837239738ad937e83edca174c273/jiter-0.12.0.tar.gz", hash = "sha256:64dfcd7d5c168b38d3f9f8bba7fc639edb3418abcc74f22fdbe6b8938293f30b", size = 168294, upload-time = "2025-11-09T20:49:23.302Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/32/f9/eaca4633486b527ebe7e681c431f529b63fe2709e7c5242fc0f43f77ce63/jiter-0.12.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:d8f8a7e317190b2c2d60eb2e8aa835270b008139562d70fe732e1c0020ec53c9", size = 316435, upload-time = "2025-11-09T20:47:02.087Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/10/c1/40c9f7c22f5e6ff715f28113ebaba27ab85f9af2660ad6e1dd6425d14c19/jiter-0.12.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:2218228a077e784c6c8f1a8e5d6b8cb1dea62ce25811c356364848554b2056cd", size = 320548, upload-time = "2025-11-09T20:47:03.409Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/6b/1b/efbb68fe87e7711b00d2cfd1f26bb4bfc25a10539aefeaa7727329ffb9cb/jiter-0.12.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9354ccaa2982bf2188fd5f57f79f800ef622ec67beb8329903abf6b10da7d423", size = 351915, upload-time = "2025-11-09T20:47:05.171Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/15/2d/c06e659888c128ad1e838123d0638f0efad90cc30860cb5f74dd3f2fc0b3/jiter-0.12.0-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:8f2607185ea89b4af9a604d4c7ec40e45d3ad03ee66998b031134bc510232bb7", size = 368966, upload-time = "2025-11-09T20:47:06.508Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/6b/20/058db4ae5fb07cf6a4ab2e9b9294416f606d8e467fb74c2184b2a1eeacba/jiter-0.12.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3a585a5e42d25f2e71db5f10b171f5e5ea641d3aa44f7df745aa965606111cc2", size = 482047, upload-time = "2025-11-09T20:47:08.382Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/49/bb/dc2b1c122275e1de2eb12905015d61e8316b2f888bdaac34221c301495d6/jiter-0.12.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bd9e21d34edff5a663c631f850edcb786719c960ce887a5661e9c828a53a95d9", size = 380835, upload-time = "2025-11-09T20:47:09.81Z" },
|
||||
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|
||||
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|
||||
{ url = "https://files.pythonhosted.org/packages/07/71/e0d11422ed027e21422f7bc1883c61deba2d9752b720538430c1deadfbca/jiter-0.12.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:b1207af186495f48f72529f8d86671903c8c10127cac6381b11dddc4aaa52df6", size = 522046, upload-time = "2025-11-09T20:47:14.6Z" },
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||||
{ url = "https://files.pythonhosted.org/packages/9f/59/b968a9aa7102a8375dbbdfbd2aeebe563c7e5dddf0f47c9ef1588a97e224/jiter-0.12.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:ef2fb241de583934c9915a33120ecc06d94aa3381a134570f59eed784e87001e", size = 513392, upload-time = "2025-11-09T20:47:16.011Z" },
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||||
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||||
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Reference in New Issue
Block a user