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vr0.6.0
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11
CHANGELOG.md
11
CHANGELOG.md
@@ -5,7 +5,16 @@ All notable changes to Crawl4AI will be documented in this file.
|
||||
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
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and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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## [0.6.0rc1] ‑ 2025‑04‑22
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## [0.6.1] - 2025-04-24
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### Added
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- New dedicated `tables` field in `CrawlResult` model for better table extraction handling
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- Updated crypto_analysis_example.py to use the new tables field with backward compatibility
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### Changed
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- Improved playground UI in Docker deployment with better endpoint handling and UI feedback
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## [0.6.0] ‑ 2025‑04‑22
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### Added
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- Browser pooling with page pre‑warming and fine‑grained **geolocation, locale, and timezone** controls
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10
README.md
10
README.md
@@ -21,9 +21,9 @@
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||||
Crawl4AI is the #1 trending GitHub repository, actively maintained by a vibrant community. It delivers blazing-fast, AI-ready web crawling tailored for LLMs, AI agents, and data pipelines. Open source, flexible, and built for real-time performance, Crawl4AI empowers developers with unmatched speed, precision, and deployment ease.
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[✨ Check out latest update v0.6.0rc1](#-recent-updates)
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[✨ Check out latest update v0.6.0](#-recent-updates)
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||||
🎉 **Version 0.6.0rc1 is now available!** This release candidate introduces World-aware Crawling with geolocation and locale settings, Table-to-DataFrame extraction, Browser pooling with pre-warming, Network and console traffic capture, MCP integration for AI tools, and a completely revamped Docker deployment! [Read the release notes →](https://docs.crawl4ai.com/blog)
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🎉 **Version 0.6.0 is now available!** This release candidate introduces World-aware Crawling with geolocation and locale settings, Table-to-DataFrame extraction, Browser pooling with pre-warming, Network and console traffic capture, MCP integration for AI tools, and a completely revamped Docker deployment! [Read the release notes →](https://docs.crawl4ai.com/blog)
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<details>
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<summary>🤓 <strong>My Personal Story</strong></summary>
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@@ -505,7 +505,7 @@ async def test_news_crawl():
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## ✨ Recent Updates
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### Version 0.6.0rc1 Release Highlights
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### Version 0.6.0 Release Highlights
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- **🌎 World-aware Crawling**: Set geolocation, language, and timezone for authentic locale-specific content:
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```python
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@@ -575,7 +575,7 @@ async def test_news_crawl():
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- **📱 Multi-stage Build System**: Optimized Dockerfile with platform-specific performance enhancements
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Read the full details in our [0.6.0rc1 Release Notes](https://docs.crawl4ai.com/blog/releases/0.6.0.html) or check the [CHANGELOG](https://github.com/unclecode/crawl4ai/blob/main/CHANGELOG.md).
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Read the full details in our [0.6.0 Release Notes](https://docs.crawl4ai.com/blog/releases/0.6.0.html) or check the [CHANGELOG](https://github.com/unclecode/crawl4ai/blob/main/CHANGELOG.md).
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### Previous Version: 0.5.0 Major Release Highlights
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||||
@@ -606,7 +606,7 @@ We use different suffixes to indicate development stages:
|
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- `dev` (0.4.3dev1): Development versions, unstable
|
||||
- `a` (0.4.3a1): Alpha releases, experimental features
|
||||
- `b` (0.4.3b1): Beta releases, feature complete but needs testing
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||||
- `rc` (0.4.3rc1): Release candidates, potential final version
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- `rc` (0.4.3): Release candidates, potential final version
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#### Installation
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- Regular installation (stable version):
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@@ -1,3 +1,3 @@
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# crawl4ai/_version.py
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__version__ = "0.6.0"
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__version__ = "0.6.3"
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@@ -427,7 +427,7 @@ class BrowserConfig:
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host: str = "localhost",
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):
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self.browser_type = browser_type
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self.headless = headless or True
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self.headless = headless
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self.browser_mode = browser_mode
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self.use_managed_browser = use_managed_browser
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self.cdp_url = cdp_url
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||||
@@ -171,7 +171,10 @@ class AsyncDatabaseManager:
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f"Code context:\n{error_context['code_context']}"
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)
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self.logger.error(
|
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message=create_box_message(error_message, type="error"),
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message="{error}",
|
||||
tag="ERROR",
|
||||
params={"error": str(error_message)},
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||||
boxes=["error"],
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||||
)
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||||
|
||||
raise
|
||||
@@ -189,7 +192,10 @@ class AsyncDatabaseManager:
|
||||
f"Code context:\n{error_context['code_context']}"
|
||||
)
|
||||
self.logger.error(
|
||||
message=create_box_message(error_message, type="error"),
|
||||
message="{error}",
|
||||
tag="ERROR",
|
||||
params={"error": str(error_message)},
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||||
boxes=["error"],
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||||
)
|
||||
raise
|
||||
finally:
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||||
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||||
@@ -1,10 +1,12 @@
|
||||
from abc import ABC, abstractmethod
|
||||
from enum import Enum
|
||||
from typing import Optional, Dict, Any
|
||||
from colorama import Fore, Style, init
|
||||
from typing import Optional, Dict, Any, List
|
||||
import os
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||||
from datetime import datetime
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from urllib.parse import unquote
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from rich.console import Console
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from rich.text import Text
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from .utils import create_box_message
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||||
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||||
class LogLevel(Enum):
|
||||
@@ -21,6 +23,26 @@ class LogLevel(Enum):
|
||||
FATAL = 10
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||||
|
||||
|
||||
def __str__(self):
|
||||
return self.name.lower()
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||||
|
||||
class LogColor(str, Enum):
|
||||
"""Enum for log colors."""
|
||||
|
||||
DEBUG = "lightblack"
|
||||
INFO = "cyan"
|
||||
SUCCESS = "green"
|
||||
WARNING = "yellow"
|
||||
ERROR = "red"
|
||||
CYAN = "cyan"
|
||||
GREEN = "green"
|
||||
YELLOW = "yellow"
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||||
MAGENTA = "magenta"
|
||||
DIM_MAGENTA = "dim magenta"
|
||||
|
||||
def __str__(self):
|
||||
"""Automatically convert rich color to string."""
|
||||
return self.value
|
||||
|
||||
|
||||
class AsyncLoggerBase(ABC):
|
||||
@@ -52,6 +74,7 @@ class AsyncLoggerBase(ABC):
|
||||
def error_status(self, url: str, error: str, tag: str = "ERROR", url_length: int = 100):
|
||||
pass
|
||||
|
||||
|
||||
class AsyncLogger(AsyncLoggerBase):
|
||||
"""
|
||||
Asynchronous logger with support for colored console output and file logging.
|
||||
@@ -79,17 +102,11 @@ class AsyncLogger(AsyncLoggerBase):
|
||||
}
|
||||
|
||||
DEFAULT_COLORS = {
|
||||
LogLevel.DEBUG: Fore.LIGHTBLACK_EX,
|
||||
LogLevel.INFO: Fore.CYAN,
|
||||
LogLevel.SUCCESS: Fore.GREEN,
|
||||
LogLevel.WARNING: Fore.YELLOW,
|
||||
LogLevel.ERROR: Fore.RED,
|
||||
LogLevel.CRITICAL: Fore.RED + Style.BRIGHT,
|
||||
LogLevel.ALERT: Fore.RED + Style.BRIGHT,
|
||||
LogLevel.NOTICE: Fore.BLUE,
|
||||
LogLevel.EXCEPTION: Fore.RED + Style.BRIGHT,
|
||||
LogLevel.FATAL: Fore.RED + Style.BRIGHT,
|
||||
LogLevel.DEFAULT: Fore.WHITE,
|
||||
LogLevel.DEBUG: LogColor.DEBUG,
|
||||
LogLevel.INFO: LogColor.INFO,
|
||||
LogLevel.SUCCESS: LogColor.SUCCESS,
|
||||
LogLevel.WARNING: LogColor.WARNING,
|
||||
LogLevel.ERROR: LogColor.ERROR,
|
||||
}
|
||||
|
||||
def __init__(
|
||||
@@ -98,7 +115,7 @@ class AsyncLogger(AsyncLoggerBase):
|
||||
log_level: LogLevel = LogLevel.DEBUG,
|
||||
tag_width: int = 10,
|
||||
icons: Optional[Dict[str, str]] = None,
|
||||
colors: Optional[Dict[LogLevel, str]] = None,
|
||||
colors: Optional[Dict[LogLevel, LogColor]] = None,
|
||||
verbose: bool = True,
|
||||
):
|
||||
"""
|
||||
@@ -112,13 +129,13 @@ class AsyncLogger(AsyncLoggerBase):
|
||||
colors: Custom colors for different log levels
|
||||
verbose: Whether to output to console
|
||||
"""
|
||||
init() # Initialize colorama
|
||||
self.log_file = log_file
|
||||
self.log_level = log_level
|
||||
self.tag_width = tag_width
|
||||
self.icons = icons or self.DEFAULT_ICONS
|
||||
self.colors = colors or self.DEFAULT_COLORS
|
||||
self.verbose = verbose
|
||||
self.console = Console()
|
||||
|
||||
# Create log file directory if needed
|
||||
if log_file:
|
||||
@@ -143,16 +160,11 @@ class AsyncLogger(AsyncLoggerBase):
|
||||
def _write_to_file(self, message: str):
|
||||
"""Write a message to the log file if configured."""
|
||||
if self.log_file:
|
||||
text = Text.from_markup(message)
|
||||
plain_text = text.plain
|
||||
timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S.%f")[:-3]
|
||||
with open(self.log_file, "a", encoding="utf-8") as f:
|
||||
# Strip ANSI color codes for file output
|
||||
clean_message = message.replace(Fore.RESET, "").replace(
|
||||
Style.RESET_ALL, ""
|
||||
)
|
||||
for color in vars(Fore).values():
|
||||
if isinstance(color, str):
|
||||
clean_message = clean_message.replace(color, "")
|
||||
f.write(f"[{timestamp}] {clean_message}\n")
|
||||
f.write(f"[{timestamp}] {plain_text}\n")
|
||||
|
||||
def _log(
|
||||
self,
|
||||
@@ -160,8 +172,9 @@ class AsyncLogger(AsyncLoggerBase):
|
||||
message: str,
|
||||
tag: str,
|
||||
params: Optional[Dict[str, Any]] = None,
|
||||
colors: Optional[Dict[str, str]] = None,
|
||||
base_color: Optional[str] = None,
|
||||
colors: Optional[Dict[str, LogColor]] = None,
|
||||
boxes: Optional[List[str]] = None,
|
||||
base_color: Optional[LogColor] = None,
|
||||
**kwargs,
|
||||
):
|
||||
"""
|
||||
@@ -173,55 +186,44 @@ class AsyncLogger(AsyncLoggerBase):
|
||||
tag: Tag for the message
|
||||
params: Parameters to format into the message
|
||||
colors: Color overrides for specific parameters
|
||||
boxes: Box overrides for specific parameters
|
||||
base_color: Base color for the entire message
|
||||
"""
|
||||
if level.value < self.log_level.value:
|
||||
return
|
||||
|
||||
# Format the message with parameters if provided
|
||||
# avoid conflict with rich formatting
|
||||
parsed_message = message.replace("[", "[[").replace("]", "]]")
|
||||
if params:
|
||||
try:
|
||||
# First format the message with raw parameters
|
||||
formatted_message = message.format(**params)
|
||||
# FIXME: If there are formatting strings in floating point format,
|
||||
# this may result in colors and boxes not being applied properly.
|
||||
# such as {value:.2f}, the value is 0.23333 format it to 0.23,
|
||||
# but we replace("0.23333", "[color]0.23333[/color]")
|
||||
formatted_message = parsed_message.format(**params)
|
||||
for key, value in params.items():
|
||||
# value_str may discard `[` and `]`, so we need to replace it.
|
||||
value_str = str(value).replace("[", "[[").replace("]", "]]")
|
||||
# check is need apply color
|
||||
if colors and key in colors:
|
||||
color_str = f"[{colors[key]}]{value_str}[/{colors[key]}]"
|
||||
formatted_message = formatted_message.replace(value_str, color_str)
|
||||
value_str = color_str
|
||||
|
||||
# Then apply colors if specified
|
||||
color_map = {
|
||||
"green": Fore.GREEN,
|
||||
"red": Fore.RED,
|
||||
"yellow": Fore.YELLOW,
|
||||
"blue": Fore.BLUE,
|
||||
"cyan": Fore.CYAN,
|
||||
"magenta": Fore.MAGENTA,
|
||||
"white": Fore.WHITE,
|
||||
"black": Fore.BLACK,
|
||||
"reset": Style.RESET_ALL,
|
||||
}
|
||||
if colors:
|
||||
for key, color in colors.items():
|
||||
# Find the formatted value in the message and wrap it with color
|
||||
if color in color_map:
|
||||
color = color_map[color]
|
||||
if key in params:
|
||||
value_str = str(params[key])
|
||||
formatted_message = formatted_message.replace(
|
||||
value_str, f"{color}{value_str}{Style.RESET_ALL}"
|
||||
)
|
||||
# check is need apply box
|
||||
if boxes and key in boxes:
|
||||
formatted_message = formatted_message.replace(value_str,
|
||||
create_box_message(value_str, type=str(level)))
|
||||
|
||||
except KeyError as e:
|
||||
formatted_message = (
|
||||
f"LOGGING ERROR: Missing parameter {e} in message template"
|
||||
)
|
||||
level = LogLevel.ERROR
|
||||
else:
|
||||
formatted_message = message
|
||||
formatted_message = parsed_message
|
||||
|
||||
# Construct the full log line
|
||||
color = base_color or self.colors[level]
|
||||
log_line = f"{color}{self._format_tag(tag)} {self._get_icon(tag)} {formatted_message}{Style.RESET_ALL}"
|
||||
color: LogColor = base_color or self.colors[level]
|
||||
log_line = f"[{color}]{self._format_tag(tag)} {self._get_icon(tag)} {formatted_message} [/{color}]"
|
||||
|
||||
# Output to console if verbose
|
||||
if self.verbose or kwargs.get("force_verbose", False):
|
||||
print(log_line)
|
||||
self.console.print(log_line)
|
||||
|
||||
# Write to file if configured
|
||||
self._write_to_file(log_line)
|
||||
@@ -292,8 +294,8 @@ class AsyncLogger(AsyncLoggerBase):
|
||||
"timing": timing,
|
||||
},
|
||||
colors={
|
||||
"status": Fore.GREEN if success else Fore.RED,
|
||||
"timing": Fore.YELLOW,
|
||||
"status": LogColor.SUCCESS if success else LogColor.ERROR,
|
||||
"timing": LogColor.WARNING,
|
||||
},
|
||||
)
|
||||
|
||||
|
||||
@@ -2,7 +2,6 @@ from .__version__ import __version__ as crawl4ai_version
|
||||
import os
|
||||
import sys
|
||||
import time
|
||||
from colorama import Fore
|
||||
from pathlib import Path
|
||||
from typing import Optional, List
|
||||
import json
|
||||
@@ -44,7 +43,6 @@ from .utils import (
|
||||
sanitize_input_encode,
|
||||
InvalidCSSSelectorError,
|
||||
fast_format_html,
|
||||
create_box_message,
|
||||
get_error_context,
|
||||
RobotsParser,
|
||||
preprocess_html_for_schema,
|
||||
@@ -419,7 +417,7 @@ class AsyncWebCrawler:
|
||||
|
||||
self.logger.error_status(
|
||||
url=url,
|
||||
error=create_box_message(error_message, type="error"),
|
||||
error=error_message,
|
||||
tag="ERROR",
|
||||
)
|
||||
|
||||
@@ -496,11 +494,13 @@ class AsyncWebCrawler:
|
||||
cleaned_html = sanitize_input_encode(
|
||||
result.get("cleaned_html", ""))
|
||||
media = result.get("media", {})
|
||||
tables = media.pop("tables", []) if isinstance(media, dict) else []
|
||||
links = result.get("links", {})
|
||||
metadata = result.get("metadata", {})
|
||||
else:
|
||||
cleaned_html = sanitize_input_encode(result.cleaned_html)
|
||||
media = result.media.model_dump()
|
||||
tables = media.pop("tables", [])
|
||||
links = result.links.model_dump()
|
||||
metadata = result.metadata
|
||||
|
||||
@@ -627,6 +627,7 @@ class AsyncWebCrawler:
|
||||
cleaned_html=cleaned_html,
|
||||
markdown=markdown_result,
|
||||
media=media,
|
||||
tables=tables, # NEW
|
||||
links=links,
|
||||
metadata=metadata,
|
||||
screenshot=screenshot_data,
|
||||
|
||||
@@ -5,7 +5,10 @@ import os
|
||||
import sys
|
||||
import shutil
|
||||
import tempfile
|
||||
import psutil
|
||||
import signal
|
||||
import subprocess
|
||||
import shlex
|
||||
from playwright.async_api import BrowserContext
|
||||
import hashlib
|
||||
from .js_snippet import load_js_script
|
||||
@@ -193,6 +196,45 @@ class ManagedBrowser:
|
||||
|
||||
if self.browser_config.extra_args:
|
||||
args.extend(self.browser_config.extra_args)
|
||||
|
||||
|
||||
# ── make sure no old Chromium instance is owning the same port/profile ──
|
||||
try:
|
||||
if sys.platform == "win32":
|
||||
if psutil is None:
|
||||
raise RuntimeError("psutil not available, cannot clean old browser")
|
||||
for p in psutil.process_iter(["pid", "name", "cmdline"]):
|
||||
cl = " ".join(p.info.get("cmdline") or [])
|
||||
if (
|
||||
f"--remote-debugging-port={self.debugging_port}" in cl
|
||||
and f"--user-data-dir={self.user_data_dir}" in cl
|
||||
):
|
||||
p.kill()
|
||||
p.wait(timeout=5)
|
||||
else: # macOS / Linux
|
||||
# kill any process listening on the same debugging port
|
||||
pids = (
|
||||
subprocess.check_output(shlex.split(f"lsof -t -i:{self.debugging_port}"))
|
||||
.decode()
|
||||
.strip()
|
||||
.splitlines()
|
||||
)
|
||||
for pid in pids:
|
||||
try:
|
||||
os.kill(int(pid), signal.SIGTERM)
|
||||
except ProcessLookupError:
|
||||
pass
|
||||
|
||||
# remove Chromium singleton locks, or new launch exits with
|
||||
# “Opening in existing browser session.”
|
||||
for f in ("SingletonLock", "SingletonSocket", "SingletonCookie"):
|
||||
fp = os.path.join(self.user_data_dir, f)
|
||||
if os.path.exists(fp):
|
||||
os.remove(fp)
|
||||
except Exception as _e:
|
||||
# non-fatal — we'll try to start anyway, but log what happened
|
||||
self.logger.warning(f"pre-launch cleanup failed: {_e}", tag="BROWSER")
|
||||
|
||||
|
||||
# Start browser process
|
||||
try:
|
||||
@@ -922,7 +964,7 @@ class BrowserManager:
|
||||
pages = context.pages
|
||||
page = next((p for p in pages if p.url == crawlerRunConfig.url), None)
|
||||
if not page:
|
||||
page = await context.new_page()
|
||||
page = context.pages[0] # await context.new_page()
|
||||
else:
|
||||
# Otherwise, check if we have an existing context for this config
|
||||
config_signature = self._make_config_signature(crawlerRunConfig)
|
||||
|
||||
@@ -15,12 +15,12 @@ import shutil
|
||||
import json
|
||||
import subprocess
|
||||
import time
|
||||
from typing import List, Dict, Optional, Any, Tuple
|
||||
from colorama import Fore, Style, init
|
||||
from typing import List, Dict, Optional, Any
|
||||
from rich.console import Console
|
||||
|
||||
from .async_configs import BrowserConfig
|
||||
from .browser_manager import ManagedBrowser
|
||||
from .async_logger import AsyncLogger, AsyncLoggerBase
|
||||
from .async_logger import AsyncLogger, AsyncLoggerBase, LogColor
|
||||
from .utils import get_home_folder
|
||||
|
||||
|
||||
@@ -45,8 +45,8 @@ class BrowserProfiler:
|
||||
logger (AsyncLoggerBase, optional): Logger for outputting messages.
