Backend-B2V / backend /app /services /scraper.py
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import os
import re
import json
import hashlib
import requests
from urllib.parse import urljoin, urlparse
from bs4 import BeautifulSoup
from sqlalchemy.orm import Session
from exa_py import Exa
from firecrawl import Firecrawl
from PIL import Image
from app.config import settings
from app.models.project import Project, ProjectStatus
from app.models.asset import Asset, AssetType
from app.services import r2_storage
# Browser headers for image downloads and fallback scraping
_BROWSER_HEADERS = {
"User-Agent": (
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
"AppleWebKit/537.36 (KHTML, like Gecko) "
"Chrome/124.0.0.0 Safari/537.36"
),
"Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8",
"Accept-Language": "en-US,en;q=0.9",
"Accept-Encoding": "gzip, deflate",
}
# Minimum chars to consider a scrape successful
_MIN_CONTENT_LENGTH = 50
# ─── Main entry point ─────────────────────────────────────
def scrape_blog(project: Project, db: Session) -> Project:
"""
Scrape blog content and images from the project's blog_url.
Scraping chain (first success wins):
1. Firecrawl (default β€” renders JS, handles SPAs)
2. requests + BeautifulSoup (free fallback for static sites)
3. Exa with livecrawl (last resort, headless browser)
"""
url = project.blog_url
text = ""
image_urls: list[str] = []
# ── Step 1: Firecrawl (default β€” handles JS/SPA sites) ──
if settings.FIRECRAWL_API_KEY:
try:
text, image_urls = _scrape_with_firecrawl(url)
if text and len(text.strip()) >= _MIN_CONTENT_LENGTH:
print(f"[SCRAPER] Firecrawl succeeded ({len(text)} chars, {len(image_urls)} images)")
else:
print(f"[SCRAPER] Firecrawl returned thin content ({len(text.strip())} chars), trying requests...")
text = ""
except Exception as e:
print(f"[SCRAPER] Firecrawl failed: {e}, trying requests...")
# ── Step 2: requests + BeautifulSoup (free fallback) ──
if not text or len(text.strip()) < _MIN_CONTENT_LENGTH:
try:
req_text, req_images = _scrape_with_requests(url)
if req_text and len(req_text.strip()) >= _MIN_CONTENT_LENGTH:
text = req_text
image_urls = req_images
print(f"[SCRAPER] requests succeeded ({len(text)} chars, {len(image_urls)} images)")
else:
print(f"[SCRAPER] requests returned thin content ({len(req_text.strip())} chars), trying Exa...")
except Exception as e:
print(f"[SCRAPER] requests failed: {e}, trying Exa...")
# ── Step 3: Exa with livecrawl (last resort) ──
if (not text or len(text.strip()) < _MIN_CONTENT_LENGTH) and settings.EXA_API_KEY:
try:
exa_text, exa_images = _scrape_with_exa(url)
if exa_text and len(exa_text.strip()) >= _MIN_CONTENT_LENGTH:
text = exa_text
image_urls = exa_images
print(f"[SCRAPER] Exa succeeded ({len(text)} chars, {len(image_urls)} images)")
except Exception as e:
print(f"[SCRAPER] Exa failed: {e}")
if not text or len(text.strip()) < _MIN_CONTENT_LENGTH:
raise ValueError(
"Could not extract meaningful content from the URL. "
"The site may require JavaScript rendering or the page may be empty."
)
# Download images (only from the original blog page β€” no external sources)
_download_images(project.user_id, project.id, image_urls, db)
# Update project
project.blog_content = text
project.status = ProjectStatus.SCRAPED
db.commit()
db.refresh(project)
return project
# ─── Exa API scraping ─────────────────────────────────────
def _scrape_with_exa(url: str) -> tuple[str, list[str]]:
"""
Use Exa API to get clean text content, HTML for code blocks, and
image URLs from a URL. Exa handles Medium/Substack/paywalled sites.
The hero/OG image is always first in the returned list.
"""
exa = Exa(api_key=settings.EXA_API_KEY)
# Request HTML-tagged text (for code blocks + inline images) plus image_links.
# Use livecrawl="preferred" so Exa tries a fresh headless-browser crawl first
# (which executes JS β†’ Medium/Substack images become visible), falling back
# to cached content if the live crawl fails.
result = exa.get_contents(
urls=[url],
text={"include_html_tags": True, "max_characters": 50000},
extras={"image_links": 40},
livecrawl="preferred",
livecrawl_timeout=15000, # 15s timeout for live crawl
)
if not result.results:
raise ValueError("Exa returned no results")
page = result.results[0]
html_text = page.text or ""
# If Exa returned very little content, the page might be paywalled/JS-rendered.
# Retry with livecrawl="always" to force a fresh headless crawl.
if len(html_text.strip()) < 500:
print(f"[SCRAPER] Exa returned thin content ({len(html_text)} chars), retrying with forced livecrawl...")
