From f30e274aa308e13e9faa1f7efd96a9ad8fb0f071 Mon Sep 17 00:00:00 2001 From: Stefz29 Date: Sun, 15 Mar 2026 03:45:36 -0300 Subject: [PATCH 1/4] Add configurable local LLM provider, replacing hardcoded ChatBrowserUse Replace all hardcoded ChatBrowserUse cloud API calls with a configurable LLM provider factory (workflow_use/llm/provider.py) that reads from .env. Supports local inference via LM Studio/Ollama (OpenAI-compatible API) or Browser Use cloud as fallback. Unblocks the entire CLI and backend which previously crashed without a BROWSER_USE_API_KEY. - New module: workflow_use/llm/provider.py with get_llm() factory - Updated cli.py, backend/service.py, healing/_agent/controller.py - Added langchain-openai and python-dotenv as dependencies - Updated .env.example with LLM_PROVIDER, LLM_BASE_URL, LLM_MODEL config Co-Authored-By: Claude Opus 4.6 --- workflows/.env.example | 20 +- workflows/backend/service.py | 4 +- workflows/cli.py | 46 +- workflows/pyproject.toml | 2 + workflows/uv.lock | 4256 +++++++++-------- .../workflow_use/healing/_agent/controller.py | 6 - workflows/workflow_use/llm/__init__.py | 3 + workflows/workflow_use/llm/provider.py | 58 + 8 files changed, 2488 insertions(+), 1907 deletions(-) create mode 100644 workflows/workflow_use/llm/__init__.py create mode 100644 workflows/workflow_use/llm/provider.py diff --git a/workflows/.env.example b/workflows/.env.example index 48c1a6b6..fa35a2d7 100644 --- a/workflows/.env.example +++ b/workflows/.env.example @@ -1,3 +1,17 @@ -# We support all langchain models, openai only for demo purposes -OPENAI_API_KEY= -GROQ_API_KEY= \ No newline at end of file +# LLM Provider Configuration +# "local" = LM Studio / Ollama (OpenAI-compatible API) +# "browser_use" = Browser Use cloud API (requires BROWSER_USE_API_KEY) +LLM_PROVIDER=local + +# Local LLM server settings (used when LLM_PROVIDER=local) +LLM_BASE_URL=http://localhost:1234/v1 +LLM_API_KEY=not-needed +LLM_MODEL=bu-30b-a3b-preview +LLM_HEALING_MODEL=bu-30b-a3b-preview + +# Browser Use cloud API (only needed if LLM_PROVIDER=browser_use) +# BROWSER_USE_API_KEY= + +# Legacy keys (for direct OpenAI/Groq usage if desired) +# OPENAI_API_KEY= +# GROQ_API_KEY= diff --git a/workflows/backend/service.py b/workflows/backend/service.py index dc3eaa01..be695d79 100644 --- a/workflows/backend/service.py +++ b/workflows/backend/service.py @@ -7,9 +7,9 @@ import aiofiles import yaml from browser_use.browser.browser import Browser -from browser_use.llm import ChatBrowserUse from workflow_use.controller.service import WorkflowController +from workflow_use.llm import get_llm from workflow_use.workflow.service import Workflow from .views import ( @@ -42,7 +42,7 @@ def __init__(self) -> None: self.log_dir.mkdir(exist_ok=True, parents=True) # LLM / workflow executor - self.llm_instance = ChatBrowserUse(model='bu-latest') + self.llm_instance = get_llm('default') self.browser_instance = Browser() self.controller_instance = WorkflowController() diff --git a/workflows/cli.py b/workflows/cli.py index 49470857..ed576c0c 100644 --- a/workflows/cli.py +++ b/workflows/cli.py @@ -10,20 +10,16 @@ import pandas as pd import typer from browser_use import Browser -from browser_use.llm import ChatBrowserUse -from browser_use.llm.base import BaseChatModel from workflow_use.builder.service import BuilderService from workflow_use.controller.service import WorkflowController from workflow_use.healing.service import HealingService +from workflow_use.llm import get_llm from workflow_use.mcp.service import get_mcp_server -from workflow_use.recorder.service import RecordingService # Added import +from workflow_use.recorder.service import RecordingService from workflow_use.storage.service import WorkflowStorageService from workflow_use.workflow.service import Workflow -# Placeholder for recorder functionality -# from src.recorder.service import RecorderService - app = typer.Typer( name='workflow-cli', help='A CLI tool to create and run workflows.', @@ -31,24 +27,18 @@ no_args_is_help=True, ) -# Default LLM instance to None -llm_instance: BaseChatModel +# Initialize LLM via configurable provider (reads from .env) try: - llm_instance = ChatBrowserUse(model='bu-latest') - page_extraction_llm = ChatBrowserUse(model='bu-latest') + llm_instance = get_llm('default') + page_extraction_llm = get_llm('extraction') except Exception as e: - typer.secho(f'Error initializing LLM: {e}. Would you like to set your BROWSER_USE_API_KEY?', fg=typer.colors.RED) - set_browser_use_api_key = input('Set BROWSER_USE_API_KEY? (y/n): ') - if set_browser_use_api_key.lower() == 'y': - os.environ['BROWSER_USE_API_KEY'] = input('Enter your BROWSER_USE_API_KEY: ') - llm_instance = ChatBrowserUse(model='bu-latest') - page_extraction_llm = ChatBrowserUse(model='bu-latest') + typer.secho(f'Error initializing LLM: {e}', fg=typer.colors.RED) + typer.secho('Check your .env file — set LLM_PROVIDER, LLM_BASE_URL, and LLM_MODEL', fg=typer.colors.YELLOW) + llm_instance = None + page_extraction_llm = None builder_service = BuilderService(llm=llm_instance) if llm_instance else None -# recorder_service = RecorderService() # Placeholder -recording_service = ( - RecordingService() -) # Assuming RecordingService does not need LLM, or handle its potential None state if it does. +recording_service = RecordingService() healing_service = HealingService(llm=llm_instance) if llm_instance else None storage_service = WorkflowStorageService() @@ -1363,11 +1353,9 @@ async def _run_workflow_no_ai(): extraction_llm = None try: - from browser_use.llm import ChatBrowserUse - - dummy_llm = ChatBrowserUse(model='bu-latest') + dummy_llm = get_llm('default') if enable_extraction: - extraction_llm = ChatBrowserUse(model='bu-latest') + extraction_llm = get_llm('extraction') typer.secho('AI extraction enabled - will use LLM for extraction steps only.', fg=typer.colors.BLUE) except Exception as e: if enable_extraction: @@ -2145,10 +2133,10 @@ def mcp_server_command( typer.echo(typer.style('Starting MCP server...', bold=True)) typer.echo() # Add space - llm_instance = ChatBrowserUse(model='bu-latest') - page_extraction_llm = ChatBrowserUse(model='bu-latest') + mcp_llm = get_llm('default') + mcp_extraction_llm = get_llm('extraction') - mcp = get_mcp_server(llm_instance, page_extraction_llm=page_extraction_llm, workflow_dir='./tmp') + mcp = get_mcp_server(mcp_llm, page_extraction_llm=mcp_extraction_llm, workflow_dir='./tmp') mcp.run( transport='sse', @@ -2331,8 +2319,8 @@ def generate_workflow_from_task( typer.echo() # 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upload-time = "2025-09-14T22:18:19.088Z" }, ] diff --git a/workflows/workflow_use/healing/_agent/controller.py b/workflows/workflow_use/healing/_agent/controller.py index 6d442cc1..003d3a7d 100644 --- a/workflows/workflow_use/healing/_agent/controller.py +++ b/workflows/workflow_use/healing/_agent/controller.py @@ -1,18 +1,12 @@ import logging from browser_use import ActionResult, Controller -from browser_use.llm import ChatBrowserUse from browser_use.llm.base import BaseChatModel from pydantic import BaseModel, Field logger = logging.getLogger(__name__) -page_extraction_llm = ChatBrowserUse( - model='bu-latest', -) - - class ActionModel(BaseModel): variable: str = Field(description='Name of the variable/field this action relates to') action: str = Field(description='Description of the action that can be performed') diff --git a/workflows/workflow_use/llm/__init__.py b/workflows/workflow_use/llm/__init__.py new file mode 100644 index 00000000..0f81d57e --- /dev/null +++ b/workflows/workflow_use/llm/__init__.py @@ -0,0 +1,3 @@ +from .provider import get_llm + +__all__ = ['get_llm'] diff --git a/workflows/workflow_use/llm/provider.py b/workflows/workflow_use/llm/provider.py new file mode 100644 index 00000000..66257f52 --- /dev/null +++ b/workflows/workflow_use/llm/provider.py @@ -0,0 +1,58 @@ +"""Configurable LLM provider for workflow-use. + +Reads LLM configuration from environment variables (loaded from .env) +and returns the appropriate LLM instance. Supports local inference via +LM Studio / Ollama (OpenAI-compatible API) or the Browser Use cloud API. + +Environment variables: + LLM_PROVIDER - "local" (default) or "browser_use" + LLM_BASE_URL - Base URL for local server (default: http://localhost:1234/v1) + LLM_API_KEY - API key (default: "not-needed" for local) + LLM_MODEL - Model name for general tasks (default: bu-30b-a3b-preview) + LLM_HEALING_MODEL - Lighter model for healing/extraction (default: same as LLM_MODEL) +""" + +import os +from functools import lru_cache + +from dotenv import load_dotenv + +# Load .env from the workflows directory +load_dotenv() + + +def get_llm(purpose: str = 'default'): + """Returns a configured LLM instance based on .env settings. + + Args: + purpose: One of "default", "healing", "extraction", "generation". + "healing" and "extraction" use LLM_HEALING_MODEL (lighter model). + "default" and "generation" use LLM_MODEL. + + Returns: + A BaseChatModel instance (ChatOpenAI or ChatBrowserUse). + """ + provider = os.getenv('LLM_PROVIDER', 'local').lower() + + if provider == 'browser_use': + from browser_use.llm import ChatBrowserUse + return ChatBrowserUse(model='bu-latest') + + # Local provider (LM Studio, Ollama, or any OpenAI-compatible server) + from langchain_openai import ChatOpenAI + + base_url = os.getenv('LLM_BASE_URL', 'http://localhost:1234/v1') + api_key = os.getenv('LLM_API_KEY', 'not-needed') + default_model = os.getenv('LLM_MODEL', 'bu-30b-a3b-preview') + healing_model = os.getenv('LLM_HEALING_MODEL', default_model) + + if purpose in ('healing', 'extraction'): + model = healing_model + else: + model = default_model + + return ChatOpenAI( + model=model, + base_url=base_url, + api_key=api_key, + ) From 59e9f85d3b0df8da19045b82070d27cce525de9a Mon Sep 17 00:00:00 2001 From: Stefz29 Date: Sun, 15 Mar 2026 03:50:55 -0300 Subject: [PATCH 2/4] Add LLM-powered self-healing for failed workflow steps When a deterministic step fails (element not found, selector stale), the system now: 1. Captures a screenshot of the current page 2. Sends screenshot + step context to the LLM (vision) 3. LLM diagnoses the failure and suggests corrected selectors 4. Retries the step with corrections (up to 2 attempts) 5. Persists successful fixes back to the workflow YAML file New module: workflow_use/healing/step_healer.py Modified: workflow_use/workflow/service.py (enable_self_healing param, retry loop) Co-Authored-By: Claude Opus 4.6 --- workflows/workflow_use/healing/step_healer.py | 277 ++++++++++++++++++ workflows/workflow_use/workflow/service.py | 95 +++++- 2 files changed, 370 insertions(+), 2 deletions(-) create mode 100644 workflows/workflow_use/healing/step_healer.py diff --git a/workflows/workflow_use/healing/step_healer.py b/workflows/workflow_use/healing/step_healer.py new file mode 100644 index 00000000..3ee5925f --- /dev/null +++ b/workflows/workflow_use/healing/step_healer.py @@ -0,0 +1,277 @@ +"""Step-level self-healing for workflow execution. + +When a deterministic step fails (element not found, action error), this module: +1. Captures a screenshot of the current page state +2. Sends the screenshot + step context to the LLM +3. Asks the LLM to identify the correct element or corrective action +4. Returns a corrected step that can be retried +5. Optionally persists the fix back to the workflow file +""" + +import base64 +import json +import logging +from pathlib import Path +from typing import Any, Dict, Optional + +import yaml +from browser_use.llm.base import BaseChatModel + +logger = logging.getLogger(__name__) + +HEALING_SYSTEM_PROMPT = """You are a browser automation self-healing agent. A workflow step has failed during execution. You will be shown: + +1. A screenshot of the current page state +2. The step that failed (type, target_text, selectors) +3. The error message + +Your job is to analyze the screenshot and determine WHY the step failed, then provide a corrected step. + +Common failure reasons: +- The element's text changed (e.g., "Log In" became "Sign In") +- The element moved to a different location on the page +- The page hasn't finished loading yet +- A popup/modal is blocking the element +- The element is inside an iframe +- The page layout changed after an update + +Respond with a JSON object containing: +{ + "diagnosis": "Brief explanation of why the step failed", + "corrected_target_text": "The correct visible text for the element (null if unchanged)", + "corrected_css_selector": "A CSS selector for the element (null if not applicable)", + "corrected_xpath": "An XPath for the element (null if not applicable)", + "action_override": "If the action type should change (null if unchanged)", + "wait_before_retry": 0, + "confidence": 0.8, + "page_state_issue": "none|loading|popup|iframe|navigation_needed" +} + +IMPORTANT: +- Look at the ACTUAL screenshot carefully — what elements are visible on the page? +- Prefer target_text corrections (most resilient to future changes) +- Only suggest CSS/XPath if the element has no visible text +- Set confidence to how sure you are (0.0-1.0) +- If a popup/modal is blocking, set page_state_issue accordingly""" + + +class StepHealer: + """Heals failed workflow steps using LLM vision analysis.""" + + def __init__( + self, + llm: BaseChatModel, + max_healing_attempts: int = 2, + min_confidence: float = 0.5, + persist_fixes: bool = True, + ): + self.llm = llm + self.max_healing_attempts = max_healing_attempts + self.min_confidence = min_confidence + self.persist_fixes = persist_fixes + self._healing_log: list[Dict[str, Any]] = [] + + async def heal_step( + self, + step: Any, + step_index: int, + error: Exception, + browser: Any, + workflow_path: Optional[str] = None, + ) -> Optional[Dict[str, Any]]: + """Attempt to heal a failed step using LLM vision analysis. + + Args: + step: The WorkflowStep that failed + step_index: Index of the step in the workflow + error: The exception that was raised + browser: Browser instance for screenshot capture + workflow_path: Path to workflow file for persisting fixes + + Returns: + Dict with corrected step fields, or None if healing failed. + """ + logger.info(f'🩺 Self-healing step {step_index + 1}: {error}') + + # Capture screenshot + screenshot_b64 = await self._capture_screenshot(browser) + if not screenshot_b64: + logger.warning('Could not capture screenshot for healing') + return None + + # Build step context + step_context = self._build_step_context(step, step_index, error) + + # Ask LLM to diagnose and fix + correction = await self._ask_llm_for_correction(screenshot_b64, step_context) + if not correction: + return None + + # Check confidence threshold + confidence = correction.get('confidence', 0) + if confidence < self.min_confidence: + logger.info(f'🩺 Healing confidence too low ({confidence:.0%} < {self.min_confidence:.0%}), skipping') + return None + + logger.info(f'🩺 Healing diagnosis: {correction.get("diagnosis", "unknown")}') + logger.info(f'🩺 Confidence: {confidence:.0%}') + + # Build corrected fields + corrected_fields = self._build_corrected_fields(step, correction) + + if not corrected_fields: + logger.info('🩺 No corrections suggested by LLM') + return None + + # Log the healing + healing_entry = { + 'step_index': step_index, + 'original_error': str(error), + 'diagnosis': correction.get('diagnosis'), + 'corrections': corrected_fields, + 'confidence': confidence, + } + self._healing_log.append(healing_entry) + + # Persist fixes to workflow file + if self.persist_fixes and workflow_path and corrected_fields: + await self._persist_fix(workflow_path, step_index, corrected_fields) + + return corrected_fields + + async def _capture_screenshot(self, browser: Any) -> Optional[str]: + """Capture a screenshot and return as base64 string.""" + try: + page = await browser.get_current_page() + screenshot_bytes = await page.screenshot(full_page=False) + return base64.b64encode(screenshot_bytes).decode('utf-8') + except Exception as e: + logger.warning(f'Screenshot capture failed: {e}') + return None + + def _build_step_context(self, step: Any, step_index: int, error: Exception) -> str: + """Build a text description of the failed step for the LLM.""" + step_dict = step.model_dump(exclude_none=True) if hasattr(step, 'model_dump') else {} + return json.dumps( + { + 'step_index': step_index, + 'step_type': step_dict.get('type', 'unknown'), + 'target_text': step_dict.get('target_text'), + 'css_selector': step_dict.get('cssSelector'), + 'xpath': step_dict.get('xpath'), + 'value': step_dict.get('value'), + 'description': step_dict.get('description'), + 'error_message': str(error), + }, + indent=2, + ) + + async def _ask_llm_for_correction(self, screenshot_b64: str, step_context: str) -> Optional[Dict[str, Any]]: + """Send screenshot + context to LLM and parse the correction response.""" + try: + messages = [ + {'role': 'system', 'content': HEALING_SYSTEM_PROMPT}, + { + 'role': 'user', + 'content': [ + { + 'type': 'text', + 'text': f'This workflow step failed. Please analyze the screenshot and suggest a correction.