added step callback for tracking generation

workflows/README.md

@@ -57,12 +57,32 @@ python cli.py run-workflow-no-ai my_workflow.json
 - **Semantic Targeting**: Use `{variable}` in `target_text`
 - **Auto-Extraction**: LLM suggests variables automatically
 
+### 📊 Real-time Progress Tracking (NEW!)
+- **Step-by-Step Visibility**: See each browser action as it's recorded
+- **Status Updates**: Track workflow processing phases in real-time
+- **Cloud Integration Ready**: Store progress in database for live UI updates
+- **Debug Friendly**: Know exactly where workflow generation fails
+- **Zero Overhead**: Optional callbacks, fully backward compatible
+
+```python
+# Track workflow generation progress in real-time
+workflow = await service.generate_workflow_from_prompt(
+    prompt="Search for Python docs",
+    agent_llm=llm,
+    extraction_llm=llm,
+    on_step_recorded=lambda s: print(f"Step {s['step_number']}: {s['description']}"),
+    on_status_update=lambda msg: print(f"Status: {msg}"),
+)
+```
+
 ---
 
 ## Documentation
 
 - **[docs/DETERMINISTIC.md](docs/DETERMINISTIC.md)** - Deterministic workflow generation
 - **[docs/VARIABLES.md](docs/VARIABLES.md)** - Variables guide
+- **[docs/PROGRESS_TRACKING.md](docs/PROGRESS_TRACKING.md)** - Real-time progress tracking ⭐ NEW
+- **[QUICK_START_PROGRESS_TRACKING.md](QUICK_START_PROGRESS_TRACKING.md)** - 5-minute integration guide
 - **[examples/README.md](examples/README.md)** - Example scripts
 
 ---
@@ -98,6 +118,7 @@ workflows/
 │   │   ├── variables/       # Variable feature examples
 │   │   ├── demos/           # Advanced demos
 │   │   └── runner.py        # Generic workflow runner
+│   ├── progress_tracking_example.py  # ⭐ NEW: Real-time progress tracking
 │   └── workflows/           # Example workflow JSON files
 │       ├── basic/           # Basic workflow examples
 │       ├── form_filling/    # Form filling examples

