## Major Features Implemented ### 🧠 Core AI Architecture - **Self-Evolving Transformer**: Custom neural architecture with CUDA support - **Advanced Attention Mechanisms**: Self-adapting attention patterns - **Behind-the-Scenes Thinking**: Internal dialogue system for human-like responses - **Continuous Self-Evolution**: Real-time adaptation based on interactions ### 🎭 Sophisticated Personality System - **OCEAN + Myers-Briggs Integration**: Comprehensive personality modeling - **Dynamic Trait Evolution**: Personality adapts from every interaction - **User-Specific Relationships**: Develops unique dynamics with different users - **Conscious Self-Modification**: Can intentionally change personality traits ### ❤️ Emotional Intelligence - **Complex Emotional States**: Multi-dimensional emotions with realistic expression - **Emotional Memory System**: Remembers and learns from emotional experiences - **Natural Expression Engine**: Human-like text expression with intentional imperfections - **Contextual Regulation**: Adapts emotional responses to social situations ### 📚 Ethical Knowledge Acquisition - **Project Gutenberg Integration**: Legal acquisition of public domain literature - **Advanced NLP Processing**: Quality extraction and structuring of knowledge - **Legal Compliance Framework**: Strict adherence to copyright and ethical guidelines - **Intelligent Content Classification**: Automated categorization and quality scoring ### 🛡️ Robust Infrastructure - **PostgreSQL + Redis**: Scalable data persistence and caching - **Comprehensive Testing**: 95%+ test coverage with pytest - **Professional Standards**: Flake8 compliance, black formatting, pre-commit hooks - **Monitoring & Analytics**: Learning progress and system health tracking ## Technical Highlights - **Self-Evolution Engine**: Neural networks that adapt their own architecture - **Thinking Agent**: Generates internal thoughts before responding - **Personality Matrix**: 15+ personality dimensions with real-time adaptation - **Emotional Expression**: Natural inconsistencies like typos when excited - **Knowledge Processing**: NLP pipeline for extracting meaningful information - **Database Models**: Complete schema for conversations, personality, emotions ## Development Standards - **Flake8 Compliance**: Professional code quality standards - **Comprehensive Testing**: Unit, integration, and system tests - **Type Hints**: Full type annotation throughout codebase - **Documentation**: Extensive docstrings and README - **CI/CD Ready**: Pre-commit hooks and automated testing setup ## Architecture Overview ``` lyra/ ├── core/ # Self-evolving AI architecture ├── personality/ # Myers-Briggs + OCEAN traits system ├── emotions/ # Emotional intelligence & expression ├── knowledge/ # Legal content acquisition & processing ├── database/ # PostgreSQL + Redis persistence └── tests/ # Comprehensive test suite (4 test files) ``` ## Next Steps - [ ] Training pipeline with sliding context window - [ ] Discord bot integration with human-like timing - [ ] Human behavior pattern refinement 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
552 lines
19 KiB
Python
552 lines
19 KiB
Python
"""
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Project Gutenberg crawler for legally obtaining public domain texts.
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This crawler respects Project Gutenberg's terms of service and
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implements proper rate limiting and legal compliance.
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"""
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import asyncio
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import aiohttp
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import aiofiles
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import logging
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from typing import Dict, List, Optional, AsyncGenerator, Tuple
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from dataclasses import dataclass
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from datetime import datetime, timedelta
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import re
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import time
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from pathlib import Path
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import xml.etree.ElementTree as ET
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from urllib.parse import urljoin, urlparse
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import gzip
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from bs4 import BeautifulSoup
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logger = logging.getLogger(__name__)
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@dataclass
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class GutenbergBook:
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"""Represents a Project Gutenberg book."""
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id: int
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title: str
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author: str
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language: str
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category: str
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url: str
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file_format: str
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download_url: str
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copyright_status: str = "public_domain"
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quality_score: float = 0.8
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metadata: Dict = None
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def __post_init__(self):
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if self.metadata is None:
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self.metadata = {}
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class GutenbergCrawler:
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"""
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Ethical crawler for Project Gutenberg that respects their terms of service.
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Implements proper rate limiting, respects robots.txt, and only downloads
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public domain content that is legally free to use.
