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Create, edit, run deterministic workflows

Project description

Workflow-Use

Semantic browser automation with deterministic workflow generation and variables.

Quick Start

1. Test Deterministic Workflow Generation (NEW!)

python examples/scripts/deterministic/run_complete_test.py

Generate workflows without LLM for step creation - 10-100x faster, guaranteed semantic steps.

2. Create Your Own Workflow

from workflow_use.healing.service import HealingService
from browser_use.llm import ChatBrowserUse

llm = ChatBrowserUse(model_name="bu-latest")
service = HealingService(llm=llm, use_deterministic_conversion=True)

workflow = await service.generate_workflow_from_prompt(
    prompt="Go to GitHub, search for browser-use, get star count",
    agent_llm=llm,
    extraction_llm=llm
)

3. Run a Workflow

cd /path/to/workflow-use/workflows
python cli.py run-workflow-no-ai my_workflow.json

# If the workflow has variables, the CLI will prompt you interactively:
# Enter value for repo_name (required, type: string): browser-use

Key Features

๐Ÿš€ Deterministic Workflow Generation

  • Direct Action Mapping: input_text โ†’ input step (no LLM)
  • Guaranteed Semantic Steps: 0 agent steps (instant execution, $0/run)
  • 10-100x Faster: 5-10s vs 20-40s for LLM-based
  • 90% Cheaper: Minimal LLM usage

๐ŸŽฏ Semantic-Only Multi-Strategy Element Finding

  • No CSS/XPath: 100% semantic strategies (text, role, ARIA, placeholder, etc.)
  • 7 Fallback Strategies: text_exact โ†’ role_text โ†’ aria_label โ†’ placeholder โ†’ title โ†’ alt_text โ†’ text_fuzzy
  • Works WITH Browser-Use: Finds element index in DOM state, then uses browser-use's controller
  • Fast & Robust: Direct index lookup when strategies match, falls back to AI when needed
  • Human-Readable: Workflow YAML contains semantic strategies, not brittle selectors

๐Ÿ”„ Variables in Workflows

  • Reusable Workflows: Parameterize dynamic values
  • Semantic Targeting: Use {variable} in target_text
  • Auto-Extraction: LLM suggests variables automatically

Documentation


Project Structure

workflows/
โ”œโ”€โ”€ workflow_use/              # Main package
โ”‚   โ”œโ”€โ”€ healing/              # Workflow generation & healing
โ”‚   โ”‚   โ”œโ”€โ”€ deterministic_converter.py   # NEW: Deterministic conversion
โ”‚   โ”‚   โ”œโ”€โ”€ variable_extractor.py        # Auto variable detection
โ”‚   โ”‚   โ””โ”€โ”€ service.py                   # Main workflow generation
โ”‚   โ”œโ”€โ”€ workflow/             # Workflow execution
โ”‚   โ”‚   โ””โ”€โ”€ semantic_executor.py         # Semantic step execution
โ”‚   โ”œโ”€โ”€ controller/           # Workflow controller
โ”‚   โ”œโ”€โ”€ recorder/             # Workflow recording
โ”‚   โ”œโ”€โ”€ storage/              # Storage logic
โ”‚   โ”œโ”€โ”€ mcp/                  # MCP integration
โ”‚   โ”œโ”€โ”€ schema/               # Schema definitions
โ”‚   โ””โ”€โ”€ builder/              # Workflow builder
โ”‚
โ”œโ”€โ”€ backend/                  # FastAPI backend service
โ”‚   โ”œโ”€โ”€ api.py               # API entry point
โ”‚   โ”œโ”€โ”€ routers.py           # API routes
โ”‚   โ””โ”€โ”€ service.py           # Business logic
โ”‚
โ”œโ”€โ”€ examples/                 # Examples organized by feature
โ”‚   โ”œโ”€โ”€ scripts/
โ”‚   โ”‚   โ”œโ”€โ”€ deterministic/   # Deterministic workflow examples
โ”‚   โ”‚   โ”‚   โ”œโ”€โ”€ run_complete_test.py        # โญ Test deterministic generation
โ”‚   โ”‚   โ”‚   โ””โ”€โ”€ create_deterministic_workflow.py
โ”‚   โ”‚   โ”œโ”€โ”€ variables/       # Variable feature examples
โ”‚   โ”‚   โ”œโ”€โ”€ demos/           # Advanced demos
โ”‚   โ”‚   โ””โ”€โ”€ runner.py        # Generic workflow runner
โ”‚   โ””โ”€โ”€ workflows/           # Example workflow JSON files
โ”‚       โ”œโ”€โ”€ basic/           # Basic workflow examples
โ”‚       โ”œโ”€โ”€ form_filling/    # Form filling examples
โ”‚       โ”œโ”€โ”€ parameterized/   # Parameterized workflows
โ”‚       โ””โ”€โ”€ advanced/        # Advanced workflows
โ”‚
โ”œโ”€โ”€ tests/                    # Test files
โ”‚   โ”œโ”€โ”€ test_button_click.py
โ”‚   โ””โ”€โ”€ test_recorded_workflow.py
โ”‚
โ”œโ”€โ”€ docs/                     # Documentation
โ”‚   โ”œโ”€โ”€ DETERMINISTIC.md     # Deterministic workflows
โ”‚   โ””โ”€โ”€ VARIABLES.md         # Variables guide
โ”‚
โ”œโ”€โ”€ data/                     # Runtime & test data
โ”‚   โ””โ”€โ”€ test_data/           # Test data (tracked in git)
โ”‚       โ”œโ”€โ”€ form-filling/
โ”‚       โ””โ”€โ”€ flight-test/
โ”‚
โ”œโ”€โ”€ cli.py                   # CLI entry point
โ”œโ”€โ”€ pyproject.toml          # Project configuration
โ””โ”€โ”€ README.md               # This file

Comparison: Deterministic vs LLM-Based

Feature Deterministic LLM-Based
Generation Speed โšก 5-10s ๐ŸŒ 20-40s
Generation Cost ๐Ÿ’ฐ $0.01-0.05 ๐Ÿ’ธ $0.10-0.30
Agent Steps โœ… 0 guaranteed โŒ Variable
Deterministic โœ… Yes โŒ No
Execution Speed โšก Instant ๐ŸŒ 5-45s
Execution Cost ๐Ÿ’ฐ $0/run ๐Ÿ’ธ $0.03-0.30/run

Recommendation: Use deterministic for most workflows (search, click, input, navigate).


Testing

# Test deterministic generation
python examples/scripts/deterministic/run_complete_test.py

# Test variables
python examples/scripts/variables/create_workflow_with_variables.py

# Compare approaches
python examples/scripts/deterministic/test_deterministic_workflow.py

Next Steps

  1. โœ… Run examples/run_complete_test.py
  2. โœ… Review the generated workflow JSON
  3. โœ… Try creating your own workflow
  4. โœ… Add variables to make it reusable

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