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Update app.py
Browse files
app.py
CHANGED
@@ -35,16 +35,43 @@ class RaindropSearchBot:
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self.newsapi = NewsApiClient(api_key=self.newsapi_key)
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def extract_content_from_url(self, url: str) -> Optional[str]:
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"""Extract main content from a URL using
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try:
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#
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except Exception as e:
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logger.error(f"Error extracting content from {url}: {e}")
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@@ -57,27 +84,33 @@ class RaindropSearchBot:
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url = item.get('link') or item.get('url')
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if not url:
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return item
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# For Raindrop items, use existing excerpt if available
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if source_type == 'raindrop' and item.get('excerpt'):
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content = item['excerpt']
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else:
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content = self.extract_content_from_url(url)
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if not content:
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return item
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# Generate summary focused on the query topic
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try:
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prompt = f"""
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Analyze this content and provide a detailed summary focusing on key points
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to our topic. Include specific details, data, and quotes if relevant.
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Content: {content[:4000]} # Limit content length for token constraints
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"""
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response = self.client.chat.completions.create(
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model="gpt-4o-mini",
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messages=[{"role": "user", "content": prompt}],
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@@ -86,10 +119,12 @@ class RaindropSearchBot:
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)
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item['detailed_summary'] = response.choices[0].message.content
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except Exception as e:
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logger.error(f"Error generating summary: {e}")
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item['detailed_summary'] = "Summary generation failed."
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return item
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except Exception as e:
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self.newsapi = NewsApiClient(api_key=self.newsapi_key)
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def extract_content_from_url(self, url: str) -> Optional[str]:
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"""Extract main content from a URL using BeautifulSoup."""
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try:
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headers = {
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'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'
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}
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response = requests.get(url, headers=headers, timeout=10)
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response.raise_for_status()
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soup = BeautifulSoup(response.text, 'html.parser')
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# Remove unwanted elements
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for element in soup(['script', 'style', 'nav', 'header', 'footer', 'iframe']):
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element.decompose()
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# Get title
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title = soup.title.string if soup.title else ''
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# Get main content
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# First try common content containers
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content_containers = soup.select('article, main, .content, .post-content, .entry-content')
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if content_containers:
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content = content_containers[0].get_text(separator='\n', strip=True)
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else:
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# Fallback to all paragraphs
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paragraphs = soup.find_all('p')
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content = '\n'.join(p.get_text(strip=True) for p in paragraphs)
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# Combine and clean
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full_content = f"{title}\n\n{content}"
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# Clean up the text
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full_content = re.sub(r'\n\s*\n', '\n\n', full_content) # Remove extra newlines
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full_content = re.sub(r'\s+', ' ', full_content) # Normalize whitespace
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return full_content if full_content.strip() else None
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except Exception as e:
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logger.error(f"Error extracting content from {url}: {e}")
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url = item.get('link') or item.get('url')
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if not url:
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return item
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# For Raindrop items, use existing excerpt if available
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if source_type == 'raindrop' and item.get('excerpt'):
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content = item['excerpt']
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else:
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content = self.extract_content_from_url(url)
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if not content:
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logger.warning(f"No content extracted from {url}")
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item['detailed_summary'] = "Content extraction failed."
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return item
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# Generate summary focused on the query topic
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try:
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prompt = f"""
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Analyze this content and provide a detailed summary focusing on key points.
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Content: {content[:4000]} # Limit content length for token constraints
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Requirements:
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1. Focus on the most important facts and findings
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2. Include specific data points and quotes if relevant
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3. Organize the information logically
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4. Keep the summary to 2-3 paragraphs
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5. Highlight any unique insights from this source
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"""
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response = self.client.chat.completions.create(
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model="gpt-4o-mini",
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messages=[{"role": "user", "content": prompt}],
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)
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item['detailed_summary'] = response.choices[0].message.content
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item['processed_content'] = content[:1000] # Store truncated content for later use
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except Exception as e:
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logger.error(f"Error generating summary: {e}")
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item['detailed_summary'] = "Summary generation failed."
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return item
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except Exception as e:
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