feat: add concurrent agents with dependency system and delightful UI

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>
This commit is contained in:
Auto
2026-01-17 12:59:42 +02:00
parent 91cc00a9d0
commit 85f6940a54
39 changed files with 4532 additions and 157 deletions

View File

@@ -15,6 +15,7 @@ from typing import Set
from fastapi import WebSocket, WebSocketDisconnect
from .schemas import AGENT_MASCOTS
from .services.dev_server_manager import get_devserver_manager
from .services.process_manager import get_manager
@@ -23,6 +24,177 @@ _count_passing_tests = None
logger = logging.getLogger(__name__)
# Pattern to extract feature ID from parallel orchestrator output
FEATURE_ID_PATTERN = re.compile(r'\[Feature #(\d+)\]\s*(.*)')
# Patterns for detecting agent activity and thoughts
THOUGHT_PATTERNS = [
# Claude's tool usage patterns (actual format: [Tool: name])
(re.compile(r'\[Tool:\s*Read\]', re.I), 'thinking'),
(re.compile(r'\[Tool:\s*(?:Write|Edit|NotebookEdit)\]', re.I), 'working'),
(re.compile(r'\[Tool:\s*Bash\]', re.I), 'testing'),
(re.compile(r'\[Tool:\s*(?:Glob|Grep)\]', re.I), 'thinking'),
(re.compile(r'\[Tool:\s*(\w+)\]', re.I), 'working'), # Fallback for other tools
# Claude's internal thoughts
(re.compile(r'(?:Reading|Analyzing|Checking|Looking at|Examining)\s+(.+)', re.I), 'thinking'),
(re.compile(r'(?:Creating|Writing|Adding|Implementing|Building)\s+(.+)', re.I), 'working'),
(re.compile(r'(?:Testing|Verifying|Running tests|Validating)\s+(.+)', re.I), 'testing'),
(re.compile(r'(?:Error|Failed|Cannot|Unable to|Exception)\s+(.+)', re.I), 'struggling'),
# Test results
(re.compile(r'(?:PASS|passed|success)', re.I), 'success'),
(re.compile(r'(?:FAIL|failed|error)', re.I), 'struggling'),
]
class AgentTracker:
"""Tracks active agents and their states for multi-agent mode."""
def __init__(self):
# feature_id -> {name, state, last_thought, agent_index}
self.active_agents: dict[int, dict] = {}
self._next_agent_index = 0
self._lock = asyncio.Lock()
async def process_line(self, line: str) -> dict | None:
"""
Process an output line and return an agent_update message if relevant.
Returns None if no update should be emitted.
"""
# Check for feature-specific output
match = FEATURE_ID_PATTERN.match(line)
if not match:
# Also check for orchestrator status messages
if line.startswith("Started agent for feature #"):
try:
feature_id = int(re.search(r'#(\d+)', line).group(1))
return await self._handle_agent_start(feature_id, line)
except (AttributeError, ValueError):
pass
elif line.startswith("Feature #") and ("completed" in line or "failed" in line):
try:
feature_id = int(re.search(r'#(\d+)', line).group(1))
is_success = "completed" in line
return await self._handle_agent_complete(feature_id, is_success)
except (AttributeError, ValueError):
pass
return None
feature_id = int(match.group(1))
content = match.group(2)
async with self._lock:
# Ensure agent is tracked
if feature_id not in self.active_agents:
agent_index = self._next_agent_index
self._next_agent_index += 1
self.active_agents[feature_id] = {
'name': AGENT_MASCOTS[agent_index % len(AGENT_MASCOTS)],
'agent_index': agent_index,
'state': 'thinking',
'feature_name': f'Feature #{feature_id}',
'last_thought': None,
}
agent = self.active_agents[feature_id]
# Detect state and thought from content
state = 'working'
thought = None
for pattern, detected_state in THOUGHT_PATTERNS:
m = pattern.search(content)
if m:
state = detected_state
thought = m.group(1) if m.lastindex else content[:100]
break
# Only emit update if state changed or we have a new thought
if state != agent['state'] or thought != agent['last_thought']:
agent['state'] = state
if thought:
agent['last_thought'] = thought
return {
'type': 'agent_update',
'agentIndex': agent['agent_index'],
'agentName': agent['name'],
'featureId': feature_id,
'featureName': agent['feature_name'],
'state': state,
'thought': thought,
'timestamp': datetime.now().isoformat(),
}
return None
def get_agent_info(self, feature_id: int) -> tuple[int | None, str | None]:
"""Get agent index and name for a feature ID.
Returns:
Tuple of (agentIndex, agentName) or (None, None) if not tracked.
"""
agent = self.active_agents.get(feature_id)
if agent:
return agent['agent_index'], agent['name']
return None, None
async def _handle_agent_start(self, feature_id: int, line: str) -> dict | None:
"""Handle agent start message from orchestrator."""
async with self._lock:
agent_index = self._next_agent_index
self._next_agent_index += 1
# Try to extract feature name from line
feature_name = f'Feature #{feature_id}'
name_match = re.search(r'#\d+:\s*(.+)$', line)
if name_match:
feature_name = name_match.group(1)
self.active_agents[feature_id] = {
'name': AGENT_MASCOTS[agent_index % len(AGENT_MASCOTS)],
'agent_index': agent_index,
'state': 'thinking',
'feature_name': feature_name,
'last_thought': 'Starting work...',
}
return {
'type': 'agent_update',
'agentIndex': agent_index,
'agentName': AGENT_MASCOTS[agent_index % len(AGENT_MASCOTS)],
'featureId': feature_id,
'featureName': feature_name,
'state': 'thinking',
'thought': 'Starting work...',
'timestamp': datetime.now().isoformat(),
}
async def _handle_agent_complete(self, feature_id: int, is_success: bool) -> dict | None:
"""Handle agent completion message from orchestrator."""
async with self._lock:
if feature_id not in self.active_agents:
return None
agent = self.active_agents[feature_id]
state = 'success' if is_success else 'error'
result = {
'type': 'agent_update',
'agentIndex': agent['agent_index'],
'agentName': agent['name'],
'featureId': feature_id,
'featureName': agent['feature_name'],
'state': state,
'thought': 'Completed successfully!' if is_success else 'Failed to complete',
'timestamp': datetime.now().isoformat(),
}
# Remove from active agents
del self.active_agents[feature_id]
return result
def _get_project_path(project_name: str) -> Path:
"""Get project path from registry."""
@@ -171,14 +343,38 @@ async def project_websocket(websocket: WebSocket, project_name: str):
# Get agent manager and register callbacks
agent_manager = get_manager(project_name, project_dir, ROOT_DIR)
# Create agent tracker for multi-agent mode
agent_tracker = AgentTracker()
async def on_output(line: str):
"""Handle agent output - broadcast to this WebSocket."""
try:
await websocket.send_json({
# Extract feature ID from line if present
feature_id = None
agent_index = None
match = FEATURE_ID_PATTERN.match(line)
if match:
feature_id = int(match.group(1))
agent_index, _ = agent_tracker.get_agent_info(feature_id)
# Send the raw log line with optional feature/agent attribution
log_msg = {
"type": "log",
"line": line,
"timestamp": datetime.now().isoformat(),
})
}
if feature_id is not None:
log_msg["featureId"] = feature_id
if agent_index is not None:
log_msg["agentIndex"] = agent_index
await websocket.send_json(log_msg)
# Check if this line indicates agent activity (parallel mode)
# and emit agent_update messages if so
agent_update = await agent_tracker.process_line(line)
if agent_update:
await websocket.send_json(agent_update)
except Exception:
pass # Connection may be closed