try:
result2 = exa.get_contents(
urls=[url],
text={"include_html_tags": True, "max_characters": 50000},
extras={"image_links": 40},
livecrawl="always",
livecrawl_timeout=30000,
)
if result2.results and len((result2.results[0].text or "").strip()) > len(html_text.strip()):
page = result2.results[0]
html_text = page.text or ""
print(f"[SCRAPER] Forced livecrawl got {len(html_text)} chars (better)")
except Exception as e2:
print(f"[SCRAPER] Forced livecrawl failed (using cached): {e2}")
# --- Parse Exa's HTML (already scoped to article content) ---
soup_exa = BeautifulSoup(html_text, "lxml") if "<" in html_text else None
# Extract code blocks
code_blocks: list[dict] = []
if soup_exa and ("<pre" in html_text or "<code" in html_text):
code_blocks = _extract_code_blocks(soup_exa)
# Convert HTML to clean plain text for the LLM
if soup_exa:
text = soup_exa.get_text(separator="\n", strip=True)
text = re.sub(r"\n{3,}", "\n\n", text).strip()
else:
text = html_text
# Inject code blocks with clear markers
if code_blocks:
text = _inject_code_blocks(text, code_blocks)
# --- Collect images ---
image_urls: list[str] = []
seen_images: set[str] = set()
seen_image_ids: set[str] = set() # Medium image IDs for dedup across sizes
is_medium = _is_medium_url(url)
def _add_image(img_url: str, trust_source: bool = False) -> bool:
"""Add an image URL if not duplicate. Returns True if added.
trust_source=True skips _is_blog_image for Exa-curated results.
"""
if not img_url or img_url in seen_images:
return False
# Upgrade Medium URLs to max resolution
if is_medium or "miro.medium.com" in img_url or "cdn-images" in img_url:
img_url = _upgrade_medium_image_url(img_url)
# Deduplicate by Medium image ID (same image at different sizes)
mid = _extract_medium_image_id(img_url)
if mid and mid in seen_image_ids:
return False
# For Exa-curated image_links, only reject obvious non-content
if trust_source:
if not _is_content_image_light_filter(img_url):
return False
else:
if not _is_blog_image(img_url):
return False
if img_url in seen_images:
return False
image_urls.append(img_url)
seen_images.add(img_url)
if mid:
seen_image_ids.add(mid)
return True
# 0. Medium JSON API β€” most reliable source for Medium images (no JS needed)
if is_medium:
medium_json_images = _extract_medium_images_via_json(url)
for img_url in medium_json_images:
_add_image(img_url, trust_source=True)
# 1. Hero / OG image from Exa
if hasattr(page, "image") and page.image:
_add_image(page.image, trust_source=True)
# 2. Exa extras.image_links β€” BEST source for Medium/Substack.
# Exa's headless browser renders JS and extracts content images,
# so these are already curated. Trust them with light filtering.
if hasattr(page, "extras") and page.extras:
exa_images = page.extras.get("image_links") or page.extras.get("imageLinks") or []
for img_url in exa_images:
if isinstance(img_url, str):
_add_image(img_url, trust_source=True)
# 3. Inline images from Exa's article HTML
if soup_exa:
for img_url in _extract_all_image_srcs(soup_exa, url):
_add_image(img_url, trust_source=True)
# 4. Fallback: direct HTML fetch β€” for any images Exa missed
# Always try for Medium since their images require JS rendering
if len(image_urls) < 5 or is_medium:
try:
resp = requests.get(url, headers=_BROWSER_HEADERS, timeout=15)
if resp.status_code == 200:
soup = BeautifulSoup(resp.text, "lxml")
# Get hero image if we still don't have one
if not image_urls:
og_img = _extract_og_image_from_soup(soup, url)
if og_img:
_add_image(og_img, trust_source=True)
# Extract images from the article body
body_images = _extract_article_image_urls(soup, url)
for img_url in body_images:
_add_image(img_url)
# Medium-specific: also try <figure> and <noscript> at page level
if is_medium:
for img_url in _extract_medium_figure_images(soup, url):
_add_image(img_url, trust_source=True)
except Exception as e:
print(f"[SCRAPER] HTML image fallback failed (non-fatal): {e}")
print(f"[SCRAPER] Exa extracted {len(text)} chars, {len(code_blocks)} code blocks, {len(image_urls)} images")
return text, image_urls
# ─── Exa image search fallback ─────────────────────────────
def _find_extra_images_via_exa(
original_url: str,
text: str,
existing_images: list[str],
) -> list[str]:
"""
When the initial scrape only found 0-1 images, use Exa's search to find
additional relevant images from pages about the same topic.