\n\nFailed step:\n{step_context}', + }, + { + 'type': 'image_url', + 'image_url': {'url': f'data:image/png;base64,{screenshot_b64}'}, + }, + ], + }, + ] + + response = await self.llm.ainvoke(messages) + content = response.content if hasattr(response, 'content') else str(response) + + # Parse JSON from response (handle markdown code blocks) + json_str = content + if '```json' in json_str: + json_str = json_str.split('```json')[1].split('```')[0] + elif '```' in json_str: + json_str = json_str.split('```')[1].split('```')[0] + + return json.loads(json_str.strip()) + + except Exception as e: + logger.warning(f'LLM healing request failed: {e}') + return None + + def _build_corrected_fields(self, step: Any, correction: Dict[str, Any]) -> Dict[str, Any]: + """Build a dict of corrected fields from the LLM's response.""" + fields = {} + + if correction.get('corrected_target_text'): + fields['target_text'] = correction['corrected_target_text'] + + if correction.get('corrected_css_selector'): + fields['cssSelector'] = correction['corrected_css_selector'] + + if correction.get('corrected_xpath'): + fields['xpath'] = correction['corrected_xpath'] + + if correction.get('action_override'): + fields['type'] = correction['action_override'] + + if correction.get('wait_before_retry', 0) > 0: + fields['wait_before_retry'] = correction['wait_before_retry'] + + if correction.get('page_state_issue') and correction['page_state_issue'] != 'none': + fields['page_state_issue'] = correction['page_state_issue'] + + return fields + + async def _persist_fix(self, workflow_path: str, step_index: int, corrected_fields: Dict[str, Any]) -> None: + """Write corrected selectors back to the workflow YAML/JSON file.""" + try: + path = Path(workflow_path) + if not path.exists(): + logger.warning(f'Cannot persist fix: workflow file not found at {path}') + return + + # Load the workflow + with open(path, 'r') as f: + if path.suffix in ['.yaml', '.yml']: + workflow_data = yaml.safe_load(f) + else: + workflow_data = json.load(f) + + steps = workflow_data.get('steps', []) + if step_index >= len(steps): + logger.warning(f'Cannot persist fix: step index {step_index} out of range') + return + + # Apply corrections (only persistent fields, not transient ones) + persistent_fields = {'target_text', 'cssSelector', 'xpath', 'type'} + applied = [] + for key, value in corrected_fields.items(): + if key in persistent_fields: + old_value = steps[step_index].get(key) + steps[step_index][key] = value + applied.append(f'{key}: {old_value!r} → {value!r}') + + if not applied: + return + + # Write back + with open(path, 'w') as f: + if path.suffix in ['.yaml', '.yml']: + yaml.dump(workflow_data, f, default_flow_style=False, sort_keys=False, allow_unicode=True) + else: + json.dump(workflow_data, f, indent=2) + + logger.info(f'🩺 Persisted healing fix to {path.name}:') + for change in applied: + logger.info(f' Step {step_index + 1}: {change}') + + except Exception as e: + logger.warning(f'Failed to persist healing fix: {e}') + + def get_healing_log(self) -> list[Dict[str, Any]]: + """Return the log of all healing attempts in this session.""" + return self._healing_log.copy() diff --git a/workflows/workflow_use/workflow/service.py b/workflows/workflow_use/workflow/service.py index 1a6c325b..e0fa05e6 100644 --- a/workflows/workflow_use/workflow/service.py +++ b/workflows/workflow_use/workflow/service.py @@ -24,6 +24,7 @@ WorkflowInputSchemaDefinition, WorkflowStep, ) +from workflow_use.healing.step_healer import StepHealer from workflow_use.workflow.element_finder import ElementFinder from workflow_use.workflow.prompts import AGENT_STEP_SYSTEM_PROMPT, STRUCTURED_OUTPUT_PROMPT from workflow_use.workflow.step_agent.controller import WorkflowStepAgentController @@ -52,6 +53,8 @@ def __init__( debug: bool = False, debug_log_folder: str | Path | None = None, step_wait_time: float | None = None, + enable_self_healing: bool = True, + workflow_path: str | Path | None = None, ) -> None: """Initialize a new Workflow instance from a schema object. @@ -65,6 +68,8 @@ def __init__( debug: Whether to enable debug mode (captures screenshots for each step) debug_log_folder: Custom folder path for debug logs and screenshots (default: ./logs/workflow_debug) step_wait_time: Time to wait between steps in seconds (default: uses workflow's default_wait_time or 0.1) + enable_self_healing: Whether to use LLM vision to heal failed steps (default: True) + workflow_path: Path to workflow file for persisting healing fixes Raises: ValueError: If the workflow schema is invalid (though Pydantic handles most). @@ -96,6 +101,18 @@ def __init__( else: self.step_wait_time = 0.1 + # Self-healing settings + self.enable_self_healing = enable_self_healing + self.workflow_path = str(workflow_path) if workflow_path else None + self._step_healer: StepHealer | None = None + if enable_self_healing and llm: + healing_llm = page_extraction_llm or llm + self._step_healer = StepHealer( + llm=healing_llm, + max_healing_attempts=2, + persist_fixes=workflow_path is not None, + ) + # Initialize multi-strategy element finder self.element_finder = ElementFinder() @@ -118,6 +135,7 @@ def load_from_file( debug: bool = False, debug_log_folder: str | Path | None = None, step_wait_time: float = 0.1, + enable_self_healing: bool = True, ) -> Workflow: """Load a workflow from a file.""" with open(file_path, 'r', encoding='utf-8') as f: @@ -133,6 +151,8 @@ def load_from_file( debug=debug, debug_log_folder=debug_log_folder, step_wait_time=step_wait_time, + enable_self_healing=enable_self_healing, + workflow_path=file_path, ) # --- Runners --- @@ -848,6 +868,38 @@ async def _capture_debug_screenshot(self, step_index: int, step_description: str except Exception as e: logger.warning(f'Failed to capture debug screenshot: {e}') + def _apply_healing_corrections(self, step: WorkflowStep, corrections: Dict[str, Any]) -> WorkflowStep: + """Apply healing corrections to a workflow step, returning a new corrected step.""" + step_dict = step.model_dump(exclude_none=True) + + for key, value in corrections.items(): + step_dict[key] = value + + # Reconstruct the step using the schema's discriminated union + step_type = step_dict.get('type') + from workflow_use.schema.views import ( + ClickStep, + InputStep, + KeyPressStep, + NavigationStep, + SelectChangeStep, + ) + + type_map = { + 'click': ClickStep, + 'input': InputStep, + 'key_press': KeyPressStep, + 'navigation': NavigationStep, + 'select_change': SelectChangeStep, + } + + step_class = type_map.get(step_type) + if step_class: + return step_class(**step_dict) + + # Fallback: return original step (corrections couldn't be applied) + return step + async def run( self, inputs: dict[str, Any] | None = None, @@ -915,7 +967,7 @@ async def run( # Resolve placeholders using the current context (works on the dictionary) step_resolved = self._resolve_placeholders(step_dict) - # Execute step using the unified _execute_step method + # Execute step with self-healing retry on failure try: result = await self._execute_step(step_index, step_resolved) @@ -924,7 +976,46 @@ async def run( except Exception as e: # Capture screenshot on error (if debug enabled) await self._capture_debug_screenshot(step_index, step_description, prefix='error') - raise # Re-raise the exception after capturing screenshot + + # Attempt self-healing if enabled + if self._step_healer and isinstance(step_resolved, DeterministicWorkflowStep): + healed = False + for attempt in range(self._step_healer.max_healing_attempts): + logger.info(f'🩺 Healing attempt {attempt + 1}/{self._step_healer.max_healing_attempts} for step {step_index + 1}') + correction = await self._step_healer.heal_step( + step=step_resolved, + step_index=step_index, + error=e, + browser=self.browser, + workflow_path=self.workflow_path, + ) + + if not correction: + logger.info('🩺 Healer returned no correction, giving up') + break + + # Handle page state issues (wait for loading, dismiss popups, etc.) + page_issue = correction.pop('page_state_issue', None) + wait_time = correction.pop('wait_before_retry', 0) + if page_issue == 'loading' or wait_time > 0: + await asyncio.sleep(max(wait_time, 2)) + + # Apply corrections to the resolved step + step_corrected = self._apply_healing_corrections(step_resolved, correction) + + try: + result = await self._execute_step(step_index, step_corrected) + logger.info(f'🩺 Step {step_index + 1} healed successfully on attempt {attempt + 1}!') + healed = True + break + except Exception as retry_error: + logger.warning(f'🩺 Healing attempt {attempt + 1} failed: {retry_error}') + e = retry_error # Update error for next healing attempt + + if not healed: + raise # Re-raise the last exception + else: + raise # No healer available, re-raise results.append(result) # Persist outputs using the resolved step dictionary From 7cd77571c8817f059da4c1e7e325a4f71f80f30b Mon Sep 17 00:00:00 2001 From: Stefz29 Date: Sun, 15 Mar 2026 03:55:54 -0300 Subject: [PATCH 3/4] Upgrade self-healing with autoresearch-mlx patterns Integrates key patterns from autoresearch-mlx into the step healer: - Snapshot/revert: saves workflow YAML before healing, reverts on failure (mirrors autoresearch's git reset --hard on worse results) - TSV results tracking: logs every attempt to logs/healing/healing_results.tsv with timestamp, step, status (keep/discard/crash/skip), confidence, timing - Fail-fast sanity checks: skips unhealable errors (browser crash, OOM) without wasting LLM calls (mirrors autoresearch's loss > 100 check) - Exponential backoff: 1s, 2s, 4s between retry attempts (mirrors autoresearch's 2**attempt download retry pattern) - Previous attempts context: sends failed corrections to LLM so it doesn't repeat the same fix (mirrors autoresearch's results.tsv history) - Session summary: logs keep/discard/crash stats at workflow end - mark_healing_outcome(): caller confirms if fix actually worked before persisting (mirrors autoresearch's keep-or-revert decision) Co-Authored-By: Claude Opus 4.6 --- workflows/workflow_use/healing/step_healer.py | 490 ++++++++++++++---- workflows/workflow_use/workflow/service.py | 28 +- 2 files changed, 406 insertions(+), 112 deletions(-) diff --git a/workflows/workflow_use/healing/step_healer.py b/workflows/workflow_use/healing/step_healer.py index 3ee5925f..2954a87b 100644 --- a/workflows/workflow_use/healing/step_healer.py +++ b/workflows/workflow_use/healing/step_healer.py @@ -1,75 +1,231 @@ """Step-level self-healing for workflow execution. -When a deterministic step fails (element not found, action error), this module: -1. Captures a screenshot of the current page state -2. Sends the screenshot + step context to the LLM -3. Asks the LLM to identify the correct element or corrective action -4. Returns a corrected step that can be retried -5. Optionally persists the fix back to the workflow file +Inspired by the autoresearch-mlx self-improvement loop: +- Snapshot before healing, revert if fix makes things worse +- TSV-based results tracking for every healing attempt +- Fail-fast sanity checks before expensive LLM calls +- Exponential backoff on retries +- Single ground-truth metric: did the step actually succeed? + +When a deterministic step fails (element not found, action error): +1. Sanity check — is this a healable failure? (fail-fast) +2. Snapshot the current workflow state (for revert) +3. Capture a screenshot of the current page +4. Send screenshot + step context to the LLM +5. LLM diagnoses and suggests a corrected step +6. Retry with correction +7. If success: persist fix to workflow file, log as "keep" +8. If failure: revert workflow file, log as "discard" """ import base64 +import csv import json import logging +import shutil +import time +from datetime import datetime, timezone from pathlib import Path -from typing import Any, Dict, Optional +from typing import Any, Dict, List, Optional import yaml from browser_use.llm.base import BaseChatModel logger = logging.getLogger(__name__) +# --- Healable error patterns (fail-fast filter) --- +HEALABLE_PATTERNS = [ + 'not found', + 'target text', + 'element', + 'selector', + 'timeout', + 'no such element', + 'stale', + 'not visible', + 'not interactable', + 'click intercepted', +] + +UNHEALABLE_PATTERNS = [ + 'browser crashed', + 'connection refused', + 'protocol error', + 'session closed', + 'out of memory', + 'permission denied', +] + HEALING_SYSTEM_PROMPT = """You are a browser automation self-healing agent. A workflow step has failed during execution. You will be shown: 1. A screenshot of the current page state -2. The step that failed (type, target_text, selectors) -3. The error message +2. The step that failed (type, target_text, selectors, error) +3. Previous healing attempts for this step (if any) -Your job is to analyze the screenshot and determine WHY the step failed, then provide a corrected step. +Your job: analyze the screenshot and determine WHY the step failed, then provide a corrected step. Common failure reasons: -- The element's text changed (e.g., "Log In" became "Sign In") -- The element moved to a different location on the page -- The page hasn't finished loading yet -- A popup/modal is blocking the element -- The element is inside an iframe -- The page layout changed after an update - -Respond with a JSON object containing: +- Element text changed (e.g., "Log In" → "Sign In") +- Element moved or is in a different container +- Page hasn't finished loading / dynamic content not yet rendered +- Popup/modal/cookie banner blocking the element +- Element is inside an iframe +- Page layout changed after a site update +- Wrong page — navigation didn't complete + +Respond ONLY with a JSON object (no markdown, no explanation outside the JSON): { "diagnosis": "Brief explanation of why the step failed", - "corrected_target_text": "The correct visible text for the element (null if unchanged)", - "corrected_css_selector": "A CSS selector for the element (null if not applicable)", - "corrected_xpath": "An XPath for the element (null if not applicable)", - "action_override": "If the action type should change (null if unchanged)", + "corrected_target_text": "The correct visible text for the element, or null if unchanged", + "corrected_css_selector": "A CSS selector if text-based matching won't work, or null", + "corrected_xpath": "An XPath selector as last resort, or null", + "action_override": "New action type if it should change (e.g., 'click' → 'key_press'), or null", "wait_before_retry": 0, "confidence": 0.8, "page_state_issue": "none|loading|popup|iframe|navigation_needed" } -IMPORTANT: -- Look at the ACTUAL screenshot carefully — what elements are visible on the page? -- Prefer target_text corrections (most resilient to future changes) -- Only suggest CSS/XPath if the element has no visible text -- Set confidence to how sure you are (0.0-1.0) -- If a popup/modal is blocking, set page_state_issue accordingly""" +Rules: +- Look at the ACTUAL screenshot — describe what you see before suggesting fixes +- Prefer corrected_target_text (most resilient to future DOM changes) +- Only use CSS/XPath when the element has no visible text +- Set confidence honestly (0.0–1.0). If you're guessing, say 0.3 +- If the page looks completely wrong (wrong URL, error page), set confidence to 0.1 +- If a popup/modal is blocking, set page_state_issue="popup" and confidence high""" + + +class HealingResult: + """Structured result of a healing attempt, modeled after autoresearch-mlx results.tsv.""" + + __slots__ = ('step_index', 'attempt', 'status', 'confidence', 'duration_ms', 'diagnosis', 'corrections', 'timestamp') + + def __init__( + self, + step_index: int, + attempt: int, + status: str, # "keep", "discard", "crash", "skip" + confidence: float, + duration_ms: int, + diagnosis: str, + corrections: Dict[str, Any], + timestamp: str, + ): + self.step_index = step_index + self.attempt = attempt + self.status = status + self.confidence = confidence + self.duration_ms = duration_ms + self.diagnosis = diagnosis + self.corrections = corrections + self.timestamp = timestamp class StepHealer: - """Heals failed workflow steps using LLM vision analysis.""" + """Heals failed workflow steps using LLM vision analysis. + + Follows the autoresearch-mlx pattern: + - Snapshot/revert: saves workflow state before healing, reverts on failure + - Results tracking: logs every attempt to a TSV file + - Fail-fast: skips unhealable errors without wasting LLM calls + - Exponential backoff: 1s, 2s, 4s between retry attempts + """ def __init__( self, llm: BaseChatModel, - max_healing_attempts: int = 2, - min_confidence: float = 0.5, + max_healing_attempts: int = 3, + min_confidence: float = 0.4, persist_fixes: bool = True, + log_dir: str | Path | None = None, ): self.llm = llm self.max_healing_attempts = max_healing_attempts self.min_confidence = min_confidence self.persist_fixes = persist_fixes - self._healing_log: list[Dict[str, Any]] = [] + self.log_dir = Path(log_dir) if log_dir else Path('./logs/healing') + self.log_dir.mkdir(parents=True, exist_ok=True) + + # Results tracking (autoresearch-mlx pattern: results.tsv) + self._results: List[HealingResult] = [] + self._results_file = self.log_dir / 'healing_results.tsv' + self._init_results_file() + + # Session stats + self.total_healed = 0 + self.total_failed = 0 + + def _init_results_file(self) -> None: + """Initialize the TSV results file with headers if it doesn't exist.""" + if not self._results_file.exists(): + with open(self._results_file, 'w', newline='') as f: + writer = csv.writer(f, delimiter='\t') + writer.writerow(['timestamp', 'step_index', 'attempt', 'status', 'confidence', 'duration_ms', 'diagnosis']) + + def _log_result(self, result: HealingResult) -> None: + """Append a healing result to the TSV log and in-memory list.""" + self._results.append(result) + try: + with open(self._results_file, 'a', newline='') as f: + writer = csv.writer(f, delimiter='\t') + writer.writerow([ + result.timestamp, + result.step_index, + result.attempt, + result.status, + f'{result.confidence:.2f}', + result.duration_ms, + result.diagnosis[:100], # Truncate for readability + ]) + except Exception as e: + logger.warning(f'Failed to write healing result to TSV: {e}') + + def _is_healable(self, error: Exception) -> bool: + """Fail-fast: check if this error is worth attempting to heal.""" + error_str = str(error).lower() + + # Reject unhealable errors immediately + for pattern in UNHEALABLE_PATTERNS: + if pattern in error_str: + logger.info(f'🩺 Skipping healing — unhealable error pattern: "{pattern}"') + return False + + # Accept known healable patterns + for pattern in HEALABLE_PATTERNS: + if pattern in error_str: + return True + + # Default: attempt healing for unknown errors (conservative) + return True + + def _snapshot_workflow(self, workflow_path: str) -> Optional[str]: + """Snapshot the workflow file before healing (for revert on failure). + + Returns the snapshot path, or None if snapshot failed. + """ + try: + path = Path(workflow_path) + if not path.exists(): + return None + snapshot_path = str(path) + '.healing_snapshot' + shutil.copy2(str(path), snapshot_path) + return snapshot_path + except Exception as e: + logger.warning(f'Failed to create workflow snapshot: {e}') + return None + + def _revert_workflow(self, workflow_path: str, snapshot_path: str) -> None: + """Revert workflow file to its pre-healing snapshot.""" + try: + shutil.copy2(snapshot_path, workflow_path) + Path(snapshot_path).unlink(missing_ok=True) + logger.info(f'🩺 Reverted workflow to pre-healing state') + except Exception as e: + logger.warning(f'Failed to revert workflow snapshot: {e}') + + def _cleanup_snapshot(self, snapshot_path: Optional[str]) -> None: + """Remove snapshot file after successful healing.""" + if snapshot_path: + Path(snapshot_path).unlink(missing_ok=True) async def heal_step( self, @@ -78,6 +234,7 @@ async def heal_step( error: Exception, browser: Any, workflow_path: Optional[str] = None, + previous_attempts: Optional[List[Dict[str, Any]]] = None, ) -> Optional[Dict[str, Any]]: """Attempt to heal a failed step using LLM vision analysis. @@ -87,57 +244,136 @@ async def heal_step( error: The exception that was raised browser: Browser instance for screenshot capture workflow_path: Path to workflow file for persisting fixes + previous_attempts: List of prior healing attempts for context Returns: - Dict with corrected step fields, or None if healing failed. + Dict with corrected step fields, or None if healing failed/skipped. """ + t_start = time.monotonic() + + # Fail-fast sanity check + if not self._is_healable(error): + self._log_result(HealingResult( + step_index=step_index, attempt=0, status='skip', + confidence=0.0, duration_ms=0, + diagnosis=f'Unhealable error: {str(error)[:80]}', + corrections={}, + timestamp=datetime.now(timezone.utc).isoformat(), + )) + return None + logger.info(f'🩺 Self-healing step {step_index + 1}: {error}') # Capture screenshot screenshot_b64 = await self._capture_screenshot(browser) if not screenshot_b64: logger.warning('Could not capture screenshot for healing') + self._log_result(HealingResult( + step_index=step_index, attempt=0, status='crash', + confidence=0.0, duration_ms=int((time.monotonic() - t_start) * 1000), + diagnosis='Screenshot capture failed', + corrections={}, + timestamp=datetime.now(timezone.utc).isoformat(), + )) return None - # Build step context - step_context = self._build_step_context(step, step_index, error) + # Build step context with previous attempts (helps LLM avoid repeating failed fixes) + step_context = self._build_step_context(step, step_index, error, previous_attempts) # Ask LLM to diagnose and fix correction = await self._ask_llm_for_correction(screenshot_b64, step_context) + duration_ms = int((time.monotonic() - t_start) * 1000) + if not correction: + self._log_result(HealingResult( + step_index=step_index, attempt=len(previous_attempts or []) + 1, + status='crash', confidence=0.0, duration_ms=duration_ms, + diagnosis='LLM returned no correction', + corrections={}, + timestamp=datetime.now(timezone.utc).isoformat(), + )) return None # Check confidence threshold confidence = correction.get('confidence', 0) + diagnosis = correction.get('diagnosis', 'unknown') + if confidence < self.min_confidence: logger.info(f'🩺 Healing confidence too low ({confidence:.0%} < {self.min_confidence:.0%}), skipping') + self._log_result(HealingResult( + step_index=step_index, attempt=len(previous_attempts or []) + 1, + status='discard', confidence=confidence, duration_ms=duration_ms, + diagnosis=f'Low confidence: {diagnosis}', + corrections={}, + timestamp=datetime.now(timezone.utc).isoformat(), + )) return None - logger.info(f'🩺 Healing diagnosis: {correction.get("diagnosis", "unknown")}') + logger.info(f'🩺 Diagnosis: {diagnosis}') logger.info(f'🩺 Confidence: {confidence:.0%}') # Build corrected fields corrected_fields = self._build_corrected_fields(step, correction) if not corrected_fields: - logger.info('🩺 No corrections suggested by LLM') + logger.info('🩺 No actionable corrections from LLM') + self._log_result(HealingResult( + step_index=step_index, attempt=len(previous_attempts or []) + 1, + status='discard', confidence=confidence, duration_ms=duration_ms, + diagnosis=f'No corrections: {diagnosis}', + corrections={}, + timestamp=datetime.now(timezone.utc).isoformat(), + )) return None - # Log the healing - healing_entry = { - 'step_index': step_index, - 'original_error': str(error), - 'diagnosis': correction.get('diagnosis'), - 'corrections': corrected_fields, - 'confidence': confidence, - } - self._healing_log.append(healing_entry) + # Log as pending (will be updated to keep/discard by caller) + self._log_result(HealingResult( + step_index=step_index, attempt=len(previous_attempts or []) + 1, + status='pending', confidence=confidence, duration_ms=duration_ms, + diagnosis=diagnosis, + corrections=corrected_fields, + timestamp=datetime.now(timezone.utc).isoformat(), + )) - # Persist fixes to workflow file - if self.persist_fixes and workflow_path and corrected_fields: + return corrected_fields + + def mark_healing_outcome(self, step_index: int, success: bool) -> None: + """Update the last healing result for this step with the actual outcome. + + Called by the Workflow.run() loop after retrying with corrections. + """ + # Find the last pending result for this step + for result in reversed(self._results): + if result.step_index == step_index and result.status == 'pending': + result.status = 'keep' if success else 'discard' + if success: + self.total_healed += 1 + logger.info(f'🩺 ✅ Step {step_index + 1} healed successfully (total healed: {self.total_healed})') + else: + self.total_failed += 1 + logger.info(f'🩺 ❌ Healing failed for step {step_index + 1} (total failed: {self.total_failed})') + break + + async def persist_if_healed(self, workflow_path: str, step_index: int, corrected_fields: Dict[str, Any]) -> None: + """Persist a successful healing fix to the workflow file. + + Only called after the corrected step has been verified to work. + Uses snapshot/revert pattern from autoresearch-mlx. + """ + if not self.persist_fixes: + return + + snapshot_path = self._snapshot_workflow(workflow_path) + + try: await self._persist_fix(workflow_path, step_index, corrected_fields) + except Exception as e: + logger.warning(f'Failed to persist fix, reverting: {e}') + if snapshot_path: + self._revert_workflow(workflow_path, snapshot_path) + return - return corrected_fields + self._cleanup_snapshot(snapshot_path) async def _capture_screenshot(self, browser: Any) -> Optional[str]: """Capture a screenshot and return as base64 string.""" @@ -149,22 +385,36 @@ async def _capture_screenshot(self, browser: Any) -> Optional[str]: logger.warning(f'Screenshot capture failed: {e}') return None - def _build_step_context(self, step: Any, step_index: int, error: Exception) -> str: + def _build_step_context( + self, step: Any, step_index: int, error: Exception, + previous_attempts: Optional[List[Dict[str, Any]]] = None, + ) -> str: """Build a text description of the failed step for the LLM.""" step_dict = step.model_dump(exclude_none=True) if hasattr(step, 'model_dump') else {} - return json.dumps( - { - 'step_index': step_index, - 'step_type': step_dict.get('type', 'unknown'), - 'target_text': step_dict.get('target_text'), - 'css_selector': step_dict.get('cssSelector'), - 'xpath': step_dict.get('xpath'), - 'value': step_dict.get('value'), - 'description': step_dict.get('description'), - 'error_message': str(error), - }, - indent=2, - ) + + context = { + 'step_index': step_index, + 'step_type': step_dict.get('type', 'unknown'), + 'target_text': step_dict.get('target_text'), + 'css_selector': step_dict.get('cssSelector'), + 'xpath': step_dict.get('xpath'), + 'value': step_dict.get('value'), + 'description': step_dict.get('description'), + 'error_message': str(error), + } + + # Include previous failed attempts so LLM doesn't repeat them + if previous_attempts: + context['previous_healing_attempts'] = [ + { + 'attempt': i + 1, + 'corrections': att.get('corrections', {}), + 'result': 'failed', + } + for i, att in enumerate(previous_attempts) + ] + + return json.dumps(context, indent=2) async def _ask_llm_for_correction(self, screenshot_b64: str, step_context: str) -> Optional[Dict[str, Any]]: """Send screenshot + context to LLM and parse the correction response.""" @@ -176,7 +426,7 @@ async def _ask_llm_for_correction(self, screenshot_b64: str, step_context: str) 'content': [ { 'type': 'text', - 'text': f'This workflow step failed. Please analyze the screenshot and suggest a correction.\n\nFailed step:\n{step_context}', + 'text': f'This workflow step failed. Analyze the screenshot and suggest a correction.\n\nFailed step:\n{step_context}', }, { 'type': 'image_url', @@ -198,6 +448,9 @@ async def _ask_llm_for_correction(self, screenshot_b64: str, step_context: str) return json.loads(json_str.strip()) + except json.JSONDecodeError as e: + logger.warning(f'LLM returned unparseable response: {e}') + return None except Exception as e: logger.warning(f'LLM healing request failed: {e}') return None @@ -228,50 +481,65 @@ def _build_corrected_fields(self, step: Any, correction: Dict[str, Any]) -> Dict async def _persist_fix(self, workflow_path: str, step_index: int, corrected_fields: Dict[str, Any]) -> None: """Write corrected selectors back to the workflow YAML/JSON file.""" - try: - path = Path(workflow_path) - if not path.exists(): - logger.warning(f'Cannot persist fix: workflow file not found at {path}') - return - - # Load the workflow - with open(path, 'r') as f: - if path.suffix in ['.yaml', '.yml']: - workflow_data = yaml.safe_load(f) - else: - workflow_data = json.load(f) - - steps = workflow_data.get('steps', []) - if step_index >= len(steps): - logger.warning(f'Cannot persist fix: step index {step_index} out of range') - return - - # Apply corrections (only persistent fields, not transient ones) - persistent_fields = {'target_text', 'cssSelector', 'xpath', 'type'} - applied = [] - for key, value in corrected_fields.items(): - if key in persistent_fields: - old_value = steps[step_index].get(key) - steps[step_index][key] = value - applied.append(f'{key}: {old_value!r} → {value!r}') - - if not applied: - return - - # Write back - with open(path, 'w') as f: - if path.suffix in ['.yaml', '.yml']: - yaml.dump(workflow_data, f, default_flow_style=False, sort_keys=False, allow_unicode=True) - else: - json.dump(workflow_data, f, indent=2) - - logger.info(f'🩺 Persisted healing fix to {path.name}:') - for change in applied: - logger.info(f' Step {step_index + 1}: {change}') - - except Exception as e: - logger.warning(f'Failed to persist healing fix: {e}') - - def get_healing_log(self) -> list[Dict[str, Any]]: - """Return the log of all healing attempts in this session.""" - return self._healing_log.copy() + path = Path(workflow_path) + if not path.exists(): + logger.warning(f'Cannot persist fix: workflow file not found at {path}') + return + + # Load the workflow + with open(path, 'r') as f: + if path.suffix in ['.yaml', '.yml']: + workflow_data = yaml.safe_load(f) + else: + workflow_data = json.load(f) + + steps = workflow_data.get('steps', []) + if step_index >= len(steps): + logger.warning(f'Cannot persist fix: step index {step_index} out of range') + return + + # Apply corrections (only persistent fields, not transient ones) + persistent_fields = {'target_text', 'cssSelector', 'xpath', 'type'} + applied = [] + for key, value in corrected_fields.items(): + if key in persistent_fields: + old_value = steps[step_index].get(key) + steps[step_index][key] = value + applied.append(f'{key}: {old_value!r} → {value!r}') + + if not applied: + return + + # Write back + with open(path, 'w') as f: + if path.suffix in ['.yaml', '.yml']: + yaml.dump(workflow_data, f, default_flow_style=False, sort_keys=False, allow_unicode=True) + else: + json.dump(workflow_data, f, indent=2) + + logger.info(f'🩺 Persisted healing fix to {path.name}:') + for change in applied: + logger.info(f' Step {step_index + 1}: {change}') + + def get_results(self) -> List[HealingResult]: + """Return all healing results from this session.""" + return self._results.copy() + + def get_session_summary(self) -> str: + """Return a human-readable summary of healing activity.""" + if not self._results: + return 'No healing attempts this session.' + + total = len(self._results) + kept = sum(1 for r in self._results if r.status == 'keep') + discarded = sum(1 for r in self._results if r.status == 'discard') + crashed = sum(1 for r in self._results if r.status == 'crash') + skipped = sum(1 for r in self._results if r.status == 'skip') + avg_confidence = sum(r.confidence for r in self._results) / total if total else 0 + total_time_ms = sum(r.duration_ms for r in self._results) + + return ( + f'Healing session: {total} attempts, {kept} kept, {discarded} discarded, ' + f'{crashed} crashed, {skipped} skipped | ' + f'avg confidence: {avg_confidence:.0%} | total time: {total_time_ms / 1000:.1f}s' + ) diff --git a/workflows/workflow_use/workflow/service.py b/workflows/workflow_use/workflow/service.py index e0fa05e6..9e53de22 100644 --- a/workflows/workflow_use/workflow/service.py +++ b/workflows/workflow_use/workflow/service.py @@ -980,7 +980,15 @@ async def run( # Attempt self-healing if enabled if self._step_healer and isinstance(step_resolved, DeterministicWorkflowStep): healed = False + previous_attempts: list[dict] = [] + for attempt in range(self._step_healer.max_healing_attempts): + # Exponential backoff: 1s, 2s, 4s (autoresearch-mlx pattern) + if attempt > 0: + backoff = 2 ** attempt + logger.info(f'🩺 Waiting {backoff}s before retry (exponential backoff)') + await asyncio.sleep(backoff) + logger.info(f'🩺 Healing attempt {attempt + 1}/{self._step_healer.max_healing_attempts} for step {step_index + 1}') correction = await self._step_healer.heal_step( step=step_resolved, @@ -988,12 +996,16 @@ async def run( error=e, browser=self.browser, workflow_path=self.workflow_path, + previous_attempts=previous_attempts, ) if not correction: logger.info('🩺 Healer returned no correction, giving up') break + # Track this attempt for context in subsequent retries + previous_attempts.append({'corrections': correction.copy()}) + # Handle page state issues (wait for loading, dismiss popups, etc.) page_issue = correction.pop('page_state_issue', None) wait_time = correction.pop('wait_before_retry', 0) @@ -1005,10 +1017,18 @@ async def run( try: result = await self._execute_step(step_index, step_corrected) - logger.info(f'🩺 Step {step_index + 1} healed successfully on attempt {attempt + 1}!') + + # Success! Mark as kept and persist the fix + self._step_healer.mark_healing_outcome(step_index, success=True) + if self.workflow_path: + await self._step_healer.persist_if_healed( + self.workflow_path, step_index, correction, + ) healed = True break except Exception as retry_error: + # Mark as discarded + self._step_healer.mark_healing_outcome(step_index, success=False) logger.warning(f'🩺 Healing attempt {attempt + 1} failed: {retry_error}') e = retry_error # Update error for next healing attempt @@ -1028,6 +1048,12 @@ async def run( output_model_result = await self._convert_results_to_output_model(results, output_model) finally: + # Log healing summary if any healing was attempted + if self._step_healer: + summary = self._step_healer.get_session_summary() + if 'No healing' not in summary: + logger.info(f'🩺 {summary}') + # Clean-up browser after finishing workflow if close_browser_at_end: self.browser.browser_profile.keep_alive = False From f03985c9d0973d24fb91be7309dfd27cbe3e2410 Mon Sep 17 00:00:00 2001 From: Stefz29 Date: Tue, 17 Mar 2026 19:08:30 -0300 Subject: [PATCH 4/4] Add Chrome extension in-browser execution and independent recording MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Phase 2a — Extension Independence: - Add recorder_router.py with 6 API endpoints for recording events - Add CORS support for Chrome extensions in api.py - Make backend URL configurable (stored in chrome.storage.sync) - Add settings-view.tsx for backend URL config + health check - Add tab-navigation.tsx with Dashboard/Record/Settings tabs - Update sidepanel index.tsx with tab navigation wrapper - Fix isRecordingEnabled defaulting to true (should be false) - Fix START_RECORDING to always broadcast to content scripts - Add chrome.scripting.executeScript() to inject into existing tabs - Add stopped-view.tsx save-to-backend button - Add storage, scripting, activeTab permissions to wxt.config.ts Phase 2b — In-Browser Execution: - Create content-executor.ts for replaying steps in the user's Chrome - Multi-strategy element finding: target_text → CSS → XPath - waitForElement with MutationObserver for dynamic content - Real DOM events for React/Vue compatibility - Visual highlight overlay on target elements - Add ExecutionEngine class to background.ts (~250 lines) - State machine: idle → running → waiting_nav → healing → completed/failed - Navigation detection + content script re-injection - Screenshot capture for self-healing - Service worker keep-alive during execution - Add dashboard-view.tsx with workflow list, Run/Stop buttons, progress bar - Add CLAUDE.md and architecture docs Co-Authored-By: Claude Opus 4.6 --- .gitignore | 1 - CLAUDE.md | 110 ++++ docs/PHASE2B_BROWSER_EXECUTION.md | 139 +++++ docs/PHASE2_PLAN.md | 171 ++++++ docs/RESUME_INSTRUCTIONS.md | 132 ++++ docs/SESSION_LOG.md | 87 +++ extension/src/entrypoints/background.ts | 522 +++++++++++++++- extension/src/entrypoints/content-executor.ts | 563 ++++++++++++++++++ .../sidepanel/components/dashboard-view.tsx | 296 +++++++++ .../sidepanel/components/settings-view.tsx | 235 ++++++++ .../sidepanel/components/stopped-view.tsx | 72 +++ .../sidepanel/components/tab-navigation.tsx | 60 ++ extension/src/entrypoints/sidepanel/index.tsx | 65 +- extension/wxt.config.ts | 4 +- workflows/backend/api.py | 10 +- workflows/backend/recorder_router.py | 150 +++++ workflows/backend/service.py | 2 +- 17 files changed, 2592 insertions(+), 27 deletions(-) create mode 100644 CLAUDE.md create mode 100644 docs/PHASE2B_BROWSER_EXECUTION.md create mode 100644 docs/PHASE2_PLAN.md create mode 100644 docs/RESUME_INSTRUCTIONS.md create mode 100644 docs/SESSION_LOG.md create mode 100644 extension/src/entrypoints/content-executor.ts create mode 100644 extension/src/entrypoints/sidepanel/components/dashboard-view.tsx create mode 100644 extension/src/entrypoints/sidepanel/components/settings-view.tsx create mode 100644 extension/src/entrypoints/sidepanel/components/tab-navigation.tsx create mode 100644 workflows/backend/recorder_router.py diff --git a/.gitignore b/.gitignore index ce42223d..53baff85 100644 --- a/.gitignore +++ b/.gitignore @@ -191,4 +191,3 @@ data/ user_data_dir .claude/ -CLAUDE.md diff --git a/CLAUDE.md b/CLAUDE.md new file mode 100644 index 00000000..cf670778 --- /dev/null +++ b/CLAUDE.md @@ -0,0 +1,110 @@ +# CLAUDE.md + +This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository. + +## Project Overview + +Workflow Use is a browser automation tool that records browser interactions and replays them as deterministic workflows, with LLM-powered self-healing when steps fail. It's a fork of `browser-use/workflow-use` with local LLM support and improved self-healing. + +**Three-tier architecture:** Chrome Extension (recorder) → Python Backend (execution) → React UI (visualization) + +## Build & Run Commands + +### Python Backend (workflows/) +```bash +cd workflows +uv sync # Install dependencies (Python 3.11+, uses hatchling) +source .venv/bin/activate +playwright install chromium # Browser engine +cp .env.example .env # Configure LLM provider +python cli.py --help # CLI entry point +python cli.py launch-gui # Starts FastAPI (8000) + Vite (5173) + opens browser +``` + +### Chrome Extension (extension/) +```bash +cd extension +npm install && npm run build # Build to .output/chrome-mv3/ +npm run dev # Watch mode +``` + +### React UI (ui/) +```bash +cd ui +npm install # postinstall auto-generates types from backend OpenAPI +npm run dev # Dev server on port 5173 +npm run type-gen-update # Regenerate TS types from running backend +``` + +### Lint (all components) +```bash +./lint.sh # Runs ruff + ESLint + tsc for all three +# Or individually: +cd workflows && uv run ruff check && uv run ruff format --check +cd ui && npm run lint +cd extension && npm run lint +``` + +### Tests +```bash +cd workflows && uv run pytest tests/ # Run all tests +uv run pytest tests/test_wait_times.py # Single test file +``` + +## Code Style + +Python: Ruff with **tabs for indentation**, single quotes, 130 char line length. Rules: ASYNC, E, F, FAST, I, PLE (see pyproject.toml `[tool.ruff]`). + +## Architecture + +### Communication Flow +``` +Extension content.ts → background.ts → HTTP POST :7331/event → RecordingService +UI (React :5173) → REST API :8000 → backend/routers.py → WorkflowService +Workflow execution: Workflow.run() → _execute_step() → controller actions → Playwright +``` + +### Key Modules (workflows/workflow_use/) + +**`llm/provider.py`** — LLM factory. Reads `.env` for `LLM_PROVIDER` (local/browser_use), `LLM_BASE_URL`, `LLM_MODEL`, `LLM_HEALING_MODEL`. Returns `ChatOpenAI` for local (LM Studio/Ollama) or `ChatBrowserUse` for cloud. Entry point: `get_llm(purpose)`. + +**`workflow/service.py`** — `Workflow` class. Main execution orchestrator. Loads from YAML, resolves variables, runs steps sequentially. On failure, delegates to `StepHealer` for vision-based repair. Key params: `enable_self_healing`, `debug` (captures screenshots). + +**`healing/step_healer.py`** — Vision-based step repair. On failure: screenshot → LLM diagnosis → corrected selectors → retry. Tracks results in `logs/healing/healing_results.tsv`. Uses snapshot/revert pattern (saves YAML before healing, reverts if fix fails). Exponential backoff between retries. + +**`healing/service.py`** — `HealingService`. Generates workflows from prompts by running a browser agent, capturing element mappings, then converting to deterministic steps. Two paths: LLM-based (`create_workflow_definition`) or deterministic (`_create_workflow_deterministically`). Post-processes with pattern-based variable identification. + +**`schema/views.py`** — Pydantic models for workflow steps. `SelectorWorkflowSteps` has `target_text` (primary, semantic), `selectorStrategies` (fallback list), and legacy `cssSelector`/`xpath`. Step types: navigation, click, input, select_change, key_press, scroll, extract_page_content, agent. + +**`recorder/service.py`** — Spawns Chromium with extension loaded, runs FastAPI on :7331 to receive events from extension. Extension captures clicks/inputs/keypresses with semantic text, XPath, CSS selectors. + +**`controller/service.py`** — Maps workflow step types to browser-use actions. `controller/utils.py` has `get_best_element_handle()` with stable selector fallback generation. + +**`workflow/element_finder.py`** — Multi-strategy element finding. Priority: semantic text strategies (exact, role, aria_label, placeholder, fuzzy) → XPath JavaScript evaluation. Returns element index or XPath string. + +**`mcp/service.py`** — Exposes workflows as MCP tools via FastMCP. Dynamically generates function signatures from workflow input_schema. + +**`storage/service.py`** — File-based CRUD. Workflows stored as `.workflow.yaml` in `storage/workflows/`. Metadata index at `storage/metadata.json`. + +### Extension (extension/src/) +- `content.ts` — Injected into pages. Captures clicks, inputs, keypresses with semantic label extraction (aria-label, label[for], sibling text, etc.). Uses RRWeb for DOM recording. +- `background.ts` — Service worker. Stores events per tab, converts to semantic format, POSTs to Python server at :7331. +- `sidepanel/` — React UI for recording controls and live event viewer. + +### CLI (workflows/cli.py) +95KB typer app. Key commands: `create-workflow`, `run-workflow`, `run-workflow-no-ai`, `run-workflow-csv`, `generate-workflow`, `launch-gui`, `mcp-server`. Module-level `get_llm()` initialization — if LLM server is down, CLI still loads but LLM-dependent commands will fail. + +## Fork-Specific Details + +- **Origin**: `github.com/Stefz29/workflow-use` (fork), **Upstream**: `github.com/browser-use/workflow-use` +- **LLM Provider**: Defaults to local LM Studio at `localhost:1234` instead of Browser Use cloud API +- **Self-Healing**: Added `StepHealer` with autoresearch-mlx patterns (snapshot/revert, TSV results tracking, exponential backoff, fail-fast checks) +- **Spec**: Full project roadmap in `~/Downloads/workflow-use-fork-instructions.md` + +## Ports +| Service | Port | +|---------|------| +| FastAPI backend | 8000 | +| Recording server | 7331 | +| Vite UI dev | 5173 | +| LM Studio (local LLM) | 1234 | diff --git a/docs/PHASE2B_BROWSER_EXECUTION.md b/docs/PHASE2B_BROWSER_EXECUTION.md new file mode 100644 index 00000000..e7912a75 --- /dev/null +++ b/docs/PHASE2B_BROWSER_EXECUTION.md @@ -0,0 +1,139 @@ +# Phase 2b: In-Browser Workflow Execution + +## Status: STARTING +**Date:** 2026-03-17 + +## Problem +Workflow execution via Playwright launches a SEPARATE Chromium browser with no cookies/sessions. +This defeats the purpose for sites requiring auth (LinkedIn Recruiter, etc.) and triggers bot detection. + +## Solution +The Chrome extension itself replays workflow steps in the SAME browser where they were recorded. +No Playwright needed. Same cookies, same sessions, same everything. + +## Architecture + +``` +YOUR Chrome (same browser, same cookies, same session) +┌─────────────────────────────────────────────────────────┐ +│ background.ts (ExecutionEngine - orchestrator) │ +│ - Manages step queue & state machine │ +│ - Survives page navigations (service worker) │ +│ - Sends one step at a time to content script │ +│ - Re-injects content script after navigation │ +│ - Captures screenshots for self-healing │ +│ │ +│ content-executor.ts (NEW - executes steps on page) │ +│ - Finds elements: target_text → CSS → XPath │ +│ - Executes: click(), fill(), keypress via real DOM │ +│ - Reports success/failure back to background │ +│ - Highlights element being acted on │ +│ │ +│ sidepanel (execution progress UI) │ +│ - "Run in Browser" button │ +│ - Step-by-step progress with status indicators │ +└─────────────────────────────────────────────────────────┘ + │ HTTP (only when healing needed) + ▼ +┌─────────────────────────────────────────────────────────┐ +│ Python Backend (:8000) │ +│ POST /api/ext-execute/heal │ +│ - Receives screenshot + failed step │ +│ - LLM diagnoses what changed on the page │ +│ - Returns corrected selectors │ +└─────────────────────────────────────────────────────────┘ +``` + +## Tab/Window Tracking + +The user may have multiple browsers open (2 Chrome, Firefox, Safari). +- The extension ONLY sees its own Chrome instance +- During recording, every event captures `tabId` and `windowId` +- At replay: check if original tab exists → use it. Original window? → find matching tab. Otherwise → ask user. +- `windowId` distinguishes between multiple Chrome windows + +## Execution Flow + +### Step-by-Step: +1. User clicks "Run in Browser" in sidepanel +2. Background resolves target tab (recorded tabId/windowId or active tab) +3. For each step in workflow: + a. **navigation**: `chrome.tabs.update(tabId, {url})` → wait for load → inject executor + b. **click/input/key_press**: send step to content-executor → wait for result + c. **scroll**: send to content-executor → `window.scrollTo()` +4. After each step that might cause navigation: + - Monitor `chrome.tabs.onUpdated` for URL change + - Wait for `status: "complete"` → re-inject executor → `EXECUTOR_READY` handshake +5. On step failure: capture screenshot → send to backend heal endpoint → retry with corrected selectors + +### State Machine: +``` +IDLE → LOADING → EXECUTING → WAITING_FOR_NAV → HEALING → COMPLETED/FAILED +``` + +## Content Executor: Element Finding + +Priority order (same as recording, but in reverse): +1. **target_text (semantic)**: Scan interactive elements, match by textContent/aria-label/placeholder/label +2. **cssSelector**: `document.querySelector(cssSelector)` +3. **xpath**: `document.evaluate(xpath)` + +### Action Execution (Real DOM Events): +- **click**: `element.focus()` → `element.click()` (or full MouseEvent sequence for React/Vue) +- **input**: Native value setter → InputEvent → change event +- **key_press**: KeyboardEvent('keydown') + ('keyup') +- **scroll**: `window.scrollTo(x, y)` + +## Navigation Handling (Critical) + +When a click causes page navigation: +1. Content script on old page DIES (Chrome destroys it) +2. Background service worker SURVIVES — it monitors `chrome.tabs.onUpdated` +3. New page finishes loading → background re-injects content-executor.ts +4. Content script sends `EXECUTOR_READY` → background sends next step + +## Self-Healing Integration + +When a step fails: +1. Content-executor reports failure with error to background +2. Background captures screenshot via `chrome.tabs.captureVisibleTab()` +3. Background POSTs screenshot + step context to `POST /api/ext-execute/heal` +4. Backend runs StepHealer LLM diagnosis → returns corrected selectors +5. Background sends corrected step to content-executor for retry +6. Max 3 retries before marking step as failed + +## Implementation Order + +### Phase 1: Content Executor +- [ ] Create `content-executor.ts` with element finding + step execution +- [ ] Register in wxt.config.ts +- [ ] Message protocol: EXECUTE_STEP / STEP_RESULT / EXECUTOR_READY + +### Phase 2: Background ExecutionEngine +- [ ] Add ExecutionEngine class to background.ts +- [ ] Step queue, state machine, tab tracking +- [ ] Navigation detection + content script re-injection +- [ ] Screenshot capture for healing + +### Phase 3: Backend Healing API +- [ ] Create ext_execution_router.py +- [ ] Adapt StepHealer to accept pre-captured screenshots +- [ ] Wire up in api.py + +### Phase 4: Sidepanel UI +- [ ] Execution progress view +- [ ] "Run in Browser" button in dashboard +- [ ] Tab/window selector + +### Phase 5: Edge Cases +- [ ] Dynamic content waits (MutationObserver) +- [ ] iframes +- [ ] New tabs/popups during execution +- [ ] Service worker sleep prevention (MV3 30s idle timeout) + +## Key Files +- `extension/src/entrypoints/content.ts` — Has reusable functions: extractSemanticInfo(), getXPath(), getEnhancedCSSSelector() +- `extension/src/entrypoints/background.ts` — Orchestrator to extend +- `extension/src/lib/workflow-types.ts` — Step type definitions +- `workflows/workflow_use/healing/step_healer.py` — Self-healing to adapt +- `workflows/backend/recorder_router.py` — Pattern for new execution router diff --git a/docs/PHASE2_PLAN.md b/docs/PHASE2_PLAN.md new file mode 100644 index 00000000..9edba660 --- /dev/null +++ b/docs/PHASE2_PLAN.md @@ -0,0 +1,171 @@ +# Phase 2: Standalone Chrome Extension Dashboard + +## Status: Phase 2a COMPLETE +**Started:** 2026-03-16 +**Phase 2a Completed:** 2026-03-16 +**Current Phase:** 2b — Dashboard & Workflow Management (ready to start) + +--- + +## Problem Statement + +The current recording flow launches a **separate Playwright Chromium instance** with the extension pre-loaded. This means: +- User's credentials/cookies are NOT available (no LinkedIn Recruiter, no logged-in sessions) +- Risk of getting banned on sites that detect automation +- Poor UX — separate browser window, no integration with user's workflow + +## Solution + +Run the extension **directly in the user's own Chrome browser**, communicating with the existing Python backend via HTTP. No Playwright needed for recording. + +``` +Current: Playwright Chromium (isolated) → extension → temp server :7331 +Phase 2: USER'S Chrome (with credentials) → extension → main backend :8000 +``` + +--- + +## Architecture Overview + +### Communication Flow (Phase 2) +``` +User's Chrome (extension) + content.ts ─── chrome.runtime.sendMessage ──→ background.ts + │ + ├── HTTP POST :8000/api/recorder/event (recording events) + ├── GET :8000/api/workflows (list workflows) + ├── POST :8000/api/workflows (save recorded workflow) + ├── POST :8000/api/workflows/{id}/execute (run workflow) + └── GET :8000/api/config (LLM settings) + + sidepanel ←── chrome.runtime messages ←── background.ts +``` + +### Key Design Decisions +- **Sidepanel** (not popup) — stays open while user browses, essential for recording +- **All API calls go through background.ts** — centralizes error handling, avoids CORS issues +- **Execution still uses Playwright** initially — extension records and manages, backend executes +- **Backend must be running** — extension shows a clear connection indicator + +--- + +## Reusability Assessment + +| Component | Status | Notes | +|-----------|--------|-------| +| `content.ts` (DOM event capture) | 100% reusable | All handlers, semantic extraction, selectors work as-is | +| `background.ts` (event aggregation) | ~90% reusable | Make endpoint configurable, add dashboard message types | +| Sidepanel views (Recording/Stopped/EventViewer) | ~80% reusable | Add tab navigation wrapper | +| Types (`lib/types.ts`, `lib/workflow-types.ts`) | 100% reusable | Independent of browser launch method | +| UI components (`components/ui/`) | 100% reusable | Shadcn primitives | +| WXT config, Tailwind, build pipeline | 100% reusable | No changes needed | +| Backend routers/services | Reusable + additions | Need recording endpoints on :8000 | + +--- + +## Phase Breakdown + +### Phase 2a — Extension Independence (CURRENT) + +**Goal:** Extension works standalone in user's Chrome, saves workflows to backend. + +#### Tasks: +1. [x] Add recording endpoints to main backend (:8000) + - `POST /api/recorder/event` — accepts RecorderEvent (same as :7331) + - `POST /api/recorder/start` — initializes recording session + - `POST /api/recorder/stop` — finalizes and saves workflow + - `GET /api/recorder/status` — check if recording is active + +2. [x] Make extension server endpoint configurable + - Replace hardcoded `http://127.0.0.1:7331/event` in background.ts + - Default to `http://127.0.0.1:8000/api/recorder/event` + - Store in `chrome.storage.sync` + +3. [x] Update extension manifest permissions + - Add `storage` permission + - Update `host_permissions` for :8000 + +4. [x] Update StoppedView to save workflow to backend + - POST workflow to backend API instead of just downloading JSON + - Show success/error feedback + +5. [x] Add CORS support for Chrome extension origin in backend + +#### Files Modified: +- `workflows/workflow_use/backend/routers.py` — new recording endpoints +- `extension/src/entrypoints/background.ts` — configurable endpoint +- `extension/wxt.config.ts` — manifest permissions +- `extension/src/entrypoints/sidepanel/views/StoppedView.tsx` — save to backend + +### Phase 2b — Dashboard & Workflow Management + +**Goal:** Full dashboard UI in the extension sidepanel. + +#### Tasks: +5. Add tab navigation to sidepanel: Dashboard | Record | Settings +6. Dashboard view — list saved workflows with Run/Edit/Delete +7. Execution status tracking — progress indicator when workflow runs + +#### New Files: +- `extension/src/entrypoints/sidepanel/views/DashboardView.tsx` +- `extension/src/entrypoints/sidepanel/components/WorkflowCard.tsx` +- `extension/src/entrypoints/sidepanel/components/TabNavigation.tsx` + +### Phase 2c — Settings & LLM Configuration + +**Goal:** Configure the backend's LLM from the extension UI. + +#### Tasks: +8. Settings view — backend URL, LLM provider dropdown, model name, "Test Connection" +9. Backend config API (`GET/PUT /api/config`) for runtime LLM changes + +#### New Files: +- `extension/src/entrypoints/sidepanel/views/SettingsView.tsx` +- `workflows/workflow_use/backend/config_router.py` + +### Phase 2d — Natural Language Features + +**Goal:** Talk in plain English to create and configure workflows. + +#### Tasks: +10. Natural language step input during recording +11. "Generate workflow from description" in Dashboard +12. Chat-like interface for workflow configuration + +--- + +## Technical Notes + +### CORS for Chrome Extensions +Chrome extension background scripts making `fetch()` requests are NOT subject to CORS. +However, if sidepanel components make direct fetch calls, the backend needs: +```python +allow_origins=["chrome-extension://"] +``` +Best practice: route all API calls through background.ts. + +### Backend Must Be Running +The extension depends on the backend being up. Need: +- Connection status indicator in sidepanel header +- Clear error messages when backend is unreachable +- Auto-reconnect logic + +### Recording Server Port Conflict +The old :7331 recording server (from Playwright flow) and the new :8000 endpoints can coexist. +The CLI `create-workflow` command still works with Playwright for users who prefer it. + +### State Synchronization +If user has both the React UI (:5173) and extension open: +- Both hit the same backend API +- React UI polls, so changes from extension appear on refresh +- No WebSocket needed initially + +--- + +## Port Reference +| Service | Port | +|---------|------| +| FastAPI backend | 8000 | +| Recording server (legacy) | 7331 | +| Vite UI dev | 5173 | +| LM Studio (local LLM) | 1234 | diff --git a/docs/RESUME_INSTRUCTIONS.md b/docs/RESUME_INSTRUCTIONS.md new file mode 100644 index 00000000..8deb6877 --- /dev/null +++ b/docs/RESUME_INSTRUCTIONS.md @@ -0,0 +1,132 @@ +# Resume Instructions for Claude Code + +## Quick Context + +This is a browser automation project (workflow-use). We're building a Chrome extension that: +1. **Records** user actions in their own Chrome browser (DONE - working) +2. **Replays** those actions in the SAME browser (IN PROGRESS) +3. **Self-heals** when steps fail using a local LLM (PLANNED) + +## How to Resume Work + +### Step 1: Read the Architecture +``` +Read these files first: +- /Users/SZ/Desktop/Claude_APPS/workflow-use/CLAUDE.md (project overview) +- /Users/SZ/Desktop/Claude_APPS/workflow-use/docs/PHASE2_PLAN.md (overall plan) +- /Users/SZ/Desktop/Claude_APPS/workflow-use/docs/PHASE2B_BROWSER_EXECUTION.md (current work) +- /Users/SZ/Desktop/Claude_APPS/workflow-use/docs/SESSION_LOG.md (what's been done) +``` + +### Step 2: Start Services +```bash +# 1. Start the Python backend +cd /Users/SZ/Desktop/Claude_APPS/workflow-use/workflows +source .venv/bin/activate +python -m uvicorn backend.api:app --host 127.0.0.1 --port 8000 --log-level info & + +# 2. Verify backend is running +curl http://127.0.0.1:8000/api/recorder/health + +# 3. LM Studio (only if testing self-healing) +# Load bu-30b-a3b-preview model, server on port 1234 +``` + +### Step 3: Build & Load Extension +```bash +# Build the extension +cd /Users/SZ/Desktop/Claude_APPS/workflow-use/extension +npm run build + +# Then in Chrome: +# 1. Go to chrome://extensions/ +# 2. Enable Developer Mode +# 3. Click "Load unpacked" → select extension/.output/chrome-mv3/ +# (use Cmd+Shift+. in Finder to show hidden .output folder) +# 4. Click the extension icon to open sidepanel +``` + +### Step 4: Current Task — Build In-Browser Execution + +**What's next:** Building the content-executor.ts and ExecutionEngine so recorded workflows replay IN the user's Chrome browser (not Playwright). + +**Key files to work with:** +- `extension/src/entrypoints/content-executor.ts` — NEW: executes steps on the page +- `extension/src/entrypoints/background.ts` — ADD: ExecutionEngine class +- `extension/src/entrypoints/sidepanel/components/dashboard-view.tsx` — ADD: "Run in Browser" button +- `workflows/backend/ext_execution_router.py` — NEW: healing API for extension execution + +**Architecture summary:** +1. `content-executor.ts` finds elements (target_text → CSS → XPath) and executes actions (click, input, keypress) +2. `background.ts` ExecutionEngine orchestrates: sends steps one-by-one, handles navigation, re-injects content script +3. Backend only involved for self-healing (screenshot → LLM → corrected selectors) + +**Critical design points:** +- Content script DIES on page navigation — background must re-inject it +- Element finding: target_text (semantic) is primary, CSS/XPath are fallbacks +- Real DOM events needed (not just element.click()) to trigger React/Vue handlers +- Tab/window tracking: extension captures tabId+windowId during recording, uses same at replay +- Service worker may sleep after 30s idle in MV3 — keep alive during execution + +**Reusable code from content.ts:** +- `extractSemanticInfo()` — extract labels/text from elements (use in REVERSE for finding) +- `getXPath()` — XPath generation +- `getEnhancedCSSSelector()` — CSS selector generation +- Overlay highlighting code from mouseover handler + +## Project Structure (Key Paths) + +``` +/Users/SZ/Desktop/Claude_APPS/workflow-use/ +├── CLAUDE.md # Project instructions +├── docs/ # Architecture docs (read these!) +│ ├── PHASE2_PLAN.md +│ ├── PHASE2B_BROWSER_EXECUTION.md +│ ├── SESSION_LOG.md +│ └── RESUME_INSTRUCTIONS.md # This file +├── extension/ # Chrome Extension (WXT + React) +│ ├── src/entrypoints/ +│ │ ├── background.ts # Service worker (orchestrator) +│ │ ├── content.ts # Recording content script +│ │ ├── content-executor.ts # NEW: Execution content script +│ │ └── sidepanel/ # React UI +│ │ ├── index.tsx # Tab navigation (Dashboard|Record|Settings) +│ │ ├── components/ +│ │ │ ├── dashboard-view.tsx # Workflow list +│ │ │ ├── settings-view.tsx # Backend config +│ │ │ ├── stopped-view.tsx # Save workflow +│ │ │ └── tab-navigation.tsx # Tab bar +│ │ └── context/ +│ │ └── workflow-provider.tsx +│ ├── wxt.config.ts # Manifest config +│ └── .output/chrome-mv3/ # Built extension (load this in Chrome) +├── workflows/ # Python Backend +│ ├── .env # LLM config (LM Studio) +│ ├── backend/ +│ │ ├── api.py # FastAPI app + CORS +│ │ ├── routers.py # Workflow CRUD + execute endpoints +│ │ ├── recorder_router.py # Recording event endpoints +│ │ └── service.py # Workflow execution service +│ └── workflow_use/ +│ ├── healing/step_healer.py # LLM self-healing +│ ├── recorder/service.py # Old Playwright recorder (legacy) +│ └── workflow/service.py # Workflow execution +└── ui/ # React UI (Vite :5173) +``` + +## .env Configuration +``` +LLM_PROVIDER=local +LLM_BASE_URL=http://192.168.1.15:1234/v1 +LLM_API_KEY=not-needed +LLM_MODEL=bu-30b-a3b-preview +LLM_HEALING_MODEL=bu-30b-a3b-preview +``` + +## Ports +| Service | Port | +|---------|------| +| FastAPI backend | 8000 | +| Recording server (legacy) | 7331 | +| Vite UI dev | 5173 | +| LM Studio (local LLM) | 1234 | diff --git a/docs/SESSION_LOG.md b/docs/SESSION_LOG.md new file mode 100644 index 00000000..e4e7de13 --- /dev/null +++ b/docs/SESSION_LOG.md @@ -0,0 +1,87 @@ +# Session Log — Workflow Use Phase 2 + +## Session 1: 2026-03-16/17 + +### What Was Accomplished + +#### Phase 1 — Project Assessment +- Assessed the existing workflow-use project (fork of browser-use/workflow-use) +- Verified Python backend runs (FastAPI on :8000) +- Verified React UI runs (Vite on :5173) +- Identified LM Studio config: `bu-30b-a3b-preview` model at `192.168.1.15:1234` +- Fixed `.env` to point to correct LM Studio IP + +#### Phase 2a — Extension Independence (COMPLETE) +- **Created `workflows/backend/recorder_router.py`** — 6 new API endpoints for recording + - POST /api/recorder/event, /start, /stop, /save + - GET /api/recorder/status, /health +- **Updated `workflows/backend/api.py`** — Added CORS for Chrome extensions + recorder router +- **Updated `extension/src/entrypoints/background.ts`**: + - Made backend URL configurable (stored in chrome.storage.sync) + - Default endpoint changed from :7331 to :8000/api/recorder/event + - Added message handlers: API_REQUEST, SAVE_WORKFLOW_TO_BACKEND, UPDATE_BACKEND_URL, CHECK_BACKEND_HEALTH + - Fixed critical bug: `isRecordingEnabled` defaulted to `true` (should be `false`) + - Fixed START_RECORDING to always broadcast (was guarded by `if (!isRecordingEnabled)`) + - Added `chrome.scripting.executeScript()` to inject content scripts into existing tabs +- **Created `extension/src/entrypoints/sidepanel/components/tab-navigation.tsx`** — 3-tab layout +- **Created `extension/src/entrypoints/sidepanel/components/dashboard-view.tsx`** — Workflow list with Run/Delete +- **Created `extension/src/entrypoints/sidepanel/components/settings-view.tsx`** — Backend URL config + health check +- **Updated `extension/src/entrypoints/sidepanel/components/stopped-view.tsx`** — Save to backend button +- **Updated `extension/src/entrypoints/sidepanel/index.tsx`** — Tab navigation wrapper +- **Updated `extension/wxt.config.ts`** — Added storage, scripting, activeTab permissions + +#### Phase 2b — In-Browser Execution (BUILT, NEEDS TESTING) +- Architecture designed and documented in `docs/PHASE2B_BROWSER_EXECUTION.md` +- Key insight: replay must happen IN the user's Chrome (not Playwright) to preserve auth/cookies +- **Created `extension/src/entrypoints/content-executor.ts`** — Full step execution engine: + - Element finding: target_text (semantic) → cssSelector → xpath + - waitForElement with MutationObserver for dynamic content + - Real DOM events: MouseEvent sequence for clicks, native value setter for inputs (React compatible) + - Visual feedback: blue highlight overlay on target element + - Message protocol: EXECUTE_STEP / STEP_RESULT / EXECUTOR_READY / EXECUTOR_PING/PONG +- **Added ExecutionEngine class to `background.ts`** (~250 lines): + - State machine: idle → running → waiting_nav → healing → completed/failed/stopped + - Step queue with sequential execution + - Navigation detection via chrome.tabs.onUpdated + - Content script re-injection after page navigation + - Screenshot capture for self-healing + - Self-healing flow: screenshot → POST /api/ext-execute/heal → retry with corrected selectors + - Status broadcast to sidepanel +- **Updated `dashboard-view.tsx`**: + - "Run" button now triggers in-browser execution (not Playwright) + - Execution progress bar with step counter + - Stop button during execution + - Status indicators: running/healing/completed/failed/stopped +- **NOT YET BUILT**: Backend `/api/ext-execute/heal` endpoint (self-healing works but endpoint is a stub) + +### Bugs Found and Fixed +1. **`isRecordingEnabled = true` default** — Comment said "OFF" but value was `true`. Content scripts would silently record, UI showed wrong state, Start Recording did nothing. +2. **START_RECORDING guard** — `if (!isRecordingEnabled)` prevented broadcast when already true. +3. **Content script not in existing tabs** — After extension reload, content scripts only exist in NEW tabs. Fixed by programmatically injecting via `chrome.scripting.executeScript()` on Start Recording. + +### Current State of Running Services +- Backend: `python -m uvicorn backend.api:app --host 127.0.0.1 --port 8000` (may need restart) +- Extension: built at `extension/.output/chrome-mv3/` — loaded as unpacked in Chrome +- LM Studio: `bu-30b-a3b-preview` model at `192.168.1.15:1234` (not required for recording/replay, only self-healing) + +### Files Modified (from git perspective) +``` +NEW: + docs/PHASE2_PLAN.md + docs/PHASE2B_BROWSER_EXECUTION.md + docs/SESSION_LOG.md + docs/RESUME_INSTRUCTIONS.md + workflows/backend/recorder_router.py + extension/src/entrypoints/sidepanel/components/tab-navigation.tsx + extension/src/entrypoints/sidepanel/components/dashboard-view.tsx + extension/src/entrypoints/sidepanel/components/settings-view.tsx + extension/src/entrypoints/content-executor.ts (if built in this session) + +MODIFIED: + workflows/backend/api.py (CORS + recorder router) + workflows/.env (LM Studio IP) + extension/wxt.config.ts (permissions) + extension/src/entrypoints/background.ts (configurable URL, bug fixes, new handlers) + extension/src/entrypoints/sidepanel/index.tsx (tab navigation) + extension/src/entrypoints/sidepanel/components/stopped-view.tsx (save to backend) +``` diff --git a/extension/src/entrypoints/background.ts b/extension/src/entrypoints/background.ts index 2f5e1506..39608a4b 100644 --- a/extension/src/entrypoints/background.ts +++ b/extension/src/entrypoints/background.ts @@ -35,10 +35,24 @@ export default defineBackground(() => { // Track recent user interactions to distinguish intentional vs side-effect navigation const recentUserInteractions: { [tabId: number]: number } = {}; // timestamp of last user interaction - let isRecordingEnabled = true; // Default to disabled (OFF) + let isRecordingEnabled = false; // Default to OFF — user clicks Start Recording let lastWorkflowHash: string | null = null; // Cache for the last logged workflow hash - const PYTHON_SERVER_ENDPOINT = "http://127.0.0.1:7331/event"; + // --- Configurable backend endpoint (Phase 2) --- + const DEFAULT_BACKEND_URL = "http://127.0.0.1:8000"; + let BACKEND_BASE_URL = DEFAULT_BACKEND_URL; + let PYTHON_SERVER_ENDPOINT = `${BACKEND_BASE_URL}/api/recorder/event`; + + // Load saved backend URL from storage + chrome.storage.sync.get(["backendUrl"], (result) => { + if (result.backendUrl) { + BACKEND_BASE_URL = result.backendUrl; + PYTHON_SERVER_ENDPOINT = `${BACKEND_BASE_URL}/api/recorder/event`; + console.log(`[Config] Using saved backend URL: ${BACKEND_BASE_URL}`); + } else { + console.log(`[Config] Using default backend URL: ${BACKEND_BASE_URL}`); + } + }); // Hashing function using SubtleCrypto (SHA-256) async function calculateSHA256(str: string): Promise { @@ -670,20 +684,35 @@ export default defineBackground(() => { ); console.log("Cleared previous recording data."); - // Start recording - if (!isRecordingEnabled) { - isRecordingEnabled = true; - console.log("Recording status set to: true"); - broadcastRecordingStatus(); // Inform content scripts and sidepanel + // Start recording — always broadcast to ensure content scripts activate + isRecordingEnabled = true; + lastWorkflowHash = null; // Reset hash so first update is sent + console.log("Recording status set to: true"); + broadcastRecordingStatus(); // Inform content scripts and sidepanel + + // Ensure content scripts are injected into all open tabs + // (they may not be present if extension was reloaded after tabs were opened) + chrome.tabs.query({}, (tabs) => { + tabs.forEach((tab) => { + if (tab.id && tab.url && !tab.url.startsWith("chrome://") && !tab.url.startsWith("chrome-extension://")) { + chrome.scripting.executeScript({ + target: { tabId: tab.id }, + files: ["content-scripts/content.js"], + }).catch((err) => { + // Content script may already be injected — that's fine + console.debug(`Content script inject for tab ${tab.id}: ${err.message}`); + }); + } + }); + }); - // Send recording started event to Python server - const eventToSend: HttpRecordingStartedEvent = { - type: "RECORDING_STARTED", - timestamp: Date.now(), - payload: { message: "Recording has started" }, - }; - sendEventToServer(eventToSend); - } + // Send recording started event to Python server + const eventToSend: HttpRecordingStartedEvent = { + type: "RECORDING_STARTED", + timestamp: Date.now(), + payload: { message: "Recording has started" }, + }; + sendEventToServer(eventToSend); sendResponse({ status: "started" }); // Send simple confirmation } else if (message.type === "STOP_RECORDING") { console.log("Received STOP_RECORDING request."); @@ -787,6 +816,138 @@ export default defineBackground(() => { sendResponse({ isRecordingEnabled }); } + // --- Phase 2: Dashboard & Settings API Proxy --- + else if (message.type === "API_REQUEST") { + // Generic API proxy: routes requests from sidepanel through background script + // This avoids CORS issues since background scripts bypass CORS + isAsync = true; + (async () => { + try { + const { endpoint, method = "GET", body } = message.payload; + const url = `${BACKEND_BASE_URL}${endpoint}`; + const options: RequestInit = { + method, + headers: { "Content-Type": "application/json" }, + }; + if (body && method !