LiteAuto 🚀
LiteAuto is a lightweight Python library that provides easy-to-use tools for web automation, content parsing, vision AI, and smart searching. It's designed to be simple yet powerful, making common automation tasks effortless.
📦 Installation
pip install liteauto
✨ Features
- 🔍 Smart Google search with multi-query support
- 📄 Fast content parsing from web pages and PDFs
- 🧠 Vision AI for content analysis
- 📧 Gmail automation
- 📚 arXiv paper analysis
- 🔄 Project to prompt conversion
- 🎯 Word-level text operations
🚀 Quick Start
Web Search and Parsing
from liteauto import google, parse
# Simple Google search
urls = google("python programming", max_urls=5)
# Parse web content
contents = parse(urls)
for content in contents:
print(f"URL: {content.url}")
print(f"Content: {content.content[:200]}...")
Vision AI Features
from liteauto import visionai, wlanswer, wlsplit
# Get AI-powered search results
results = visionai("machine learning fundamentals", k=3)
print(results)
# Split text into meaningful chunks
chunks = wlsplit(long_text)
# Get relevant answers from context
answer = wlanswer(context="long text...", query="specific question", k=1)
Gmail Automation
from liteauto import gmail, automail
# Send a simple email
gmail(body="Hello World!",
subject="Test Email",
to_email="recipient@example.com")
# Create an automated email responder
def auto_response(subject, body):
return f"Auto-reply to: {subject}"
automail(auto_response, sleep_time=2)
arXiv Integration
from liteauto import get_todays_arxiv_papers, research_paper_analysis
# Get today's arXiv papers
papers_df = get_todays_arxiv_papers()
# Analyze a research paper
paper_insights = research_paper_analysis("https://arxiv.org/pdf/2301.00001.pdf")
print(paper_insights.summary_insights)
Project Analysis
from liteauto import ProjectToPrompt, project_to_markdown
# Convert project to documentation
project = ProjectToPrompt("path/to/project")
docs = project.generate_markdown()
# Generate markdown from project
markdown = project_to_markdown("path/to/project")
📚 Main Components
from liteauto import (
# Search and parsing
google, # Google search functionality
parse, # Web content parser
aparse, # Async web content parser
# Vision AI
visionai, # Advanced vision AI search
minivisionai, # Lightweight vision AI
deepvisionai, # Deep vision AI analysis
# Text operations
wlanswer, # Get answers from context
wlsplit, # Split text into chunks
wlsimchunks, # Get similar chunks
wltopk, # Get top-k similar items
# Email
gmail, # Gmail operations
automail, # Email automation
GmailAutomation,# Full Gmail automation class
# arXiv
get_todays_arxiv_papers, # Get recent arXiv papers
research_paper_analysis, # Analyze research papers
# Project tools
ProjectToPrompt, # Convert project to prompts
project_to_markdown # Convert project to markdown
)
🛠️ Advanced Usage
Custom Search Configuration
# Configure advanced search parameters
urls = google(
query="python tutorials",
max_urls=10,
animation=False,
allow_pdf_extraction=True,
allow_youtube_urls_extraction=True
)
Vision AI with Custom Parameters
results = visionai(
query="deep learning applications",
max_urls=15,
k=10,
model="llama3.2:1b-instruct-q4_K_M",
temperature=0.05,
genai_query_k=7,
query_k=15
)
Automated Paper Analysis
from liteauto import research_paper_analysis
paper = research_paper_analysis("paper_url.pdf")
print(f"Problem Statement: {paper.abs_insights.problem_statement}")
print(f"Key Approach: {paper.abs_insights.key_approach}")
print(f"Main Findings: {paper.summary_insights.main_results}")
🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
- Fork the repository
- Create your feature branch (
git checkout -b feature/AmazingFeature) - Commit your changes (
git commit -m 'Add some AmazingFeature') - Push to the branch (
git push origin feature/AmazingFeature) - Open a Pull Request
📝 License
This project is licensed under the MIT License - see the LICENSE file for details.
✨ Contributors
🌟 Star History
1 maintainer
Metadata
1 maintainer
Release files for liteauto 0.2.25
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| liteauto-0.2.25.tar.gz | 125.4 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| liteauto-0.2.25-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 268.5 kB
Release files / liteauto-0.2.25.tar.gz
| Download URL | liteauto-0.2.25.tar.gz |
|---|---|
| Size | 125.4 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / liteauto-0.2.25-py3-none-any.whl
| Download URL | liteauto-0.2.25-py3-none-any.whl |
|---|---|
| Size | 143.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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