|
||||
If None, a default AsyncLogger will be created.
|
||||
"""
|
||||
# Initialize colorama for colorful terminal output
|
||||
init()
|
||||
# Initialize rich console for colorful input prompts
|
||||
self.console = Console()
|
||||
|
||||
# Create a logger if not provided
|
||||
if logger is None:
|
||||
@@ -127,26 +127,30 @@ class BrowserProfiler:
|
||||
profile_path = os.path.join(self.profiles_dir, profile_name)
|
||||
os.makedirs(profile_path, exist_ok=True)
|
||||
|
||||
# Print instructions for the user with colorama formatting
|
||||
border = f"{Fore.CYAN}{'='*80}{Style.RESET_ALL}"
|
||||
self.logger.info(f"\n{border}", tag="PROFILE")
|
||||
self.logger.info(f"Creating browser profile: {Fore.GREEN}{profile_name}{Style.RESET_ALL}", tag="PROFILE")
|
||||
self.logger.info(f"Profile directory: {Fore.YELLOW}{profile_path}{Style.RESET_ALL}", tag="PROFILE")
|
||||
# Print instructions for the user with rich formatting
|
||||
border = "{'='*80}"
|
||||
self.logger.info("{border}", tag="PROFILE", params={"border": f"\n{border}"}, colors={"border": LogColor.CYAN})
|
||||
self.logger.info("Creating browser profile: {profile_name}", tag="PROFILE", params={"profile_name": profile_name}, colors={"profile_name": LogColor.GREEN})
|
||||
self.logger.info("Profile directory: {profile_path}", tag="PROFILE", params={"profile_path": profile_path}, colors={"profile_path": LogColor.YELLOW})
|
||||
|
||||
self.logger.info("\nInstructions:", tag="PROFILE")
|
||||
self.logger.info("1. A browser window will open for you to set up your profile.", tag="PROFILE")
|
||||
self.logger.info(f"2. {Fore.CYAN}Log in to websites{Style.RESET_ALL}, configure settings, etc. as needed.", tag="PROFILE")
|
||||
self.logger.info(f"3. When you're done, {Fore.YELLOW}press 'q' in this terminal{Style.RESET_ALL} to close the browser.", tag="PROFILE")
|
||||
self.logger.info("{segment}, configure settings, etc. as needed.", tag="PROFILE", params={"segment": "2. Log in to websites"}, colors={"segment": LogColor.CYAN})
|
||||
self.logger.info("3. When you're done, {segment} to close the browser.", tag="PROFILE", params={"segment": "press 'q' in this terminal"}, colors={"segment": LogColor.YELLOW})
|
||||
self.logger.info("4. The profile will be saved and ready to use with Crawl4AI.", tag="PROFILE")
|
||||
self.logger.info(f"{border}\n", tag="PROFILE")
|
||||
self.logger.info("{border}", tag="PROFILE", params={"border": f"{border}\n"}, colors={"border": LogColor.CYAN})
|
||||
|
||||
browser_config.headless = False
|
||||
browser_config.user_data_dir = profile_path
|
||||
|
||||
|
||||
# Create managed browser instance
|
||||
managed_browser = ManagedBrowser(
|
||||
browser_type=browser_config.browser_type,
|
||||
user_data_dir=profile_path,
|
||||
headless=False, # Must be visible
|
||||
browser_config=browser_config,
|
||||
# user_data_dir=profile_path,
|
||||
# headless=False, # Must be visible
|
||||
logger=self.logger,
|
||||
debugging_port=browser_config.debugging_port
|
||||
# debugging_port=browser_config.debugging_port
|
||||
)
|
||||
|
||||
# Set up signal handlers to ensure cleanup on interrupt
|
||||
@@ -181,7 +185,7 @@ class BrowserProfiler:
|
||||
import select
|
||||
|
||||
# First output the prompt
|
||||
self.logger.info(f"{Fore.CYAN}Press '{Fore.WHITE}q{Fore.CYAN}' when you've finished using the browser...{Style.RESET_ALL}", tag="PROFILE")
|
||||
self.logger.info("Press 'q' when you've finished using the browser...", tag="PROFILE")
|
||||
|
||||
# Save original terminal settings
|
||||
fd = sys.stdin.fileno()
|
||||
@@ -197,7 +201,7 @@ class BrowserProfiler:
|
||||
if readable:
|
||||
key = sys.stdin.read(1)
|
||||
if key.lower() == 'q':
|
||||
self.logger.info(f"{Fore.GREEN}Closing browser and saving profile...{Style.RESET_ALL}", tag="PROFILE")
|
||||
self.logger.info("Closing browser and saving profile...", tag="PROFILE", base_color=LogColor.GREEN)
|
||||
user_done_event.set()
|
||||
return
|
||||
|
||||
@@ -223,7 +227,7 @@ class BrowserProfiler:
|
||||
self.logger.error("Failed to start browser process.", tag="PROFILE")
|
||||
return None
|
||||
|
||||
self.logger.info(f"Browser launched. {Fore.CYAN}Waiting for you to finish...{Style.RESET_ALL}", tag="PROFILE")
|
||||
self.logger.info("Browser launched. Waiting for you to finish...", tag="PROFILE")
|
||||
|
||||
# Start listening for keyboard input
|
||||
listener_task = asyncio.create_task(listen_for_quit_command())
|
||||
@@ -245,10 +249,10 @@ class BrowserProfiler:
|
||||
self.logger.info("Terminating browser process...", tag="PROFILE")
|
||||
await managed_browser.cleanup()
|
||||
|
||||
self.logger.success(f"Browser closed. Profile saved at: {Fore.GREEN}{profile_path}{Style.RESET_ALL}", tag="PROFILE")
|
||||
self.logger.success(f"Browser closed. Profile saved at: {profile_path}", tag="PROFILE")
|
||||
|
||||
except Exception as e:
|
||||
self.logger.error(f"Error creating profile: {str(e)}", tag="PROFILE")
|
||||
self.logger.error(f"Error creating profile: {e!s}", tag="PROFILE")
|
||||
await managed_browser.cleanup()
|
||||
return None
|
||||
finally:
|
||||
@@ -440,25 +444,27 @@ class BrowserProfiler:
|
||||
```
|
||||
"""
|
||||
while True:
|
||||
self.logger.info(f"\n{Fore.CYAN}Profile Management Options:{Style.RESET_ALL}", tag="MENU")
|
||||
self.logger.info(f"1. {Fore.GREEN}Create a new profile{Style.RESET_ALL}", tag="MENU")
|
||||
self.logger.info(f"2. {Fore.YELLOW}List available profiles{Style.RESET_ALL}", tag="MENU")
|
||||
self.logger.info(f"3. {Fore.RED}Delete a profile{Style.RESET_ALL}", tag="MENU")
|
||||
self.logger.info("\nProfile Management Options:", tag="MENU")
|
||||
self.logger.info("1. Create a new profile", tag="MENU", base_color=LogColor.GREEN)
|
||||
self.logger.info("2. List available profiles", tag="MENU", base_color=LogColor.YELLOW)
|
||||
self.logger.info("3. Delete a profile", tag="MENU", base_color=LogColor.RED)
|
||||
|
||||
# Only show crawl option if callback provided
|
||||
if crawl_callback:
|
||||
self.logger.info(f"4. {Fore.CYAN}Use a profile to crawl a website{Style.RESET_ALL}", tag="MENU")
|
||||
self.logger.info(f"5. {Fore.MAGENTA}Exit{Style.RESET_ALL}", tag="MENU")
|
||||
self.logger.info("4. Use a profile to crawl a website", tag="MENU", base_color=LogColor.CYAN)
|
||||
self.logger.info("5. Exit", tag="MENU", base_color=LogColor.MAGENTA)
|
||||
exit_option = "5"
|
||||
else:
|
||||
self.logger.info(f"4. {Fore.MAGENTA}Exit{Style.RESET_ALL}", tag="MENU")
|
||||
self.logger.info("4. Exit", tag="MENU", base_color=LogColor.MAGENTA)
|
||||
exit_option = "4"
|
||||
|
||||
choice = input(f"\n{Fore.CYAN}Enter your choice (1-{exit_option}): {Style.RESET_ALL}")
|
||||
self.logger.print(f"\n[cyan]Enter your choice (1-{exit_option}): [/cyan]", end="")
|
||||
choice = input()
|
||||
|
||||
if choice == "1":
|
||||
# Create new profile
|
||||
name = input(f"{Fore.GREEN}Enter a name for the new profile (or press Enter for auto-generated name): {Style.RESET_ALL}")
|
||||
self.console.print("[green]Enter a name for the new profile (or press Enter for auto-generated name): [/green]", end="")
|
||||
name = input()
|
||||
await self.create_profile(name or None)
|
||||
|
||||
elif choice == "2":
|
||||
@@ -472,8 +478,8 @@ class BrowserProfiler:
|
||||
# Print profile information with colorama formatting
|
||||
self.logger.info("\nAvailable profiles:", tag="PROFILES")
|
||||
for i, profile in enumerate(profiles):
|
||||
self.logger.info(f"[{i+1}] {Fore.CYAN}{profile['name']}{Style.RESET_ALL}", tag="PROFILES")
|
||||
self.logger.info(f" Path: {Fore.YELLOW}{profile['path']}{Style.RESET_ALL}", tag="PROFILES")
|
||||
self.logger.info(f"[{i+1}] {profile['name']}", tag="PROFILES")
|
||||
self.logger.info(f" Path: {profile['path']}", tag="PROFILES", base_color=LogColor.YELLOW)
|
||||
self.logger.info(f" Created: {profile['created'].strftime('%Y-%m-%d %H:%M:%S')}", tag="PROFILES")
|
||||
self.logger.info(f" Browser type: {profile['type']}", tag="PROFILES")
|
||||
self.logger.info("", tag="PROFILES") # Empty line for spacing
|
||||
@@ -486,12 +492,13 @@ class BrowserProfiler:
|
||||
continue
|
||||
|
||||
# Display numbered list
|
||||
self.logger.info(f"\n{Fore.YELLOW}Available profiles:{Style.RESET_ALL}", tag="PROFILES")
|
||||
self.logger.info("\nAvailable profiles:", tag="PROFILES", base_color=LogColor.YELLOW)
|
||||
for i, profile in enumerate(profiles):
|
||||
self.logger.info(f"[{i+1}] {profile['name']}", tag="PROFILES")
|
||||
|
||||
# Get profile to delete
|
||||
profile_idx = input(f"{Fore.RED}Enter the number of the profile to delete (or 'c' to cancel): {Style.RESET_ALL}")
|
||||
self.console.print("[red]Enter the number of the profile to delete (or 'c' to cancel): [/red]", end="")
|
||||
profile_idx = input()
|
||||
if profile_idx.lower() == 'c':
|
||||
continue
|
||||
|
||||
@@ -499,17 +506,18 @@ class BrowserProfiler:
|
||||
idx = int(profile_idx) - 1
|
||||
if 0 <= idx < len(profiles):
|
||||
profile_name = profiles[idx]["name"]
|
||||
self.logger.info(f"Deleting profile: {Fore.YELLOW}{profile_name}{Style.RESET_ALL}", tag="PROFILES")
|
||||
self.logger.info(f"Deleting profile: [yellow]{profile_name}[/yellow]", tag="PROFILES")
|
||||
|
||||
# Confirm deletion
|
||||
confirm = input(f"{Fore.RED}Are you sure you want to delete this profile? (y/n): {Style.RESET_ALL}")
|
||||
self.console.print("[red]Are you sure you want to delete this profile? (y/n): [/red]", end="")
|
||||
confirm = input()
|
||||
if confirm.lower() == 'y':
|
||||
success = self.delete_profile(profiles[idx]["path"])
|
||||
|
||||
if success:
|
||||
self.logger.success(f"Profile {Fore.GREEN}{profile_name}{Style.RESET_ALL} deleted successfully", tag="PROFILES")
|
||||
self.logger.success(f"Profile {profile_name} deleted successfully", tag="PROFILES")
|
||||
else:
|
||||
self.logger.error(f"Failed to delete profile {Fore.RED}{profile_name}{Style.RESET_ALL}", tag="PROFILES")
|
||||
self.logger.error(f"Failed to delete profile {profile_name}", tag="PROFILES")
|
||||
else:
|
||||
self.logger.error("Invalid profile number", tag="PROFILES")
|
||||
except ValueError:
|
||||
@@ -523,12 +531,13 @@ class BrowserProfiler:
|
||||
continue
|
||||
|
||||
# Display numbered list
|
||||
self.logger.info(f"\n{Fore.YELLOW}Available profiles:{Style.RESET_ALL}", tag="PROFILES")
|
||||
self.logger.info("\nAvailable profiles:", tag="PROFILES", base_color=LogColor.YELLOW)
|
||||
for i, profile in enumerate(profiles):
|
||||
self.logger.info(f"[{i+1}] {profile['name']}", tag="PROFILES")
|
||||
|
||||
# Get profile to use
|
||||
profile_idx = input(f"{Fore.CYAN}Enter the number of the profile to use (or 'c' to cancel): {Style.RESET_ALL}")
|
||||
self.console.print("[cyan]Enter the number of the profile to use (or 'c' to cancel): [/cyan]", end="")
|
||||
profile_idx = input()
|
||||
if profile_idx.lower() == 'c':
|
||||
continue
|
||||
|
||||
@@ -536,7 +545,8 @@ class BrowserProfiler:
|
||||
idx = int(profile_idx) - 1
|
||||
if 0 <= idx < len(profiles):
|
||||
profile_path = profiles[idx]["path"]
|
||||
url = input(f"{Fore.CYAN}Enter the URL to crawl: {Style.RESET_ALL}")
|
||||
self.console.print("[cyan]Enter the URL to crawl: [/cyan]", end="")
|
||||
url = input()
|
||||
if url:
|
||||
# Call the provided crawl callback
|
||||
await crawl_callback(profile_path, url)
|
||||
@@ -599,11 +609,11 @@ class BrowserProfiler:
|
||||
# Print initial information
|
||||
border = f"{Fore.CYAN}{'='*80}{Style.RESET_ALL}"
|
||||
self.logger.info(f"\n{border}", tag="CDP")
|
||||
self.logger.info(f"Launching standalone browser with CDP debugging", tag="CDP")
|
||||
self.logger.info(f"Browser type: {Fore.GREEN}{browser_type}{Style.RESET_ALL}", tag="CDP")
|
||||
self.logger.info(f"Profile path: {Fore.YELLOW}{profile_path}{Style.RESET_ALL}", tag="CDP")
|
||||
self.logger.info(f"Debugging port: {Fore.CYAN}{debugging_port}{Style.RESET_ALL}", tag="CDP")
|
||||
self.logger.info(f"Headless mode: {Fore.CYAN}{headless}{Style.RESET_ALL}", tag="CDP")
|
||||
self.logger.info("Launching standalone browser with CDP debugging", tag="CDP")
|
||||
self.logger.info("Browser type: {browser_type}", tag="CDP", params={"browser_type": browser_type}, colors={"browser_type": LogColor.CYAN})
|
||||
self.logger.info("Profile path: {profile_path}", tag="CDP", params={"profile_path": profile_path}, colors={"profile_path": LogColor.YELLOW})
|
||||
self.logger.info(f"Debugging port: {debugging_port}", tag="CDP")
|
||||
self.logger.info(f"Headless mode: {headless}", tag="CDP")
|
||||
|
||||
# Create managed browser instance
|
||||
managed_browser = ManagedBrowser(
|
||||
@@ -646,7 +656,7 @@ class BrowserProfiler:
|
||||
import select
|
||||
|
||||
# First output the prompt
|
||||
self.logger.info(f"{Fore.CYAN}Press '{Fore.WHITE}q{Fore.CYAN}' to stop the browser and exit...{Style.RESET_ALL}", tag="CDP")
|
||||
self.logger.info("Press 'q' to stop the browser and exit...", tag="CDP")
|
||||
|
||||
# Save original terminal settings
|
||||
fd = sys.stdin.fileno()
|
||||
@@ -662,7 +672,7 @@ class BrowserProfiler:
|
||||
if readable:
|
||||
key = sys.stdin.read(1)
|
||||
if key.lower() == 'q':
|
||||
self.logger.info(f"{Fore.GREEN}Closing browser...{Style.RESET_ALL}", tag="CDP")
|
||||
self.logger.info("Closing browser...", tag="CDP")
|
||||
user_done_event.set()
|
||||
return
|
||||
|
||||
@@ -716,20 +726,20 @@ class BrowserProfiler:
|
||||
self.logger.error("Failed to start browser process.", tag="CDP")
|
||||
return None
|
||||
|
||||
self.logger.info(f"Browser launched successfully. Retrieving CDP information...", tag="CDP")
|
||||
self.logger.info("Browser launched successfully. Retrieving CDP information...", tag="CDP")
|
||||
|
||||
# Get CDP URL and JSON config
|
||||
cdp_url, config_json = await get_cdp_json(debugging_port)
|
||||
|
||||
if cdp_url:
|
||||
self.logger.success(f"CDP URL: {Fore.GREEN}{cdp_url}{Style.RESET_ALL}", tag="CDP")
|
||||
self.logger.success(f"CDP URL: {cdp_url}", tag="CDP")
|
||||
|
||||
if config_json:
|
||||
# Display relevant CDP information
|
||||
self.logger.info(f"Browser: {Fore.CYAN}{config_json.get('Browser', 'Unknown')}{Style.RESET_ALL}", tag="CDP")
|
||||
self.logger.info(f"Protocol Version: {config_json.get('Protocol-Version', 'Unknown')}", tag="CDP")
|
||||
self.logger.info(f"Browser: {config_json.get('Browser', 'Unknown')}", tag="CDP", colors={"Browser": LogColor.CYAN})
|
||||
self.logger.info(f"Protocol Version: {config_json.get('Protocol-Version', 'Unknown')}", tag="CDP", colors={"Protocol-Version": LogColor.CYAN})
|
||||
if 'webSocketDebuggerUrl' in config_json:
|
||||
self.logger.info(f"WebSocket URL: {Fore.GREEN}{config_json['webSocketDebuggerUrl']}{Style.RESET_ALL}", tag="CDP")
|
||||
self.logger.info("WebSocket URL: {webSocketDebuggerUrl}", tag="CDP", params={"webSocketDebuggerUrl": config_json['webSocketDebuggerUrl']}, colors={"webSocketDebuggerUrl": LogColor.GREEN})
|
||||
else:
|
||||
self.logger.warning("Could not retrieve CDP configuration JSON", tag="CDP")
|
||||
else:
|
||||
@@ -757,7 +767,7 @@ class BrowserProfiler:
|
||||
self.logger.info("Terminating browser process...", tag="CDP")
|
||||
await managed_browser.cleanup()
|
||||
|
||||
self.logger.success(f"Browser closed.", tag="CDP")
|
||||
self.logger.success("Browser closed.", tag="CDP")
|
||||
|
||||
except Exception as e:
|
||||
self.logger.error(f"Error launching standalone browser: {str(e)}", tag="CDP")
|
||||
@@ -972,3 +982,30 @@ class BrowserProfiler:
|
||||
'info': browser_info
|
||||
}
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
# Example usage
|
||||
profiler = BrowserProfiler()
|
||||
|
||||
# Create a new profile
|
||||
import os
|
||||
from pathlib import Path
|
||||
home_dir = Path.home()
|
||||
profile_path = asyncio.run(profiler.create_profile( str(home_dir / ".crawl4ai/profiles/test-profile")))
|
||||
|
||||
|
||||
|
||||
# Launch a standalone browser
|
||||
asyncio.run(profiler.launch_standalone_browser())
|
||||
|
||||
# List profiles
|
||||
profiles = profiler.list_profiles()
|
||||
for profile in profiles:
|
||||
print(f"Profile: {profile['name']}, Path: {profile['path']}")
|
||||
|
||||
# Delete a profile
|
||||
success = profiler.delete_profile("my-profile")
|
||||
if success:
|
||||
print("Profile deleted successfully")
|
||||
else:
|
||||
print("Failed to delete profile")
|
||||
