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Major feature implementation for parallel agent execution with dependency-aware scheduling and an engaging multi-agent UI experience. Backend Changes: - Add parallel_orchestrator.py for concurrent feature processing - Add api/dependency_resolver.py with cycle detection (Kahn's algorithm + DFS) - Add atomic feature_claim_next() with retry limit and exponential backoff - Fix circular dependency check arguments in 4 locations - Add AgentTracker class for parsing agent output and emitting updates - Add browser isolation with --isolated flag for Playwright MCP - Extend WebSocket protocol with agent_update messages and log attribution - Add WSAgentUpdateMessage schema with agent states and mascot names - Fix WSProgressMessage to include in_progress field New UI Components: - AgentMissionControl: Dashboard showing active agents with collapsible activity - AgentCard: Individual agent status with avatar and thought bubble - AgentAvatar: SVG mascots (Spark, Fizz, Octo, Hoot, Buzz) with animations - ActivityFeed: Recent activity stream with stable keys (no flickering) - CelebrationOverlay: Confetti animation with click/Escape dismiss - DependencyGraph: Interactive node graph visualization with dagre layout - DependencyBadge: Visual indicator for feature dependencies - ViewToggle: Switch between Kanban and Graph views - KeyboardShortcutsHelp: Help overlay accessible via ? key UI/UX Improvements: - Celebration queue system to handle rapid success messages - Accessibility attributes on AgentAvatar (role, aria-label, aria-live) - Collapsible Recent Activity section with persisted preference - Agent count display in header - Keyboard shortcut G to toggle Kanban/Graph view - Real-time thought bubbles and state animations Bug Fixes: - Fix circular dependency validation (swapped source/target arguments) - Add MAX_CLAIM_RETRIES=10 to prevent stack overflow under contention - Fix THOUGHT_PATTERNS to match actual [Tool: name] format - Fix ActivityFeed key prop to prevent re-renders on new items - Add featureId/agentIndex to log messages for proper attribution Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
184 lines
5.7 KiB
Python
184 lines
5.7 KiB
Python
#!/usr/bin/env python3
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"""
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Autonomous Coding Agent Demo
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============================
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A minimal harness demonstrating long-running autonomous coding with Claude.
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This script implements the two-agent pattern (initializer + coding agent) and
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incorporates all the strategies from the long-running agents guide.
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Example Usage:
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# Using absolute path directly
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python autonomous_agent_demo.py --project-dir C:/Projects/my-app
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# Using registered project name (looked up from registry)
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python autonomous_agent_demo.py --project-dir my-app
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# Limit iterations for testing
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python autonomous_agent_demo.py --project-dir my-app --max-iterations 5
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# YOLO mode: rapid prototyping without browser testing
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python autonomous_agent_demo.py --project-dir my-app --yolo
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# Parallel execution with 3 concurrent agents (default)
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python autonomous_agent_demo.py --project-dir my-app --parallel
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# Parallel execution with 5 concurrent agents
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python autonomous_agent_demo.py --project-dir my-app --parallel 5
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"""
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import argparse
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import asyncio
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from pathlib import Path
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from dotenv import load_dotenv
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# Load environment variables from .env file (if it exists)
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# IMPORTANT: Must be called BEFORE importing other modules that read env vars at load time
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load_dotenv()
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from agent import run_autonomous_agent
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from registry import DEFAULT_MODEL, get_project_path
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def parse_args() -> argparse.Namespace:
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"""Parse command line arguments."""
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parser = argparse.ArgumentParser(
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description="Autonomous Coding Agent Demo - Long-running agent harness",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog="""
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Examples:
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# Use absolute path directly
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python autonomous_agent_demo.py --project-dir C:/Projects/my-app
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# Use registered project name (looked up from registry)
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python autonomous_agent_demo.py --project-dir my-app
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# Use a specific model
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python autonomous_agent_demo.py --project-dir my-app --model claude-sonnet-4-5-20250929
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# Limit iterations for testing
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python autonomous_agent_demo.py --project-dir my-app --max-iterations 5
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# YOLO mode: rapid prototyping without browser testing
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python autonomous_agent_demo.py --project-dir my-app --yolo
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Authentication:
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Uses Claude CLI authentication (run 'claude login' if not logged in)
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Authentication is handled by start.bat/start.sh before this runs
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""",
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)
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parser.add_argument(
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"--project-dir",
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type=str,
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required=True,
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help="Project directory path (absolute) or registered project name",
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)
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parser.add_argument(
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"--max-iterations",
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type=int,
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default=None,
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help="Maximum number of agent iterations (default: unlimited)",
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)
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parser.add_argument(
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"--model",
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type=str,
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default=DEFAULT_MODEL,
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help=f"Claude model to use (default: {DEFAULT_MODEL})",
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)
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parser.add_argument(
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"--yolo",
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action="store_true",
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default=False,
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help="Enable YOLO mode: rapid prototyping without browser testing",
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)
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parser.add_argument(
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"--parallel",
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"-p",
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type=int,
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nargs="?",
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const=3,
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default=None,
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metavar="N",
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help="Enable parallel execution with N concurrent agents (default: 3, max: 5)",
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)
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parser.add_argument(
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"--feature-id",
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type=int,
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default=None,
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help="Work on a specific feature ID only (used by parallel orchestrator)",
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)
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return parser.parse_args()
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def main() -> None:
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"""Main entry point."""
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args = parse_args()
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# Note: Authentication is handled by start.bat/start.sh before this script runs.
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# The Claude SDK auto-detects credentials from ~/.claude/.credentials.json
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# Resolve project directory:
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# 1. If absolute path, use as-is
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# 2. Otherwise, look up from registry by name
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project_dir_input = args.project_dir
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project_dir = Path(project_dir_input)
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if project_dir.is_absolute():
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# Absolute path provided - use directly
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if not project_dir.exists():
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print(f"Error: Project directory does not exist: {project_dir}")
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return
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else:
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# Treat as a project name - look up from registry
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registered_path = get_project_path(project_dir_input)
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if registered_path:
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project_dir = registered_path
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else:
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print(f"Error: Project '{project_dir_input}' not found in registry")
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print("Use an absolute path or register the project first.")
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return
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try:
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if args.parallel is not None:
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# Parallel execution mode
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from parallel_orchestrator import run_parallel_orchestrator
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print(f"Running in parallel mode with {args.parallel} concurrent agents")
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asyncio.run(
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run_parallel_orchestrator(
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project_dir=project_dir,
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max_concurrency=args.parallel,
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model=args.model,
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yolo_mode=args.yolo,
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)
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)
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else:
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# Standard single-agent mode (MCP server handles feature database)
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asyncio.run(
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run_autonomous_agent(
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project_dir=project_dir,
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model=args.model,
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max_iterations=args.max_iterations,
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yolo_mode=args.yolo,
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feature_id=args.feature_id,
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)
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)
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except KeyboardInterrupt:
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print("\n\nInterrupted by user")
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print("To resume, run the same command again")
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except Exception as e:
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print(f"\nFatal error: {e}")
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raise
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if __name__ == "__main__":
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main()
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