Extracts the blog title/topic from the first ~200 chars and searches Exa
for related content with image_links.
"""
try:
exa = Exa(api_key=settings.EXA_API_KEY)
# Build a short topic query from the blog text
topic = text[:300].split("\n")[0].strip()
if len(topic) > 120:
topic = topic[:120]
# Search Exa for pages about this topic β€” request image_links
search_results = exa.search_and_contents(
query=topic,
num_results=5,
text={"max_characters": 500},
extras={"image_links": 20},
type="neural",
)
existing_set = set(existing_images)
extra: list[str] = []
seen_ids: set[str] = set()
for result in search_results.results:
# Skip the original article itself
if result.url and result.url.rstrip("/") == original_url.rstrip("/"):
continue
# Collect images from extras.image_links
if hasattr(result, "extras") and result.extras:
imgs = result.extras.get("image_links") or result.extras.get("imageLinks") or []
for img_url in imgs:
if not isinstance(img_url, str):
continue
if img_url in existing_set:
continue
if not _is_content_image_light_filter(img_url):
continue
# Deduplicate by Medium image ID
mid = _extract_medium_image_id(img_url)
if mid and mid in seen_ids:
continue
extra.append(img_url)
existing_set.add(img_url)
if mid:
seen_ids.add(mid)
# Cap at 8 extra images
if len(extra) >= 8:
return extra
# Also check page.image (hero/OG image)
if hasattr(result, "image") and result.image:
img_url = result.image
if img_url not in existing_set and _is_content_image_light_filter(img_url):
extra.append(img_url)
existing_set.add(img_url)
return extra
except Exception as e:
print(f"[SCRAPER] Exa image search fallback failed (non-fatal): {e}")
return []
# ─── Requests + BeautifulSoup fallback ────────────────────
# ─── Firecrawl scraping ───────────────────────────────────
def _scrape_with_firecrawl(url: str) -> tuple[str, list[str]]:
"""
Use Firecrawl to scrape a page. Firecrawl renders JavaScript, so it
handles SPAs and dynamically-rendered blogs that requests cannot.
Returns (text, image_urls).
"""
app = Firecrawl(api_key=settings.FIRECRAWL_API_KEY)
# Firecrawl v4 returns a Document object with attributes, not a dict.
doc = app.scrape(url, formats=["markdown", "html"])
markdown_text = (getattr(doc, "markdown", None) or "").strip()
html_content = (getattr(doc, "html", None) or "").strip()
metadata = getattr(doc, "metadata", None) or {}
# metadata may be a dict or an object β€” normalise to dict
if not isinstance(metadata, dict):
metadata = metadata.__dict__ if hasattr(metadata, "__dict__") else {}
# --- Extract text ---
# Prefer markdown (cleaner), fall back to HTML→text
if markdown_text and len(markdown_text) >= _MIN_CONTENT_LENGTH:
text = markdown_text
elif html_content:
soup = BeautifulSoup(html_content, "lxml")
text = _extract_text(soup)
else:
text = ""
# --- Extract images ---
image_urls: list[str] = []
seen: set[str] = set()
MAX_IMAGES = 15
def _add(img_url: str) -> None:
if len(image_urls) >= MAX_IMAGES:
return
if img_url and img_url not in seen and _is_blog_image(img_url):
image_urls.append(img_url)
seen.add(img_url)
# OG image / hero from metadata
og = metadata.get("ogImage") or metadata.get("og:image")
if og:
_add(og if isinstance(og, str) else (og.get("url", "") if isinstance(og, dict) else str(og)))
# Images from rendered HTML
if html_content:
soup = BeautifulSoup(html_content, "lxml")
for img_url in _extract_all_image_srcs(soup, url):
_add(img_url)
# Images from markdown ![alt](url)
if markdown_text:
for m in re.finditer(r"!\[.*?\]\((https?://[^\s)]+)\)", markdown_text):
_add(m.group(1))
print(f"[SCRAPER][Firecrawl] Got {len(text)} chars, {len(image_urls)} images from {url}")
return text, image_urls
# ─── Requests + BeautifulSoup scraping ────────────────────
def _scrape_with_requests(url: str) -> tuple[str, list[str]]:
"""
Scraper using requests + BeautifulSoup.
Hero/OG image is always first in the returned list.