@@ -27,8 +27,7 @@ import json
|
||||
import hashlib
|
||||
from pathlib import Path
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
from .async_logger import AsyncLogger, LogLevel
|
||||
from colorama import Fore, Style
|
||||
from .async_logger import AsyncLogger, LogLevel, LogColor
|
||||
|
||||
|
||||
class RelevantContentFilter(ABC):
|
||||
@@ -846,8 +845,7 @@ class LLMContentFilter(RelevantContentFilter):
|
||||
},
|
||||
colors={
|
||||
**AsyncLogger.DEFAULT_COLORS,
|
||||
LogLevel.INFO: Fore.MAGENTA
|
||||
+ Style.DIM, # Dimmed purple for LLM ops
|
||||
LogLevel.INFO: LogColor.DIM_MAGENTA # Dimmed purple for LLM ops
|
||||
},
|
||||
)
|
||||
else:
|
||||
@@ -892,7 +890,7 @@ class LLMContentFilter(RelevantContentFilter):
|
||||
"Starting LLM markdown content filtering process",
|
||||
tag="LLM",
|
||||
params={"provider": self.llm_config.provider},
|
||||
colors={"provider": Fore.CYAN},
|
||||
colors={"provider": LogColor.CYAN},
|
||||
)
|
||||
|
||||
# Cache handling
|
||||
@@ -929,7 +927,7 @@ class LLMContentFilter(RelevantContentFilter):
|
||||
"LLM markdown: Split content into {chunk_count} chunks",
|
||||
tag="CHUNK",
|
||||
params={"chunk_count": len(html_chunks)},
|
||||
colors={"chunk_count": Fore.YELLOW},
|
||||
colors={"chunk_count": LogColor.YELLOW},
|
||||
)
|
||||
|
||||
start_time = time.time()
|
||||
@@ -1038,7 +1036,7 @@ class LLMContentFilter(RelevantContentFilter):
|
||||
"LLM markdown: Completed processing in {time:.2f}s",
|
||||
tag="LLM",
|
||||
params={"time": end_time - start_time},
|
||||
colors={"time": Fore.YELLOW},
|
||||
colors={"time": LogColor.YELLOW},
|
||||
)
|
||||
|
||||
result = ordered_results if ordered_results else []
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
from pydantic import BaseModel, HttpUrl, PrivateAttr
|
||||
from pydantic import BaseModel, HttpUrl, PrivateAttr, Field
|
||||
from typing import List, Dict, Optional, Callable, Awaitable, Union, Any
|
||||
from typing import AsyncGenerator
|
||||
from typing import Generic, TypeVar
|
||||
@@ -150,6 +150,7 @@ class CrawlResult(BaseModel):
|
||||
redirected_url: Optional[str] = None
|
||||
network_requests: Optional[List[Dict[str, Any]]] = None
|
||||
console_messages: Optional[List[Dict[str, Any]]] = None
|
||||
tables: List[Dict] = Field(default_factory=list) # NEW – [{headers,rows,caption,summary}]
|
||||
|
||||
class Config:
|
||||
arbitrary_types_allowed = True
|
||||
|
||||
@@ -20,7 +20,6 @@ from urllib.parse import urljoin
|
||||
import requests
|
||||
from requests.exceptions import InvalidSchema
|
||||
import xxhash
|
||||
from colorama import Fore, Style, init
|
||||
import textwrap
|
||||
import cProfile
|
||||
import pstats
|
||||
@@ -441,14 +440,13 @@ def create_box_message(
|
||||
str: A formatted string containing the styled message box.
|
||||
"""
|
||||
|
||||
init()
|
||||
|
||||
# Define border and text colors for different types
|
||||
styles = {
|
||||
"warning": (Fore.YELLOW, Fore.LIGHTYELLOW_EX, "⚠"),
|
||||
"info": (Fore.BLUE, Fore.LIGHTBLUE_EX, "ℹ"),
|
||||
"success": (Fore.GREEN, Fore.LIGHTGREEN_EX, "✓"),
|
||||
"error": (Fore.RED, Fore.LIGHTRED_EX, "×"),
|
||||
"warning": ("yellow", "bright_yellow", "⚠"),
|
||||
"info": ("blue", "bright_blue", "ℹ"),
|
||||
"debug": ("lightblack", "bright_black", "⋯"),
|
||||
"success": ("green", "bright_green", "✓"),
|
||||
"error": ("red", "bright_red", "×"),
|
||||
}
|
||||
|
||||
border_color, text_color, prefix = styles.get(type.lower(), styles["info"])
|
||||
@@ -480,12 +478,12 @@ def create_box_message(
|
||||
# Create the box with colored borders and lighter text
|
||||
horizontal_line = h_line * (width - 1)
|
||||
box = [
|
||||
f"{border_color}{tl}{horizontal_line}{tr}",
|
||||
f"[{border_color}]{tl}{horizontal_line}{tr}[/{border_color}]",
|
||||
*[
|
||||
f"{border_color}{v_line}{text_color} {line:<{width-2}}{border_color}{v_line}"
|
||||
f"[{border_color}]{v_line}[{text_color}] {line:<{width-2}}[/{text_color}][{border_color}]{v_line}[/{border_color}]"
|
||||
for line in formatted_lines
|
||||
],
|
||||
f"{border_color}{bl}{horizontal_line}{br}{Style.RESET_ALL}",
|
||||
f"[{border_color}]{bl}{horizontal_line}{br}[/{border_color}]",
|
||||
]
|
||||
|
||||
result = "\n".join(box)
|
||||
@@ -2778,4 +2776,3 @@ def preprocess_html_for_schema(html_content, text_threshold=100, attr_value_thre
|
||||
# Fallback for parsing errors
|
||||
return html_content[:max_size] if len(html_content) > max_size else html_content
|
||||
|
||||
|
||||
|
||||
@@ -58,7 +58,7 @@ Pull and run images directly from Docker Hub without building locally.
|
||||
|
||||
#### 1. Pull the Image
|
||||
|
||||
Our latest release candidate is `0.6.0rc1-r1`. Images are built with multi-arch manifests, so Docker automatically pulls the correct version for your system.
|
||||
Our latest release candidate is `0.6.0-r1`. Images are built with multi-arch manifests, so Docker automatically pulls the correct version for your system.
|
||||
|
||||
```bash
|
||||
# Pull the release candidate (recommended for latest features)
|
||||
@@ -124,9 +124,9 @@ docker stop crawl4ai && docker rm crawl4ai
|
||||
#### Docker Hub Versioning Explained
|
||||
|
||||
* **Image Name:** `unclecode/crawl4ai`
|
||||
* **Tag Format:** `LIBRARY_VERSION[-SUFFIX]` (e.g., `0.6.0rc1-r1`)
|
||||
* **Tag Format:** `LIBRARY_VERSION[-SUFFIX]` (e.g., `0.6.0-r1`)
|
||||
* `LIBRARY_VERSION`: The semantic version of the core `crawl4ai` Python library
|
||||
* `SUFFIX`: Optional tag for release candidates (`rc1`) and revisions (`r1`)
|
||||
* `SUFFIX`: Optional tag for release candidates (``) and revisions (`r1`)
|
||||
* **`latest` Tag:** Points to the most recent stable version
|
||||
* **Multi-Architecture Support:** All images support both `linux/amd64` and `linux/arm64` architectures through a single tag
|
||||
|
||||
|
||||
@@ -193,7 +193,48 @@
|
||||
<textarea id="urls" class="w-full bg-dark border border-border rounded p-2 h-32 text-sm mb-4"
|
||||
spellcheck="false">https://example.com</textarea>
|
||||
|
||||
<details class="mb-4">
|
||||
<!-- Specific options for /md endpoint -->
|
||||
<details id="md-options" class="mb-4 hidden">
|
||||
<summary class="text-sm text-secondary cursor-pointer">/md Options</summary>
|
||||
<div class="mt-2 space-y-3 p-2 border border-border rounded">
|
||||
<div>
|
||||
<label for="md-filter" class="block text-xs text-secondary mb-1">Filter Type</label>
|
||||
<select id="md-filter" class="bg-dark border border-border rounded px-2 py-1 text-sm w-full">
|
||||
<option value="fit">fit - Adaptive content filtering</option>
|
||||
<option value="raw">raw - No filtering</option>
|
||||
<option value="bm25">bm25 - BM25 keyword relevance</option>
|
||||
<option value="llm">llm - LLM-based filtering</option>
|
||||
</select>
|
||||
</div>
|
||||
<div>
|
||||
<label for="md-query" class="block text-xs text-secondary mb-1">Query (for BM25/LLM filters)</label>
|
||||
<input id="md-query" type="text" placeholder="Enter search terms or instructions"
|
||||
class="bg-dark border border-border rounded px-2 py-1 text-sm w-full">
|
||||
</div>
|
||||
<div>
|
||||
<label for="md-cache" class="block text-xs text-secondary mb-1">Cache Mode</label>
|
||||
<select id="md-cache" class="bg-dark border border-border rounded px-2 py-1 text-sm w-full">
|
||||
<option value="0">Write-Only (0)</option>
|
||||
<option value="1">Enabled (1)</option>
|
||||
</select>
|
||||
</div>
|
||||
</div>
|
||||
</details>
|
||||
|
||||
<!-- Specific options for /llm endpoint -->
|
||||
<details id="llm-options" class="mb-4 hidden">
|
||||
<summary class="text-sm text-secondary cursor-pointer">/llm Options</summary>
|
||||
<div class="mt-2 space-y-3 p-2 border border-border rounded">
|
||||
<div>
|
||||
<label for="llm-question" class="block text-xs text-secondary mb-1">Question</label>
|
||||
<input id="llm-question" type="text" value="What is this page about?"
|
||||
class="bg-dark border border-border rounded px-2 py-1 text-sm w-full">
|
||||
</div>
|
||||
</div>
|
||||
</details>
|
||||
|
||||
<!-- Advanced config for /crawl endpoints -->
|
||||
<details id="adv-config" class="mb-4">
|
||||
<summary class="text-sm text-secondary cursor-pointer">Advanced Config <span
|
||||
class="text-xs text-primary">(Python → auto‑JSON)</span></summary>
|
||||
|
||||
@@ -437,6 +478,33 @@
|
||||
cm.setValue(TEMPLATES[e.target.value]);
|
||||
document.getElementById('cfg-status').textContent = '';
|
||||
});
|
||||
|
||||
// Handle endpoint selection change to show appropriate options
|
||||
document.getElementById('endpoint').addEventListener('change', function(e) {
|
||||
const endpoint = e.target.value;
|
||||
const mdOptions = document.getElementById('md-options');
|
||||
const llmOptions = document.getElementById('llm-options');
|
||||
const advConfig = document.getElementById('adv-config');
|
||||
|
||||
// Hide all option sections first
|
||||
mdOptions.classList.add('hidden');
|
||||
llmOptions.classList.add('hidden');
|
||||
advConfig.classList.add('hidden');
|
||||
|
||||
// Show the appropriate section based on endpoint
|
||||
if (endpoint === 'md') {
|
||||
mdOptions.classList.remove('hidden');
|
||||
// Auto-open the /md options
|
||||
mdOptions.setAttribute('open', '');
|
||||
} else if (endpoint === 'llm') {
|
||||
llmOptions.classList.remove('hidden');
|
||||
// Auto-open the /llm options
|
||||
llmOptions.setAttribute('open', '');
|
||||
} else {
|
||||
// For /crawl endpoints, show the advanced config
|
||||
advConfig.classList.remove('hidden');
|
||||
}
|
||||
});
|
||||
|
||||
async function pyConfigToJson() {
|
||||
const code = cm.getValue().trim();
|
||||
@@ -494,10 +562,18 @@
|
||||
}
|
||||
|
||||
// Generate code snippets
|
||||
function generateSnippets(api, payload) {
|
||||
function generateSnippets(api, payload, method = 'POST') {
|
||||
// Python snippet
|
||||
const pyCodeEl = document.querySelector('#python-content code');
|
||||
const pySnippet = `import httpx\n\nasync def crawl():\n async with httpx.AsyncClient() as client:\n response = await client.post(\n "${window.location.origin}${api}",\n json=${JSON.stringify(payload, null, 4).replace(/\n/g, '\n ')}\n )\n return response.json()`;
|
||||
let pySnippet;
|
||||
|
||||
if (method === 'GET') {
|
||||
// GET request (for /llm endpoint)
|
||||
pySnippet = `import httpx\n\nasync def crawl():\n async with httpx.AsyncClient() as client:\n response = await client.get(\n "${window.location.origin}${api}"\n )\n return response.json()`;
|
||||
} else {
|
||||
// POST request (for /crawl and /md endpoints)
|
||||
pySnippet = `import httpx\n\nasync def crawl():\n async with httpx.AsyncClient() as client:\n response = await client.post(\n "${window.location.origin}${api}",\n json=${JSON.stringify(payload, null, 4).replace(/\n/g, '\n ')}\n )\n return response.json()`;
|
||||
}
|
||||
|
||||
pyCodeEl.textContent = pySnippet;
|
||||
pyCodeEl.className = 'python hljs'; // Reset classes
|
||||
@@ -505,7 +581,15 @@
|
||||
|
||||
// cURL snippet
|
||||
const curlCodeEl = document.querySelector('#curl-content code');
|
||||
const curlSnippet = `curl -X POST ${window.location.origin}${api} \\\n -H "Content-Type: application/json" \\\n -d '${JSON.stringify(payload)}'`;
|
||||
let curlSnippet;
|
||||
|
||||
if (method === 'GET') {
|
||||
// GET request (for /llm endpoint)
|
||||
curlSnippet = `curl -X GET "${window.location.origin}${api}"`;
|
||||
} else {
|
||||
// POST request (for /crawl and /md endpoints)
|
||||
curlSnippet = `curl -X POST ${window.location.origin}${api} \\\n -H "Content-Type: application/json" \\\n -d '${JSON.stringify(payload)}'`;
|
||||
}
|
||||
|
||||
curlCodeEl.textContent = curlSnippet;
|
||||
curlCodeEl.className = 'bash hljs'; // Reset classes
|
||||
@@ -536,20 +620,39 @@
|
||||
|
||||
const endpointMap = {
|
||||
crawl: '/crawl',
|
||||
};
|
||||
|
||||
/*const endpointMap = {
|
||||
crawl: '/crawl',
|
||||
crawl_stream: '/crawl/stream',
|
||||
// crawl_stream: '/crawl/stream',
|
||||
md: '/md',
|
||||
llm: '/llm'
|
||||
};*/
|
||||
};
|
||||
|
||||
const api = endpointMap[endpoint];
|
||||
const payload = {
|
||||
urls,
|
||||
...advConfig
|
||||
};
|
||||
let payload;
|
||||
|
||||
// Create appropriate payload based on endpoint type
|
||||
if (endpoint === 'md') {
|
||||
// Get values from the /md specific inputs
|
||||
const filterType = document.getElementById('md-filter').value;
|
||||
const query = document.getElementById('md-query').value.trim();
|
||||
const cache = document.getElementById('md-cache').value;
|
||||
|
||||
// MD endpoint expects: { url, f, q, c }
|
||||
payload = {
|
||||
url: urls[0], // Take first URL
|
||||
f: filterType, // Lowercase filter type as required by server
|
||||
q: query || null, // Use the query if provided, otherwise null
|
||||
c: cache
|
||||
};
|
||||
} else if (endpoint === 'llm') {
|
||||
// LLM endpoint has a different URL pattern and uses query params
|
||||
// This will be handled directly in the fetch below
|
||||
payload = null;
|
||||
} else {
|
||||
// Default payload for /crawl and /crawl/stream
|
||||
payload = {
|
||||
urls,
|
||||
...advConfig
|
||||
};
|
||||
}
|
||||
|
||||
updateStatus('processing');
|
||||
|
||||
@@ -557,7 +660,18 @@
|
||||
const startTime = performance.now();
|
||||
let response, responseData;
|
||||
|
||||
if (endpoint === 'crawl_stream') {
|
||||
if (endpoint === 'llm') {
|
||||
// Special handling for LLM endpoint which uses URL pattern: /llm/{encoded_url}?q={query}
|
||||
const url = urls[0];
|
||||
const encodedUrl = encodeURIComponent(url);
|
||||
// Get the question from the LLM-specific input
|
||||
const question = document.getElementById('llm-question').value.trim() || "What is this page about?";
|
||||
|
||||
response = await fetch(`${api}/${encodedUrl}?q=${encodeURIComponent(question)}`, {
|
||||
method: 'GET',
|
||||
headers: { 'Accept': 'application/json' }
|
||||
});
|
||||
} else if (endpoint === 'crawl_stream') {
|
||||
// Stream processing
|
||||
response = await fetch(api, {
|
||||
method: 'POST',
|
||||
@@ -597,7 +711,7 @@
|
||||
document.querySelector('#response-content code').className = 'json hljs'; // Reset classes
|
||||
forceHighlightElement(document.querySelector('#response-content code'));
|
||||
} else {
|
||||
// Regular request
|
||||
// Regular request (handles /crawl and /md)
|
||||
response = await fetch(api, {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
@@ -625,7 +739,16 @@
|
||||
}
|
||||
|
||||
forceHighlightElement(document.querySelector('#response-content code'));
|
||||
generateSnippets(api, payload);
|
||||
|
||||
// For generateSnippets, handle the LLM case specially
|
||||
if (endpoint === 'llm') {
|
||||
const url = urls[0];
|
||||
const encodedUrl = encodeURIComponent(url);
|
||||
const question = document.getElementById('llm-question').value.trim() || "What is this page about?";
|
||||
generateSnippets(`${api}/${encodedUrl}?q=${encodeURIComponent(question)}`, null, 'GET');
|
||||
} else {
|
||||
generateSnippets(api, payload);
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Error:', error);
|
||||
updateStatus('error');
|
||||
@@ -807,9 +930,24 @@
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
// Function to initialize UI based on selected endpoint
|
||||
function initUI() {
|
||||
// Trigger the endpoint change handler to set initial UI state
|
||||
const endpointSelect = document.getElementById('endpoint');
|
||||
const event = new Event('change');
|
||||
endpointSelect.dispatchEvent(event);
|
||||
|
||||
// Initialize copy buttons
|
||||
initCopyButtons();
|
||||
}
|
||||
|
||||
// Call this in your DOMContentLoaded or initialization
|
||||
initCopyButtons();
|
||||
// Initialize on page load
|
||||
document.addEventListener('DOMContentLoaded', initUI);
|
||||
// Also call it immediately in case the script runs after DOM is already loaded
|
||||
if (document.readyState !== 'loading') {
|
||||
initUI();
|
||||
}
|
||||
|
||||
</script>
|
||||
</body>
|
||||
|
||||
126
docs/apps/linkdin/README.md
Normal file
126
docs/apps/linkdin/README.md
Normal file
@@ -0,0 +1,126 @@
|
||||
# Crawl4AI Prospect‑Wizard – step‑by‑step guide
|
||||
|
||||
A three‑stage demo that goes from **LinkedIn scraping** ➜ **LLM reasoning** ➜ **graph visualisation**.