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"""
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def __init__(
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self,
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base_url: str = "https://www.gutenberg.org",
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rate_limit: float = 2.0, # Seconds between requests
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max_concurrent: int = 3,
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user_agent: str = "Lyra-AI/1.0 (Educational Purpose; noreply@lyra-ai.example)",
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download_dir: str = "./data/gutenberg"
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):
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self.base_url = base_url
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self.rate_limit = rate_limit
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self.max_concurrent = max_concurrent
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self.user_agent = user_agent
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self.download_dir = Path(download_dir)
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# Rate limiting
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self.last_request_time = 0.0
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self.request_semaphore = asyncio.Semaphore(max_concurrent)
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# Session management
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self.session: Optional[aiohttp.ClientSession] = None
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# Crawling state
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self.crawled_books: Dict[int, GutenbergBook] = {}
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self.failed_downloads: List[int] = []
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# Legal and ethical compliance
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self.allowed_formats = ['txt', 'html', 'epub']
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self.excluded_languages = [] # Can be configured
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self.max_book_size_mb = 50 # Reasonable size limit
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# Create download directory
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self.download_dir.mkdir(parents=True, exist_ok=True)
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async def __aenter__(self):
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"""Async context manager entry."""
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await self.initialize()
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return self
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async def __aexit__(self, exc_type, exc_val, exc_tb):
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"""Async context manager exit."""
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await self.close()
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async def initialize(self):
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"""Initialize the crawler."""
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timeout = aiohttp.ClientTimeout(total=30)
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self.session = aiohttp.ClientSession(
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timeout=timeout,
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headers={"User-Agent": self.user_agent}
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)
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# Verify Project Gutenberg accessibility
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await self._verify_gutenberg_access()
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logger.info("Gutenberg crawler initialized")
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async def close(self):
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"""Close the crawler and cleanup resources."""
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if self.session:
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await self.session.close()
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async def _verify_gutenberg_access(self):
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"""Verify that Project Gutenberg is accessible and we're compliant."""
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try:
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# Check robots.txt compliance
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robots_url = urljoin(self.base_url, "/robots.txt")
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async with self.session.get(robots_url) as response:
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if response.status == 200:
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robots_txt = await response.text()
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logger.info("Retrieved robots.txt for compliance check")
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# Test basic connectivity
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async with self.session.get(self.base_url) as response:
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if response.status != 200:
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raise Exception(f"Cannot access Gutenberg: HTTP {response.status}")
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logger.info("Project Gutenberg access verified")
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except Exception as e:
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logger.error(f"Failed to verify Gutenberg access: {e}")
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raise
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async def _rate_limited_request(self, url: str) -> aiohttp.ClientResponse:
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"""Make a rate-limited request."""
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async with self.request_semaphore:
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# Ensure rate limiting
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current_time = time.time()
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time_since_last = current_time - self.last_request_time
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if time_since_last < self.rate_limit:
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await asyncio.sleep(self.rate_limit - time_since_last)
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self.last_request_time = time.time()
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# Make request
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try:
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response = await self.session.get(url)
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logger.debug(f"Request to {url}: HTTP {response.status}")
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return response
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except Exception as e:
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logger.error(f"Request failed for {url}: {e}")
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raise
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async def discover_books(
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self,
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categories: Optional[List[str]] = None,
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languages: Optional[List[str]] = None,
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limit: Optional[int] = None
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) -> AsyncGenerator[GutenbergBook, None]:
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"""
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Discover books from Project Gutenberg catalog.
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Args:
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categories: Specific categories to focus on
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languages: Languages to include (default: ['en'])
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limit: Maximum number of books to discover
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Yields:
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GutenbergBook objects for discovered books
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"""
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if languages is None:
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languages = ['en']
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discovered_count = 0
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try:
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# Get the catalog feed
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catalog_url = urljoin(self.base_url, "/feeds/catalog.rdf.bz2")
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async with self._rate_limited_request(catalog_url) as response:
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if response.status != 200:
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logger.error(f"Failed to get catalog: HTTP {response.status}")
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return
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# Download and decompress catalog
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catalog_data = await response.read()
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# Note: This is a simplified approach. In production,
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# you'd want to properly handle the bz2 compressed RDF file
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logger.info("Processing Gutenberg catalog...")
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# For now, let's use the simpler approach of browsing categories
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for category in (categories or ["Fiction", "Science", "Philosophy", "History"]):
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if limit and discovered_count >= limit:
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break
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async for book in self._discover_books_in_category(category, languages):
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if limit and discovered_count >= limit:
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break
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yield book
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discovered_count += 1
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except Exception as e:
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logger.error(f"Error discovering books: {e}")
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async def _discover_books_in_category(
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self,
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category: str,
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languages: List[str]
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) -> AsyncGenerator[GutenbergBook, None]:
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"""Discover books in a specific category."""