workflows/examples/progress_tracking_example.py

@@ -0,0 +1,256 @@
+"""
+Example: Real-time Progress Tracking for Workflow Generation
+
+This example demonstrates how to use the new on_step_recorded and on_status_update
+callbacks to track workflow generation progress in real-time.
+
+Usage:
+    python examples/progress_tracking_example.py
+"""
+
+import asyncio
+from datetime import datetime
+
+from browser_use.llm import ChatBrowserUse
+
+from workflow_use.healing.service import HealingService
+
+
+# Example 1: Simple console logging
+async def simple_console_example():
+	"""Basic example: Print steps to console as they're recorded."""
+	print('=' * 80)
+	print('EXAMPLE 1: Simple Console Logging')
+	print('=' * 80)
+
+	def step_callback(step_data: dict):
+		"""Called each time a step is recorded."""
+		print(f'\n📍 Step {step_data["step_number"]}: {step_data["description"]}')
+		print(f'   Type: {step_data["action_type"]}')
+		print(f'   URL: {step_data["url"]}')
+		if step_data.get('target_text'):
+			print(f'   Target: {step_data["target_text"]}')
+		if step_data.get('extracted_data'):
+			print(f'   Extracted: {step_data["extracted_data"]}')
+
+	def status_callback(status: str):
+		"""Called for general status updates."""
+		print(f'\n🔄 {status}')
+
+	# Initialize service
+	llm = ChatBrowserUse(model='bu-latest')
+	healing_service = HealingService(
+		llm=llm,
+		use_deterministic_conversion=True,
+		enable_variable_extraction=True,
+	)
+
+	# Generate workflow with callbacks
+	workflow = await healing_service.generate_workflow_from_prompt(
+		prompt='Go to example.com and extract the page title',
+		agent_llm=llm,
+		extraction_llm=llm,
+		use_cloud=False,
+		on_step_recorded=step_callback,
+		on_status_update=status_callback,
+	)
+
+	print(f'\n✅ Generated workflow with {len(workflow.steps)} steps!')
+
+
+# Example 2: Store steps in a list (for database storage)
+async def database_storage_example():
+	"""Example: Store steps in memory (simulates database storage)."""
+	print('\n' + '=' * 80)
+	print('EXAMPLE 2: Database Storage Pattern')
+	print('=' * 80)
+
+	# Simulated database storage
+	stored_steps = []
+	status_history = []
+
+	async def step_callback(step_data: dict):
+		"""Store step in database (simulated with list)."""
+		stored_steps.append(step_data)
+		print(f'✓ Stored step {step_data["step_number"]} in database')
+
+	async def status_callback(status: str):
+		"""Store status update in database."""
+		status_history.append({'timestamp': datetime.now().isoformat(), 'status': status})
+		print(f'ℹ️  {status}')
+
+	# Initialize service
+	llm = ChatBrowserUse(model='bu-latest')
+	healing_service = HealingService(
+		llm=llm,
+		use_deterministic_conversion=True,
+		enable_variable_extraction=True,
+	)
+
+	# Generate workflow with async callbacks
+	workflow = await healing_service.generate_workflow_from_prompt(
+		prompt='Go to example.com and extract the page title',
+		agent_llm=llm,
+		extraction_llm=llm,
+		use_cloud=False,
+		on_step_recorded=lambda data: asyncio.create_task(step_callback(data)),
+		on_status_update=lambda status: asyncio.create_task(status_callback(status)),
+	)
+
+	# Display stored data
+	print(f'\n📊 Stored {len(stored_steps)} steps and {len(status_history)} status updates')
+	print('\nStored Steps:')
+	for step in stored_steps:
+		print(f'  {step["step_number"]}. {step["description"]}')
+
+	print('\nStatus History:')
+	for status in status_history:
+		print(f'  [{status["timestamp"]}] {status["status"]}')
+
+
+# Example 3: Real-time progress bar
+async def progress_bar_example():
+	"""Example: Show progress with a simple progress indicator."""
+	print('\n' + '=' * 80)
+	print('EXAMPLE 3: Progress Bar')
+	print('=' * 80)
+
+	step_count = {'count': 0}
+
+	def step_callback(step_data: dict):
+		"""Update progress bar as steps are recorded."""
+		step_count['count'] = step_data['step_number']
+		# Simple progress indicator
+		bar = '█' * step_data['step_number'] + '░' * (10 - step_data['step_number'])
+		print(f'\rProgress: [{bar}] Step {step_data["step_number"]}: {step_data["description"][:40]}...', end='')
+
+	def status_callback(status: str):
+		"""Display status updates."""
+		print(f'\n\n🔄 {status}')
+
+	# Initialize service
+	llm = ChatBrowserUse(model='bu-latest')
+	healing_service = HealingService(
+		llm=llm,
+		use_deterministic_conversion=True,
+		enable_variable_extraction=True,