|
||||
|
||||
```
|
||||
prospect‑wizard/
|
||||
├─ c4ai_discover.py # Stage 1 – scrape companies + people
|
||||
├─ c4ai_insights.py # Stage 2 – embeddings, org‑charts, scores
|
||||
├─ graph_view_template.html # Stage 3 – graph viewer (static HTML)
|
||||
└─ data/ # output lands here (*.jsonl / *.json)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 1 Install & boot a LinkedIn profile (one‑time)
|
||||
|
||||
### 1.1 Install dependencies
|
||||
```bash
|
||||
pip install crawl4ai openai sentence-transformers networkx pandas vis-network rich
|
||||
```
|
||||
|
||||
### 1.2 Create / warm a LinkedIn browser profile
|
||||
```bash
|
||||
crwl profiler
|
||||
```
|
||||
1. The interactive shell shows **New profile** – hit **enter**.
|
||||
2. Choose a name, e.g. `profile_linkedin_uc`.
|
||||
3. A Chromium window opens – log in to LinkedIn, solve whatever CAPTCHA, then close.
|
||||
|
||||
> Remember the **profile name**. All future runs take `--profile-name <your_name>`.
|
||||
|
||||
---
|
||||
|
||||
## 2 Discovery – scrape companies & people
|
||||
|
||||
```bash
|
||||
python c4ai_discover.py full \
|
||||
--query "health insurance management" \
|
||||
--geo 102713980 \ # Malaysia geoUrn
|
||||
--title_filters "" \ # or "Product,Engineering"
|
||||
--max_companies 10 \ # default set small for workshops
|
||||
--max_people 20 \ # \^ same
|
||||
--profile-name profile_linkedin_uc \
|
||||
--outdir ./data \
|
||||
--concurrency 2 \
|
||||
--log_level debug
|
||||
```
|
||||
**Outputs** in `./data/`:
|
||||
* `companies.jsonl` – one JSON per company
|
||||
* `people.jsonl` – one JSON per employee
|
||||
|
||||
🛠️ **Dry‑run:** `C4AI_DEMO_DEBUG=1 python c4ai_discover.py full --query coffee` uses bundled HTML snippets, no network.
|
||||
|
||||
### Handy geoUrn cheatsheet
|
||||
| Location | geoUrn |
|
||||
|----------|--------|
|
||||
| Singapore | **103644278** |
|
||||
| Malaysia | **102713980** |
|
||||
| United States | **103644922** |
|
||||
| United Kingdom | **102221843** |
|
||||
| Australia | **101452733** |
|
||||
_See more: <https://www.linkedin.com/search/results/companies/?geoUrn=XXX> – the number after `geoUrn=` is what you need._
|
||||
|
||||
---
|
||||
|
||||
## 3 Insights – embeddings, org‑charts, decision makers
|
||||
|
||||
```bash
|
||||
python c4ai_insights.py \
|
||||
--in ./data \
|
||||
--out ./data \
|
||||
--embed_model all-MiniLM-L6-v2 \
|
||||
--top_k 10 \
|
||||
--openai_model gpt-4.1 \
|
||||
--max_llm_tokens 8024 \
|
||||
--llm_temperature 1.0 \
|
||||
--workers 4
|
||||
```
|
||||
Emits next to the Stage‑1 files:
|
||||
* `company_graph.json` – inter‑company similarity graph
|
||||
* `org_chart_<handle>.json` – one per company
|
||||
* `decision_makers.csv` – hand‑picked ‘who to pitch’ list
|
||||
|
||||
Flags reference (straight from `build_arg_parser()`):
|
||||
| Flag | Default | Purpose |
|
||||
|------|---------|---------|
|
||||
| `--in` | `.` | Stage‑1 output dir |
|
||||
| `--out` | `.` | Destination dir |
|
||||
| `--embed_model` | `all-MiniLM-L6-v2` | Sentence‑Transformer model |
|
||||
| `--top_k` | `10` | Neighbours per company in graph |
|
||||
| `--openai_model` | `gpt-4.1` | LLM for scoring decision makers |
|
||||
| `--max_llm_tokens` | `8024` | Token budget per LLM call |
|
||||
| `--llm_temperature` | `1.0` | Creativity knob |
|
||||
| `--stub` | off | Skip OpenAI and fabricate tiny charts |
|
||||
| `--workers` | `4` | Parallel LLM workers |
|
||||
|
||||
---
|
||||
|
||||
## 4 Visualise – interactive graph
|
||||
|
||||
After Stage 2 completes, simply open the HTML viewer from the project root:
|
||||
```bash
|
||||
open graph_view_template.html # or Live Server / Python -http
|
||||
```
|
||||
The page fetches `data/company_graph.json` and the `org_chart_*.json` files automatically; keep the `data/` folder beside the HTML file.
|
||||
|
||||
* Left pane → list of companies (clans).
|
||||
* Click a node to load its org‑chart on the right.
|
||||
* Chat drawer lets you ask follow‑up questions; context is pulled from `people.jsonl`.
|
||||
|
||||
---
|
||||
|
||||
## 5 Common snags
|
||||
|
||||
| Symptom | Fix |
|
||||
|---------|-----|
|
||||
| Infinite CAPTCHA | Use a residential proxy: `--proxy http://user:pass@ip:port` |
|
||||
| 429 Too Many Requests | Lower `--concurrency`, rotate profile, add delay |
|
||||
| Blank graph | Check JSON paths, clear `localStorage` in browser |
|
||||
|
||||
---
|
||||
|
||||
### TL;DR
|
||||
`crwl profiler` → `c4ai_discover.py` → `c4ai_insights.py` → open `graph_view_template.html`.
|
||||
Live long and `import crawl4ai`.
|
||||
|
||||
440
docs/apps/linkdin/c4ai_discover.py
Normal file
440
docs/apps/linkdin/c4ai_discover.py
Normal file
@@ -0,0 +1,440 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
c4ai-discover — Stage‑1 Discovery CLI
|
||||
|
||||
Scrapes LinkedIn company search + their people pages and dumps two newline‑delimited
|
||||
JSON files: companies.jsonl and people.jsonl.
|
||||
|
||||
Key design rules
|
||||
----------------
|
||||
* No BeautifulSoup — Crawl4AI only for network + HTML fetch.
|
||||
* JsonCssExtractionStrategy for structured scraping; schema auto‑generated once
|
||||
from sample HTML provided by user and then cached under ./schemas/.
|
||||
* Defaults are embedded so the file runs inside VS Code debugger without CLI args.
|
||||
* If executed as a console script (argv > 1), CLI flags win.
|
||||
* Lightweight deps: argparse + Crawl4AI stack.
|
||||
|
||||
Author: Tom @ Kidocode 2025‑04‑26
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import warnings, re
|
||||
warnings.filterwarnings(
|
||||
"ignore",
|
||||
message=r"The pseudo class ':contains' is deprecated, ':-soup-contains' should be used.*",
|
||||
category=FutureWarning,
|
||||
module=r"soupsieve"
|
||||
)
|
||||
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# Imports
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
import argparse
|
||||
import random
|
||||
import asyncio
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import pathlib
|
||||
import sys
|
||||
# 3rd-party rich for pretty logging
|
||||
from rich.console import Console
|
||||
from rich.logging import RichHandler
|
||||
|
||||
from datetime import datetime, UTC
|
||||
from itertools import cycle
|
||||
from textwrap import dedent
|
||||
from types import SimpleNamespace
|
||||
from typing import Dict, List, Optional
|
||||
from urllib.parse import quote
|
||||
from pathlib import Path
|
||||
from glob import glob
|
||||
|
||||
from crawl4ai import (
|
||||
AsyncWebCrawler,
|
||||
BrowserConfig,
|
||||
CacheMode,
|
||||
CrawlerRunConfig,
|
||||
JsonCssExtractionStrategy,
|
||||
BrowserProfiler,
|
||||
LLMConfig,
|
||||
)
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# Constants / paths
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
BASE_DIR = pathlib.Path(__file__).resolve().parent
|
||||
SCHEMA_DIR = BASE_DIR / "schemas"
|
||||
SCHEMA_DIR.mkdir(parents=True, exist_ok=True)
|
||||
COMPANY_SCHEMA_PATH = SCHEMA_DIR / "company_card.json"
|
||||
PEOPLE_SCHEMA_PATH = SCHEMA_DIR / "people_card.json"
|
||||
|
||||
# ---------- deterministic target JSON examples ----------
|
||||
_COMPANY_SCHEMA_EXAMPLE = {
|
||||
"handle": "/company/posify/",
|
||||
"profile_image": "https://media.licdn.com/dms/image/v2/.../logo.jpg",
|
||||
"name": "Management Research Services, Inc. (MRS, Inc)",
|
||||
"descriptor": "Insurance • Milwaukee, Wisconsin",
|
||||
"about": "Insurance • Milwaukee, Wisconsin",
|
||||
"followers": 1000
|
||||
}
|
||||
|
||||
_PEOPLE_SCHEMA_EXAMPLE = {
|
||||
"profile_url": "https://www.linkedin.com/in/lily-ng/",
|
||||
"name": "Lily Ng",
|
||||
"headline": "VP Product @ Posify",
|
||||
"followers": 890,
|
||||
"connection_degree": "2nd",
|
||||
"avatar_url": "https://media.licdn.com/dms/image/v2/.../lily.jpg"
|
||||
}
|
||||
|
||||
# Provided sample HTML snippets (trimmed) — used exactly once to cold‑generate schema.
|
||||
_SAMPLE_COMPANY_HTML = (Path(__file__).resolve().parent / "snippets/company.html").read_text()
|
||||
_SAMPLE_PEOPLE_HTML = (Path(__file__).resolve().parent / "snippets/people.html").read_text()
|
||||
|
||||
# --------- tighter schema prompts ----------
|
||||
_COMPANY_SCHEMA_QUERY = dedent(
|
||||
"""
|
||||
Using the supplied <li> company-card HTML, build a JsonCssExtractionStrategy schema that,
|
||||
for every card, outputs *exactly* the keys shown in the example JSON below.
|
||||
JSON spec:
|
||||
• handle – href of the outermost <a> that wraps the logo/title, e.g. "/company/posify/"
|
||||
• profile_image – absolute URL of the <img> inside that link
|
||||
• name – text of the <a> inside the <span class*='t-16'>
|
||||
• descriptor – text line with industry • location
|
||||
• about – text of the <div class*='t-normal'> below the name (industry + geo)
|
||||
• followers – integer parsed from the <div> containing 'followers'
|
||||
|
||||
IMPORTANT: Do not use the base64 kind of classes to target element. It's not reliable.
|
||||
The main div parent contains these li element is "div.search-results-container" you can use this.
|
||||
The <ul> parent has "role" equal to "list". Using these two should be enough to target the <li> elements."
|
||||
"""
|
||||
)
|
||||
|
||||
_PEOPLE_SCHEMA_QUERY = dedent(
|
||||
"""
|
||||
Using the supplied <li> people-card HTML, build a JsonCssExtractionStrategy schema that
|
||||
outputs exactly the keys in the example JSON below.
|
||||
Fields:
|
||||
• profile_url – href of the outermost profile link
|
||||
• name – text inside artdeco-entity-lockup__title
|
||||
• headline – inner text of artdeco-entity-lockup__subtitle
|
||||
• followers – integer parsed from the span inside lt-line-clamp--multi-line
|
||||
• connection_degree – '1st', '2nd', etc. from artdeco-entity-lockup__badge
|
||||
• avatar_url – src of the <img> within artdeco-entity-lockup__image
|
||||
|
||||
IMPORTANT: Do not use the base64 kind of classes to target element. It's not reliable.
|
||||
The main div parent contains these li element is a "div" has these classes "artdeco-card org-people-profile-card__card-spacing org-people__card-margin-bottom".
|
||||
"""
|
||||
)
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Utility helpers
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def _load_or_build_schema(
|
||||
path: pathlib.Path,
|
||||
sample_html: str,
|
||||
query: str,
|
||||
example_json: Dict,
|
||||
force = False
|
||||
) -> Dict:
|
||||
"""Load schema from path, else call generate_schema once and persist."""
|
||||
if path.exists() and not force:
|
||||
return json.loads(path.read_text())
|
||||
|
||||
logging.info("[SCHEMA] Generating schema %s", path.name)
|
||||
schema = JsonCssExtractionStrategy.generate_schema(
|
||||
html=sample_html,
|
||||
llm_config=LLMConfig(
|
||||
provider=os.getenv("C4AI_SCHEMA_PROVIDER", "openai/gpt-4o"),
|
||||
api_token=os.getenv("OPENAI_API_KEY", "env:OPENAI_API_KEY"),
|
||||
),
|
||||
query=query,
|
||||
target_json_example=json.dumps(example_json, indent=2),
|
||||
)
|
||||
path.write_text(json.dumps(schema, indent=2))
|
||||
return schema
|
||||
|
||||
|
||||
def _openai_friendly_number(text: str) -> Optional[int]:
|
||||
"""Extract first int from text like '1K followers' (returns 1000)."""
|
||||
import re
|
||||
|
||||
m = re.search(r"(\d[\d,]*)", text.replace(",", ""))
|
||||
if not m:
|
||||
return None
|
||||
val = int(m.group(1))
|
||||
if "k" in text.lower():
|
||||
val *= 1000
|
||||
if "m" in text.lower():
|
||||
val *= 1_000_000
|
||||
return val
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Core async workers
|
||||
# ---------------------------------------------------------------------------
|
||||
async def crawl_company_search(crawler: AsyncWebCrawler, url: str, schema: Dict, limit: int) -> List[Dict]:
|
||||
"""Paginate 10-item company search pages until `limit` reached."""