"""
session = requests.Session()
session.headers.update(_BROWSER_HEADERS)
response = session.get(url, timeout=30, allow_redirects=True)
# Retry once (some sites set cookies on first 403)
if response.status_code == 403:
response = session.get(url, timeout=30, allow_redirects=True)
response.raise_for_status()
soup = BeautifulSoup(response.text, "lxml")
text = _extract_text(soup)
# Extract hero image (og:image) first, then remaining images
hero_url = _extract_og_image_from_soup(soup, url)
image_urls = _extract_image_urls(soup, url)
# Ensure hero image is first and deduplicated
if hero_url:
image_urls = [hero_url] + [u for u in image_urls if u != hero_url]
return text, image_urls
def _extract_og_image(url: str) -> str | None:
"""Quick fetch to extract og:image from a URL's HTML head."""
try:
resp = requests.get(url, headers=_BROWSER_HEADERS, timeout=10)
if resp.status_code == 200:
soup = BeautifulSoup(resp.text[:10000], "lxml") # only parse head
return _extract_og_image_from_soup(soup, url)
except Exception:
pass
return None
def _extract_og_image_from_soup(soup: BeautifulSoup, base_url: str) -> str | None:
"""Extract the og:image or twitter:image from parsed HTML."""
for prop in ["og:image", "twitter:image", "twitter:image:src"]:
tag = soup.find("meta", property=prop) or soup.find("meta", attrs={"name": prop})
if tag and tag.get("content"):
return urljoin(base_url, tag["content"])
return None
def _extract_code_blocks(soup: BeautifulSoup) -> list[dict]:
"""
Extract code blocks (<pre>, <code>, or <pre><code>) from the HTML.
Returns a list of { "language": str|None, "code": str }.
"""
blocks = []
seen_code = set()
# Find <pre> tags (often wrapping <code>)
for pre in soup.find_all("pre"):
code_tag = pre.find("code")
raw = (code_tag or pre).get_text(strip=False)
raw = raw.strip()
if not raw or len(raw) < 10 or raw in seen_code:
continue
seen_code.add(raw)
# Try to detect language from class
lang = None
for tag in [code_tag, pre]:
if tag and tag.get("class"):
for cls in tag["class"]:
m = re.match(r"(?:language-|lang-|highlight-)(\w+)", cls, re.I)
if m:
lang = m.group(1)
break
if lang:
break
blocks.append({"language": lang, "code": raw})
# Also find standalone <code> blocks that are long enough to be meaningful
for code_tag in soup.find_all("code"):
if code_tag.parent and code_tag.parent.name == "pre":
continue # Already captured
raw = code_tag.get_text(strip=False).strip()
if len(raw) > 40 and raw not in seen_code:
seen_code.add(raw)
blocks.append({"language": None, "code": raw})
return blocks
def _inject_code_blocks(text: str, code_blocks: list[dict]) -> str:
"""
Append extracted code blocks to the text content with clear markers
so the LLM knows code exists in the blog.
"""
if not code_blocks:
return text
code_section = "\n\n═══ CODE BLOCKS FROM THIS BLOG ═══\n"
for i, block in enumerate(code_blocks, 1):
lang_label = block["language"] or "code"
code_section += f"\n--- Code Block {i} ({lang_label}) ---\n"
# Limit each block to first 60 lines to avoid token explosion
lines = block["code"].split("\n")
if len(lines) > 60:
code_section += "\n".join(lines[:60])
code_section += f"\n... ({len(lines) - 60} more lines truncated)\n"
else:
code_section += block["code"]
code_section += "\n"
return text + code_section
def _extract_text(soup: BeautifulSoup) -> str:
"""
Extract the main article text from the page, preserving code blocks
with clear markers so the LLM can identify them.
"""
for element in soup(["script", "style", "nav", "footer", "header", "aside"]):
element.decompose()
# Extract code blocks BEFORE decomposing them
code_blocks = _extract_code_blocks(soup)
article = (
soup.find("article")
or soup.find("main")
or soup.find("div", class_=re.compile(r"(post|article|content|entry)", re.I))
or soup.find("div", id=re.compile(r"(post|article|content|entry)", re.I))
)
if article:
text = article.get_text(separator="\n", strip=True)
else:
body = soup.find("body")
text = body.get_text(separator="\n", strip=True) if body else soup.get_text(separator="\n", strip=True)
text = re.sub(r"\n{3,}", "\n\n", text)
text = text.strip()
# Inject code blocks with clear markers
text = _inject_code_blocks(text, code_blocks)
return text
def _extract_all_image_srcs(container: BeautifulSoup, base_url: str) -> list[str]:
"""
Comprehensively extract image URLs from a container, handling:
- Regular <img src="...">
- Lazy-loaded <img data-src="..."> / <img data-lazy-src="...">
- srcset attributes on <img> and <source>
- <picture><source srcset="..."> wrappers
- <noscript><img src="..."> fallbacks (Medium uses these)
- <figure> wrappers with background-image styles
Returns de-duplicated, filtered URLs in order found.
