Spaces:
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Update app.py
Browse files
app.py
CHANGED
@@ -1,16 +1,19 @@
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import gradio as gr
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from openai import OpenAI
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import requests
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import json
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import os
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import logging
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from typing import Dict, List,
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from newspaper import Article
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import markdown
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from datetime import datetime
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from bs4 import BeautifulSoup
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from googlesearch import search
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from newsapi import NewsApiClient
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# Set up logging
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logging.basicConfig(
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@@ -23,10 +26,9 @@ class RaindropSearchBot:
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def __init__(self):
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self.openai_api_key = os.getenv('openaikey')
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self.raindrop_api_token = os.getenv('raindroptoken')
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self.serpapi_key = os.getenv('serpapikey')
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self.newsapi_key = os.getenv('newsapikey')
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if not all([self.openai_api_key, self.raindrop_api_token, self.
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raise EnvironmentError(
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"Missing required environment variables. Please ensure all API keys are set."
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)
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@@ -34,6 +36,38 @@ class RaindropSearchBot:
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self.client = OpenAI(api_key=self.openai_api_key)
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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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@@ -84,18 +118,18 @@ 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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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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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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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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logger.error(f"Error processing item: {e}")
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return item
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def get_google_results(self, query: str, num_results: int = 5) -> List[Dict]:
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"""Get Google search results using googlesearch-python."""
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try:
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search_results = []
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for result in search(query, num_results=num_results, advanced=True):
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search_results.append({
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'title': result.title,
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'link': result.url,
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'snippet': result.description
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})
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return search_results
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except Exception as e:
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logger.error(f"Google search error: {e}")
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return []
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def get_news_results(self, query: str, num_results: int = 5) -> List[Dict]:
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"""Get news articles using NewsAPI."""
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try:
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news_results = self.newsapi.get_everything(
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q=query,
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language='en',
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sort_by='relevancy',
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page_size=num_results
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)
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return news_results.get('articles', [])
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except Exception as e:
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logger.error(f"News API error: {e}")
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return []
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def generate_search_query(self, user_request: str) -> str:
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"""Convert user request to optimized search terms."""
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logger.info(f"Generating search query for: {user_request}")
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prompt = f"""
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You are a search expert. Create a search query to find relevant documents about:
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{user_request}
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Guidelines:
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- Focus on key concepts and synonyms
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- Use simple keywords that would appear in titles or descriptions
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- Avoid complex operators or special characters
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- Return only the search terms, no explanation
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- Include alternative phrasings
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- Keep it concise (max 3-4 key terms/phrases)
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Return only the search query terms.
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"""
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try:
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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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temperature=0.3,
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max_tokens=50
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)
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search_query = response.choices[0].message.content.strip()
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logger.info(f"Generated search query: {search_query}")
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return search_query
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except Exception as e:
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logger.error(f"Error generating search query: {e}")
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return user_request
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def search_raindrop(self, search_query: str) -> List[Dict]:
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"""Search Raindrop.io with enhanced error handling and logging."""
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logger.error(f"Search error: {e}")
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return []
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def analyze_results(self, results: List[Dict], google_results: List[Dict],
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news_results: List[Dict], user_query: str) -> str:
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"""Generate an analysis of all search results."""
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if not any([results, google_results, news_results]):
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return "No relevant results found. Try modifying your search terms."
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# Create context for analysis
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context = f"Based on the search query: '{user_query}'\n\n"
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context += "Analyze these sources:\n\n"
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# Add Raindrop results
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if results:
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context += "Bookmarked Sources:\n"
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for item in results:
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context += f"Title: {item.get('title', 'No title')}\n"
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if item.get('excerpt'):
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context += f"Content: {item['excerpt'][:500]}...\n"
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context += f"Created: {item.get('created', 'No date')}\n\n"
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# Add Google results
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if google_results:
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context += "Web Sources:\n"
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for item in google_results:
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context += f"Title: {item.get('title', 'No title')}\n"
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if item.get('snippet'):
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context += f"Content: {item['snippet']}\n\n"
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# Add News results
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if news_results:
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context += "News Sources:\n"
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for item in news_results:
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context += f"Title: {item.get('title', 'No title')}\n"
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if item.get('description'):
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context += f"Content: {item['description']}\n"
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context += f"Published: {item.get('publishedAt', 'No date')}\n\n"
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try:
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prompt = f"""
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Based on all available sources, provide a comprehensive analysis of {user_query}.
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Requirements:
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1. Focus on the most relevant and recent information
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2. Organize the response by key themes
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3. Include only factual information from the sources
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4. Highlight any significant developments or changes
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5. Note any conflicts or differences between sources
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6. Prioritize official sources and recent developments
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Context:
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{context}
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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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temperature=0.5,
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max_tokens=1000
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)
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analysis = response.choices[0].message.content
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return analysis
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except Exception as e:
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logger.error(f"Analysis generation error: {e}")
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return "Error generating analysis."
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def format_results(self, results: Tuple[List[Dict], List[Dict], List[Dict]],
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essay: str) -> str:
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"""Format the essay and results with detailed summaries."""