|
||||
extraction = JsonCssExtractionStrategy(schema)
|
||||
cfg = CrawlerRunConfig(
|
||||
extraction_strategy=extraction,
|
||||
cache_mode=CacheMode.BYPASS,
|
||||
wait_for = ".search-marvel-srp",
|
||||
session_id="company_search",
|
||||
delay_before_return_html=1,
|
||||
magic = True,
|
||||
verbose= False,
|
||||
)
|
||||
companies, page = [], 1
|
||||
while len(companies) < max(limit, 10):
|
||||
paged_url = f"{url}&page={page}"
|
||||
res = await crawler.arun(paged_url, config=cfg)
|
||||
batch = json.loads(res[0].extracted_content)
|
||||
if not batch:
|
||||
break
|
||||
for item in batch:
|
||||
name = item.get("name", "").strip()
|
||||
handle = item.get("handle", "").strip()
|
||||
if not handle or not name:
|
||||
continue
|
||||
descriptor = item.get("descriptor")
|
||||
about = item.get("about")
|
||||
followers = _openai_friendly_number(str(item.get("followers", "")))
|
||||
companies.append(
|
||||
{
|
||||
"handle": handle,
|
||||
"name": name,
|
||||
"descriptor": descriptor,
|
||||
"about": about,
|
||||
"followers": followers,
|
||||
"people_url": f"{handle}people/",
|
||||
"captured_at": datetime.now(UTC).isoformat(timespec="seconds") + "Z",
|
||||
}
|
||||
)
|
||||
page += 1
|
||||
logging.info(
|
||||
f"[dim]Page {page}[/] — running total: {len(companies)}/{limit} companies"
|
||||
)
|
||||
|
||||
return companies[:max(limit, 10)]
|
||||
|
||||
|
||||
async def crawl_people_page(
|
||||
crawler: AsyncWebCrawler,
|
||||
people_url: str,
|
||||
schema: Dict,
|
||||
limit: int,
|
||||
title_kw: str,
|
||||
) -> List[Dict]:
|
||||
people_u = f"{people_url}?keywords={quote(title_kw)}"
|
||||
extraction = JsonCssExtractionStrategy(schema)
|
||||
cfg = CrawlerRunConfig(
|
||||
extraction_strategy=extraction,
|
||||
# scan_full_page=True,
|
||||
cache_mode=CacheMode.BYPASS,
|
||||
magic=True,
|
||||
wait_for=".org-people-profile-card__card-spacing",
|
||||
delay_before_return_html=1,
|
||||
session_id="people_search",
|
||||
)
|
||||
res = await crawler.arun(people_u, config=cfg)
|
||||
if not res[0].success:
|
||||
return []
|
||||
raw = json.loads(res[0].extracted_content)
|
||||
people = []
|
||||
for p in raw[:limit]:
|
||||
followers = _openai_friendly_number(str(p.get("followers", "")))
|
||||
people.append(
|
||||
{
|
||||
"profile_url": p.get("profile_url"),
|
||||
"name": p.get("name"),
|
||||
"headline": p.get("headline"),
|
||||
"followers": followers,
|
||||
"connection_degree": p.get("connection_degree"),
|
||||
"avatar_url": p.get("avatar_url"),
|
||||
}
|
||||
)
|
||||
return people
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# CLI + main
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def build_arg_parser() -> argparse.ArgumentParser:
|
||||
ap = argparse.ArgumentParser("c4ai-discover — Crawl4AI LinkedIn discovery")
|
||||
sub = ap.add_subparsers(dest="cmd", required=False, help="run scope")
|
||||
|
||||
def add_flags(parser: argparse.ArgumentParser):
|
||||
parser.add_argument("--query", required=False, help="query keyword(s)")
|
||||
parser.add_argument("--geo", required=False, type=int, help="LinkedIn geoUrn")
|
||||
parser.add_argument("--title-filters", default="Product,Engineering", help="comma list of job keywords")
|
||||
parser.add_argument("--max-companies", type=int, default=1000)
|
||||
parser.add_argument("--max-people", type=int, default=500)
|
||||
parser.add_argument("--profile-path", default=str(pathlib.Path.home() / ".crawl4ai/profiles/profile_linkedin_uc"))
|
||||
parser.add_argument("--outdir", default="./output")
|
||||
parser.add_argument("--concurrency", type=int, default=4)
|
||||
parser.add_argument("--log-level", default="info", choices=["debug", "info", "warn", "error"])
|
||||
|
||||
add_flags(sub.add_parser("full"))
|
||||
add_flags(sub.add_parser("companies"))
|
||||
add_flags(sub.add_parser("people"))
|
||||
|
||||
# global flags
|
||||
ap.add_argument(
|
||||
"--debug",
|
||||
action="store_true",
|
||||
help="Use built-in demo defaults (same as C4AI_DEMO_DEBUG=1)",
|
||||
)
|
||||
return ap
|
||||
|
||||
|
||||
def detect_debug_defaults(force = False) -> SimpleNamespace:
|
||||
if not force and sys.gettrace() is None and not os.getenv("C4AI_DEMO_DEBUG"):
|
||||
return SimpleNamespace()
|
||||
# ----- debug‑friendly defaults -----
|
||||
return SimpleNamespace(
|
||||
cmd="full",
|
||||
query="health insurance management",
|
||||
geo=102713980,
|
||||
# title_filters="Product,Engineering",
|
||||
title_filters="",
|
||||
max_companies=10,
|
||||
max_people=5,
|
||||
profile_name="profile_linkedin_uc",
|
||||
outdir="./debug_out",
|
||||
concurrency=2,
|
||||
log_level="debug",
|
||||
)
|
||||
|
||||
|
||||
async def async_main(opts):
|
||||
# ─────────── logging setup ───────────
|
||||
console = Console()
|
||||
logging.basicConfig(
|
||||
level=opts.log_level.upper(),
|
||||
format="%(message)s",
|
||||
handlers=[RichHandler(console=console, markup=True, rich_tracebacks=True)],
|
||||
)
|
||||
|
||||
# -------------------------------------------------------------------
|
||||
# Load or build schemas (one‑time LLM call each)
|
||||
# -------------------------------------------------------------------
|
||||
company_schema = _load_or_build_schema(
|
||||
COMPANY_SCHEMA_PATH,
|
||||
_SAMPLE_COMPANY_HTML,
|
||||
_COMPANY_SCHEMA_QUERY,
|
||||
_COMPANY_SCHEMA_EXAMPLE,
|
||||
# True
|
||||
)
|
||||
people_schema = _load_or_build_schema(
|
||||
PEOPLE_SCHEMA_PATH,
|
||||
_SAMPLE_PEOPLE_HTML,
|
||||
_PEOPLE_SCHEMA_QUERY,
|
||||
_PEOPLE_SCHEMA_EXAMPLE,
|
||||
# True
|
||||
)
|
||||
|
||||
outdir = BASE_DIR / pathlib.Path(opts.outdir)
|
||||
outdir.mkdir(parents=True, exist_ok=True)
|
||||
f_companies = (BASE_DIR / outdir / "companies.jsonl").open("a", encoding="utf-8")
|
||||
f_people = (BASE_DIR / outdir / "people.jsonl").open("a", encoding="utf-8")
|
||||
|
||||
# -------------------------------------------------------------------
|
||||
# Prepare crawler with cookie pool rotation
|
||||
# -------------------------------------------------------------------
|
||||
profiler = BrowserProfiler()
|
||||
path = profiler.get_profile_path(opts.profile_name)
|
||||
bc = BrowserConfig(
|
||||
headless=False,
|
||||
verbose=False,
|
||||
user_data_dir=path,
|
||||
use_managed_browser=True,
|
||||
user_agent_mode = "random",
|
||||
user_agent_generator_config= {
|
||||
"platforms": "mobile",
|
||||
"os": "Android"
|
||||
},
|
||||
verbose=False,
|
||||
)
|
||||
crawler = AsyncWebCrawler(config=bc)
|
||||
|
||||
await crawler.start()
|
||||
|
||||
# Single worker for simplicity; concurrency can be scaled by arun_many if needed.
|
||||
# crawler = await next_crawler().start()
|
||||
try:
|
||||
# Build LinkedIn search URL
|
||||
search_url = f"https://www.linkedin.com/search/results/companies/?keywords={quote(opts.query)}&geoUrn={opts.geo}"
|
||||
logging.info("Seed URL => %s", search_url)
|
||||
|
||||
companies: List[Dict] = []
|
||||
if opts.cmd in ("companies", "full"):
|
||||
companies = await crawl_company_search(
|
||||
crawler, search_url, company_schema, opts.max_companies
|
||||
)
|
||||
for c in companies:
|
||||
f_companies.write(json.dumps(c, ensure_ascii=False) + "\n")
|
||||
logging.info(f"[bold green]✓[/] Companies scraped so far: {len(companies)}")
|
||||
|
||||
if opts.cmd in ("people", "full"):
|
||||
if not companies:
|
||||
# load from previous run
|
||||
src = outdir / "companies.jsonl"
|
||||
if not src.exists():
|
||||
logging.error("companies.jsonl missing — run companies/full first")
|
||||
return 10
|
||||
companies = [json.loads(l) for l in src.read_text().splitlines()]
|
||||
total_people = 0
|
||||
title_kw = " ".join([t.strip() for t in opts.title_filters.split(",") if t.strip()]) if opts.title_filters else ""
|
||||
for comp in companies:
|
||||
people = await crawl_people_page(
|
||||
crawler,
|
||||
comp["people_url"],
|
||||
people_schema,
|
||||
opts.max_people,
|
||||
title_kw,
|
||||
)
|
||||
for p in people:
|
||||
rec = p | {
|
||||
"company_handle": comp["handle"],
|
||||
# "captured_at": datetime.now(UTC).isoformat(timespec="seconds") + "Z",
|
||||
"captured_at": datetime.now(UTC).isoformat(timespec="seconds") + "Z",
|
||||
}
|
||||
f_people.write(json.dumps(rec, ensure_ascii=False) + "\n")
|
||||
total_people += len(people)
|
||||
logging.info(
|
||||
f"{comp['name']} — [cyan]{len(people)}[/] people extracted"
|
||||
)
|
||||
await asyncio.sleep(random.uniform(0.5, 1))
|
||||
logging.info("Total people scraped: %d", total_people)
|
||||
finally:
|
||||
await crawler.close()
|
||||
f_companies.close()
|
||||
f_people.close()
|
||||
|
||||
return 0
|
||||
|
||||
|
||||
def main():
|
||||
parser = build_arg_parser()
|
||||
cli_opts = parser.parse_args()
|
||||
|
||||
# decide on debug defaults
|
||||
if cli_opts.debug:
|
||||
opts = detect_debug_defaults(force=True)
|
||||
else:
|
||||
env_defaults = detect_debug_defaults()
|
||||
env_defaults = detect_debug_defaults()
|
||||
opts = env_defaults if env_defaults else cli_opts
|
||||
|
||||
if not getattr(opts, "cmd", None):
|
||||
opts.cmd = "full"
|
||||
|
||||
exit_code = asyncio.run(async_main(opts))
|
||||
sys.exit(exit_code)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
372
docs/apps/linkdin/c4ai_insights.py
Normal file
372
docs/apps/linkdin/c4ai_insights.py
Normal file
@@ -0,0 +1,372 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Stage-2 Insights builder
|
||||
------------------------
|
||||
Reads companies.jsonl & people.jsonl (Stage-1 output) and produces:
|
||||
• company_graph.json
|
||||
• org_chart_<handle>.json (one per company)
|
||||
• decision_makers.csv
|
||||
• graph_view.html (interactive visualisation)
|
||||
|
||||
Run:
|
||||
python c4ai_insights.py --in ./stage1_out --out ./stage2_out
|
||||
|
||||
Author : Tom @ Kidocode, 2025-04-28
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# Imports & Third-party
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
|
||||
import argparse, asyncio, json, os, sys, pathlib, random, time, csv
|
||||
from datetime import datetime, UTC
|
||||
from types import SimpleNamespace
|
||||
from pathlib import Path
|
||||
from typing import List, Dict, Any
|
||||
# Pretty CLI UX
|
||||
from rich.console import Console
|
||||
from rich.logging import RichHandler
|
||||
from rich.progress import Progress, SpinnerColumn, BarColumn, TextColumn, TimeElapsedColumn
|
||||
import logging
|
||||
from jinja2 import Environment, FileSystemLoader, select_autoescape
|
||||
|
||||
BASE_DIR = pathlib.Path(__file__).resolve().parent
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# 3rd-party deps
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
import numpy as np
|
||||
# from sentence_transformers import SentenceTransformer
|
||||
# from sklearn.metrics.pairwise import cosine_similarity
|
||||
import pandas as pd
|
||||
import hashlib
|
||||
|
||||
from openai import OpenAI # same SDK you pre-loaded
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# Utils
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
def load_jsonl(path: Path) -> List[Dict[str, Any]]:
|
||||
with open(path, "r", encoding="utf-8") as f:
|
||||
return [json.loads(l) for l in f]
|
||||
|
||||
def dump_json(obj, path: Path):
|
||||
with open(path, "w", encoding="utf-8") as f:
|
||||
json.dump(obj, f, ensure_ascii=False, indent=2)
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# Constants
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
BASE_DIR = pathlib.Path(__file__).resolve().parent
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# Debug defaults (mirrors Stage-1 trick)
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
def dev_defaults() -> SimpleNamespace:
|
||||
return SimpleNamespace(
|
||||
in_dir="./debug_out",
|
||||
out_dir="./insights_debug",
|
||||
embed_model="all-MiniLM-L6-v2",
|
||||
top_k=10,
|
||||
openai_model="gpt-4.1",
|
||||
max_llm_tokens=8000,
|
||||
llm_temperature=1.0,
|
||||
workers=4, # parallel processing
|
||||
stub=False, # manual
|
||||
)
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# Graph builders
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
def embed_descriptions(companies, model_name:str, opts) -> np.ndarray:
|
||||
from sentence_transformers import SentenceTransformer
|
||||
|
||||
logging.debug(f"Using embedding model: {model_name}")
|
||||
cache_path = BASE_DIR / Path(opts.out_dir) / "embeds_cache.json"
|
||||
cache = {}
|
||||
if cache_path.exists():
|
||||
with open(cache_path) as f:
|
||||
cache = json.load(f)
|
||||
# flush cache if model differs
|
||||
if cache.get("_model") != model_name:
|
||||
cache = {}
|
||||
|
||||
model = SentenceTransformer(model_name)
|
||||
new_texts, new_indices = [], []
|
||||
vectors = np.zeros((len(companies), 384), dtype=np.float32)
|
||||
|
||||
for idx, comp in enumerate(companies):
|
||||
text = comp.get("about") or comp.get("descriptor","")
|
||||
h = hashlib.sha1(text.encode("utf-8")).hexdigest()
|
||||
cached = cache.get(comp["handle"])
|
||||
if cached and cached["hash"] == h:
|
||||
vectors[idx] = np.array(cached["vector"], dtype=np.float32)
|
||||
else:
|
||||
new_texts.append(text)
|
||||
new_indices.append((idx, comp["handle"], h))
|
||||
|
||||
if new_texts:
|
||||
embeds = model.encode(new_texts, show_progress_bar=False, convert_to_numpy=True)
|
||||
for vec, (idx, handle, h) in zip(embeds, new_indices):
|
||||
vectors[idx] = vec
|
||||
cache[handle] = {"hash": h, "vector": vec.tolist()}
|
||||
cache["_model"] = model_name
|
||||
with open(cache_path, "w") as f:
|
||||
json.dump(cache, f)
|
||||
|
||||
return vectors
|
||||
|
||||
def build_company_graph(companies, embeds:np.ndarray, top_k:int) -> Dict[str,Any]:
|
||||
from sklearn.metrics.pairwise import cosine_similarity
|
||||
sims = cosine_similarity(embeds)
|
||||
nodes, edges = [], []
|
||||
idx_of = {c["handle"]: i for i,c in enumerate(companies)}
|
||||
for i,c in enumerate(companies):
|
||||
node = dict(
|
||||
id=c["handle"].strip("/"),
|
||||
name=c["name"],
|
||||
handle=c["handle"],
|
||||
about=c.get("about",""),
|
||||
people_url=c.get("people_url",""),
|
||||
industry=c.get("descriptor","").split("•")[0].strip(),
|
||||
geoUrn=c.get("geoUrn"),
|
||||
followers=c.get("followers",0),
|
||||
# desc_embed=embeds[i].tolist(),
|
||||
desc_embed=[],
|
||||
)
|
||||
nodes.append(node)
|
||||
# pick top-k most similar except itself
|
||||
top_idx = np.argsort(sims[i])[::-1][1:top_k+1]
|
||||
for j in top_idx:
|
||||
tgt = companies[j]
|
||||
weight = float(sims[i,j])
|
||||
if node["industry"] == tgt.get("descriptor","").split("•")[0].strip():
|
||||
weight += 0.10
|
||||
if node["geoUrn"] == tgt.get("geoUrn"):
|
||||
weight += 0.05
|
||||
tgt['followers'] = tgt.get("followers", None) or 1
|
||||
node["followers"] = node.get("followers", None) or 1
|
||||
follower_ratio = min(node["followers"], tgt.get("followers",1)) / max(node["followers"] or 1, tgt.get("followers",1))
|
||||
weight += 0.05 * follower_ratio
|
||||
edges.append(dict(
|
||||
source=node["id"],
|
||||
target=tgt["handle"].strip("/"),
|
||||
weight=round(weight,4),
|
||||
drivers=dict(
|
||||
embed_sim=round(float(sims[i,j]),4),
|
||||
industry_match=0.10 if node["industry"] == tgt.get("descriptor","").split("•")[0].strip() else 0,
|
||||
geo_overlap=0.05 if node["geoUrn"] == tgt.get("geoUrn") else 0,
|
||||
)
|
||||
))
|
||||
# return {"nodes":nodes,"edges":edges,"meta":{"generated_at":datetime.now(UTC).isoformat()}}
|
||||
return {"nodes":nodes,"edges":edges,"meta":{"generated_at":datetime.now(UTC).isoformat()}}
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# Org-chart via LLM
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
async def infer_org_chart_llm(company, people, client:OpenAI, model_name:str, max_tokens:int, temperature:float, stub:bool):
|
||||
if stub:
|
||||
# Tiny fake org-chart when debugging offline
|
||||
chief = random.choice(people)
|
||||
nodes = [{
|
||||
"id": chief["profile_url"],
|
||||
"name": chief["name"],
|
||||
"title": chief["headline"],
|
||||
"dept": chief["headline"].split()[:1][0],
|
||||
"yoe_total": 8,
|
||||
"yoe_current": 2,
|
||||
"seniority_score": 0.8,
|
||||
"decision_score": 0.9,
|
||||
"avatar_url": chief.get("avatar_url")
|
||||
}]
|
||||
return {"nodes":nodes,"edges":[],"meta":{"debug_stub":True,"generated_at":datetime.now(UTC).isoformat()}}
|
||||
|
||||
prompt = [
|
||||
{"role":"system","content":"You are an expert B2B org-chart reasoner."},