+	)
+
+	# Generate workflow with callbacks
+	workflow = await healing_service.generate_workflow_from_prompt(
+		prompt='Go to example.com and extract the page title',
+		agent_llm=llm,
+		extraction_llm=llm,
+		use_cloud=False,
+		on_step_recorded=step_callback,
+		on_status_update=status_callback,
+	)
+
+	print(f'\n\n✅ Completed! Generated workflow with {step_count["count"]} steps')
+
+
+# Example 4: Real-world pattern for Browser-Use Cloud backend
+async def cloud_backend_pattern():
+	"""
+	Example: Pattern for Browser-Use Cloud backend integration.
+
+	This shows how to integrate with your database to store steps
+	in real-time for frontend polling.
+	"""
+	print('\n' + '=' * 80)
+	print('EXAMPLE 4: Browser-Use Cloud Backend Pattern')
+	print('=' * 80)
+
+	# Simulated workflow_id (would come from your database)
+	workflow_id = 'wf_123abc'
+	generation_metadata = {'steps': [], 'status_history': []}
+
+	async def step_callback(step_data: dict):
+		"""
+		Store step immediately in database for real-time display.
+
+		In your actual implementation, this would be:
+		async with await database.get_session() as session:
+		    workflow = await get_workflow(session, workflow_id)
+		    if workflow and workflow.generation_metadata:
+		        steps = workflow.generation_metadata.get('steps', [])
+		        steps.append(step_data)
+		        workflow.generation_metadata['steps'] = steps
+		        await session.commit()
+		"""
+		# Simulated database storage
+		generation_metadata['steps'].append(step_data)
+
+		print(f'💾 Stored step {step_data["step_number"]} to workflow {workflow_id}')
+		print(f'   Description: {step_data["description"]}')
+		print(f'   Type: {step_data["action_type"]}')
+		print(f'   Timestamp: {step_data["timestamp"]}')
+
+	async def status_callback(status: str):
+		"""Store status updates for display in the frontend."""
+		status_entry = {'timestamp': datetime.now().isoformat(), 'message': status}
+		generation_metadata['status_history'].append(status_entry)
+
+		print(f'ℹ️  Status update: {status}')
+
+	# Initialize service
+	llm = ChatBrowserUse(model='bu-latest')
+	healing_service = HealingService(
+		llm=llm,
+		use_deterministic_conversion=True,
+		enable_variable_extraction=True,
+	)
+
+	# Generate workflow with progress tracking
+	print(f'\n🚀 Starting workflow generation for {workflow_id}...')
+
+	workflow = await healing_service.generate_workflow_from_prompt(
+		prompt='Go to example.com and extract the page title',
+		agent_llm=llm,
+		extraction_llm=llm,
+		use_cloud=False,
+		on_step_recorded=lambda data: asyncio.create_task(step_callback(data)),
+		on_status_update=lambda status: asyncio.create_task(status_callback(status)),
+	)
+
+	# Display final metadata (what would be in your database)
+	print('\n' + '=' * 80)
+	print('FINAL DATABASE STATE')
+	print('=' * 80)
+	print(f'\nWorkflow ID: {workflow_id}')
+	print(f'Total Steps Recorded: {len(generation_metadata["steps"])}')
+	print(f'Total Status Updates: {len(generation_metadata["status_history"])}')
+
+	print('\n📋 Steps Timeline:')
+	for step in generation_metadata['steps']:
+		print(f'  [{step["timestamp"]}] Step {step["step_number"]}: {step["description"]}')
+
+	print('\n📊 Status Timeline:')
+	for status in generation_metadata['status_history']:
+		print(f'  [{status["timestamp"]}] {status["message"]}')
+
+	print(f'\n✅ Workflow generation complete! Final workflow has {len(workflow.steps)} steps')
+
+
+# Run all examples
+async def main():
+	"""Run all examples (commented out to avoid actual API calls)."""
+	print('Progress Tracking Examples')
+	print('=' * 80)
+	print('\nThese examples demonstrate different patterns for tracking')
+	print('workflow generation progress in real-time.')
+	print('\nNote: Examples are commented out to avoid actual API calls.')
+	print('Uncomment the examples you want to run.\n')
+
+	# Uncomment the examples you want to run:
+
+	# await simple_console_example()
+	# await database_storage_example()
+	# await progress_bar_example()
+	# await cloud_backend_pattern()
+
+	print('\n✅ Examples completed!')
+
+
+if __name__ == '__main__':
+	asyncio.run(main())

workflows/pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "workflow-use"
-version = "0.2.10"
+version = "0.2.11"
 authors = [{ name = "Gregor Zunic" }]
 description = "Create, edit, run deterministic workflows"
 readme = "README.md"