mirror of
https://github.com/arkorty/B.Tech-Project-III.git
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214 lines
6.8 KiB
Python
214 lines
6.8 KiB
Python
"""Link Fetcher — extracts, summarizes, and stores content from URLs shared in chat."""
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import re
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import uuid
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import logging
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import asyncio
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from datetime import datetime
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import httpx
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from bs4 import BeautifulSoup
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from backend.providers import call_llm
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from backend.config import ENABLE_LINK_FETCH
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logger = logging.getLogger("thirdeye.agents.link_fetcher")
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# Patterns to skip (images, downloads, social media embeds, etc.)
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SKIP_PATTERNS = [
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r"\.(png|jpg|jpeg|gif|svg|webp|ico|bmp)(\?.*)?$",
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r"\.(zip|tar|gz|rar|7z|exe|msi|dmg|apk|deb)(\?.*)?$",
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r"\.(mp3|mp4|avi|mov|mkv|wav|flac)(\?.*)?$",
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r"^https?://(www\.)?(twitter|x)\.com/.*/status/",
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r"^https?://(www\.)?instagram\.com/p/",
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r"^https?://(www\.)?tiktok\.com/",
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r"^https?://(www\.)?youtube\.com/shorts/",
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r"^https?://t\.me/", # Other Telegram links
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]
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SKIP_COMPILED = [re.compile(p, re.IGNORECASE) for p in SKIP_PATTERNS]
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def extract_urls(text: str) -> list[str]:
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"""Extract all HTTP/HTTPS URLs from a text string."""
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url_pattern = re.compile(
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r"https?://[^\s<>\"')\]},;]+"
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)
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urls = url_pattern.findall(text)
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# Clean trailing punctuation
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cleaned = []
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for url in urls:
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url = url.rstrip(".,;:!?)")
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if len(url) > 10:
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cleaned.append(url)
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return cleaned
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def should_fetch(url: str) -> bool:
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"""Decide if a URL is worth fetching (skip images, downloads, social embeds)."""
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for pattern in SKIP_COMPILED:
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if pattern.search(url):
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return False
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return True
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async def fetch_url_content(url: str, timeout: float = 15.0) -> dict | None:
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"""
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Fetch a URL and extract main text content.
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Returns:
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{title, text, url} or None if fetch fails
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"""
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try:
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async with httpx.AsyncClient(
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follow_redirects=True,
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timeout=timeout,
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headers={
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"User-Agent": "Mozilla/5.0 (compatible; ThirdEye/1.0; +https://thirdeye.dev)",
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"Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8",
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},
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) as client:
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response = await client.get(url)
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if response.status_code != 200:
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logger.info(f"URL returned {response.status_code}: {url[:80]}")
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return None
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content_type = response.headers.get("content-type", "")
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if "text/html" not in content_type and "application/xhtml" not in content_type:
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logger.info(f"Skipping non-HTML content ({content_type}): {url[:80]}")
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return None
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html = response.text
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except httpx.TimeoutException:
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logger.info(f"URL timed out: {url[:80]}")
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return None
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except Exception as e:
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logger.info(f"URL fetch failed ({type(e).__name__}): {url[:80]}")
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return None
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# Parse HTML
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try:
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soup = BeautifulSoup(html, "html.parser")
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# Extract title
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title = ""
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if soup.title and soup.title.string:
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title = soup.title.string.strip()
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# Remove script, style, nav, footer, header elements
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for tag in soup(["script", "style", "nav", "footer", "header", "aside", "noscript", "form"]):
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tag.decompose()
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# Try to find main content area
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main = soup.find("main") or soup.find("article") or soup.find("div", {"role": "main"})
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if main:
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text = main.get_text(separator="\n", strip=True)
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else:
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text = soup.get_text(separator="\n", strip=True)
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# Clean up
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lines = [line.strip() for line in text.split("\n") if line.strip()]
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text = "\n".join(lines)
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# Skip if too little content
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if len(text) < 100:
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logger.info(f"Too little text content ({len(text)} chars): {url[:80]}")
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return None
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# Truncate very long content
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if len(text) > 8000:
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text = text[:8000] + "\n\n[Content truncated]"
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return {
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"title": title or url,
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"text": text,
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"url": url,
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}
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except Exception as e:
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logger.warning(f"HTML parsing failed for {url[:80]}: {e}")
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return None
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async def summarize_content(title: str, text: str, url: str) -> str:
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"""Use LLM to create a concise summary of fetched content."""
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# Limit text sent to LLM
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text_preview = text[:3000]
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messages = [
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{"role": "system", "content": """You are a content summarizer for ThirdEye.
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Given the title and text of a web page, produce a concise 2-4 sentence summary that captures the key information.
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Focus on: main topic, key facts, any actionable insights, any deadlines or decisions mentioned.
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Respond with ONLY the summary text, nothing else."""},
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{"role": "user", "content": f"Title: {title}\nURL: {url}\n\nContent:\n{text_preview}"},
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]
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try:
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result = await call_llm("fast_small", messages, temperature=0.2, max_tokens=300)
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return result["content"].strip()
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except Exception as e:
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logger.warning(f"Link summarization failed: {e}")
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# Fallback: use first 200 chars of text
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return text[:200] + "..."
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async def process_links_from_message(
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text: str,
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group_id: str,
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shared_by: str = "Unknown",
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) -> list[dict]:
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"""
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Full pipeline: extract URLs from message → fetch → summarize → produce signals.
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Designed to be called in the background (non-blocking to the main message pipeline).
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Returns:
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List of signal dicts ready for store_signals()
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"""
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if not ENABLE_LINK_FETCH:
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return []
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urls = extract_urls(text)
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fetchable = [u for u in urls if should_fetch(u)]
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if not fetchable:
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return []
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signals = []
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# Process up to 3 links per message to avoid overload
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for url in fetchable[:3]:
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try:
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content = await fetch_url_content(url)
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if not content:
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continue
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summary = await summarize_content(content["title"], content["text"], url)
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signal = {
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"id": str(uuid.uuid4()),
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"type": "link_knowledge",
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"summary": f"[Link: {content['title'][:80]}] {summary[:200]}",
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"entities": [f"@{shared_by}", url[:100]],
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"severity": "low",
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"status": "reference",
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"sentiment": "neutral",
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"urgency": "none",
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"raw_quote": summary,
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"timestamp": datetime.utcnow().isoformat(),
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"group_id": group_id,
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"lens": "link",
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"keywords": [content["title"][:50], "link", "web", shared_by],
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}
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signals.append(signal)
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logger.info(f"Link ingested: {content['title'][:50]} ({url[:60]})")
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except Exception as e:
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logger.warning(f"Link processing failed for {url[:60]}: {e}")
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continue
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return signals
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