|
||||
{"role":"user","content":f"""Here is the company description:
|
||||
|
||||
<company>
|
||||
{json.dumps(company, ensure_ascii=False)}
|
||||
</company>
|
||||
|
||||
Here is a JSON list of employees:
|
||||
<employees>
|
||||
{json.dumps(people, ensure_ascii=False)}
|
||||
</employees>
|
||||
|
||||
1) Build a reporting tree (manager -> direct reports)
|
||||
2) For each person output a decision_score 0-1 for buying new software
|
||||
|
||||
Return JSON: {{ "nodes":[{{id,name,title,dept,yoe_total,yoe_current,seniority_score,decision_score,avatar_url,profile_url}}], "edges":[{{source,target,type,confidence}}] }}
|
||||
"""}
|
||||
]
|
||||
resp = client.chat.completions.create(
|
||||
model=model_name,
|
||||
messages=prompt,
|
||||
max_tokens=max_tokens,
|
||||
temperature=temperature,
|
||||
response_format={"type":"json_object"}
|
||||
)
|
||||
chart = json.loads(resp.choices[0].message.content)
|
||||
chart["meta"] = dict(model=model_name, generated_at=datetime.now(UTC).isoformat())
|
||||
return chart
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# CSV flatten
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
def export_decision_makers(charts_dir:Path, csv_path:Path, threshold:float=0.5):
|
||||
rows=[]
|
||||
for p in charts_dir.glob("org_chart_*.json"):
|
||||
data=json.loads(p.read_text())
|
||||
comp = p.stem.split("org_chart_")[1]
|
||||
for n in data.get("nodes",[]):
|
||||
if n.get("decision_score",0)>=threshold:
|
||||
rows.append(dict(
|
||||
company=comp,
|
||||
person=n["name"],
|
||||
title=n["title"],
|
||||
decision_score=n["decision_score"],
|
||||
profile_url=n["id"]
|
||||
))
|
||||
pd.DataFrame(rows).to_csv(csv_path,index=False)
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# HTML rendering
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
def render_html(out:Path, template_dir:Path):
|
||||
# From template folder cp graph_view.html and ai.js in out folder
|
||||
import shutil
|
||||
shutil.copy(template_dir/"graph_view_template.html", out / "graph_view.html")
|
||||
shutil.copy(template_dir/"ai.js", out)
|
||||
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# Main async pipeline
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
async def run(opts):
|
||||
# ── silence SDK noise ──────────────────────────────────────────────────────
|
||||
for noisy in ("openai", "httpx", "httpcore"):
|
||||
lg = logging.getLogger(noisy)
|
||||
lg.setLevel(logging.WARNING) # or ERROR if you want total silence
|
||||
lg.propagate = False # optional: stop them reaching root
|
||||
|
||||
# ────────────── logging bootstrap ──────────────
|
||||
console = Console()
|
||||
logging.basicConfig(
|
||||
level="INFO",
|
||||
format="%(message)s",
|
||||
handlers=[RichHandler(console=console, markup=True, rich_tracebacks=True)],
|
||||
)
|
||||
|
||||
in_dir = BASE_DIR / Path(opts.in_dir)
|
||||
out_dir = BASE_DIR / Path(opts.out_dir)
|
||||
out_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
companies = load_jsonl(in_dir/"companies.jsonl")
|
||||
people = load_jsonl(in_dir/"people.jsonl")
|
||||
|
||||
logging.info(f"[bold cyan]Loaded[/] {len(companies)} companies, {len(people)} people")
|
||||
|
||||
logging.info("[bold]⇢[/] Embedding company descriptions…")
|
||||
# embeds = embed_descriptions(companies, opts.embed_model, opts)
|
||||
|
||||
logging.info("[bold]⇢[/] Building similarity graph")
|
||||
# company_graph = build_company_graph(companies, embeds, opts.top_k)
|
||||
# dump_json(company_graph, out_dir/"company_graph.json")
|
||||
|
||||
# OpenAI client (only built if not debugging)
|
||||
stub = bool(opts.stub)
|
||||
client = OpenAI() if not stub else None
|
||||
|
||||
# Filter companies that need processing
|
||||
to_process = []
|
||||
for comp in companies:
|
||||
handle = comp["handle"].strip("/").replace("/","_")
|
||||
out_file = out_dir/f"org_chart_{handle}.json"
|
||||
if out_file.exists() and False:
|
||||
logging.info(f"[green]✓[/] Skipping existing {comp['name']}")
|
||||
continue
|
||||
to_process.append(comp)
|
||||
|
||||
|
||||
if not to_process:
|
||||
logging.info("[yellow]All companies already processed[/]")
|
||||
else:
|
||||
workers = getattr(opts, 'workers', 1)
|
||||
parallel = workers > 1
|
||||
|
||||
logging.info(f"[bold]⇢[/] Inferring org-charts via LLM {f'(parallel={workers} workers)' if parallel else ''}")
|
||||
|
||||
with Progress(
|
||||
SpinnerColumn(),
|
||||
BarColumn(),
|
||||
TextColumn("[progress.description]{task.description}"),
|
||||
TimeElapsedColumn(),
|
||||
console=console,
|
||||
) as progress:
|
||||
task = progress.add_task("Org charts", total=len(to_process))
|
||||
|
||||
async def process_one(comp):
|
||||
handle = comp["handle"].strip("/").replace("/","_")
|
||||
persons = [p for p in people if p["company_handle"].strip("/") == comp["handle"].strip("/")]
|
||||
|
||||
chart = await infer_org_chart_llm(
|
||||
comp, persons,
|
||||
client=client if client else OpenAI(api_key="sk-debug"),
|
||||
model_name=opts.openai_model,
|
||||
max_tokens=opts.max_llm_tokens,
|
||||
temperature=opts.llm_temperature,
|
||||
stub=stub,
|
||||
)
|
||||
chart["meta"]["company"] = comp["name"]
|
||||
|
||||
# Save the result immediately
|
||||
dump_json(chart, out_dir/f"org_chart_{handle}.json")
|
||||
|
||||
progress.update(task, advance=1, description=f"{comp['name']} ({len(persons)} ppl)")
|
||||
|
||||
# Create tasks for all companies
|
||||
tasks = [process_one(comp) for comp in to_process]
|
||||
|
||||
# Process in batches based on worker count
|
||||
semaphore = asyncio.Semaphore(workers)
|
||||
|
||||
async def bounded_process(coro):
|
||||
async with semaphore:
|
||||
return await coro
|
||||
|
||||
# Run with concurrency control
|
||||
await asyncio.gather(*(bounded_process(task) for task in tasks))
|
||||
|
||||
logging.info("[bold]⇢[/] Flattening decision-makers CSV")
|
||||
export_decision_makers(out_dir, out_dir/"decision_makers.csv")
|
||||
|
||||
render_html(out_dir, template_dir=BASE_DIR/"templates")
|
||||
logging.success = lambda msg, **k: console.print(f"[bold green]✓[/] {msg}", **k)
|
||||
logging.success(f"Stage-2 artefacts written to {out_dir}")
|
||||
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
# CLI
|
||||
# ───────────────────────────────────────────────────────────────────────────────
|
||||
def build_arg_parser():
|
||||
p = argparse.ArgumentParser(description="Build graphs & visualisation from Stage-1 output")
|
||||
p.add_argument("--in", dest="in_dir", required=False, help="Stage-1 output dir", default=".")
|
||||
p.add_argument("--out", dest="out_dir", required=False, help="Destination dir", default=".")
|
||||
p.add_argument("--embed_model", default="all-MiniLM-L6-v2")
|
||||
p.add_argument("--top_k", type=int, default=10, help="Top-k neighbours per company")
|
||||
p.add_argument("--openai_model", default="gpt-4.1")
|
||||
p.add_argument("--max_llm_tokens", type=int, default=8024)
|
||||
p.add_argument("--llm_temperature", type=float, default=1.0)
|
||||
p.add_argument("--stub", action="store_true", help="Skip OpenAI call and generate tiny fake org charts")
|
||||
p.add_argument("--workers", type=int, default=4, help="Number of parallel workers for LLM inference")
|
||||
return p
|
||||
|
||||
def main():
|
||||
dbg = dev_defaults()
|
||||
opts = dbg if True else build_arg_parser().parse_args()
|
||||
asyncio.run(run(opts))
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
39
docs/apps/linkdin/schemas/company_card.json
Normal file
39
docs/apps/linkdin/schemas/company_card.json
Normal file
@@ -0,0 +1,39 @@
|
||||
{
|
||||
"name": "LinkedIn Company Card",
|
||||
"baseSelector": "div.search-results-container ul[role='list'] > li",
|
||||
"fields": [
|
||||
{
|
||||
"name": "handle",
|
||||
"selector": "a[href*='/company/']",
|
||||
"type": "attribute",
|
||||
"attribute": "href"
|
||||
},
|
||||
{
|
||||
"name": "profile_image",
|
||||
"selector": "a[href*='/company/'] img",
|
||||
"type": "attribute",
|
||||
"attribute": "src"
|
||||
},
|
||||
{
|
||||
"name": "name",
|
||||
"selector": "span[class*='t-16'] a",
|
||||
"type": "text"
|
||||
},
|
||||
{
|
||||
"name": "descriptor",
|
||||
"selector": "div[class*='t-black t-normal']",
|
||||
"type": "text"
|
||||
},
|
||||
{
|
||||
"name": "about",
|
||||
"selector": "p[class*='entity-result__summary--2-lines']",
|
||||
"type": "text"
|
||||
},
|
||||
{
|
||||
"name": "followers",
|
||||
"selector": "div:contains('followers')",
|
||||
"type": "regex",
|
||||
"pattern": "(\\d+)\\s*followers"
|
||||
}
|
||||
]
|
||||
}
|
||||
38
docs/apps/linkdin/schemas/people_card.json
Normal file
38
docs/apps/linkdin/schemas/people_card.json
Normal file
@@ -0,0 +1,38 @@
|
||||
{
|
||||
"name": "LinkedIn People Card",
|
||||
"baseSelector": "li.org-people-profile-card__profile-card-spacing",
|
||||
"fields": [
|
||||
{
|
||||
"name": "profile_url",
|
||||
"selector": "a.eETATgYTipaVsmrBChiBJJvFsdPhNpulhPZUVLHLo",
|
||||
"type": "attribute",
|
||||
"attribute": "href"
|
||||
},
|
||||
{
|
||||
"name": "name",
|
||||
"selector": ".artdeco-entity-lockup__title .lt-line-clamp--single-line",
|
||||
"type": "text"
|
||||
},
|
||||
{
|
||||
"name": "headline",
|
||||
"selector": ".artdeco-entity-lockup__subtitle .lt-line-clamp--multi-line",
|
||||
"type": "text"
|
||||
},
|
||||
{
|
||||
"name": "followers",
|
||||
"selector": ".lt-line-clamp--multi-line.t-12",
|
||||
"type": "text"
|
||||
},
|
||||
{
|
||||
"name": "connection_degree",
|
||||
"selector": ".artdeco-entity-lockup__badge .artdeco-entity-lockup__degree",
|
||||
"type": "text"
|
||||
},
|
||||
{
|
||||
"name": "avatar_url",
|
||||
"selector": ".artdeco-entity-lockup__image img",
|
||||
"type": "attribute",
|
||||
"attribute": "src"
|
||||
}
|
||||
]
|
||||
}
|
||||
143
docs/apps/linkdin/snippets/company.html
Normal file
143
docs/apps/linkdin/snippets/company.html
Normal file
@@ -0,0 +1,143 @@
|
||||
<li class="yCLWzruNprmIzaZzFFonVFBtMrbaVYnuDFA">
|
||||
<!----><!---->
|
||||
|
||||
|
||||
|
||||
<div class="IxlEPbRZwQYrRltKPvHAyjBmCdIWTAoYo" data-chameleon-result-urn="urn:li:company:362492"
|
||||
data-view-name="search-entity-result-universal-template">
|
||||
|
||||
|
||||
|
||||
|
||||
<div class="linked-area flex-1
|
||||
cursor-pointer">
|
||||
|
||||
<div class="BAEgVqVuxosMJZodcelsgPoyRcrkiqgVCGHXNQ">
|
||||
<div class="afcvrbGzNuyRlhPPQWrWirJtUdHAAtUlqxwvVA">
|
||||
<div class="display-flex align-items-center">
|
||||
<!---->
|
||||
|
||||
<a class="eETATgYTipaVsmrBChiBJJvFsdPhNpulhPZUVLHLo scale-down " aria-hidden="true"
|
||||
tabindex="-1" href="https://www.linkedin.com/company/managment-research-services-inc./"
|
||||
data-test-app-aware-link="">
|
||||
|
||||
<div class="ivm-image-view-model ">
|
||||
|
||||
<div class="ivm-view-attr__img-wrapper
|
||||
|
||||
">
|
||||
<!---->
|
||||
<!----> <img width="48"
|
||||
src="https://media.licdn.com/dms/image/v2/C560BAQFWpusEOgW-ww/company-logo_100_100/company-logo_100_100/0/1630583697877/managment_research_services_inc_logo?e=1750896000&v=beta&t=Ch9vyEZdfng-1D1m_XqP5kjNpVXUBKkk9cNhMZUhx0E"
|
||||
loading="lazy" height="48" alt="Management Research Services, Inc. (MRS, Inc)"
|
||||
id="ember28"
|
||||
class="ivm-view-attr__img--centered EntityPhoto-square-3 evi-image lazy-image ember-view">
|
||||
</div>
|
||||
|
||||
</div>
|
||||
|
||||
</a>
|
||||
|
||||
|
||||
</div>
|
||||
</div>
|
||||
<div
|
||||
class="wympnVuDByXHvafWrMGJLZuchDmCRqLmWPwg MmzCPRicJimZvjJhvqTzDcDbdHhWPzspERzA pt3 pb3 t-12 t-black--light">
|
||||
<div class="mb1">
|
||||
|
||||
<div class="t-roman t-sans">
|
||||
|
||||
|
||||
|
||||
<div class="display-flex">
|
||||
<span class="TikBXjihYvcNUoIzkslUaEjfIuLmYxfs OoHEyXgsiIqGADjcOtTmfdpoYVXrLKTvkwI ">
|
||||
<span class="CgaWLOzmXNuKbRIRARSErqCJcBPYudEKo
|
||||
t-16">
|
||||
<a class="eETATgYTipaVsmrBChiBJJvFsdPhNpulhPZUVLHLo "
|
||||
href="https://www.linkedin.com/company/managment-research-services-inc./"
|
||||
data-test-app-aware-link="">
|
||||
<!---->Management Research Services, Inc. (MRS, Inc)<!---->
|
||||
<!----> </a>
|
||||
<!----> </span>
|
||||
</span>
|
||||
<!---->
|
||||
</div>
|
||||
|
||||
|
||||
|
||||
</div>
|
||||
|
||||
|
||||
|
||||
<div class="LjmdKCEqKITHihFOiQsBAQylkdnsWhqZii
|
||||
t-14 t-black t-normal">
|
||||
<!---->Insurance • Milwaukee, Wisconsin<!---->
|
||||
</div>
|
||||
|
||||
<div class="cTPhJiHyNLmxdQYFlsEOutjznmqrVHUByZwZ
|
||||
t-14 t-normal">
|
||||
<!---->1K followers<!---->
|
||||
</div>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
</div>
|
||||
|
||||
<!---->
|
||||
<p class="yWzlqwKNlvCWVNoKqmzoDDEnBMUuyynaLg
|
||||
entity-result__summary--2-lines
|
||||
t-12 t-black--light
|
||||
">
|
||||
<!---->MRS combines 30 years of experience supporting the Life,<span class="white-space-pre">
|
||||
</span><strong><!---->Health<!----></strong><span class="white-space-pre"> </span>and
|
||||
Annuities<span class="white-space-pre"> </span><strong><!---->Insurance<!----></strong><span
|
||||
class="white-space-pre"> </span>Industry with customized<span class="white-space-pre">
|
||||
</span><strong><!---->insurance<!----></strong><span class="white-space-pre">
|
||||
</span>underwriting solutions that efficiently support clients’ workflows. Supported by the
|
||||
Agenium Platform (www.agenium.ai) our innovative underwriting solutions are guaranteed to
|
||||
optimize requirements...<!---->
|
||||
</p>
|
||||
|
||||
<!---->
|
||||
</div>
|
||||
<div class="qXxdnXtzRVFTnTnetmNpssucBwQBsWlUuk MmzCPRicJimZvjJhvqTzDcDbdHhWPzspERzA">
|
||||
<!---->
|
||||
|
||||
|
||||
<div>
|
||||
|
||||
|
||||
|
||||
|
||||
<button aria-label="Follow Management Research Services, Inc. (MRS, Inc)" id="ember61"
|
||||
class="artdeco-button artdeco-button--2 artdeco-button--secondary ember-view"
|
||||
type="button"><!---->
|
||||
<span class="artdeco-button__text">
|
||||
Follow
|
||||
</span></button>
|
||||
|
||||
|
||||
|
||||
<!---->
|
||||
<!---->
|
||||
|
||||
|
||||
</div>
|
||||
|
||||
|
||||
|
||||
</div>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
|
||||
|
||||
|
||||
|
||||
</div>
|
||||
|
||||
|
||||
|
||||
</li>
|
||||
94
docs/apps/linkdin/snippets/people.html
Normal file
94
docs/apps/linkdin/snippets/people.html
Normal file
@@ -0,0 +1,94 @@
|
||||
<li class="grid grid__col--lg-8 block org-people-profile-card__profile-card-spacing">
|
||||
<div>
|
||||
|
||||
|
||||
<section class="artdeco-card full-width qQdPErXQkSAbwApNgNfuxukTIPPykttCcZGOHk">
|
||||
<!---->
|
||||
|
||||
<img width="210" src="data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7"
|
||||
ariarole="presentation" loading="lazy" height="210" alt="" id="ember96"
|
||||
class="evi-image lazy-image ghost-default ember-view org-people-profile-card__cover-photo org-people-profile-card__cover-photo--people">
|
||||
|
||||
<div class="org-people-profile-card__profile-info">
|
||||
<div id="ember97"
|
||||
class="artdeco-entity-lockup artdeco-entity-lockup--stacked-center artdeco-entity-lockup--size-7 ember-view">
|
||||
<div id="ember98"
|
||||
class="artdeco-entity-lockup__image artdeco-entity-lockup__image--type-circle ember-view"
|
||||
type="circle">
|
||||
|
||||
<a class="eETATgYTipaVsmrBChiBJJvFsdPhNpulhPZUVLHLo "
|
||||
id="org-people-profile-card__profile-image-0"
|
||||
href="https://www.linkedin.com/in/speakerrayna?miniProfileUrn=urn%3Ali%3Afs_miniProfile%3AACoAABsqUBoBr5x071PuGGpNtK3NlvSARiVXPIs"
|
||||
data-test-app-aware-link="">
|
||||
<img width="104"
|
||||
src="https://media.licdn.com/dms/image/v2/D5603AQGs2Vyju4xZ7A/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1681741067031?e=1750896000&v=beta&t=Hvj--IrrmpVIH7pec7-l_PQok8vsS__CGeUqBWOw7co"
|
||||
loading="lazy" height="104" alt="Dr. Rayna S." id="ember99"
|
||||
class="evi-image lazy-image ember-view">
|
||||
</a>
|
||||
|
||||
|
||||
</div>
|
||||
<div id="ember100" class="artdeco-entity-lockup__content ember-view">
|
||||
<div id="ember101" class="artdeco-entity-lockup__title ember-view">
|
||||
<a class="eETATgYTipaVsmrBChiBJJvFsdPhNpulhPZUVLHLo link-without-visited-state"
|
||||
aria-label="View Dr. Rayna S.’s profile"
|
||||
href="https://www.linkedin.com/in/speakerrayna?miniProfileUrn=urn%3Ali%3Afs_miniProfile%3AACoAABsqUBoBr5x071PuGGpNtK3NlvSARiVXPIs"
|
||||
data-test-app-aware-link="">
|
||||
<div id="ember103" class="ember-view lt-line-clamp lt-line-clamp--single-line AGabuksChUpCmjWshSnaZryLKSthOKkwclxY
|
||||
t-black" style="">
|
||||
Dr. Rayna S.