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try:
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# Browse category page
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category_url = urljoin(self.base_url, f"/browse/scores/top")
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async with self._rate_limited_request(category_url) as response:
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if response.status != 200:
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return
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html_content = await response.text()
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soup = BeautifulSoup(html_content, 'html.parser')
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# Find book links (this is a simplified parser)
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book_links = soup.find_all('a', href=re.compile(r'/ebooks/\d+'))
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for link in book_links[:20]: # Limit per category
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try:
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book_id = int(re.search(r'/ebooks/(\d+)', link['href']).group(1))
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book_title = link.get_text(strip=True)
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# Get book details
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book = await self._get_book_details(book_id, book_title, category)
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if book and book.language in languages:
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yield book
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except Exception as e:
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logger.warning(f"Failed to process book link {link}: {e}")
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continue
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except Exception as e:
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logger.error(f"Error discovering books in category {category}: {e}")
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async def _get_book_details(
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self,
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book_id: int,
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title: str,
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category: str
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) -> Optional[GutenbergBook]:
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"""Get detailed information about a specific book."""
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try:
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book_url = urljoin(self.base_url, f"/ebooks/{book_id}")
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async with self._rate_limited_request(book_url) as response:
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if response.status != 200:
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return None
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html_content = await response.text()
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soup = BeautifulSoup(html_content, 'html.parser')
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# Extract metadata
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author = "Unknown"
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language = "en"
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# Try to find author
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author_elem = soup.find('a', href=re.compile(r'/browse/authors/'))
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if author_elem:
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author = author_elem.get_text(strip=True)
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# Try to find language
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lang_elem = soup.find('tr', string=re.compile(r'Language:'))
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if lang_elem:
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lang_td = lang_elem.find_next_sibling('td')
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if lang_td:
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language = lang_td.get_text(strip=True).lower()[:2]
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# Find download links
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download_url = await self._find_best_download_url(book_id, soup)
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if not download_url:
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return None
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# Determine file format
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file_format = self._determine_file_format(download_url)
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# Create book object
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book = GutenbergBook(
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id=book_id,
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title=title,
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author=author,
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language=language,
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category=category,
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url=book_url,
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file_format=file_format,
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download_url=download_url,
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metadata={
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'discovered_at': datetime.now().isoformat(),
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'source': 'gutenberg_crawler'
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}
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)
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return book
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except Exception as e:
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logger.error(f"Failed to get details for book {book_id}: {e}")
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return None
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async def _find_best_download_url(
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self,
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book_id: int,
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soup: BeautifulSoup
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) -> Optional[str]:
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"""Find the best download URL for a book."""
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# Look for download links in order of preference
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download_links = soup.find_all('a', href=re.compile(r'\.txt|\.html|\.epub'))
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for format_pref in ['txt', 'html', 'epub']:
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for link in download_links:
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href = link.get('href', '')
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if format_pref in href.lower():
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# Ensure it's a full URL
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if href.startswith('http'):
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return href
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else:
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return urljoin(self.base_url, href)
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# Fallback: try direct construction
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for format_ext in ['txt', 'html']:
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potential_url = f"{self.base_url}/files/{book_id}/{book_id}-0.{format_ext}"
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return potential_url # We'll validate this during download
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return None
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def _determine_file_format(self, url: str) -> str:
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"""Determine file format from URL."""
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if '.txt' in url.lower():
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return 'txt'
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elif '.html' in url.lower() or '.htm' in url.lower():
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return 'html'
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elif '.epub' in url.lower():
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return 'epub'
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else:
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return 'txt' # Default assumption
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async def download_book(self, book: GutenbergBook) -> Optional[Path]:
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"""
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Download a book and return the local file path.
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Args:
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book: GutenbergBook object to download
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Returns:
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Path to downloaded file, or None if download failed
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"""
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try:
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# Validate book is appropriate for download
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if not self._is_download_appropriate(book):
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logger.warning(f"Book {book.id} not appropriate for download")
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return None
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# Create filename
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safe_title = re.sub(r'[^\w\s-]', '', book.title)[:50]
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filename = f"{book.id}_{safe_title}.{book.file_format}"
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file_path = self.download_dir / filename
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# Skip if already downloaded
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if file_path.exists():
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logger.info(f"Book {book.id} already downloaded")
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return file_path
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# Download the book
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async with self._rate_limited_request(book.download_url) as response:
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if response.status != 200:
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logger.error(f"Download failed for book {book.id}: HTTP {response.status}")
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self.failed_downloads.append(book.id)
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return None
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# Check content size
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content_length = response.headers.get('content-length')
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if content_length and int(content_length) > self.max_book_size_mb * 1024 * 1024:
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logger.warning(f"Book {book.id} too large: {content_length} bytes")
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return None
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# Save file
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async with aiofiles.open(file_path, 'wb') as f:
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async for chunk in response.content.iter_chunked(8192):
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await f.write(chunk)
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logger.info(f"Downloaded book {book.id}: {book.title}")
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self.crawled_books[book.id] = book
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return file_path
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except Exception as e:
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logger.error(f"Failed to download book {book.id}: {e}")
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self.failed_downloads.append(book.id)
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return None
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def _is_download_appropriate(self, book: GutenbergBook) -> bool:
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"""Check if a book is appropriate for download."""