"""
urls: list[str] = []
seen: set[str] = set()
def _add(raw_url: str):
if not raw_url or raw_url.startswith("data:"):
return
full = urljoin(base_url, raw_url.strip())
if full not in seen:
seen.add(full)
urls.append(full)
def _parse_srcset(srcset: str):
"""Extract highest-resolution URL from a srcset string."""
if not srcset:
return
candidates = []
for part in srcset.split(","):
part = part.strip()
if not part:
continue
pieces = part.split()
if pieces:
url_candidate = pieces[0]
# Parse the width descriptor (e.g. "700w") to pick the largest
width = 0
if len(pieces) > 1:
desc = pieces[-1]
m = re.match(r"(\d+)w", desc)
if m:
width = int(m.group(1))
candidates.append((url_candidate, width))
if candidates:
# Sort by width descending, pick the largest
candidates.sort(key=lambda c: c[1], reverse=True)
_add(candidates[0][0])
# 1. <img> tags β€” check src, data-src, data-lazy-src, srcset
for img in container.find_all("img"):
src = img.get("src") or img.get("data-src") or img.get("data-lazy-src") or ""
if src and not src.startswith("data:"):
_add(src)
# Also check srcset
srcset = img.get("srcset") or img.get("data-srcset") or ""
if srcset:
_parse_srcset(srcset)
# 2. <picture> > <source> tags
for picture in container.find_all("picture"):
for source in picture.find_all("source"):
srcset = source.get("srcset") or ""
if srcset:
_parse_srcset(srcset)
# 3. <noscript> fallback images (Medium hides the real src here)
for noscript in container.find_all("noscript"):
noscript_html = noscript.string or noscript.decode_contents()
if "<img" in noscript_html:
ns_soup = BeautifulSoup(noscript_html, "lxml")
for img in ns_soup.find_all("img"):
src = img.get("src") or img.get("data-src") or ""
if src:
_add(src)
srcset = img.get("srcset") or ""
if srcset:
_parse_srcset(srcset)
# 4. <figure> with inline background-image style
for fig in container.find_all("figure"):
style = fig.get("style") or ""
m = re.search(r'url\(["\']?(https?://[^"\')\s]+)', style)
if m:
_add(m.group(1))
return urls
def _extract_article_image_urls(soup: BeautifulSoup, base_url: str) -> list[str]:
"""
Extract images ONLY from the article/main content area β€” not the
sidebar, header, footer, nav, or other page chrome.
This ensures we only get images that sit next to the blog text.
"""
# Find the article body container
article = (
soup.find("article")
or soup.find("main")
or soup.find("div", class_=re.compile(r"(post|article|content|entry|story)", re.I))
or soup.find("div", id=re.compile(r"(post|article|content|entry|story)", re.I))
)
# If we can't find a specific container, fall back to body
# but strip nav/footer/aside/header first
if not article:
article = soup.find("body") or soup
for tag_name in ["nav", "footer", "header", "aside"]:
for el in article.find_all(tag_name):
el.decompose()
# Use comprehensive image extraction
raw_urls = _extract_all_image_srcs(article, base_url)
# Filter: only keep actual blog images
image_urls = []
for img_url in raw_urls:
if not _is_blog_image(img_url):
continue
image_urls.append(img_url)
return image_urls
def _extract_image_urls(soup: BeautifulSoup, base_url: str) -> list[str]:
"""Legacy wrapper β€” delegates to article-scoped extraction."""
return _extract_article_image_urls(soup, base_url)
# ─── Medium-specific helpers ──────────────────────────────
# Known content image CDN domains β€” images from these are almost always blog content
_CONTENT_CDN_DOMAINS = {
"miro.medium.com",
"cdn-images-1.medium.com",
"cdn-images-2.medium.com",
"cdn-images-3.medium.com",
"cdn-images-4.medium.com",
"substackcdn.com",
"substack-post-media",
"ghost.io",
"hashnode.dev",
"hashnode.com",
"wp.com",
"wordpress.com",
}
def _is_medium_url(url: str) -> bool:
"""Return True if the URL is a Medium article."""
lower = url.lower()
return (
"medium.com" in lower
or "towardsdatascience.com" in lower
or "betterprogramming.pub" in lower
or "levelup.gitconnected.com" in lower
or "blog.devgenius.io" in lower
or "javascript.plainenglish.io" in lower
or "python.plainenglish.io" in lower
or "pub." in lower and "medium" in lower
)
def _extract_medium_images_via_json(url: str) -> list[str]:
"""
Extract ALL image URLs from a Medium article using Medium's undocumented
JSON API (?format=json). This is the most reliable way to get Medium images
because it doesn't require JS rendering.
