CEEMEESEEK / app.py
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import csv
import logging
import os
from typing import List, Tuple
import aiohttp
import datetime
import difflib
import hashlib
from pathlib import Path
import feedparser
import gradio as gr
from huggingface_hub import InferenceClient
from sqlalchemy import create_engine, Column, Integer, String, Text, DateTime
from sqlalchemy.orm import declarative_base, sessionmaker
from sqlalchemy.exc import SQLAlchemyError
import validators
import asyncio
# Configure logging
logging.basicConfig(level=logging.INFO,
format='%(asctime)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
# Configuration
HUGGINGFACE_API_KEY = os.getenv("HUGGINGFACE_API_KEY")
DEFAULT_MONITORING_INTERVAL = 300
MAX_MONITORING_INTERVAL = 600
CHANGE_FREQUENCY_THRESHOLD = 3
# Global variables
monitoring_tasks = {}
url_monitoring_intervals = {}
change_counts = {}
history = []
engine = None # Initialize the database engine globally
# Database setup
Base = declarative_base()
def generate_rss_feed():
session = Session()
try:
articles = session.query(Article).order_by(
Article.timestamp.desc()).limit(20).all()
feed = feedparser.FeedParserDict()
feed['title'] = 'Website Changes Feed'
feed['link'] = 'http://yourwebsite.com/feed' # Replace if needed
feed['description'] = 'Feed of changes detected on monitored websites.'
feed['entries'] = [{
'title': article.title,
'link': article.url,
'description': article.content,
'published': article.timestamp
} for article in articles]
return feedparser.FeedGenerator().feed_from_dictionary(
feed).writeString('utf-8')
except SQLAlchemyError as e:
logger.error(f"Database error: {e}")
return None
finally:
session.close()
async def update_feed_content():
return generate_rss_feed()
# Periodic update function
async def periodic_update():
while True:
await asyncio.sleep(300) # Wait for 5 minutes
await update_feed_content()
async def update_feed_content():
return generate_rss_feed()
def start_periodic_task():
loop = asyncio.get_event_loop()
if loop.is_running():
asyncio.create_task(periodic_update())
else:
loop.run_until_complete(periodic_update())
# Start the periodic update task
start_periodic_task()
class Article(Base):
__tablename__ = 'articles'
id = Column(Integer, primary_key=True)
url = Column(String(255), nullable=False)
title = Column(String(255))
content = Column(Text)
hash = Column(String(32))
timestamp = Column(DateTime, default=datetime.datetime.utcnow)
# Utility functions
def sanitize_url(url: str) -> str:
return validators.url(url)
async def fetch_url_content(url: str,
session: aiohttp.ClientSession) -> Tuple[str, str]:
async with session.get(url) as response:
content = await response.text()
soup = BeautifulSoup(content, 'html.parser')
title = soup.title.string if soup.title else "No Title"
return title, content
def calculate_hash(content: str) -> str:
return hashlib.md5(content.encode('utf-8')).hexdigest()
async def save_to_database(url: str, title: str, content: str, hash: str):
session = Session()
try:
article = Article(url=url, title=title, content=content, hash=hash)
session.add(article)
session.commit()
except SQLAlchemyError as e:
logger.error(f"Database error: {e}")
session.rollback()
finally:
session.close()
def save_to_csv(storage_location: str, url: str, title: str, content: str,
timestamp: datetime.datetime):
try:
with open(storage_location, "a", newline='', encoding="utf-8") as csvfile:
csv_writer = csv.writer(csvfile)
csv_writer.writerow([
timestamp.strftime("%Y-%m-%d %H:%M:%S"), url, title, content
])
except Exception as e:
logger.error(f"Error saving to CSV: {e}")
async def monitor_url(url: str, interval: int, storage_location: str,
feed_rss: bool):
previous_hash = ""
async with aiohttp.ClientSession() as session:
while True:
try:
title, content = await fetch_url_content(url, session)
