curllm 1.0.3

Browser Automation with Local LLM (8GB GPU compatible)

curllm - Browser Automation with Local LLM

🤖 Intelligent Browser Automation using 8GB GPU-Compatible Local LLMs

curllm combines the power of local LLMs with browser automation for intelligent web scraping, form filling, and workflow automation - all running on your local machine with complete privacy.

✨ Features

• 🧠 Local LLM Integration: Run on 8GB GPUs with models like Qwen 2.5, Mistral, or Llama
• 👁️ Visual Analysis: Computer vision for CAPTCHA detection and page understanding
• 🥷 Stealth Mode: Advanced anti-bot detection bypass techniques
• 🔍 BQL Support: Browser Query Language for structured data extraction
• 🎯 Smart Navigation: AI-driven page interaction and form filling
• 🔒 Privacy-First: Everything runs locally - no data leaves your machine
• ⚡ GPU Optimized: Quantized models for efficient inference on consumer GPUs

📋 Requirements

Minimum Hardware

• GPU: NVIDIA GPU with 6-8GB VRAM (RTX 3060, RTX 4060, etc.)
• RAM: 16GB system memory
• Storage: 10GB free space
• CPU: Modern processor (Intel i5/AMD Ryzen 5 or better)

Software

• Python 3.11+ (tested on 3.13)
• Docker (optional, for Browserless features)
• CUDA toolkit (for GPU acceleration)

🚀 Quick Start

make install

📚 More Documentation & Example Scripts

• Full examples with commands and context: docs/EXAMPLES.md
• Generate runnable scripts: make examples
  • Scripts are created in examples/ as executable files (curllm-*.sh)
  • Run with: ./examples/curllm-extract-links.sh

Installing curllm dependencies...
╔════════════════════════════════════════════╗
║       curllm Installation Script           ║
║   Browser Automation with Local LLM        ║
╚════════════════════════════════════════════╝

[1/7] Checking system requirements...
✓ Python 3.13.5 found
✓ GPU detected: NVIDIA GeForce RTX 4060, 8188 MiB
✓ Docker is installed

[2/7] Installing Ollama...
✓ Ollama is already installed

...

1. Installation

# Clone the repository
git clone https://github.com/wronai/curllm.git
cd curllm

# Run automatic installer
chmod +x install.sh
./install.sh

# Or manual installation
pip install -r requirements.txt
ollama pull qwen2.5:7b

2. Start Services

Start all required services (auto-selects free ports and saves them to .env)

curllm --start-services

Check status (reads ports from .env)

curllm --status

output:

=== curllm Service Status ===
✓ Ollama is running
✓ curllm API is running
✓ Model qwen2.5:7b is available

GPU Status:
NVIDIA GeForce RTX 4060, 1190 MiB, 8188 MiB

3. Basic Usage

# Simple extraction (ensure services are running)
curllm "https://example.com" -d "extract all links"

output:

{
  "links": [
    {
      "href": "https://iana.org/domains/example",
      "text": "Learn more"
    }
  ]
}
Run log: ./logs/run-20251123-113145.md

Form automation with authentication

curllm -X POST --visual --stealth \
  -d '{"instruction": "Login and download invoice", 
       "credentials": {"user": "[e-mail]", "pass": "secret"}}' \
  https://app.example.com

BQL query for structured data

curllm --bql -d 'query {
  page(url: "https://news.ycombinator.com") {
    title
    links: select(css: "a.storylink, a.titlelink") { text url: attr(name: "href") }
  }
}'

🎯 Examples

For a comprehensive, curated set of examples and ready-to-run scripts, see:

• docs/EXAMPLES.md
• Generate scripts: make examples (scripts are created in examples/ as curllm-*.sh)

Validated examples (tested)

• Extract links (basic)

curllm "https://example.com" -d "extract all links"

Expected output (truncated):

{
  "links": [
    { "href": "https://iana.org/domains/example", "text": "Learn more" }
  ]
}

• Extract links (Polish site)

curllm "https://www.prototypowanie.pl/kontakt/" -d "extract all links"

• Extract emails

curllm "https://www.prototypowanie.pl/kontakt/" -d "extract all email addresses"

output:

{
  "emails": [
    "[e-mail]"
  ]
}

• Extract emails

curllm "https://4coils.eu" -d "extract all email addresses"

output:

{
  "emails": [
    "[e-mail]",
    "[e-mail]"
  ]
}

• Visual mode / Stealth mode

curllm --visual "https://example.com" -d "extract all links"
curllm --stealth "https://example.com" -d "extract all links"
curllm --visual --stealth "https://example.com" -d "extract all email addresses"

Notes:

• Results and step logs are saved to files in ./logs/run-*.md (path is printed in CLI output as run_log).
• Ports and hosts are auto-managed; run curllm --start-services once, then curllm --status.
• By default, the server uses a lightweight Ollama HTTP backend. To switch to LangChain's langchain_ollama, set CURLLM_LLM_BACKEND=langchain and ensure langchain-ollama is installed.

Extract Data from Dynamic Pages

curllm --visual "https://allegro.com" \
  -d "Find all products under 150 and extract names, prices and urls"

Create screenshot in folder name of domain

command:

curllm "https://www.prototypowanie.pl"  -d "Create screenshot in folder name of domain"

output:

{"result":{"screenshot_saved":"screenshots/www.prototypowanie.pl/step_0_1763903516.803199.png"},"run_log":"logs/run-20251123-141151.md","screenshots":["screenshots/www.prototypowanie.pl/step_0_1763903516.803199.png"],"steps_taken":0,"success":true,"timestamp":"2025-11-23T14:11:57.025193"}

screenshot:

Handle 2FA Authentication

curllm --visual --captcha \
  -d '{"task": "login", "username": "[e-mail]", 
       "password": "pass", "2fa_code": "123456"}' \
  https://secure-app.com

Automated Form Filling with Honeypot Detection

curllm --stealth --visual \
  -d "Fill contact form: name=John Doe, email=[e-mail], message=Hello" \
  https://www.prototypowanie.pl/kontakt/

Extract only email and phone links

curllm "https://www.prototypowanie.pl/kontakt/" -d "extract only email and phone links"

output:

{
  "emails": ["[e-mail]"],
  "phones": ["[phone]"]
}
Run log: ./logs/run-YYYYMMDD-HHMMSS.md

Extract all links

curllm "https://www.prototypowanie.pl/kontakt/" -d "extract all links"

output:

{
  "links": [
    {
      "href": "https://www.prototypowanie.pl/kontakt/#content",
      "text": "Skip to content"
    },
    {
      "href": "https://www.prototypowanie.pl/",
      "text": "PROTOTYPOWANIE.PL"
    },
    {
      "href": "https://www.prototypowanie.pl/blog/",
      "text": "BLOG"
    },
    {
      "href": "https://www.prototypowanie.pl/",
      "text": "WYCENA"
    },
    {
      "href": "https://www.prototypowanie.pl/technologie/",
      "text": "TECHNOLOGIE"
    },
    {
      "href": "https://www.prototypowanie.pl/portfolio-open-source/",
      "text": "PORTFOLIO"
    },
    {
      "href": "https://www.prototypowanie.pl/marka/ondayrun/",
      "text": "USŁUGI"
    },
    {
      "href": "https://www.prototypowanie.pl/kontakt/",
      "text": "KONTAKT"
    },
    {
      "href": "https://www.prototypowanie.pl/blog/",
      "text": "blog"
    },
    {
      "href": "https://www.prototypowanie.pl/co-napisac-w-formularzu-zlecenia-praktyczny-przewodnik/",
      "text": "Co napisać w formularzu zlecenia?"
    },
    {
      "href": "https://www.prototypowanie.pl/uslugi/",
      "text": "Do usług"
    },
    {
      "href": "https://www.prototypowanie.pl/faq-wszystko-o-wspolpracy-z-prototypowanie-pl/",
      "text": "Jak zacząć z Prototypowanie?pl"
    },
    {
      "href": "https://www.prototypowanie.pl/konsultacja/",
      "text": "Konsultacja"
    },
    {
      "href": "https://www.prototypowanie.pl/kontakt/",
      "text": "Kontakt"
    },
    {
      "href": "https://www.prototypowanie.pl/polityka-prywatnosci/",
      "text": "Polityka prywatności"
    },
    {
      "href": "https://www.prototypowanie.pl/polityka-prywatnosci/cookie-policy-eu/",
      "text": "Cookie policy (EU)"
    },
    {
      "href": "https://www.prototypowanie.pl/polityka-prywatnosci/privacy-policy/",
      "text": "Privacy Policy"
    },
    {
      "href": "https://www.prototypowanie.pl/polityka-prywatnosci/privacy-tools/",
      "text": "Privacy Tools"
    },
    {
      "href": "https://www.prototypowanie.pl/portfolio-open-source/",
      "text": "Portfolio Open Source"
    },
    {
      "href": "https://www.prototypowanie.pl/technologie/",
      "text": "Technologie"
    },
    {
      "href": "https://www.prototypowanie.pl/terms-conditions/",
      "text": "Terms & conditions"
    },
    {
      "href": "https://www.prototypowanie.pl/tomasz-sapletta/",
      "text": "Tomasz Sapletta"
    },
    {
      "href": "https://www.prototypowanie.pl/",
      "text": "Twoje oprogramowanie gotowe w 24h?"
    },
    {
      "href": "https://www.prototypowanie.pl/wycena/",
      "text": "Wycena"
    },
    {
      "href": "mailto:[e-mail]",
      "text": "[e-mail]"
    },
    {
      "href": "tel:[phone]",
      "text": "[phone]"
    },
    {
      "href": "https://www.linkedin.com/company/prototypowanie-pl/",
      "text": "Linkedin"
    },
    {
      "href": "https://www.prototypowanie.pl/",
      "text": "rototypowanie.pl"
    },
    {
      "href": "https://wordpress.org/plugins/gdpr-cookie-compliance/",
      "text": "Powered by  Zgodności ciasteczek z RODO"
    }
  ]
}
Run log: logs/run-20251123-115654.md

Complex Workflow Automation

curllm -X POST --visual --stealth --captcha \
  -d '{
    "workflow": [
      {"action": "navigate", "url": "https://portal.example.com"},
      {"action": "login", "username": "user", "password": "pass"},
      {"action": "click", "text": "Reports"},
      {"action": "download", "pattern": "*.pdf"},
      {"action": "extract_table", "format": "csv"}
    ]
  }'

🔧 Configuration

Environment Variables (.env)

# The installer creates .env (from .env.example). Key variables:
# Ports and hosts (auto-maintained when starting services)
CURLLM_API_PORT=8000
CURLLM_API_HOST=http://localhost:8000
CURLLM_OLLAMA_PORT=11434
CURLLM_OLLAMA_HOST=http://localhost:11434

# Model and runtime
CURLLM_MODEL=qwen2.5:7b
CURLLM_MAX_STEPS=20
CURLLM_NUM_CTX=8192
CURLLM_NUM_PREDICT=512
CURLLM_TEMPERATURE=0.3
CURLLM_TOP_P=0.9
CURLLM_DEBUG=false

# Browserless (optional)
CURLLM_BROWSERLESS=false
BROWSERLESS_URL=ws://localhost:3000
BROWSERLESS_PORT=3000
REDIS_PORT=6379

# CAPTCHA (optional)
CAPTCHA_API_KEY=

Configuration File

Edit ~/.config/curllm/config.yml:

# Model settings
model: qwen2.5:7b
ollama_host: http://localhost:11434
temperature: 0.3
top_p: 0.9

# Browser settings
max_steps: 20
screenshot_dir: ./screenshots
headless: true

# Features
visual_mode: false
stealth_mode: false
captcha_solver: false
use_bql: false

# Performance
num_ctx: 8192
num_predict: 512
gpu_layers: 35

🐳 Docker Deployment

Using Docker Compose

# Start all services
docker-compose up -d

# Scale browserless instances
docker-compose up -d --scale browserless=3

# View logs
docker-compose logs -f curllm-api

Standalone Docker

# Build image
docker build -t curllm:latest .

# Run container
docker run -d \
  --name curllm \
  --gpus all \
  -p 8000:8000 \
  -v ~/.ollama:/root/.ollama \
  curllm:latest