|
||||
|
||||
<!---->
|
||||
</div>
|
||||
|
||||
</a>
|
||||
|
||||
</div>
|
||||
<div id="ember104" class="artdeco-entity-lockup__badge ember-view"> <span class="a11y-text">3rd+
|
||||
degree connection</span>
|
||||
<span class="artdeco-entity-lockup__degree" aria-hidden="true">
|
||||
· 3rd
|
||||
</span>
|
||||
<!----><!---->
|
||||
</div>
|
||||
<div id="ember105" class="artdeco-entity-lockup__subtitle ember-view">
|
||||
<div class="t-14 t-black--light t-normal">
|
||||
<div id="ember107" class="ember-view lt-line-clamp lt-line-clamp--multi-line"
|
||||
style="-webkit-line-clamp: 2">
|
||||
Leadership and Talent Development Consultant and Professional Speaker
|
||||
|
||||
<!---->
|
||||
</div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
<div id="ember108" class="artdeco-entity-lockup__caption ember-view"></div>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
<span class="text-align-center">
|
||||
<span id="ember110"
|
||||
class="ember-view lt-line-clamp lt-line-clamp--multi-line t-12 t-black--light mt2"
|
||||
style="-webkit-line-clamp: 3">
|
||||
727 followers
|
||||
|
||||
<!----> </span>
|
||||
|
||||
</span>
|
||||
</div>
|
||||
|
||||
<footer class="ph3 pb3">
|
||||
<button aria-label="Follow Dr. Rayna S." id="ember111"
|
||||
class="artdeco-button artdeco-button--2 artdeco-button--secondary ember-view full-width"
|
||||
type="button"><!---->
|
||||
<span class="artdeco-button__text">
|
||||
Follow
|
||||
</span></button>
|
||||
</footer>
|
||||
|
||||
</section>
|
||||
|
||||
|
||||
</div>
|
||||
|
||||
</li>
|
||||
50
docs/apps/linkdin/templates/ai.js
Normal file
50
docs/apps/linkdin/templates/ai.js
Normal file
@@ -0,0 +1,50 @@
|
||||
// ==== File: ai.js ====
|
||||
|
||||
class ApiHandler {
|
||||
constructor(apiKey = null) {
|
||||
this.apiKey = apiKey || localStorage.getItem("openai_api_key") || "";
|
||||
console.log("ApiHandler ready");
|
||||
}
|
||||
|
||||
setApiKey(k) {
|
||||
this.apiKey = k.trim();
|
||||
if (this.apiKey) localStorage.setItem("openai_api_key", this.apiKey);
|
||||
}
|
||||
|
||||
async *chatStream(messages, {model = "gpt-4o", temperature = 0.7} = {}) {
|
||||
if (!this.apiKey) throw new Error("OpenAI API key missing");
|
||||
const payload = {model, messages, stream: true, max_tokens: 1024};
|
||||
const controller = new AbortController();
|
||||
|
||||
const res = await fetch("https://api.openai.com/v1/chat/completions", {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
Authorization: `Bearer ${this.apiKey}`,
|
||||
},
|
||||
body: JSON.stringify(payload),
|
||||
signal: controller.signal,
|
||||
});
|
||||
if (!res.ok) throw new Error(`OpenAI: ${res.statusText}`);
|
||||
const reader = res.body.getReader();
|
||||
const dec = new TextDecoder();
|
||||
|
||||
let buf = "";
|
||||
while (true) {
|
||||
const {done, value} = await reader.read();
|
||||
if (done) break;
|
||||
buf += dec.decode(value, {stream: true});
|
||||
for (const line of buf.split("\n")) {
|
||||
if (!line.startsWith("data: ")) continue;
|
||||
if (line.includes("[DONE]")) return;
|
||||
const json = JSON.parse(line.slice(6));
|
||||
const delta = json.choices?.[0]?.delta?.content;
|
||||
if (delta) yield delta;
|
||||
}
|
||||
buf = buf.endsWith("\n") ? "" : buf; // keep partial line
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
window.API = new ApiHandler();
|
||||
|
||||
1171
docs/apps/linkdin/templates/graph_view_template.html
Normal file
1171
docs/apps/linkdin/templates/graph_view_template.html
Normal file
File diff suppressed because it is too large
Load Diff
51
docs/codebase/browser.md
Normal file
51
docs/codebase/browser.md
Normal file
@@ -0,0 +1,51 @@
|
||||
### browser_manager.py
|
||||
|
||||
| Function | What it does |
|
||||
|---|---|
|
||||
| `ManagedBrowser.build_browser_flags` | Returns baseline Chromium CLI flags, disables GPU and sandbox, plugs locale, timezone, stealth tweaks, and any extras from `BrowserConfig`. |
|
||||
| `ManagedBrowser.__init__` | Stores config and logger, creates temp dir, preps internal state. |
|
||||
| `ManagedBrowser.start` | Spawns or connects to the Chromium process, returns its CDP endpoint plus the `subprocess.Popen` handle. |
|
||||
| `ManagedBrowser._initial_startup_check` | Pings the CDP endpoint once to be sure the browser is alive, raises if not. |
|
||||
| `ManagedBrowser._monitor_browser_process` | Async-loops on the subprocess, logs exits or crashes, restarts if policy allows. |
|
||||
| `ManagedBrowser._get_browser_path_WIP` | Old helper that maps OS + browser type to an executable path. |
|
||||
| `ManagedBrowser._get_browser_path` | Current helper, checks env vars, Playwright cache, and OS defaults for the real executable. |
|
||||
| `ManagedBrowser._get_browser_args` | Builds the final CLI arg list by merging user flags, stealth flags, and defaults. |
|
||||
| `ManagedBrowser.cleanup` | Terminates the browser, stops monitors, deletes the temp dir. |
|
||||
| `ManagedBrowser.create_profile` | Opens a visible browser so a human can log in, then zips the resulting user-data-dir to `~/.crawl4ai/profiles/<name>`. |
|
||||
| `ManagedBrowser.list_profiles` | Thin wrapper, now forwarded to `BrowserProfiler.list_profiles()`. |
|
||||
| `ManagedBrowser.delete_profile` | Thin wrapper, now forwarded to `BrowserProfiler.delete_profile()`. |
|
||||
| `BrowserManager.__init__` | Holds the global Playwright instance, browser handle, config signature cache, session map, and logger. |
|
||||
| `BrowserManager.start` | Boots the underlying `ManagedBrowser`, then spins up the default Playwright browser context with stealth patches. |
|
||||
| `BrowserManager._build_browser_args` | Translates `CrawlerRunConfig` (proxy, UA, timezone, headless flag, etc.) into Playwright `launch_args`. |
|
||||
| `BrowserManager.setup_context` | Applies locale, geolocation, permissions, cookies, and UA overrides on a fresh context. |
|
||||
| `BrowserManager.create_browser_context` | Internal helper that actually calls `browser.new_context(**options)` after running `setup_context`. |
|
||||
| `BrowserManager._make_config_signature` | Hashes the non-ephemeral parts of `CrawlerRunConfig` so contexts can be reused safely. |
|
||||
| `BrowserManager.get_page` | Returns a ready `Page` for a given session id, reusing an existing one or creating a new context/page, injects helper scripts, updates `last_used`. |
|
||||
| `BrowserManager.kill_session` | Force-closes a context/page for a session and removes it from the session map. |
|
||||
| `BrowserManager._cleanup_expired_sessions` | Periodic sweep that drops sessions idle longer than `ttl_seconds`. |
|
||||
| `BrowserManager.close` | Gracefully shuts down all contexts, the browser, Playwright, and background tasks. |
|
||||
|
||||
---
|
||||
|
||||
### browser_profiler.py
|
||||
|
||||
| Function | What it does |
|
||||
|---|---|
|
||||
| `BrowserProfiler.__init__` | Sets up profile folder paths, async logger, and signal handlers. |
|
||||
| `BrowserProfiler.create_profile` | Launches a visible browser with a new user-data-dir for manual login, on exit compresses and stores it as a named profile. |
|
||||
| `BrowserProfiler.cleanup_handler` | General SIGTERM/SIGINT cleanup wrapper that kills child processes. |
|
||||
| `BrowserProfiler.sigint_handler` | Handles Ctrl-C during an interactive session, makes sure the browser shuts down cleanly. |
|
||||
| `BrowserProfiler.listen_for_quit_command` | Async REPL that exits when the user types `q`. |
|
||||
| `BrowserProfiler.list_profiles` | Enumerates `~/.crawl4ai/profiles`, prints profile name, browser type, size, and last modified. |
|
||||
| `BrowserProfiler.get_profile_path` | Returns the absolute path of a profile given its name, or `None` if missing. |
|
||||
| `BrowserProfiler.delete_profile` | Removes a profile folder or a direct path from disk, with optional confirmation prompt. |
|
||||
| `BrowserProfiler.interactive_manager` | Text UI loop for listing, creating, deleting, or launching profiles. |
|
||||
| `BrowserProfiler.launch_standalone_browser` | Starts a non-headless Chromium with remote debugging enabled and keeps it alive for manual tests. |
|
||||
| `BrowserProfiler.get_cdp_json` | Pulls `/json/version` from a CDP endpoint and returns the parsed JSON. |
|
||||
| `BrowserProfiler.launch_builtin_browser` | Spawns a headless Chromium in the background, saves `{wsEndpoint, pid, started_at}` to `~/.crawl4ai/builtin_browser.json`. |
|
||||
| `BrowserProfiler.get_builtin_browser_info` | Reads that JSON file, verifies the PID, and returns browser status info. |
|
||||
| `BrowserProfiler._is_browser_running` | Cross-platform helper that checks if a PID is still alive. |
|
||||
| `BrowserProfiler.kill_builtin_browser` | Terminates the background builtin browser and removes its status file. |
|
||||
| `BrowserProfiler.get_builtin_browser_status` | Returns `{running: bool, wsEndpoint, pid, started_at}` for quick health checks. |
|
||||
|
||||
Let me know what you want to tweak or dive into next.
|
||||
40
docs/codebase/cli.md
Normal file
40
docs/codebase/cli.md
Normal file
@@ -0,0 +1,40 @@
|
||||
### `cli.py` command surface
|
||||
|
||||
| Command | Inputs / flags | What it does |
|
||||
|---|---|---|
|
||||
| **profiles** | *(none)* | Opens the interactive profile manager, lets you list, create, delete saved browser profiles that live in `~/.crawl4ai/profiles`. |
|
||||
| **browser status** | – | Prints whether the always-on *builtin* browser is running, shows its CDP URL, PID, start time. |
|
||||
| **browser stop** | – | Kills the builtin browser and deletes its status file. |
|
||||
| **browser view** | `--url, -u` URL *(optional)* | Pops a visible window of the builtin browser, navigates to `URL` or `about:blank`. |
|
||||
| **config list** | – | Dumps every global setting, showing current value, default, and description. |
|
||||
| **config get** | `key` | Prints the value of a single setting, falls back to default if unset. |
|
||||
| **config set** | `key value` | Persists a new value in the global config (stored under `~/.crawl4ai/config.yml`). |
|
||||
| **examples** | – | Just spits out real-world CLI usage samples. |
|
||||
| **crawl** | `url` *(positional)*<br>`--browser-config,-B` path<br>`--crawler-config,-C` path<br>`--filter-config,-f` path<br>`--extraction-config,-e` path<br>`--json-extract,-j` [desc]\*<br>`--schema,-s` path<br>`--browser,-b` k=v list<br>`--crawler,-c` k=v list<br>`--output,-o` all,json,markdown,md,markdown-fit,md-fit *(default all)*<br>`--output-file,-O` path<br>`--bypass-cache,-b` *(flag, default true — note flag reuse)*<br>`--question,-q` str<br>`--verbose,-v` *(flag)*<br>`--profile,-p` profile-name | One-shot crawl + extraction. Builds `BrowserConfig` and `CrawlerRunConfig` from inline flags or separate YAML/JSON files, runs `AsyncWebCrawler.run()`, can route through a named saved profile and pipe the result to stdout or a file. |
|
||||
| **(default)** | Same flags as **crawl**, plus `--example` | Shortcut so you can type just `crwl https://site.com`. When first arg is not a known sub-command, it falls through to *crawl*. |
|
||||
|
||||
\* `--json-extract/-j` with no value turns on LLM-based JSON extraction using an auto schema, supplying a string lets you prompt-engineer the field descriptions.
|
||||
|
||||
> Quick mental model
|
||||
> `profiles` = manage identities,
|
||||
> `browser ...` = control long-running headless Chrome that all crawls can piggy-back on,
|
||||
> `crawl` = do the actual work,
|
||||
> `config` = tweak global defaults,
|
||||
> everything else is sugar.