== "GET") { + options.body = JSON.stringify(body); + } + const response = await fetch(url, options); + const data = await response.json(); + sendResponse({ success: true, data, status: response.status }); + } catch (error) { + console.error("[API_REQUEST] Error:", error); + sendResponse({ + success: false, + error: error instanceof Error ? error.message : String(error), + }); + } + })(); + return true; // Keep channel open for async + } + else if (message.type === "SAVE_WORKFLOW_TO_BACKEND") { + // Save recorded workflow to backend + isAsync = true; + (async () => { + try { + const { workflow, name } = message.payload; + const url = `${BACKEND_BASE_URL}/api/recorder/save`; + const response = await fetch(url, { + method: "POST", + headers: { "Content-Type": "application/json" }, + body: JSON.stringify({ workflow, name }), + }); + const data = await response.json(); + sendResponse({ success: data.success, data }); + } catch (error) { + console.error("[SAVE_WORKFLOW] Error:", error); + sendResponse({ + success: false, + error: error instanceof Error ? error.message : String(error), + }); + } + })(); + return true; + } + else if (message.type === "UPDATE_BACKEND_URL") { + // Update the backend URL + const newUrl = message.payload.url; + if (newUrl) { + BACKEND_BASE_URL = newUrl; + PYTHON_SERVER_ENDPOINT = `${BACKEND_BASE_URL}/api/recorder/event`; + chrome.storage.sync.set({ backendUrl: newUrl }); + console.log(`[Config] Backend URL updated to: ${BACKEND_BASE_URL}`); + sendResponse({ success: true, url: BACKEND_BASE_URL }); + } else { + sendResponse({ success: false, error: "No URL provided" }); + } + } + else if (message.type === "GET_BACKEND_URL") { + sendResponse({ url: BACKEND_BASE_URL }); + } + else if (message.type === "CHECK_BACKEND_HEALTH") { + isAsync = true; + (async () => { + try { + const response = await fetch(`${BACKEND_BASE_URL}/api/recorder/health`, { + method: "GET", + signal: AbortSignal.timeout(5000), + }); + const data = await response.json(); + sendResponse({ connected: true, data }); + } catch (error) { + sendResponse({ + connected: false, + error: error instanceof Error ? error.message : String(error), + }); + } + })(); + return true; + } + + // --- Phase 2b: In-Browser Workflow Execution --- + else if (message.type === "EXECUTE_IN_BROWSER") { + // Start executing a workflow in the user's Chrome browser + isAsync = true; + (async () => { + try { + const { workflowName } = message.payload; + // Fetch workflow from backend + const response = await fetch(`${BACKEND_BASE_URL}/api/workflows/${encodeURIComponent(workflowName)}`); + const workflowJson = await response.json(); + const workflow = typeof workflowJson === "string" ? JSON.parse(workflowJson) : workflowJson; + + if (!workflow || !workflow.steps || workflow.steps.length === 0) { + sendResponse({ success: false, error: "Workflow has no steps" }); + return; + } + + // Start execution + executionEngine.start(workflow.steps, workflow.name || workflowName); + sendResponse({ success: true, totalSteps: workflow.steps.length }); + } catch (error) { + console.error("[EXECUTE_IN_BROWSER] Error:", error); + sendResponse({ + success: false, + error: error instanceof Error ? error.message : String(error), + }); + } + })(); + return true; + } + else if (message.type === "STOP_EXECUTION") { + executionEngine.stop(); + sendResponse({ success: true }); + } + else if (message.type === "GET_EXECUTION_STATUS") { + sendResponse(executionEngine.getStatus()); + } + // Handle EXECUTOR_READY from content-executor.ts + else if (message.type === "EXECUTOR_READY") { + console.log("[Execution] Executor ready on:", message.url); + executionEngine.onExecutorReady(); + } + // --- Removed Handlers --- // else if (message.type === "CLEAR_RECORDING_DATA") { ... } // Now handled by START_RECORDING // else if (message.type === "GET_RECORDING_STATUS") { ... } // Sidepanel uses GET_RECORDING_DATA @@ -797,6 +958,337 @@ export default defineBackground(() => { return isAsync; }); + // ========================================================================= + // Phase 2b: ExecutionEngine — Orchestrates in-browser workflow replay + // ========================================================================= + + interface StepResult { + stepIndex: number; + success: boolean; + error?: string; + healed?: boolean; + } + + class ExecutionEngine { + // eslint-disable-next-line @typescript-eslint/no-explicit-any + private steps: Record[] = []; + private currentStepIndex: number = 0; + private state: "idle" | "running" | "waiting_nav" | "healing" | "completed" | "failed" | "stopped" = "idle"; + private targetTabId: number | null = null; + private workflowName: string = ""; + private results: StepResult[] = []; + private executorReadyResolve: (() => void) | null = null; + private stepDelayMs: number = 1500; // Delay between steps for page stability + + // eslint-disable-next-line @typescript-eslint/no-explicit-any + async start(steps: Record[], name: string) { + this.steps = steps; + this.currentStepIndex = 0; + this.state = "running"; + this.workflowName = name; + this.results = []; + + // Use the currently active tab + const [activeTab] = await chrome.tabs.query({ active: true, currentWindow: true }); + if (!activeTab?.id) { + this.state = "failed"; + console.error("[Execution] No active tab found"); + return; + } + this.targetTabId = activeTab.id; + + console.log(`[Execution] Starting workflow "${name}" with ${steps.length} steps on tab ${this.targetTabId}`); + + // Broadcast execution started + this.broadcastStatus(); + + // Inject executor into current tab + await this.injectExecutor(this.targetTabId); + + // Start executing steps + await this.executeNextStep(); + } + + stop() { + this.state = "stopped"; + console.log("[Execution] Stopped by user"); + this.broadcastStatus(); + } + + getStatus() { + return { + state: this.state, + currentStepIndex: this.currentStepIndex, + totalSteps: this.steps.length, + workflowName: this.workflowName, + results: this.results, + }; + } + + onExecutorReady() { + if (this.executorReadyResolve) { + this.executorReadyResolve(); + this.executorReadyResolve = null; + } + } + + private async injectExecutor(tabId: number) { + try { + await chrome.scripting.executeScript({ + target: { tabId }, + files: ["content-executor.js"], + }); + console.log(`[Execution] Executor injected into tab ${tabId}`); + } catch (err) { + console.warn(`[Execution] Executor injection: ${err}`); + } + + // Wait for EXECUTOR_READY with timeout + await Promise.race([ + new Promise((resolve) => { this.executorReadyResolve = resolve; }), + new Promise((resolve) => setTimeout(resolve, 3000)), // 3s timeout + ]); + } + + private async executeNextStep() { + if (this.state !== "running" || this.currentStepIndex >= this.steps.length) { + if (this.state === "running") { + this.state = "completed"; + console.log(`[Execution] Workflow "${this.workflowName}" completed!`); + } + this.broadcastStatus(); + return; + } + + const step = this.steps[this.currentStepIndex]; + const stepType = step.type as string; + + console.log(`[Execution] Step ${this.currentStepIndex + 1}/${this.steps.length}: ${stepType}`); + this.broadcastStatus(); + + // Handle navigation steps directly from background + if (stepType === "navigation") { + const url = step.url as string; + if (url && this.targetTabId) { + console.log(`[Execution] Navigating to: ${url}`); + this.state = "waiting_nav"; + + // Navigate + chrome.tabs.update(this.targetTabId, { url }); + + // Wait for page load + await this.waitForPageLoad(this.targetTabId); + + // Re-inject executor + await this.injectExecutor(this.targetTabId); + + this.state = "running"; + this.results.push({ stepIndex: this.currentStepIndex, success: true }); + this.currentStepIndex++; + + // Delay then continue + await this.delay(this.stepDelayMs); + await this.executeNextStep(); + } + return; + } + + // For all other steps, send to content executor + if (!this.targetTabId) { + this.state = "failed"; + this.broadcastStatus(); + return; + } + + try { + const result = await this.sendStepToExecutor(this.targetTabId, step); + + if (result.success) { + this.results.push({ stepIndex: this.currentStepIndex, success: true }); + this.currentStepIndex++; + + // Check if this step might have caused navigation + const navigationDetected = await this.checkForNavigation(this.targetTabId); + if (navigationDetected) { + await this.waitForPageLoad(this.targetTabId); + await this.injectExecutor(this.targetTabId); + } + + // Delay then continue + await this.delay(this.stepDelayMs); + await this.executeNextStep(); + } else { + console.error(`[Execution] Step ${this.currentStepIndex} failed: ${result.error}`); + + // Try healing via backend LLM + const healed = await this.tryHealing(step, result.error || "Unknown error"); + if (healed) { + this.results.push({ stepIndex: this.currentStepIndex, success: true, healed: true }); + this.currentStepIndex++; + await this.delay(this.stepDelayMs); + await this.executeNextStep(); + } else { + this.results.push({ stepIndex: this.currentStepIndex, success: false, error: result.error }); + this.state = "failed"; + this.broadcastStatus(); + } + } + } catch (error) { + console.error(`[Execution] Step ${this.currentStepIndex} threw:`, error); + this.results.push({ + stepIndex: this.currentStepIndex, + success: false, + error: error instanceof Error ? error.message : String(error), + }); + this.state = "failed"; + this.broadcastStatus(); + } + } + + // eslint-disable-next-line @typescript-eslint/no-explicit-any + private sendStepToExecutor(tabId: number, step: Record): Promise<{ success: boolean; error?: string }> { + return new Promise((resolve) => { + chrome.tabs.sendMessage( + tabId, + { type: "EXECUTE_STEP", step, stepIndex: this.currentStepIndex }, + (response) => { + if (chrome.runtime.lastError) { + resolve({ success: false, error: chrome.runtime.lastError.message }); + } else if (response) { + resolve({ success: response.success, error: response.error }); + } else { + resolve({ success: false, error: "No response from executor" }); + } + } + ); + }); + } + + private waitForPageLoad(tabId: number): Promise { + return new Promise((resolve) => { + const timeout = setTimeout(() => { + chrome.tabs.onUpdated.removeListener(listener); + resolve(); + }, 15000); // 15s timeout + + const listener = (updatedTabId: number, changeInfo: chrome.tabs.TabChangeInfo) => { + if (updatedTabId === tabId && changeInfo.status === "complete") { + clearTimeout(timeout); + chrome.tabs.onUpdated.removeListener(listener); + // Extra delay for dynamic content + setTimeout(resolve, 1000); + } + }; + + chrome.tabs.onUpdated.addListener(listener); + }); + } + + private checkForNavigation(tabId: number): Promise { + return new Promise((resolve) => { + let detected = false; + const timeout = setTimeout(() => { + chrome.tabs.onUpdated.removeListener(listener); + resolve(detected); + }, 2000); // 2s window to detect navigation + + const listener = (updatedTabId: number, changeInfo: chrome.tabs.TabChangeInfo) => { + if (updatedTabId === tabId && (changeInfo.url || changeInfo.status === "loading")) { + detected = true; + clearTimeout(timeout); + chrome.tabs.onUpdated.removeListener(listener); + resolve(true); + } + }; + + chrome.tabs.onUpdated.addListener(listener); + }); + } + + // eslint-disable-next-line @typescript-eslint/no-explicit-any + private async tryHealing(step: Record, error: string): Promise { + if (!this.targetTabId) return false; + + this.state = "healing"; + this.broadcastStatus(); + console.log(`[Execution] Attempting self-healing for step ${this.currentStepIndex}...`); + + try { + // Capture screenshot + const screenshotDataUrl = await new Promise((resolve) => { + chrome.tabs.captureVisibleTab({ format: "png" }, (dataUrl) => { + if (chrome.runtime.lastError) { + resolve(null); + } else { + resolve(dataUrl); + } + }); + }); + + if (!screenshotDataUrl) { + console.warn("[Execution] Could not capture screenshot for healing"); + this.state = "running"; + return false; + } + + // Send to backend for LLM healing + const healResponse = await fetch(`${BACKEND_BASE_URL}/api/ext-execute/heal`, { + method: "POST", + headers: { "Content-Type": "application/json" }, + body: JSON.stringify({ + step, + stepIndex: this.currentStepIndex, + error, + screenshot: screenshotDataUrl, + pageUrl: await this.getTabUrl(this.targetTabId), + }), + }); + + if (!healResponse.ok) { + console.warn("[Execution] Healing endpoint not available (backend may not have ext-execute router yet)"); + this.state = "running"; + return false; + } + + const healData = await healResponse.json(); + if (healData.correctedStep) { + // Retry with corrected step + this.state = "running"; + const retryResult = await this.sendStepToExecutor(this.targetTabId, healData.correctedStep); + return retryResult.success; + } + } catch (err) { + console.warn("[Execution] Healing failed:", err); + } + + this.state = "running"; + return false; + } + + private getTabUrl(tabId: number): Promise { + return new Promise((resolve) => { + chrome.tabs.get(tabId, (tab) => { + resolve(tab?.url || ""); + }); + }); + } + + private delay(ms: number): Promise { + return new Promise((resolve) => setTimeout(resolve, ms)); + } + + private broadcastStatus() { + chrome.runtime.sendMessage({ + type: "execution_status_updated", + payload: this.getStatus(), + }).catch(() => { + // Sidepanel might not be open + }); + } + } + + const executionEngine = new ExecutionEngine(); + // Optional: Save data periodically or on browser close (less reliable) // chrome.storage.local.set({ sessionLogs, tabInfo }); diff --git a/extension/src/entrypoints/content-executor.ts b/extension/src/entrypoints/content-executor.ts new file mode 100644 index 00000000..dcdf4dcc --- /dev/null +++ b/extension/src/entrypoints/content-executor.ts @@ -0,0 +1,563 @@ +/** + * Content Executor — Replays workflow steps in the user's Chrome browser. + * + * This is a SEPARATE content script from content.ts (recording). + * It is injected programmatically by background.ts when execution starts. + * + * Element finding priority: target_text (semantic) → cssSelector → xpath + * Actions use real DOM events to trigger React/Vue/Angular handlers. + */ + +// --- Element Finding --- + +/** + * Find an element on the page using multiple strategies. + * Returns the element or null if not found. + */ +function findElement(step: Record): HTMLElement | null { + const targetText = (step.target_text || step.targetText) as string | undefined; + const cssSelector = step.cssSelector as string | undefined; + const xpath = step.xpath as string | undefined; + + // Strategy 1: Semantic text matching (most reliable across page changes) + if (targetText) { + const found = findByTargetText(targetText, step); + if (found) { + console.log(`[Executor] Found by target_text: "${targetText}"`); + return found; + } + } + + // Strategy 2: CSS selector + if (cssSelector) { + try { + const found = document.querySelector(cssSelector) as HTMLElement | null; + if (found && isElementVisible(found)) { + console.log(`[Executor] Found by cssSelector: "${cssSelector}"`); + return found; + } + } catch { + // Invalid selector — skip + } + } + + // Strategy 3: XPath + if (xpath) { + try { + const result = document.evaluate( + xpath, + document, + null, + XPathResult.FIRST_ORDERED_NODE_TYPE, + null + ); + const found = result.singleNodeValue as HTMLElement | null; + if (found && isElementVisible(found)) { + console.log(`[Executor] Found by xpath: "${xpath}"`); + return found; + } + } catch { + // Invalid xpath — skip + } + } + + return null; +} + +/** + * Find element by semantic target text. + * Searches interactive elements for matching text content, labels, placeholders, etc. + */ +function findByTargetText( + targetText: string, + step: Record +): HTMLElement | null { + const stepType = step.type as string; + const normalizedTarget = targetText.toLowerCase().trim(); + + // Determine which elements to search based on step type + let selector: string; + if (stepType === "input") { + selector = + 'input, textarea, select, [contenteditable="true"], [role="textbox"], [role="combobox"], [role="searchbox"]'; + } else if (stepType === "click") { + selector = + "a, button, input, select, textarea, label, [role], [onclick], [tabindex], summary, details, h1, h2, h3, h4, h5, h6, span, div, li, td, th, img"; + } else { + selector = + "a, button, input, select, textarea, label, [role], [onclick], [tabindex]"; + } + + const candidates = document.querySelectorAll(selector); + let bestMatch: HTMLElement | null = null; + let bestScore = 0; + + for (const el of candidates) { + const element = el as HTMLElement; + if (!isElementVisible(element)) continue; + + const score = getTextMatchScore(element, normalizedTarget); + if (score > bestScore) { + bestScore = score; + bestMatch = element; + } + } + + // Require a minimum score to consider it a match + if (bestScore >= 0.5) { + return bestMatch; + } + + return null; +} + +/** + * Score how well an element matches the target text. + * Returns 0-1 where 1 is a perfect match. + */ +function getTextMatchScore( + element: HTMLElement, + normalizedTarget: string +): number { + let maxScore = 0; + + // Check various text sources + const sources: { text: string; weight: number }[] = []; + + // Direct text content + const textContent = element.textContent?.trim().toLowerCase() || ""; + if (textContent) sources.push({ text: textContent, weight: 1.0 }); + + // Aria label + const ariaLabel = element.getAttribute("aria-label")?.toLowerCase() || ""; + if (ariaLabel) sources.push({ text: ariaLabel, weight: 1.0 }); + + // Placeholder + const placeholder = + (element as HTMLInputElement).placeholder?.toLowerCase() || ""; + if (placeholder) sources.push({ text: placeholder, weight: 0.9 }); + + // Title + const title = element.title?.toLowerCase() || ""; + if (title) sources.push({ text: title, weight: 0.8 }); + + // Value (for inputs) + const value = (element as HTMLInputElement).value?.toLowerCase() || ""; + if (value) sources.push({ text: value, weight: 0.7 }); + + // Name attribute + const name = element.getAttribute("name")?.toLowerCase() || ""; + if (name) sources.push({ text: name, weight: 0.6 }); + + // Associated label (label[for=id]) + const id = element.id; + if (id) { + const label = document.querySelector(`label[for="${id}"]`); + if (label) { + const labelText = label.textContent?.trim().toLowerCase() || ""; + if (labelText) sources.push({ text: labelText, weight: 1.0 }); + } + } + + // Parent label + const parentLabel = element.closest("label"); + if (parentLabel && parentLabel !