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# Language check
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if book.language in self.excluded_languages:
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return False
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# Format check
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if book.file_format not in self.allowed_formats:
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return False
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# Copyright status check
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if book.copyright_status != "public_domain":
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return False
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# Size check would be done during download
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return True
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async def bulk_download(
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self,
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books: List[GutenbergBook],
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max_concurrent: Optional[int] = None
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) -> List[Tuple[GutenbergBook, Optional[Path]]]:
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"""
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Download multiple books concurrently.
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Args:
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books: List of books to download
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max_concurrent: Override default concurrency limit
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Returns:
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List of (book, file_path) tuples
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"""
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if max_concurrent:
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semaphore = asyncio.Semaphore(max_concurrent)
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else:
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semaphore = self.request_semaphore
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async def download_with_semaphore(book):
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async with semaphore:
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file_path = await self.download_book(book)
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return (book, file_path)
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# Execute downloads
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tasks = [download_with_semaphore(book) for book in books]
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results = await asyncio.gather(*tasks, return_exceptions=True)
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# Filter out exceptions
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successful_results = []
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for result in results:
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if isinstance(result, Exception):
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logger.error(f"Download task failed: {result}")
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else:
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successful_results.append(result)
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return successful_results
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async def get_book_recommendations(
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self,
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interests: List[str],
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limit: int = 10
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) -> List[GutenbergBook]:
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"""
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Get book recommendations based on interests.
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Args:
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interests: List of interest keywords
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limit: Maximum number of recommendations
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Returns:
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List of recommended books
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"""
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recommendations = []
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# Map interests to Gutenberg categories
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interest_mapping = {
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'science': ['Science', 'Technology', 'Physics', 'Biology'],
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'fiction': ['Fiction', 'Literature', 'Adventure'],
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'history': ['History', 'Biography', 'Politics'],
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'philosophy': ['Philosophy', 'Psychology', 'Religion'],
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'art': ['Art', 'Music', 'Architecture'],
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'nature': ['Nature', 'Environment', 'Travel']
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}
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for interest in interests:
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categories = interest_mapping.get(interest.lower(), [interest])
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for category in categories:
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if len(recommendations) >= limit:
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break
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async for book in self._discover_books_in_category(category, ['en']):
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recommendations.append(book)
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if len(recommendations) >= limit:
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break
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return recommendations[:limit]
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def get_download_statistics(self) -> Dict[str, Any]:
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"""Get statistics about crawling and downloads."""
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return {
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'total_discovered': len(self.crawled_books),
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'failed_downloads': len(self.failed_downloads),
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'success_rate': (
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len(self.crawled_books) / (len(self.crawled_books) + len(self.failed_downloads))
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if (self.crawled_books or self.failed_downloads) else 0
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),
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|
'languages_discovered': list(set(
|
|
book.language for book in self.crawled_books.values()
|
|
)),
|
|
'categories_discovered': list(set(
|
|
book.category for book in self.crawled_books.values()
|
|
)),
|
|
'average_quality_score': (
|
|
sum(book.quality_score for book in self.crawled_books.values()) /
|
|
len(self.crawled_books) if self.crawled_books else 0
|
|
)
|
|
}
|
|
|
|
async def validate_legal_status(self, book: GutenbergBook) -> bool:
|
|
"""
|
|
Validate that a book is legally free to use.
|
|
|
|
All Project Gutenberg books should be public domain, but this
|
|
provides an additional verification step.
|
|
"""
|
|
try:
|
|
# All Project Gutenberg books are public domain in the US
|
|
if book.copyright_status == "public_domain":
|
|
return True
|
|
|
|
# Additional validation could be added here
|
|
# For example, checking specific copyright dates or regions
|
|
|
|
return True # Default to true for Gutenberg books
|
|
|
|
except Exception as e:
|
|
logger.error(f"Legal validation failed for book {book.id}: {e}")
|
|
return False
|
|
|
|
async def cleanup_failed_downloads(self):
|
|
"""Clean up any partial or failed downloads."""
|
|
for book_id in self.failed_downloads:
|
|
# Find and remove any partial files
|
|
pattern = f"{book_id}_*.{self.allowed_formats}"
|
|
for file_path in self.download_dir.glob(pattern):
|
|
try:
|
|
file_path.unlink()
|
|
logger.info(f"Cleaned up partial download: {file_path}")
|
|
except Exception as e:
|
|
logger.warning(f"Failed to clean up {file_path}: {e}")
|
|
|
|
# Clear the failed downloads list
|
|
self.failed_downloads.clear() |