current_hash = calculate_hash(content)
if current_hash != previous_hash:
previous_hash = current_hash
timestamp = datetime.datetime.now()
if feed_rss:
await save_to_database(url, title, content,
current_hash)
if storage_location:
save_to_csv(storage_location, url, title, content,
timestamp)
history.append(
f"Change detected at {url} on {timestamp.strftime('%Y-%m-%d %H:%M:%S')}"
)
logger.info(f"Change detected at {url}")
change_counts[url] = change_counts.get(url, 0) + 1
if change_counts[url] >= CHANGE_FREQUENCY_THRESHOLD:
interval = max(60, interval // 2)
else:
change_counts[url] = 0
interval = min(interval * 2, MAX_MONITORING_INTERVAL)
url_monitoring_intervals[url] = interval
except Exception as e:
logger.error(f"Error monitoring {url}: {e}")
history.append(f"Error monitoring {url}: {e}")
await asyncio.sleep(interval)
async def start_monitoring(urls: List[str], storage_location: str,
feed_rss: bool):
for url in urls:
if url not in monitoring_tasks:
sanitized_url = sanitize_url(url)
if sanitized_url:
task = asyncio.create_task(
monitor_url(sanitized_url, DEFAULT_MONITORING_INTERVAL,
storage_location, feed_rss))
monitoring_tasks[sanitized_url] = task
else:
logger.warning(f"Invalid URL: {url}")
history.append(f"Invalid URL: {url}")
def stop_monitoring(url: str):
if url in monitoring_tasks:
monitoring_tasks[url].cancel()
del monitoring_tasks[url]
async def chatbot_response(message: str, history: List[Tuple[str, str]]):
try:
client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1",
token=HUGGINGFACE_API_KEY)
response = await client.inference(message)
# Format the response as a dictionary
history.append({"role": "user", "content": message}) # Add user message
history.append({
"role": "assistant",
"content": response
}) # Add assistant response
return history, history
except Exception as e:
logger.error(f"Chatbot error: {e}")
history.append({"role": "user", "content": message}) # Add user message
history.append({
"role": "assistant",
"content": "Error: Could not get a response from the chatbot."
}) # Add error message
return history, history
def create_db_engine(db_url):
global engine, Base, Session
try:
engine = create_engine(db_url)
Base.metadata.create_all(engine)
Session = sessionmaker(bind=engine)
return "Database connected successfully!"
except SQLAlchemyError as e:
logger.error(f"Database error: {e}")
return f"Database error: {e}"
# Gradio interface
with gr.Blocks() as demo:
gr.Markdown("# Website Monitor and Chatbot")
with gr.Row():
with gr.Column(): # Side pane for database configuration
db_url = gr.Textbox(label="Database URL",
placeholder="e.g., sqlite:///monitoring.db")
db_connect_button = gr.Button("Connect to Database")
db_status = gr.Textbox(label="Database Status",
interactive=False,
value="Not connected")
db_connect_button.click(create_db_engine,
inputs=db_url,
outputs=db_status)
with gr.Column(): # Main pane for monitoring and chatbot
with gr.Tab("Configuration"):
target_urls = gr.Textbox(
label="Target URLs (comma-separated)",
placeholder=
"https://example.com, https://another-site.com")
storage_location = gr.Textbox(
label="Storage Location (CSV file path)",
placeholder="/path/to/your/file.csv")
feed_rss_checkbox = gr.Checkbox(label="Enable RSS Feed")
start_button = gr.Button("Start Monitoring")
stop_button = gr.Button("Stop Monitoring")
status_text = gr.Textbox(label="Status", interactive=False)
history_text = gr.Textbox(label="History",
lines=10,
interactive=False)
with gr.Tab("User-End View"):
feed_content = gr.JSON(label="RSS Feed Content")
with gr.Tab("Chatbot"):
chatbot_interface = gr.Chatbot(type='messages')
message_input = gr.Textbox(
placeholder="Type your message here...")
send_button = gr.Button("Send")
if __name__ == "__main__":
loop = asyncio.get_event_loop()
if not loop.is_running():
loop.run_until_complete(periodic_update())
demo.launch()