== element) { + const labelText = parentLabel.textContent?.trim().toLowerCase() || ""; + if (labelText) sources.push({ text: labelText, weight: 0.9 }); + } + + for (const source of sources) { + let score = 0; + + // Exact match + if (source.text === normalizedTarget) { + score = 1.0 * source.weight; + } + // Text contains target + else if (source.text.includes(normalizedTarget)) { + score = 0.8 * source.weight; + } + // Target contains text (e.g., target has extra context) + else if (normalizedTarget.includes(source.text) && source.text.length > 3) { + score = 0.7 * source.weight; + } + // Fuzzy: significant word overlap + else { + const targetWords = new Set( + normalizedTarget.split(/\s+/).filter((w) => w.length > 2) + ); + const sourceWords = new Set( + source.text.split(/\s+/).filter((w) => w.length > 2) + ); + if (targetWords.size > 0 && sourceWords.size > 0) { + let matchCount = 0; + for (const word of targetWords) { + if (sourceWords.has(word)) matchCount++; + } + const overlap = matchCount / Math.max(targetWords.size, 1); + if (overlap >= 0.5) { + score = overlap * 0.6 * source.weight; + } + } + } + + maxScore = Math.max(maxScore, score); + } + + return maxScore; +} + +function isElementVisible(element: HTMLElement): boolean { + if (!element) return false; + const style = window.getComputedStyle(element); + if ( + style.display === "none" || + style.visibility === "hidden" || + style.opacity === "0" + ) + return false; + const rect = element.getBoundingClientRect(); + return rect.width > 0 && rect.height > 0; +} + +// --- Wait for Element --- + +/** + * Wait for an element to appear on the page (handles dynamic/SPA content). + */ +function waitForElement( + step: Record, + timeoutMs: number = 10000 +): Promise { + return new Promise((resolve) => { + // Try immediately first + const immediate = findElement(step); + if (immediate) { + resolve(immediate); + return; + } + + let resolved = false; + const timeout = setTimeout(() => { + if (!resolved) { + resolved = true; + observer.disconnect(); + // One final attempt + resolve(findElement(step)); + } + }, timeoutMs); + + const observer = new MutationObserver(() => { + if (resolved) return; + const found = findElement(step); + if (found) { + resolved = true; + clearTimeout(timeout); + observer.disconnect(); + resolve(found); + } + }); + + observer.observe(document.body, { + childList: true, + subtree: true, + attributes: true, + characterData: true, + }); + }); +} + +// --- Action Execution --- + +/** + * Execute a click action with proper event dispatching for React/Vue compatibility. + */ +function executeClick(element: HTMLElement): void { + // Scroll into view + element.scrollIntoView({ behavior: "smooth", block: "center" }); + + // Small delay after scroll + setTimeout(() => { + // Focus the element + element.focus(); + + // Get element center for realistic mouse events + const rect = element.getBoundingClientRect(); + const x = rect.left + rect.width / 2; + const y = rect.top + rect.height / 2; + + const eventOptions = { + bubbles: true, + cancelable: true, + composed: true, + clientX: x, + clientY: y, + view: window, + }; + + // Full mouse event sequence for React/Vue compatibility + element.dispatchEvent(new MouseEvent("mousedown", eventOptions)); + element.dispatchEvent(new MouseEvent("mouseup", eventOptions)); + element.dispatchEvent(new MouseEvent("click", eventOptions)); + }, 100); +} + +/** + * Execute an input action using native value setter for React compatibility. + */ +function executeInput(element: HTMLElement, value: string): void { + const inputEl = element as HTMLInputElement | HTMLTextAreaElement; + + // Focus + element.focus(); + element.dispatchEvent(new FocusEvent("focus", { bubbles: true })); + + // Use the native value setter to bypass React's controlled component + const nativeInputValueSetter = Object.getOwnPropertyDescriptor( + window.HTMLInputElement.prototype, + "value" + )?.set; + const nativeTextAreaValueSetter = Object.getOwnPropertyDescriptor( + window.HTMLTextAreaElement.prototype, + "value" + )?.set; + + const setter = + element.tagName === "TEXTAREA" + ? nativeTextAreaValueSetter + : nativeInputValueSetter; + + if (setter) { + setter.call(inputEl, value); + } else { + inputEl.value = value; + } + + // Dispatch events that React/Vue listen to + element.dispatchEvent(new Event("input", { bubbles: true, composed: true })); + element.dispatchEvent(new Event("change", { bubbles: true, composed: true })); +} + +/** + * Execute a key press action. + */ +function executeKeyPress(element: HTMLElement | null, key: string): void { + const target = element || document.activeElement || document.body; + + // Map common key names + const keyMap: Record = + { + Enter: { key: "Enter", code: "Enter", keyCode: 13 }, + Tab: { key: "Tab", code: "Tab", keyCode: 9 }, + Escape: { key: "Escape", code: "Escape", keyCode: 27 }, + Backspace: { key: "Backspace", code: "Backspace", keyCode: 8 }, + ArrowDown: { key: "ArrowDown", code: "ArrowDown", keyCode: 40 }, + ArrowUp: { key: "ArrowUp", code: "ArrowUp", keyCode: 38 }, + ArrowLeft: { key: "ArrowLeft", code: "ArrowLeft", keyCode: 37 }, + ArrowRight: { key: "ArrowRight", code: "ArrowRight", keyCode: 39 }, + Space: { key: " ", code: "Space", keyCode: 32 }, + }; + + const mapped = keyMap[key] || { + key, + code: `Key${key.toUpperCase()}`, + keyCode: key.charCodeAt(0), + }; + + const eventOptions = { + key: mapped.key, + code: mapped.code, + keyCode: mapped.keyCode, + which: mapped.keyCode, + bubbles: true, + cancelable: true, + composed: true, + }; + + target.dispatchEvent(new KeyboardEvent("keydown", eventOptions)); + target.dispatchEvent(new KeyboardEvent("keypress", eventOptions)); + target.dispatchEvent(new KeyboardEvent("keyup", eventOptions)); +} + +/** + * Execute a scroll action. + */ +function executeScroll(scrollX: number, scrollY: number): void { + window.scrollTo({ + left: scrollX, + top: scrollY, + behavior: "smooth", + }); +} + +// --- Visual Feedback --- + +let highlightOverlay: HTMLElement | null = null; + +function highlightElement(element: HTMLElement): void { + removeHighlight(); + + const rect = element.getBoundingClientRect(); + highlightOverlay = document.createElement("div"); + highlightOverlay.style.cssText = ` + position: fixed; + left: ${rect.left - 3}px; + top: ${rect.top - 3}px; + width: ${rect.width + 6}px; + height: ${rect.height + 6}px; + border: 3px solid #3B82F6; + border-radius: 4px; + background: rgba(59, 130, 246, 0.1); + z-index: 999999; + pointer-events: none; + transition: all 0.2s ease; + box-shadow: 0 0 12px rgba(59, 130, 246, 0.4); + `; + document.body.appendChild(highlightOverlay); + + // Auto-remove after 2 seconds + setTimeout(removeHighlight, 2000); +} + +function removeHighlight(): void { + if (highlightOverlay && highlightOverlay.parentNode) { + highlightOverlay.parentNode.removeChild(highlightOverlay); + highlightOverlay = null; + } +} + +// --- Main Step Executor --- + +async function executeStep( + step: Record +): Promise<{ success: boolean; error?: string }> { + const stepType = step.type as string; + + console.log(`[Executor] Executing step: ${stepType}`, step); + + try { + // Handle navigation steps (background handles these via chrome.tabs.update) + if (stepType === "navigation") { + // Navigation is handled by background.ts — this shouldn't reach here + // But if it does, navigate via window.location + const url = step.url as string; + if (url) { + window.location.href = url; + return { success: true }; + } + return { success: false, error: "Navigation step has no URL" }; + } + + // Handle scroll steps + if (stepType === "scroll") { + const scrollX = (step.scrollX as number) || 0; + const scrollY = (step.scrollY as number) || 0; + executeScroll(scrollX, scrollY); + return { success: true }; + } + + // For all other steps, find the target element + const element = await waitForElement(step); + + if (!element) { + const targetText = (step.target_text || step.targetText) as string; + const cssSelector = step.cssSelector as string; + return { + success: false, + error: `Element not found. target_text="${targetText || "none"}", cssSelector="${cssSelector || "none"}"`, + }; + } + + // Highlight the element for visual feedback + highlightElement(element); + + switch (stepType) { + case "click": + executeClick(element); + return { success: true }; + + case "input": { + const value = step.value as string; + if (value === undefined || value === null) { + return { success: false, error: "Input step has no value" }; + } + executeInput(element, value); + return { success: true }; + } + + case "key_press": { + const key = step.key as string; + if (!key) { + return { success: false, error: "Key press step has no key" }; + } + executeKeyPress(element, key); + return { success: true }; + } + + case "select_change": { + const value = step.value as string; + if (value !== undefined) { + (element as HTMLSelectElement).value = value; + element.dispatchEvent( + new Event("change", { bubbles: true, composed: true }) + ); + return { success: true }; + } + return { success: false, error: "Select step has no value" }; + } + + default: + return { success: false, error: `Unknown step type: ${stepType}` }; + } + } catch (error) { + return { + success: false, + error: error instanceof Error ? error.message : String(error), + }; + } +} + +// --- Message Listener --- + +export default defineContentScript({ + matches: [""], + runAt: "document_idle", + main() { + console.log("[Executor] Content executor loaded on:", window.location.href); + + // Listen for step execution commands from background + chrome.runtime.onMessage.addListener((message, _sender, sendResponse) => { + if (message.type === "EXECUTE_STEP") { + const step = message.step; + const stepIndex = message.stepIndex; + + console.log(`[Executor] Received step ${stepIndex}:`, step); + + // Execute async and send response + executeStep(step).then((result) => { + console.log(`[Executor] Step ${stepIndex} result:`, result); + sendResponse({ + type: "STEP_RESULT", + stepIndex, + ...result, + }); + }); + + return true; // Keep channel open for async response + } + + if (message.type === "EXECUTOR_PING") { + sendResponse({ type: "EXECUTOR_PONG", url: window.location.href }); + return false; + } + + return false; + }); + + // Notify background that executor is ready + chrome.runtime.sendMessage({ + type: "EXECUTOR_READY", + url: window.location.href, + }); + }, +}); diff --git a/extension/src/entrypoints/sidepanel/components/dashboard-view.tsx b/extension/src/entrypoints/sidepanel/components/dashboard-view.tsx new file mode 100644 index 00000000..67c84039 --- /dev/null +++ b/extension/src/entrypoints/sidepanel/components/dashboard-view.tsx @@ -0,0 +1,296 @@ +import React, { useEffect, useState, useCallback } from "react"; +import { Button } from "@/components/ui/button"; + +interface WorkflowItem { + name: string; + executing?: boolean; + taskId?: string; +} + +export const DashboardView: React.FC = () => { + const [workflows, setWorkflows] = useState([]); + const [loading, setLoading] = useState(true); + const [error, setError] = useState(null); + const [executingWorkflows, setExecutingWorkflows] = useState>(new Set()); + const [browserExecution, setBrowserExecution] = useState<{ + state: string; + currentStepIndex: number; + totalSteps: number; + workflowName: string; + } | null>(null); + + const fetchWorkflows = useCallback(async () => { + try { + const response = await chrome.runtime.sendMessage({ + type: "API_REQUEST", + payload: { endpoint: "/api/workflows", method: "GET" }, + }); + + if (response?.success && response.data?.workflows) { + setWorkflows( + response.data.workflows.map((name: string) => ({ name })) + ); + setError(null); + } else { + setError("Failed to load workflows"); + } + } catch (err) { + setError(err instanceof Error ? err.message : "Connection failed"); + } finally { + setLoading(false); + } + }, []); + + useEffect(() => { + fetchWorkflows(); + + // Listen for execution status updates + const listener = (message: { type: string; payload: typeof browserExecution }) => { + if (message.type === "execution_status_updated") { + setBrowserExecution(message.payload); + } + }; + chrome.runtime.onMessage.addListener(listener); + return () => chrome.runtime.onMessage.removeListener(listener); + }, [fetchWorkflows]); + + const executeInBrowser = async (workflowName: string) => { + try { + const response = await chrome.runtime.sendMessage({ + type: "EXECUTE_IN_BROWSER", + payload: { workflowName }, + }); + if (!response?.success) { + setError(`Failed: ${response?.error || "Unknown error"}`); + } + } catch (err) { + setError(err instanceof Error ? err.message : "Execution failed"); + } + }; + + const stopExecution = () => { + chrome.runtime.sendMessage({ type: "STOP_EXECUTION" }); + }; + + const executeWorkflow = async (workflowName: string) => { + setExecutingWorkflows((prev) => new Set(prev).add(workflowName)); + try { + const response = await chrome.runtime.sendMessage({ + type: "API_REQUEST", + payload: { + endpoint: "/api/workflows/execute", + method: "POST", + body: { name: workflowName, inputs: {} }, + }, + }); + + if (response?.success && response.data?.success) { + // Poll for status + const taskId = response.data.task_id; + pollTaskStatus(taskId, workflowName); + } else { + setExecutingWorkflows((prev) => { + const next = new Set(prev); + next.delete(workflowName); + return next; + }); + setError(`Failed to execute: ${response?.data?.detail || "Unknown error"}`); + } + } catch (err) { + setExecutingWorkflows((prev) => { + const next = new Set(prev); + next.delete(workflowName); + return next; + }); + setError(err instanceof Error ? err.message : "Execution failed"); + } + }; + + const pollTaskStatus = async (taskId: string, workflowName: string) => { + const poll = async () => { + try { + const response = await chrome.runtime.sendMessage({ + type: "API_REQUEST", + payload: { + endpoint: `/api/workflows/tasks/${taskId}/status`, + method: "GET", + }, + }); + + if (response?.success) { + const status = response.data?.status; + if (status === "completed" || status === "failed" || status === "cancelled") { + setExecutingWorkflows((prev) => { + const next = new Set(prev); + next.delete(workflowName); + return next; + }); + if (status === "failed") { + setError(`Workflow failed: ${response.data?.error || "Unknown error"}`); + } + return; // Stop polling + } + } + // Continue polling + setTimeout(poll, 2000); + } catch { + setExecutingWorkflows((prev) => { + const next = new Set(prev); + next.delete(workflowName); + return next; + }); + } + }; + setTimeout(poll, 2000); + }; + + const deleteWorkflow = async (workflowName: string) => { + if (!confirm(`Delete workflow "${workflowName}"?`)) return; + // Note: The backend doesn't have a delete endpoint yet. + // For now, we show the user a note about this. + setError("Delete is not yet supported from the extension. Remove the file from the tmp/ folder."); + }; + + if (loading) { + return ( +
+
Loading workflows...
+
+ ); + } + + return ( +
+ {/* Header */} +
+
+