Medium's JSON response contains paragraphs with type=4 (images), each with
a metadata.id field like "1*abc123.png". These map to:
https://miro.medium.com/v2/resize:fit:1400/{id}
"""
try:
# Append ?format=json (or &format=json if query params already exist)
separator = "&" if "?" in url else "?"
json_url = f"{url}{separator}format=json"
resp = requests.get(json_url, headers=_BROWSER_HEADERS, timeout=15)
if resp.status_code != 200:
return []
# Strip Medium's XSS protection prefix: ])}while(1);</x>
raw = resp.text
prefix_end = raw.find("{")
if prefix_end == -1:
return []
data = json.loads(raw[prefix_end:])
# Navigate to the paragraphs list
paragraphs = (
data.get("payload", {})
.get("value", {})
.get("content", {})
.get("bodyModel", {})
.get("paragraphs", [])
)
image_urls: list[str] = []
seen_ids: set[str] = set()
# Also grab the preview/hero image
preview_id = (
data.get("payload", {})
.get("value", {})
.get("virtuals", {})
.get("previewImage", {})
.get("imageId")
)
if preview_id and preview_id not in seen_ids:
seen_ids.add(preview_id)
image_urls.append(f"https://miro.medium.com/v2/resize:fit:1400/{preview_id}")
# Extract images from paragraphs (type 4 = image)
for para in paragraphs:
if para.get("type") != 4:
continue
meta = para.get("metadata", {})
image_id = meta.get("id")
if not image_id or image_id in seen_ids:
continue
seen_ids.add(image_id)
image_urls.append(f"https://miro.medium.com/v2/resize:fit:1400/{image_id}")
print(f"[SCRAPER] Medium JSON API found {len(image_urls)} images")
return image_urls
except Exception as e:
print(f"[SCRAPER] Medium JSON API image extraction failed (non-fatal): {e}")
return []
def _is_from_content_cdn(url: str) -> bool:
"""Return True if the image URL is from a known content CDN."""
lower = url.lower()
return any(cdn in lower for cdn in _CONTENT_CDN_DOMAINS)
def _upgrade_medium_image_url(url: str) -> str:
"""
Upgrade a Medium image URL to maximum resolution.
Medium URLs look like:
https://miro.medium.com/v2/resize:fit:700/format:webp/1*abc.jpeg
https://miro.medium.com/v2/resize:fit:700/1*abc.jpeg
We want: resize:fit:1400 (or even larger) for best quality.
"""
if "miro.medium.com" not in url and "cdn-images" not in url:
return url
# Upgrade resize:fit to max width 1400
upgraded = re.sub(r"resize:fit:\d+", "resize:fit:1400", url)
# Remove format:webp to get original format (better for Remotion)
# Actually keep webp β€” Remotion handles it fine and it's smaller
return upgraded
def _extract_medium_image_id(url: str) -> str | None:
"""
Extract the unique image identifier from a Medium image URL for deduplication.
Medium URLs contain IDs like: 1*abc123def.jpeg or 0*abc123def.png
"""
if "miro.medium.com" not in url and "cdn-images" not in url:
return None
# Match patterns like /1*abc123.jpeg or /0*xyz.png at end of path
m = re.search(r"/(\d\*[a-zA-Z0-9_-]+)\.", url)
if m:
return m.group(1)
# Also match hash-style IDs: /abc123def456 (no extension)
m = re.search(r"/([a-f0-9]{12,})", url)
if m:
return m.group(1)
return None
def _extract_medium_figure_images(soup: BeautifulSoup, base_url: str) -> list[str]:
"""
Medium-specific: extract images from <figure> tags and <noscript> fallbacks.
Medium wraps content images in <figure role="presentation"> and hides
the real src behind lazy loading with a <noscript> fallback.