🎮 Advanced Features

Visual Mode

Visual mode enables screenshot analysis for:

• CAPTCHA detection
• Dynamic content verification
• Visual element interaction
• Honeypot field detection

curllm --visual "https://example.com" -d "Click the red button"

Stealth Mode

Bypasses common bot detection:

• Removes automation indicators
• Randomizes behavior patterns
• Mimics human interactions
• Custom user agents and headers

curllm --stealth "https://pypi.org/project/curllm/" -d "Extract data"

BQL (Browser Query Language)

GraphQL-like syntax for structured extraction:

query {
  page(url: "https://example.com") {
    title
    meta: select(css: "meta[property^='og:']") {
      property: attr(name: "property")
      content: attr(name: "content")
    }
    links: select(css: "a[href^='http']") {
      text
      url: attr(name: "href")
    }
  }
}

📊 Performance Benchmarks

Model	VRAM Usage	Inference Speed	Tool-calling F1	Avg Response Time
Qwen 2.5 7B	6.8GB	40 tok/sec	93.3%	8-12 sec
Mistral 7B	6.5GB	45 tok/sec	89.1%	7-10 sec
Llama 3.2 8B	7.2GB	35 tok/sec	87.5%	10-15 sec
Phi-3 Mini	3.8GB	60 tok/sec	82.3%	5-8 sec

🛠️ API Reference

REST Endpoints

POST /api/execute
Content-Type: application/json

{
  "url": "https://example.com",
  "data": "instruction or query",
  "visual_mode": true,
  "stealth_mode": false,
  "captcha_solver": false,
  "use_bql": false
}

Python Client

from curllm import CurllmClient

client = CurllmClient(
    model="qwen2.5:7b",
    visual_mode=True
)

result = await client.execute(
    url="https://example.com",
    instruction="Extract all product prices"
)

print(result.data)

🐛 Troubleshooting

Common Issues

Out of Memory (OOM)

# Reduce context length
export CURLLM_NUM_CTX=4096

# Use smaller model
ollama pull phi3:mini

Slow Response

# Check GPU utilization
nvidia-smi

# Use quantized model
ollama pull qwen2.5:7b-q4_K_M

CAPTCHA Detection Issues

# Enable visual mode
curllm --visual --captcha ...

# Increase screenshot quality
export SCREENSHOT_QUALITY=100

🗺️ Roadmap

• Multi-agent orchestration
• Fine-tuning interface for domain-specific tasks
• WebSocket support for real-time automation
• Integration with Selenium Grid
• Voice-guided automation
• Mobile browser support
• Distributed scraping with Ray
• Custom model training pipeline

Files

tree -L 3 -I node_modules -I venv

$ tree -L 3 -I node_modules -I venv
.
├── bql_parser.py
├── CHANGELOG.md
├── curllm
├── curllm_server.py
├── docker-compose.yml
├── Dockerfile
├── docs
│   └── EXAMPLES.md
├── downloads
├── examples.py
├── install.sh
├── INSTRUKCJA.md
├── LICENSE
├── logs
│   └── run-20251123-141151.md
├── Makefile
├── __pycache__
│   └── curllm_server.cpython-313.pyc
├── pyproject.toml
├── QUICKSTART.sh
├── README.md
├── requirements.txt
├── screenshots
│   └── www.prototypowanie.pl
│       └── step_0_1763903516.803199.png
├── tests
│   └── e2e.sh
├── TODO.md
├── tools
│   └── generate_examples.sh
└── workspace

12 directories, 37 files

🤝 Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

# Development setup
git clone https://github.com/wronai/curllm.git
cd curllm
pip install -e .
pytest tests/

📄 License

Apache License - see LICENSE for details.

🙏 Acknowledgments

• Ollama for local LLM serving
• Browser-Use for browser automation
• Playwright for browser control
• LangChain for LLM orchestration
• Browserless for headless browser infrastructure

📞 Support

• 📧 Email: [e-mail]
• 💬 Discord: Join our server
• 🐛 Issues: GitHub Issues
• 📚 Docs: Documentation

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