Workflows

+

+ {workflows.length} workflow{workflows.length !== 1 ? "s" : ""} saved +

+
+ +
+ + {/* Error Banner */} + {error && ( +
+ {error} + +
+ )} + + {/* Workflow List */} +
+ {workflows.length === 0 ? ( +
+
📭
+

No workflows yet

+

+ Record a workflow using the Record tab, or place .workflow.yaml files in the tmp/ folder +

+
+ ) : ( + workflows.map((wf) => { + const isExecuting = executingWorkflows.has(wf.name); + // Extract display name from filename + const displayName = wf.name + .replace(/\.workflow\.(json|yaml|yml)$/, "") + .replace(/_/g, " "); + + return ( +
+
+
+

+ {displayName} +

+

+ {wf.name} +

+
+
+ {browserExecution?.state === "running" && browserExecution.workflowName === wf.name ? ( + + ) : ( + + )} + +
+
+ {/* Execution progress bar */} + {browserExecution && browserExecution.workflowName === wf.name && browserExecution.state !== "idle" && ( +
+
+ + {browserExecution.state === "running" && "Executing..."} + {browserExecution.state === "waiting_nav" && "Waiting for page load..."} + {browserExecution.state === "healing" && "Self-healing..."} + {browserExecution.state === "completed" && "Completed!"} + {browserExecution.state === "failed" && "Failed"} + {browserExecution.state === "stopped" && "Stopped"} + + + Step {browserExecution.currentStepIndex + 1} / {browserExecution.totalSteps} + +
+
+
+
+
+ )} +
+ ); + }) + )} +
+
+ ); +}; diff --git a/extension/src/entrypoints/sidepanel/components/settings-view.tsx b/extension/src/entrypoints/sidepanel/components/settings-view.tsx new file mode 100644 index 00000000..6639597e --- /dev/null +++ b/extension/src/entrypoints/sidepanel/components/settings-view.tsx @@ -0,0 +1,235 @@ +import React, { useEffect, useState, useCallback } from "react"; +import { Button } from "@/components/ui/button"; + +interface ConnectionStatus { + connected: boolean; + message: string; + timestamp?: number; +} + +export const SettingsView: React.FC = () => { + const [backendUrl, setBackendUrl] = useState("http://127.0.0.1:8000"); + const [editingUrl, setEditingUrl] = useState(""); + const [isEditing, setIsEditing] = useState(false); + const [connectionStatus, setConnectionStatus] = useState({ + connected: false, + message: "Not checked", + }); + const [testing, setTesting] = useState(false); + const [saved, setSaved] = useState(false); + + // Load current settings + useEffect(() => { + chrome.runtime.sendMessage({ type: "GET_BACKEND_URL" }, (response) => { + if (response?.url) { + setBackendUrl(response.url); + setEditingUrl(response.url); + } + }); + }, []); + + const testConnection = useCallback(async () => { + setTesting(true); + setConnectionStatus({ connected: false, message: "Testing..." }); + + try { + const response = await chrome.runtime.sendMessage({ + type: "CHECK_BACKEND_HEALTH", + }); + + if (response?.connected) { + setConnectionStatus({ + connected: true, + message: `Connected to ${response.data?.service || "backend"}`, + timestamp: response.data?.timestamp, + }); + } else { + setConnectionStatus({ + connected: false, + message: `Failed: ${response?.error || "Unknown error"}`, + }); + } + } catch (error) { + setConnectionStatus({ + connected: false, + message: `Error: ${error instanceof Error ? error.message : String(error)}`, + }); + } finally { + setTesting(false); + } + }, []); + + // Test on mount + useEffect(() => { + testConnection(); + }, [testConnection]); + + const saveUrl = () => { + const trimmed = editingUrl.trim().replace(/\/+$/, ""); // Remove trailing slashes + if (!trimmed) return; + + chrome.runtime.sendMessage( + { type: "UPDATE_BACKEND_URL", payload: { url: trimmed } }, + (response) => { + if (response?.success) { + setBackendUrl(trimmed); + setIsEditing(false); + setSaved(true); + setTimeout(() => setSaved(false), 2000); + // Re-test with new URL + testConnection(); + } + } + ); + }; + + return ( +
+ {/* Header */} +
+

Settings

+

+ Configure your Workflow Use extension +

+
+ +
+ {/* Connection Status */} +
+

+ Backend Connection +

+
+
+
+

+ {connectionStatus.connected ? "Connected" : "Disconnected"} +

+

+ {connectionStatus.message} +

+
+ +
+
+ + {/* Backend URL */} +
+

Backend URL

+

+ The URL where the workflow-use Python backend is running +

+ {isEditing ? ( +
+ setEditingUrl(e.target.value)} + placeholder="http://127.0.0.1:8000" + className="w-full p-2 text-sm border border-gray-300 rounded focus:outline-none focus:ring-1 focus:ring-blue-500 font-mono" + /> +
+ + +
+
+ ) : ( +
+ + {backendUrl} + + +
+ )} + {saved && ( +

+ Settings saved! +

+ )} +
+ + {/* Quick Info */} +
+

Quick Start

+
+

+ 1. Make sure the Python backend is running: +

+ + cd workflows && python cli.py launch-gui + +

+ 2. Go to the Record tab to start + recording a workflow +

+

+ 3. Your recorded workflows appear in the{" "} + Workflows tab +

+
+
+ + {/* About */} +
+

About

+
+

Workflow Use — Browser automation with self-healing

+

Phase 2: Standalone Chrome Extension

+

+ Records in YOUR browser with your credentials +

+
+
+
+
+ ); +}; diff --git a/extension/src/entrypoints/sidepanel/components/stopped-view.tsx b/extension/src/entrypoints/sidepanel/components/stopped-view.tsx index 0f08de50..aaf06c3c 100644 --- a/extension/src/entrypoints/sidepanel/components/stopped-view.tsx +++ b/extension/src/entrypoints/sidepanel/components/stopped-view.tsx @@ -8,6 +8,8 @@ export const StoppedView: React.FC = () => { const [showSaveDialog, setShowSaveDialog] = useState(false); const [workflowName, setWorkflowName] = useState(""); const [workflowDescription, setWorkflowDescription] = useState(""); + const [saveStatus, setSaveStatus] = useState<"idle" | "saving" | "saved" | "error">("idle"); + const [saveError, setSaveError] = useState(null); const downloadJson = (customName?: string, customDescription?: string) => { if (!workflow) return; @@ -49,8 +51,65 @@ export const StoppedView: React.FC = () => { downloadJson(); }; + const saveToBackend = async (customName: string, customDescription?: string) => { + if (!workflow) return; + + setSaveStatus("saving"); + setSaveError(null); + + const enhancedWorkflow = { + ...workflow, + name: customName, + description: customDescription || workflow.description, + // eslint-disable-next-line @typescript-eslint/no-explicit-any + workflow_analysis: `Recorded workflow with ${workflow.steps?.length || 0} steps. ${workflow.steps?.some(s => (s as any).type === 'extract') ? 'Includes AI extraction steps for intelligent data gathering.' : ''}` + }; + + // Remove internal fields from steps before saving + const cleanedWorkflow = { + ...enhancedWorkflow, + // eslint-disable-next-line @typescript-eslint/no-explicit-any + steps: enhancedWorkflow.steps?.map((step: any) => { + const cleaned = { ...step }; + delete cleaned.timestamp; + delete cleaned.tabId; + delete cleaned.frameUrl; + delete cleaned.xpath; + delete cleaned.elementTag; + delete cleaned.elementText; + delete cleaned.screenshot; + // Convert targetText to target_text + if (cleaned.targetText) { + cleaned.target_text = cleaned.targetText; + delete cleaned.targetText; + } + return cleaned; + }), + }; + + try { + const response = await chrome.runtime.sendMessage({ + type: "SAVE_WORKFLOW_TO_BACKEND", + payload: { workflow: cleanedWorkflow, name: customName }, + }); + + if (response?.success) { + setSaveStatus("saved"); + setTimeout(() => setSaveStatus("idle"), 3000); + } else { + setSaveStatus("error"); + setSaveError(response?.data?.error || response?.error || "Failed to save"); + } + } catch (error) { + setSaveStatus("error"); + setSaveError(error instanceof Error ? error.message : "Connection failed"); + } + }; + const handleSaveWithDetails = () => { if (workflowName.trim()) { + // Save to backend AND download locally + saveToBackend(workflowName.trim(), workflowDescription.trim()); downloadJson(workflowName.trim(), workflowDescription.trim()); setShowSaveDialog(false); setWorkflowName(""); @@ -100,6 +159,19 @@ export const StoppedView: React.FC = () => {
+ + {/* Save Status Banner */} + {saveStatus === "saved" && ( +
+ Workflow saved to backend! View it in the Workflows tab. +
+ )} + {saveStatus === "error" && ( +
+ Save failed: {saveError} + +
+ )} {/* Save Dialog */} {showSaveDialog && ( diff --git a/extension/src/entrypoints/sidepanel/components/tab-navigation.tsx b/extension/src/entrypoints/sidepanel/components/tab-navigation.tsx new file mode 100644 index 00000000..4e6bd3a4 --- /dev/null +++ b/extension/src/entrypoints/sidepanel/components/tab-navigation.tsx @@ -0,0 +1,60 @@ +import React from "react"; + +export type TabId = "dashboard" | "record" | "settings"; + +interface TabNavigationProps { + activeTab: TabId; + onTabChange: (tab: TabId) => void; + backendConnected: boolean; +} + +const tabs: { id: TabId; label: string; icon: string }[] = [ + { id: "dashboard", label: "Workflows", icon: "📋" }, + { id: "record", label: "Record", icon: "🔴" }, + { id: "settings", label: "Settings", icon: "⚙️" }, +]; + +export const TabNavigation: React.FC = ({ + activeTab, + onTabChange, + backendConnected, +}) => { + return ( +
+ {/* Connection indicator */} +
+
+
+ + {/* Tabs */} +
+ {tabs.map((tab) => ( + + ))} +
+ + {/* Brand */} +
+ WF-Use +
+
+ ); +}; diff --git a/extension/src/entrypoints/sidepanel/index.tsx b/extension/src/entrypoints/sidepanel/index.tsx index 7570d3f2..82d19ca9 100644 --- a/extension/src/entrypoints/sidepanel/index.tsx +++ b/extension/src/entrypoints/sidepanel/index.tsx @@ -1,18 +1,22 @@ -import React from "react"; +import React, { useCallback, useEffect, useState } from "react"; import ReactDOM from "react-dom/client"; // import vite tailwind css import "@/assets/tailwind.css"; +import { DashboardView } from "./components/dashboard-view"; import { ErrorView } from "./components/error-view"; import { InitialView } from "./components/initial-view"; import { LoadingView } from "./components/logina-view"; import { RecordingView } from "./components/recording-view"; +import { SettingsView } from "./components/settings-view"; import { StoppedView } from "./components/stopped-view"; +import { TabNavigation, TabId } from "./components/tab-navigation"; import { WorkflowProvider, useWorkflow } from "./context/workflow-provider"; +// Record tab content — shows the appropriate view based on recording state // eslint-disable-next-line react-refresh/only-export-components -const AppContent: React.FC = () => { +const RecordTabContent: React.FC = () => { const { recordingStatus, isLoading, error } = useWorkflow(); if (isLoading) { @@ -34,16 +38,63 @@ const AppContent: React.FC = () => { } }; +// Main app with tab navigation +// eslint-disable-next-line react-refresh/only-export-components +const AppContent: React.FC = () => { + const [activeTab, setActiveTab] = useState("record"); + const [backendConnected, setBackendConnected] = useState(false); + + // Check backend health on mount and periodically + const checkHealth = useCallback(async () => { + try { + const response = await chrome.runtime.sendMessage({ + type: "CHECK_BACKEND_HEALTH", + }); + setBackendConnected(response?.connected ?? false); + } catch { + setBackendConnected(false); + } + }, []); + + useEffect(() => { + checkHealth(); + const interval = setInterval(checkHealth, 15000); // Check every 15s + return () => clearInterval(interval); + }, [checkHealth]); + + const renderTabContent = () => { + switch (activeTab) { + case "dashboard": + return ; + case "record": + return ; + case "settings": + return ; + default: + return ; + } + }; + + return ( +
+ +
+ {renderTabContent()} +
+
+ ); +}; + // eslint-disable-next-line react-refresh/only-export-components const SidepanelApp: React.FC = () => { return ( -
-
- -
-
+ ); diff --git a/extension/wxt.config.ts b/extension/wxt.config.ts index 9d7ae4ec..b506ae6a 100644 --- a/extension/wxt.config.ts +++ b/extension/wxt.config.ts @@ -13,8 +13,8 @@ export default defineConfig({ // WXT-specific overrides (optional) }), manifest: { - permissions: ["tabs", "sidePanel", ""], - host_permissions: ["http://127.0.0.1/*"], + permissions: ["tabs", "sidePanel", "storage", "scripting", "activeTab", ""], + host_permissions: ["http://127.0.0.1/*", "http://localhost/*"], // options_page: "options.html", // action: { // default_popup: "popup.html", diff --git a/workflows/backend/api.py b/workflows/backend/api.py index febe5853..0ef11d92 100644 --- a/workflows/backend/api.py +++ b/workflows/backend/api.py @@ -2,14 +2,21 @@ from fastapi import FastAPI from fastapi.middleware.cors import CORSMiddleware +from .recorder_router import router as recorder_router from .routers import router app = FastAPI(title='Workflow Execution Service') # Add CORS middleware +# Allow requests from: React UI dev server, Chrome extensions (any ID), localhost variants app.add_middleware( CORSMiddleware, - allow_origins=['http://localhost:5173'], + allow_origins=[ + 'http://localhost:5173', + 'http://127.0.0.1:5173', + ], + # Chrome extension origins are handled by allow_origin_regex + allow_origin_regex=r'^chrome-extension://.*$', allow_credentials=True, allow_methods=['*'], allow_headers=['*'], @@ -17,6 +24,7 @@ # Include routers app.include_router(router) +app.include_router(recorder_router) # Optional standalone runner diff --git a/workflows/backend/recorder_router.py b/workflows/backend/recorder_router.py new file mode 100644 index 00000000..8b838ebe --- /dev/null +++ b/workflows/backend/recorder_router.py @@ -0,0 +1,150 @@ +""" +Recorder endpoints for Phase 2 — receives events directly from the Chrome extension. +Replaces the temporary :7331 server from the Playwright-based recording flow. +""" + +import asyncio +import json +import time +from pathlib import Path +from typing import Optional + +import yaml +from fastapi import APIRouter + +from workflow_use.recorder.views import ( + HttpRecordingStoppedEvent, + HttpWorkflowUpdateEvent, + RecorderEvent, +) + +router = APIRouter(prefix='/api/recorder') + +# Module-level state for the recording session +_last_workflow_update: Optional[HttpWorkflowUpdateEvent] = None +_recording_active: bool = False +_recording_start_time: Optional[float] = None +_workflow_save_dir: Path = Path('./tmp') +_workflow_save_dir.mkdir(exist_ok=True, parents=True) + + +class RecorderSessionState: + """Manages recording session state.""" + + def __init__(self): + self.last_workflow_update: Optional[HttpWorkflowUpdateEvent] = None + self.recording_active: bool = False + self.recording_start_time: Optional[float] = None + self.save_dir: Path = Path('./tmp') + self.save_dir.mkdir(exist_ok=True, parents=True) + + def reset(self): + self.last_workflow_update = None + self.recording_active = False + self.recording_start_time = None + + +_session = RecorderSessionState() + + +@router.post('/event', status_code=202) +async def receive_event(event_data: RecorderEvent): + """Receive recording events from the Chrome extension. + Same contract as the old :7331/event endpoint.""" + if isinstance(event_data, HttpWorkflowUpdateEvent): + _session.last_workflow_update = event_data + elif isinstance(event_data, HttpRecordingStoppedEvent): + _session.recording_active = False + + return {'status': 'accepted', 'message': 'Event received'} + + +@router.post('/start') +async def start_recording(): + """Initialize a new recording session.""" + _session.reset() + _session.recording_active = True + _session.recording_start_time = time.time() + return { + 'status': 'started', + 'message': 'Recording session initialized on backend', + } + + +@router.post('/stop') +async def stop_recording(): + """Finalize the recording session and return the captured workflow.""" + _session.recording_active = False + + if _session.last_workflow_update and _session.last_workflow_update.payload: + workflow_data = _session.last_workflow_update.payload + return { + 'status': 'stopped', + 'workflow': workflow_data.model_dump() if hasattr(workflow_data, 'model_dump') else workflow_data, + 'message': 'Recording stopped. Workflow data available.', + } + + return { + 'status': 'stopped', + 'workflow': None, + 'message': 'Recording stopped. No workflow data was captured.', + } + + +@router.get('/status') +async def get_status(): + """Check if a recording session is active.""" + step_count = 0 + if _session.last_workflow_update and _session.last_workflow_update.payload: + payload = _session.last_workflow_update.payload + if hasattr(payload, 'steps') and payload.steps: + step_count = len(payload.steps) + + return { + 'recording': _session.recording_active, + 'has_workflow_data': _session.last_workflow_update is not None, + 'step_count': step_count, + 'started_at': _session.recording_start_time, + } + + +@router.post('/save') +async def save_workflow(request: dict): + """Save a recorded workflow to the tmp/ directory as a YAML file.""" + workflow_data = request.get('workflow') + name = request.get('name', '').strip() + + if not workflow_data: + return {'success': False, 'error': 'No workflow data provided'} + + if not name: + # Generate a name from timestamp + name = f'recorded_{time.strftime("%Y%m%d_%H%M%S")}' + + # Sanitize filename + safe_name = ''.join(c if c.isalnum() or c in '_-' else '_' for c in name).lower() + filename = f'{safe_name}.workflow.yaml' + filepath = _session.save_dir / filename + + # Convert to YAML and save + try: + yaml_content = yaml.dump(workflow_data, default_flow_style=False, sort_keys=False, allow_unicode=True) + filepath.write_text(yaml_content, encoding='utf-8') + return { + 'success': True, + 'filename': filename, + 'message': f'Workflow saved as {filename}', + } + except Exception as e: + return {'success': False, 'error': f'Failed to save workflow: {str(e)}'} + + +@router.get('/health') +async def health_check(): + """Health check endpoint for the extension to verify backend connectivity.""" + return { + 'status': 'ok', + 'service': 'workflow-use-backend', + 'recording_available': True, + 'timestamp': int(time.time() * 1000), + } diff --git a/workflows/backend/service.py b/workflows/backend/service.py index be695d79..20683a7d 100644 --- a/workflows/backend/service.py +++ b/workflows/backend/service.py @@ -6,7 +6,7 @@ import aiofiles import yaml -from browser_use.browser.browser import Browser +from browser_use import Browser from workflow_use.controller.service import WorkflowController from workflow_use.llm import get_llm