"""
urls = []
seen = set()
# 1. <figure> tags (Medium's standard image wrapper)
for fig in soup.find_all("figure"):
# Check <img> inside <figure>
for img in fig.find_all("img"):
for attr in ("src", "data-src", "data-lazy-src"):
src = img.get(attr, "")
if src and not src.startswith("data:") and "miro.medium.com" in src:
full = urljoin(base_url, src)
if full not in seen:
seen.add(full)
urls.append(full)
break
# Check <noscript> inside <figure>
for noscript in fig.find_all("noscript"):
ns_html = noscript.string or noscript.decode_contents()
if "<img" in ns_html:
ns_soup = BeautifulSoup(ns_html, "lxml")
for img in ns_soup.find_all("img"):
src = img.get("src", "")
if src and "miro.medium.com" in src:
full = urljoin(base_url, src)
if full not in seen:
seen.add(full)
urls.append(full)
# 2. <img> tags with Medium CDN (may be outside <figure>)
for img in soup.find_all("img"):
src = img.get("src") or img.get("data-src") or ""
if src and "miro.medium.com" in src and not src.startswith("data:"):
full = urljoin(base_url, src)
if full not in seen:
seen.add(full)
urls.append(full)
return urls
# ─── Image filtering ──────────────────────────────────────
# URL substrings that indicate non-blog images (icons, UI chrome, tracking)
_SKIP_URL_PATTERNS = [
"avatar", "logo", "icon", "emoji", "gravatar", "pixel", "tracking",
"1x1", "badge", "button", "spinner", "loader", "arrow", "caret",
"chevron", "close", "hamburger", "menu", "nav-", "social",
"share", "like", "clap", "bookmark", "follow", "subscribe",
"profile", "author", "user-image", "favicon",
"sprite", "widget", "ad-", "ads/", "banner-ad", "doubleclick",
"googlesyndication", "analytics", "stat", "beacon",
"placeholder", "spacer", "blank", "transparent",
"shield.io", "shields.io", "img.shields", "badge/",
"buymeacoffee", "ko-fi", "patreon", "paypal",
"github-mark", "twitter-logo", "linkedin-logo", "facebook-logo",
]
# File extensions that are never blog content images
_SKIP_EXTENSIONS = {".svg", ".ico"}
# Note: .gif is allowed β€” some blogs use animated GIFs as content images
# Minimum URL path length (very short paths are usually generic assets)
_MIN_PATH_LEN = 10
def _is_content_image_light_filter(url: str) -> bool:
"""
Light filter for Exa-curated image_links.
Exa already extracts only content images, so we only reject:
- data: URIs
- Obvious non-content (avatars, icons, tiny resize:fill)
- SVG/ICO files
"""
lower = url.lower()
if lower.startswith("data:"):
return False
# Skip SVG/ICO only
parsed = urlparse(lower)
ext = os.path.splitext(parsed.path)[1]
if ext in {".svg", ".ico"}:
return False
# Medium avatars: resize:fill with small dimensions
fill_match = re.search(r"resize:fill:(\d+):(\d+)", lower)
if fill_match:
w, h = int(fill_match.group(1)), int(fill_match.group(2))
if w < 200 or h < 200:
return False
# Only reject the most obvious non-content patterns
_LIGHT_SKIP = [
"avatar", "gravatar", "favicon", "1x1", "pixel",
"tracking", "beacon", "spacer", "transparent",
]
if any(p in lower for p in _LIGHT_SKIP):
return False
return True
def _is_blog_image(url: str) -> bool:
"""Return True only if the URL looks like an actual blog content image."""
lower = url.lower()
# Always allow images from known content CDNs (with minimal filtering)
if _is_from_content_cdn(url):
return _is_content_image_light_filter(url)
# Skip by extension
parsed = urlparse(lower)
ext = os.path.splitext(parsed.path)[1]
if ext in _SKIP_EXTENSIONS:
return False
# Skip by URL pattern
if any(p in lower for p in _SKIP_URL_PATTERNS):
return False
# Medium-specific: resize:fill with small dimensions = avatars/icons
# e.g. miro.medium.com/v2/resize:fill:64:64/... β†’ icon
# but miro.medium.com/v2/resize:fit:700/... β†’ content image
fill_match = re.search(r"resize:fill:(\d+):(\d+)", lower)
if fill_match:
w, h = int(fill_match.group(1)), int(fill_match.group(2))
if w < 200 or h < 200:
return False
# Skip very short paths (e.g. /img.png, /x.jpg β€” usually site assets)
path = parsed.path.strip("/")
if len(path) < _MIN_PATH_LEN and "." in path:
return False
# Skip base64/data URIs
if lower.startswith("data:"):
return False
return True
# Minimum file size in bytes to keep a downloaded image (skip tiny icons)
_MIN_IMAGE_BYTES = 15_000 # 15 KB β€” real blog images are usually 50 KB+
_MIN_IMAGE_BYTES_CDN = 5_000 # 5 KB β€” lower threshold for known content CDNs (webp is very compact)
# GIF caps β€” animated GIFs are decoded frame-by-frame in Remotion, each frame
# held as raw RGBA in memory. Large GIFs can easily consume 50-200 MB per scene.
_MAX_GIF_BYTES = 5 * 1024 * 1024 # 5 MB β€” GIFs larger than this are converted to static PNG
_MAX_GIF_DIMENSION = 480 # px β€” GIFs wider or taller than this are resized
# ─── Image downloading ────────────────────────────────────
def _download_images(user_id: int, project_id: int, image_urls: list[str], db: Session) -> list[str]:
"""Download images, discard anything that's too small to be a real blog image."""