|
||||
|
||||
### Quick-fire “profile” usage cheatsheet
|
||||
|
||||
| Scenario | Command (copy-paste ready) | Notes |
|
||||
|---|---|---|
|
||||
| **Launch interactive Profile Manager UI** | `crwl profiles` | Opens TUI with options: 1 List, 2 Create, 3 Delete, 4 Use-to-crawl, 5 Exit. |
|
||||
| **Create a fresh profile** | `crwl profiles` → choose **2** → name it → browser opens → log in → press **q** in terminal | Saves to `~/.crawl4ai/profiles/<name>`. |
|
||||
| **List saved profiles** | `crwl profiles` → choose **1** | Shows name, browser type, size, last-modified. |
|
||||
| **Delete a profile** | `crwl profiles` → choose **3** → pick the profile index → confirm | Removes the folder. |
|
||||
| **Crawl with a profile (default alias)** | `crwl https://site.com/dashboard -p my-profile` | Keeps login cookies, sets `use_managed_browser=true` under the hood. |
|
||||
| **Crawl + verbose JSON output** | `crwl https://site.com -p my-profile -o json -v` | Any other `crawl` flags work the same. |
|
||||
| **Crawl with extra browser tweaks** | `crwl https://site.com -p my-profile -b "headless=true,viewport_width=1680"` | CLI overrides go on top of the profile. |
|
||||
| **Same but via explicit sub-command** | `crwl crawl https://site.com -p my-profile` | Identical to default alias. |
|
||||
| **Use profile from inside Profile Manager** | `crwl profiles` → choose **4** → pick profile → enter URL → follow prompts | Handy when demo-ing to non-CLI folks. |
|
||||
| **One-off crawl with a profile folder path (no name lookup)** | `crwl https://site.com -b "user_data_dir=$HOME/.crawl4ai/profiles/my-profile,use_managed_browser=true"` | Bypasses registry, useful for CI scripts. |
|
||||
| **Launch a dev browser on CDP port with the same identity** | `crwl cdp -d $HOME/.crawl4ai/profiles/my-profile -P 9223` | Lets Puppeteer/Playwright attach for debugging. |
|
||||
|
||||
@@ -391,12 +391,14 @@ async def main():
|
||||
# Process results
|
||||
raw_df = pd.DataFrame()
|
||||
for result in results:
|
||||
if result.success and result.media["tables"]:
|
||||
# Use the new tables field, falling back to media["tables"] for backward compatibility
|
||||
tables = result.tables if hasattr(result, "tables") and result.tables else result.media.get("tables", [])
|
||||
if result.success and tables:
|
||||
# Extract primary market table
|
||||
# DataFrame
|
||||
raw_df = pd.DataFrame(
|
||||
result.media["tables"][0]["rows"],
|
||||
columns=result.media["tables"][0]["headers"],
|
||||
tables[0]["rows"],
|
||||
columns=tables[0]["headers"],
|
||||
)
|
||||
break
|
||||
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -31,7 +31,7 @@ async def example_cdp():
|
||||
|
||||
|
||||
async def main():
|
||||
browser_config = BrowserConfig(headless=True, verbose=True)
|
||||
browser_config = BrowserConfig(headless=False, verbose=True)
|
||||
async with AsyncWebCrawler(config=browser_config) as crawler:
|
||||
crawler_config = CrawlerRunConfig(
|
||||
cache_mode=CacheMode.BYPASS,
|
||||
|
||||
@@ -412,17 +412,41 @@ footer {
|
||||
background-color: var(--primary-dimmed-color, #09b5a5);
|
||||
color: var(--background-color, #070708);
|
||||
border: none;
|
||||
padding: 4px 8px;
|
||||
padding: 6px 10px;
|
||||
font-size: 0.8em;
|
||||
border-radius: 4px;
|
||||
cursor: pointer;
|
||||
box-shadow: 0 2px 5px rgba(0, 0, 0, 0.3);
|
||||
transition: background-color 0.2s ease;
|
||||
box-shadow: 0 3px 8px rgba(0, 0, 0, 0.3);
|
||||
transition: background-color 0.2s ease, transform 0.15s ease;
|
||||
white-space: nowrap;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
font-weight: 500;
|
||||
animation: askAiButtonAppear 0.2s ease-out;
|
||||
}
|
||||
|
||||
@keyframes askAiButtonAppear {
|
||||
from {
|
||||
opacity: 0;
|
||||
transform: scale(0.9);
|
||||
}
|
||||
to {
|
||||
opacity: 1;
|
||||
transform: scale(1);
|
||||
}
|
||||
}
|
||||
|
||||
.ask-ai-selection-button:hover {
|
||||
background-color: var(--primary-color, #50ffff);
|
||||
transform: scale(1.05);
|
||||
}
|
||||
|
||||
/* Mobile styles for Ask AI button */
|
||||
@media screen and (max-width: 768px) {
|
||||
.ask-ai-selection-button {
|
||||
padding: 8px 12px; /* Larger touch target on mobile */
|
||||
font-size: 0.9em; /* Slightly larger text */
|
||||
}
|
||||
}
|
||||
|
||||
/* ==== File: docs/assets/layout.css (Additions) ==== */
|
||||
|
||||
@@ -8,12 +8,32 @@ document.addEventListener('DOMContentLoaded', () => {
|
||||
const button = document.createElement('button');
|
||||
button.id = 'ask-ai-selection-btn';
|
||||
button.className = 'ask-ai-selection-button';
|
||||
button.textContent = 'Ask AI'; // Or use an icon
|
||||
|
||||
// Add icon and text for better visibility
|
||||
button.innerHTML = `
|
||||
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" width="12" height="12" fill="currentColor" style="margin-right: 4px; vertical-align: middle;">
|
||||
<path d="M20 2H4c-1.1 0-2 .9-2 2v12c0 1.1.9 2 2 2h14l4 4V4c0-1.1-.9-2-2-2z"/>
|
||||
</svg>
|
||||
<span>Ask AI</span>
|
||||
`;
|
||||
|
||||
// Common styles
|
||||
button.style.display = 'none'; // Initially hidden
|
||||
button.style.position = 'absolute';
|
||||
button.style.zIndex = '1500'; // Ensure it's on top
|
||||
button.style.boxShadow = '0 3px 8px rgba(0, 0, 0, 0.4)'; // More pronounced shadow
|
||||
button.style.transition = 'transform 0.15s ease, background-color 0.2s ease'; // Smooth hover effect
|
||||
|
||||
// Add transform on hover
|
||||
button.addEventListener('mouseover', () => {
|
||||
button.style.transform = 'scale(1.05)';
|
||||
});
|
||||
|
||||
button.addEventListener('mouseout', () => {
|
||||
button.style.transform = 'scale(1)';
|
||||
});
|
||||
|
||||
document.body.appendChild(button);
|
||||
|
||||
button.addEventListener('click', handleAskAiClick);
|
||||
return button;
|
||||
}
|
||||
@@ -43,11 +63,38 @@ document.addEventListener('DOMContentLoaded', () => {
|
||||
const range = selection.getRangeAt(0);
|
||||
const rect = range.getBoundingClientRect();
|
||||
|
||||
// Calculate position: top-right of the selection
|
||||
// Get viewport dimensions
|
||||
const viewportWidth = window.innerWidth;
|
||||
const viewportHeight = window.innerHeight;
|
||||
|
||||
// Calculate position based on selection
|
||||
const scrollX = window.scrollX;
|
||||
const scrollY = window.scrollY;
|
||||
const buttonTop = rect.top + scrollY - askAiButton.offsetHeight - 5; // 5px above
|
||||
const buttonLeft = rect.right + scrollX + 5; // 5px to the right
|
||||
|
||||
// Default position (top-right of selection)
|
||||
let buttonTop = rect.top + scrollY - askAiButton.offsetHeight - 5; // 5px above
|
||||
let buttonLeft = rect.right + scrollX + 5; // 5px to the right
|
||||
|
||||
// Check if we're on mobile (which we define as less than 768px)
|
||||
const isMobile = viewportWidth <= 768;
|
||||
|
||||
if (isMobile) {
|
||||
// On mobile, position centered above selection to avoid edge issues
|
||||
buttonTop = rect.top + scrollY - askAiButton.offsetHeight - 10; // 10px above on mobile
|
||||
buttonLeft = rect.left + scrollX + (rect.width / 2) - (askAiButton.offsetWidth / 2); // Centered
|
||||
} else {
|
||||
// For desktop, ensure the button doesn't go off screen
|
||||
// Check right edge
|
||||
if (buttonLeft + askAiButton.offsetWidth > scrollX + viewportWidth) {
|
||||
buttonLeft = scrollX + viewportWidth - askAiButton.offsetWidth - 10; // 10px from right edge
|
||||
}
|
||||
}
|
||||
|
||||
// Check top edge (for all devices)
|
||||
if (buttonTop < scrollY) {
|
||||
// If would go above viewport, position below selection instead
|
||||
buttonTop = rect.bottom + scrollY + 5; // 5px below
|
||||
}
|
||||
|
||||
askAiButton.style.top = `${buttonTop}px`;
|
||||
askAiButton.style.left = `${buttonLeft}px`;
|
||||
@@ -77,8 +124,8 @@ document.addEventListener('DOMContentLoaded', () => {
|
||||
|
||||
// --- Event Listeners ---
|
||||
|
||||
// Show button on mouse up after selection
|
||||
document.addEventListener('mouseup', (event) => {
|
||||
// Function to handle selection events (both mouse and touch)
|
||||
function handleSelectionEvent(event) {
|
||||
// Slight delay to ensure selection is registered
|
||||
setTimeout(() => {
|
||||
const selectedText = getSafeSelectedText();
|
||||
@@ -86,7 +133,7 @@ document.addEventListener('DOMContentLoaded', () => {
|
||||
if (!askAiButton) {
|
||||
askAiButton = createAskAiButton();
|
||||
}
|
||||
// Don't position if the click was ON the button itself
|
||||
// Don't position if the event was ON the button itself
|
||||
if (event.target !== askAiButton) {
|
||||
positionButton(event);
|
||||
}
|
||||
@@ -94,16 +141,46 @@ document.addEventListener('DOMContentLoaded', () => {
|
||||
hideButton();
|
||||
}
|
||||
}, 10); // Small delay
|
||||
}
|
||||
|
||||
// Mouse selection events (desktop)
|
||||
document.addEventListener('mouseup', handleSelectionEvent);
|
||||
|
||||
// Touch selection events (mobile)
|
||||
document.addEventListener('touchend', handleSelectionEvent);
|
||||
document.addEventListener('selectionchange', () => {
|
||||
// This helps with mobile selection which can happen without mouseup/touchend
|
||||
setTimeout(() => {
|
||||
const selectedText = getSafeSelectedText();
|
||||
if (selectedText && askAiButton) {
|
||||
positionButton();
|
||||
}
|
||||
}, 300); // Longer delay for selection change
|
||||
});
|
||||
|
||||
// Hide button on scroll or click elsewhere
|
||||
// Hide button on various events
|
||||
document.addEventListener('mousedown', (event) => {
|
||||
// Hide if clicking anywhere EXCEPT the button itself
|
||||
if (askAiButton && event.target !== askAiButton) {
|
||||
hideButton();
|
||||
}
|
||||
});
|
||||
|
||||
document.addEventListener('touchstart', (event) => {
|
||||
// Same for touch events, but only hide if not on the button
|
||||
if (askAiButton && event.target !== askAiButton) {
|
||||
hideButton();
|
||||
}
|
||||
});
|
||||
|
||||
document.addEventListener('scroll', hideButton, true); // Capture scroll events
|
||||
|
||||
// Also hide when pressing Escape key
|
||||
document.addEventListener('keydown', (event) => {
|
||||
if (event.key === 'Escape') {
|
||||
hideButton();
|
||||
}
|
||||
});
|
||||
|
||||
console.log("Selection Ask AI script loaded.");
|
||||
});
|
||||
@@ -4,6 +4,32 @@ Welcome to the Crawl4AI blog! Here you'll find detailed release notes, technical
|
||||
|
||||
## Latest Release
|
||||
|
||||
Here’s the blog index entry for **v0.6.0**, written to match the exact tone and structure of your previous entries:
|
||||
|
||||
---
|
||||
|
||||
### [Crawl4AI v0.6.0 – World-Aware Crawling, Pre-Warmed Browsers, and the MCP API](releases/0.6.0.md)
|
||||
*April 23, 2025*
|
||||
|
||||
Crawl4AI v0.6.0 is our most powerful release yet. This update brings major architectural upgrades including world-aware crawling (set geolocation, locale, and timezone), real-time traffic capture, and a memory-efficient crawler pool with pre-warmed pages.
|
||||
|
||||
The Docker server now exposes a full-featured MCP socket + SSE interface, supports streaming, and comes with a new Playground UI. Plus, table extraction is now native, and the new stress-test framework supports crawling 1,000+ URLs.
|
||||
|
||||
Other key changes:
|
||||
|
||||
* Native support for `result.media["tables"]` to export DataFrames
|
||||
* Full network + console logs and MHTML snapshot per crawl
|
||||
* Browser pooling and pre-warming for faster cold starts
|
||||
* New streaming endpoints via MCP API and Playground
|
||||
* Robots.txt support, proxy rotation, and improved session handling
|
||||
* Deprecated old markdown names, legacy modules cleaned up
|
||||
* Massive repo cleanup: ~36K insertions, ~5K deletions across 121 files
|
||||
|
||||
[Read full release notes →](releases/0.6.0.md)
|
||||
|
||||
---
|
||||
|
||||
Let me know if you want me to auto-update the actual file or just paste this into the markdown.
|
||||
|
||||
### [Crawl4AI v0.5.0: Deep Crawling, Scalability, and a New CLI!](releases/0.5.0.md)
|
||||
|
||||
|
||||
@@ -1,51 +1,143 @@
|
||||
# Crawl4AI 0.6.0
|
||||
# Crawl4AI v0.6.0 Release Notes
|
||||
|
||||
*Release date: 2025‑04‑22*
|
||||
|
||||
0.6.0 is the **biggest jump** since the 0.5 series, packing a smarter browser core, pool‑based crawlers, and a ton of DX candy. Expect faster runs, lower RAM burn, and richer diagnostics.
|
||||
We're excited to announce the release of **Crawl4AI v0.6.0**, our biggest and most feature-rich update yet. This version introduces major architectural upgrades, brand-new capabilities for geo-aware crawling, high-efficiency scraping, and real-time streaming support for scalable deployments.
|
||||
|
||||
---
|
||||
|
||||
## 🚀 Key upgrades
|
||||
## Highlights
|
||||
|
||||
| Area | What changed |
|
||||
|------|--------------|
|
||||
| **Browser** | New **Browser** management with pooling, page pre‑warm, geolocation + locale + timezone switches |
|
||||
| **Crawler** | Console and network log capture, MHTML snapshots, safer `get_page` API |
|
||||
| **Server & API** | **Crawler Pool Manager** endpoint, MCP socket + SSE support |
|
||||
| **Docs** | v2 layout, floating Ask‑AI helper, GitHub stats badge, copy‑code buttons, Docker API demo |
|
||||
| **Tests** | Memory + load benchmarks, 90+ new cases covering MCP and Docker |
|
||||
### 1. **World-Aware Crawlers**
|
||||
Crawl as if you’re anywhere in the world. With v0.6.0, each crawl can simulate:
|
||||
- Specific GPS coordinates
|
||||
- Browser locale
|
||||
- Timezone
|
||||
|
||||
Example:
|
||||
```python
|
||||
CrawlerRunConfig(
|
||||
url="https://browserleaks.com/geo",
|
||||
locale="en-US",
|
||||
timezone_id="America/Los_Angeles",
|
||||
geolocation=GeolocationConfig(
|
||||
latitude=34.0522,
|
||||
longitude=-118.2437,
|
||||
accuracy=10.0
|
||||
)
|
||||
)
|
||||
```
|
||||
Great for accessing region-specific content or testing global behavior.
|
||||
|
||||
---
|
||||
|
||||
## ⚠️ Breaking changes
|
||||
### 2. **Native Table Extraction**
|
||||
Extract HTML tables directly into usable formats like Pandas DataFrames or CSV with zero parsing hassle. All table data is available under `result.media["tables"]`.
|
||||
|
||||
1. **`get_page` signature** – returns `(html, metadata)` instead of plain html.
|
||||
2. **Docker** – new Chromium base layer, rebuild images.
|
||||
Example:
|
||||
```python
|
||||
raw_df = pd.DataFrame(
|
||||
result.media["tables"][0]["rows"],
|
||||
columns=result.media["tables"][0]["headers"]
|
||||
)
|
||||
```
|
||||
This makes it ideal for scraping financial data, pricing pages, or anything tabular.
|
||||
|
||||
---
|
||||
|
||||
## How to upgrade
|
||||
### 3. **Browser Pooling & Pre-Warming**
|
||||
We've overhauled browser management. Now, multiple browser instances can be pooled and pages pre-warmed for ultra-fast launches:
|
||||
- Reduces cold-start latency
|
||||
- Lowers memory spikes
|
||||
- Enhances parallel crawling stability
|
||||
|
||||
This powers the new **Docker Playground** experience and streamlines heavy-load crawling.
|
||||
|
||||
---
|
||||
|
||||
### 4. **Traffic & Snapshot Capture**
|
||||
Need full visibility? You can now capture:
|
||||
- Full network traffic logs
|
||||
- Console output
|
||||
- MHTML page snapshots for post-crawl audits and debugging
|
||||
|
||||
No more guesswork on what happened during your crawl.
|
||||
|
||||
---
|
||||
|
||||
### 5. **MCP API and Streaming Support**
|
||||
We’re exposing **MCP socket and SSE endpoints**, allowing:
|
||||
- Live streaming of crawl results
|
||||
- Real-time integration with agents or frontends
|
||||
- A new Playground UI for interactive crawling
|
||||
|
||||
This is a major step towards making Crawl4AI real-time ready.
|
||||
|
||||
---
|
||||
|
||||
### 6. **Stress-Test Framework**
|
||||
Want to test performance under heavy load? v0.6.0 includes a new memory stress-test suite that supports 1,000+ URL workloads. Ideal for:
|
||||
- Load testing
|
||||
- Performance benchmarking
|
||||
- Validating memory efficiency
|
||||
|
||||
---
|
||||
|
||||
## Core Improvements
|
||||
- Robots.txt compliance
|
||||
- Proxy rotation support
|
||||
- Improved URL normalization and session reuse
|
||||
- Shared data across crawler hooks
|
||||
- New page routing logic
|
||||
|
||||
---
|
||||
|
||||
## Breaking Changes & Deprecations
|
||||
- Legacy `crawl4ai/browser/*` modules are removed. Update imports accordingly.
|
||||
- `AsyncPlaywrightCrawlerStrategy.get_page` now uses a new function signature.
|
||||
- Deprecated markdown generator aliases now point to `DefaultMarkdownGenerator` with warning.
|
||||
|
||||
---
|
||||
|
||||
## Miscellaneous Updates
|
||||
- FastAPI validators replaced custom validation logic
|
||||
- Docker build now based on a Chromium layer
|
||||
- Repo-wide cleanup: ~36,000 insertions, ~5,000 deletions
|
||||
|
||||
---
|
||||
|
||||
## New Examples Included
|
||||
- Geo-location crawling
|
||||
- Network + console log capture
|
||||
- Docker MCP API usage
|
||||
- Markdown selector usage
|
||||
- Crypto project data extraction
|
||||
|
||||
---
|
||||
|
||||
## Watch the Release Video
|
||||
Want a visual walkthrough of all these updates? Watch the video:
|
||||
🔗 https://youtu.be/9x7nVcjOZks
|
||||
|
||||
If you're new to Crawl4AI, start here:
|
||||
🔗 https://www.youtube.com/watch?v=xo3qK6Hg9AA&t=15s
|
||||
|
||||
---
|
||||
|
||||
## Join the Community
|
||||
We’ve just opened up our **Discord** for the public. Join us to:
|
||||
- Ask questions
|
||||
- Share your projects
|
||||
- Get help or contribute
|
||||
|
||||
💬 https://discord.gg/wpYFACrHR4
|
||||
|
||||
---
|
||||
|
||||
## Install or Upgrade
|
||||
```bash
|
||||
pip install -U crawl4ai==0.6.0
|
||||
pip install -U crawl4ai
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Full changelog
|
||||
|
||||
The diff between `main` and `next` spans **36 k insertions, 4.9 k deletions** over 121 files. Read the [compare view](https://github.com/unclecode/crawl4ai/compare/0.5.0.post8...0.6.0) or see `CHANGELOG.md` for the granular list.
|
||||
|
||||
---
|
||||
|
||||
## Upgrade tips
|
||||
|
||||
* Using the Docker API? Pull `unclecode/crawl4ai:0.6.0`, new args are documented in `/deploy/docker/README.md`.
|
||||
* Stress‑test your stack with `tests/memory/run_benchmark.py` before production rollout.
|
||||
* Markdown generators renamed but aliased, update when convenient, warnings will remind you.
|
||||
|
||||
---
|
||||
|
||||
Happy crawling, ping `@unclecode` on X for questions or memes.
|
||||
Live long and import crawl4ai. 🖖
|
||||
|
||||
|
||||
@@ -58,7 +58,7 @@ Pull and run images directly from Docker Hub without building locally.
|
||||
|
||||
#### 1. Pull the Image
|
||||
|
||||
Our latest release candidate is `0.6.0rc1-r2`. Images are built with multi-arch manifests, so Docker automatically pulls the correct version for your system.
|
||||
Our latest release candidate is `0.6.0-r2`. Images are built with multi-arch manifests, so Docker automatically pulls the correct version for your system.
|
||||
|
||||
```bash
|
||||
# Pull the release candidate (recommended for latest features)
|
||||
@@ -124,9 +124,9 @@ docker stop crawl4ai && docker rm crawl4ai
|
||||
#### Docker Hub Versioning Explained
|
||||
|
||||
* **Image Name:** `unclecode/crawl4ai`
|
||||
* **Tag Format:** `LIBRARY_VERSION[-SUFFIX]` (e.g., `0.6.0rc1-r2`)
|
||||
* **Tag Format:** `LIBRARY_VERSION[-SUFFIX]` (e.g., `0.6.0-r2`)
|
||||
* `LIBRARY_VERSION`: The semantic version of the core `crawl4ai` Python library
|
||||
* `SUFFIX`: Optional tag for release candidates (`rc1`) and revisions (`r1`)
|
||||
* `SUFFIX`: Optional tag for release candidates (``) and revisions (`r1`)
|
||||
* **`latest` Tag:** Points to the most recent stable version
|
||||
* **Multi-Architecture Support:** All images support both `linux/amd64` and `linux/arm64` architectures through a single tag
|
||||
|
||||
|
||||
32
tests/profiler/test_crteate_profile.py
Normal file
32
tests/profiler/test_crteate_profile.py
Normal file
@@ -0,0 +1,32 @@
|
||||
from crawl4ai import BrowserProfiler
|
||||
import asyncio
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
# Example usage
|
||||
profiler = BrowserProfiler()
|
||||
|
||||
# Create a new profile
|
||||
import os
|
||||
from pathlib import Path
|
||||
home_dir = Path.home()
|
||||
profile_path = asyncio.run(profiler.create_profile( str(home_dir / ".crawl4ai/profiles/test-profile")))
|
||||
|
||||
print(f"Profile created at: {profile_path}")
|
||||
|
||||
|
||||
|
||||
# # Launch a standalone browser
|
||||
# asyncio.run(profiler.launch_standalone_browser())
|
||||
|
||||
# # List profiles
|
||||
# profiles = profiler.list_profiles()
|
||||
# for profile in profiles:
|
||||
# print(f"Profile: {profile['name']}, Path: {profile['path']}")
|
||||
|
||||
# # Delete a profile
|
||||
# success = profiler.delete_profile("my-profile")
|
||||
# if success:
|
||||
# print("Profile deleted successfully")
|
||||
# else:
|
||||
# print("Failed to delete profile")
|
||||
Reference in New Issue
Block a user