project_media_dir = os.path.join(settings.MEDIA_DIR, f"projects/{project_id}/images")
os.makedirs(project_media_dir, exist_ok=True)
# Use image-specific Accept header so servers like Medium
# respond with the correct Content-Type (including webp)
_IMAGE_HEADERS = {
**_BROWSER_HEADERS,
"Accept": "image/webp,image/avif,image/png,image/jpeg,image/*,*/*;q=0.8",
}
local_paths = []
for url in image_urls:
try:
response = requests.get(url, headers=_IMAGE_HEADERS, timeout=15, stream=True)
response.raise_for_status()
# Check Content-Type β€” only keep actual images
ctype = (response.headers.get("Content-Type") or "").lower()
if ctype and "image" not in ctype:
print(f"[SCRAPER] Skipping non-image content-type ({ctype}): {url[:80]}")
continue
# Determine correct extension from Content-Type first (Medium
# serves WebP images from URLs with no extension at all)
_CTYPE_TO_EXT = {
"image/webp": ".webp",
"image/png": ".png",
"image/jpeg": ".jpg",
"image/jpg": ".jpg",
"image/gif": ".gif",
"image/avif": ".avif",
}
ext = None
for ct_key, ct_ext in _CTYPE_TO_EXT.items():
if ct_key in ctype:
ext = ct_ext
break
# Fallback: try to get extension from the URL path
if not ext:
parsed = urlparse(url)
ext = os.path.splitext(parsed.path)[1] or ".jpg"
if ext not in (".jpg", ".jpeg", ".png", ".webp", ".avif", ".gif"):
ext = ".jpg"
url_hash = hashlib.md5(url.encode()).hexdigest()[:10]
filename = f"img_{url_hash}{ext}"
local_path = os.path.join(project_media_dir, filename)
with open(local_path, "wb") as f:
for chunk in response.iter_content(chunk_size=8192):
f.write(chunk)
# Discard tiny files β€” they are icons/badges, not blog images
# Use lower threshold for known content CDNs (webp is very compact)
file_size = os.path.getsize(local_path)
min_size = _MIN_IMAGE_BYTES_CDN if _is_from_content_cdn(url) else _MIN_IMAGE_BYTES
if file_size < min_size:
os.remove(local_path)
print(f"[SCRAPER] Discarded tiny image ({file_size} bytes, min={min_size}): {url[:80]}")
continue
# Cap GIFs β€” large/high-res GIFs eat too much memory during Remotion render.
# Convert oversized GIFs to a static PNG (first frame).
if ext == ".gif":
needs_static = file_size > _MAX_GIF_BYTES
try:
with Image.open(local_path) as img:
w, h = img.size
if w > _MAX_GIF_DIMENSION or h > _MAX_GIF_DIMENSION:
needs_static = True
if needs_static:
# Extract first frame, resize if needed
img.seek(0)
frame = img.convert("RGBA")
if w > _MAX_GIF_DIMENSION or h > _MAX_GIF_DIMENSION:
frame.thumbnail((_MAX_GIF_DIMENSION, _MAX_GIF_DIMENSION), Image.LANCZOS)
# Save as PNG, update filename/path
new_filename = filename.replace(".gif", ".png")
new_path = os.path.join(project_media_dir, new_filename)
frame.save(new_path, "PNG")
os.remove(local_path)
local_path = new_path
filename = new_filename
ext = ".png"
reason = f"size={file_size // 1024}KB" if file_size > _MAX_GIF_BYTES else f"dims={w}x{h}"
print(f"[SCRAPER] GIF capped ({reason}) β†’ static PNG: {filename}")
except Exception as e:
print(f"[SCRAPER] GIF cap check failed (keeping as-is): {e}")
# Upload to R2 if configured
r2_key = None
r2_url = None
if r2_storage.is_r2_configured():
try:
r2_url = r2_storage.upload_project_image(user_id, project_id, local_path, filename)
r2_key = r2_storage.image_key(user_id, project_id, filename)
except Exception as e:
print(f"[SCRAPER] R2 upload failed for {filename}: {e}")
asset = Asset(
project_id=project_id,
asset_type=AssetType.IMAGE,
original_url=url,
local_path=local_path,
filename=filename,
r2_key=r2_key,
r2_url=r2_url,
)
db.add(asset)
local_paths.append(local_path)
except Exception as e:
print(f"[SCRAPER] Failed to download image {url}: {e}")
continue
db.commit()
print(f"[SCRAPER] Downloaded {len(local_paths)} blog images (discarded icons/small files)")
return local_paths