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raindrop_results, google_results, news_results = results
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output = f"{essay}\n\n"
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output += "---\n\n"
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output += "# References and Detailed Summaries\n\n"
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ref_counter = 1
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# Format Raindrop results
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if raindrop_results:
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output += "## π Bookmarked Sources\n\n"
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for item in raindrop_results:
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output += f"### [{ref_counter}] {item.get('title', 'No Title')}\n"
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output += f"**Link**: {item.get('link')}\n"
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if item.get('tags'):
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output += f"**Tags**: {', '.join(item['tags'])}\n"
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if item.get('created'):
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output += f"**Created**: {item['created'][:10]}\n"
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output += "\n**Summary**:\n"
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output += f"{item.get('detailed_summary', 'No summary available.')}\n\n"
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ref_counter += 1
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# Format Google results
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if google_results:
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output += "## π Web Sources\n\n"
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for item in google_results:
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output += f"### [{ref_counter}] {item.get('title', 'No Title')}\n"
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output += f"**Link**: {item.get('link')}\n"
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output += "\n**Summary**:\n"
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output += f"{item.get('detailed_summary', 'No summary available.')}\n\n"
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ref_counter += 1
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# Format News results
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if news_results:
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output += "## π° Recent News\n\n"
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for item in news_results:
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output += f"### [{ref_counter}] {item.get('title', 'No Title')}\n"
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output += f"**Link**: {item.get('url')}\n"
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if item.get('source', {}).get('name'):
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output += f"**Source**: {item['source']['name']}\n"
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if item.get('publishedAt'):
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output += f"**Published**: {item['publishedAt'][:10]}\n"
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output += "\n**Summary**:\n"
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output += f"{item.get('detailed_summary', 'No summary available.')}\n\n"
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ref_counter += 1
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return output
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def process_all_results(self, raindrop_results: List[Dict],
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google_results: List[Dict],
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news_results: List[Dict]) -> Tuple[List[Dict], List[Dict], List[Dict]]:
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except Exception as e:
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logger.error(f"Error generating essay: {e}")
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return "Error generating analysis."
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def process_request(self, user_request: str) -> str:
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"""Process the user request with enhanced content collection and analysis."""
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try:
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logger.error(f"Error processing request: {e}", exc_info=True)
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return f"An error occurred while processing your request. Please try again."
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# Initialize bot
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bot = RaindropSearchBot()
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# Launch the interface
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if __name__ == "__main__":
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demo.launch(share=True)
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python
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import gradio as gr
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from openai import OpenAI
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import requests
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import json
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import os
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import logging
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from typing import Dict, List, Optional, Tuple
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from datetime import datetime
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from bs4 import BeautifulSoup
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from googlesearch import search
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from newsapi import NewsApiClient
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import markdown
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import re
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import time
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# Set up logging
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logging.basicConfig(
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def __init__(self):
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self.openai_api_key = os.getenv('openaikey')
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self.raindrop_api_token = os.getenv('raindroptoken')
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self.newsapi_key = os.getenv('newsapikey')
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if not all([self.openai_api_key, self.raindrop_api_token, self.newsapi_key]):
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raise EnvironmentError(
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"Missing required environment variables. Please ensure all API keys are set."
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)
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self.client = OpenAI(api_key=self.openai_api_key)
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self.newsapi = NewsApiClient(api_key=self.newsapi_key)
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def get_google_results(self, query: str, num_results: int = 5) -> List[Dict]:
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"""Get Google search results using googlesearch-python."""
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try:
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search_results = []
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for result in search(query, num_results=num_results, advanced=True):
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search_results.append({
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'title': result.title,
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'link': result.url,
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'snippet': result.description
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})
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return search_results
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except Exception as e:
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logger.error(f"Google search error: {e}")
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return []
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def get_news_results(self, query: str, num_results: int = 5) -> List[Dict]:
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"""Get news articles using NewsAPI."""
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try:
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news_results = self.newsapi.get_everything(
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q=query,
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language='en',
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sort_by='relevancy',
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page_size=num_results
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)
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return news_results.get('articles', [])
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except Exception as e:
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logger.error(f"News API error: {e}")
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return []
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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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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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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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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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logger.error(f"Error processing item: {e}")
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return item
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167 |
|
168 |
def search_raindrop(self, search_query: str) -> List[Dict]:
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169 |
"""Search Raindrop.io with enhanced error handling and logging."""
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|
213 |
logger.error(f"Search error: {e}")
|
214 |
return []
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|
216 |
def process_all_results(self, raindrop_results: List[Dict],
|
217 |
google_results: List[Dict],
|
218 |
news_results: List[Dict]) -> Tuple[List[Dict], List[Dict], List[Dict]]:
|
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|
292 |
except Exception as e:
|
293 |
logger.error(f"Error generating essay: {e}")
|
294 |
return "Error generating analysis."
|
295 |
+
|
296 |
+
def format_results(self, results: Tuple[List[Dict], List[Dict], List[Dict]],
|
297 |
+
essay: str) -> str:
|
298 |
+
"""Format the essay and results with detailed summaries."""
|
299 |
+
raindrop_results, google_results, news_results = results
|
300 |
+
|
301 |
+
output = f"{essay}\n\n"
|
302 |
+
output += "---\n\n"
|
303 |
+
output += "# References and Detailed Summaries\n\n"
|
304 |
+
|
305 |
+
ref_counter = 1
|
306 |
+
|
307 |
+
# Format Raindrop results
|
308 |
+
if raindrop_results:
|
309 |
+
output += "## π Bookmarked Sources\n\n"
|
310 |
+
for item in raindrop_results:
|
311 |
+
output += f"### [{ref_counter}] {item.get('title', 'No Title')}\n"
|
312 |
+
output += f"**Link**: {item.get('link')}\n"
|
313 |
+
if item.get('tags'):
|
314 |
+
output += f"**Tags**: {', '.join(item['tags'])}\n"
|
315 |
+
if item.get('created'):
|
316 |
+
output += f"**Created**: {item['created'][:10]}\n"
|
317 |
+
output += "\n**Summary**:\n"
|
318 |
+
output += f"{item.get('detailed_summary', 'No summary available.')}\n\n"
|
319 |
+
ref_counter += 1
|
320 |
+
|
321 |
+
# Format Google results
|
322 |
+
if google_results:
|
323 |
+
output += "## π Web Sources\n\n"
|
324 |
+
for item in google_results:
|
325 |
+
output += f"### [{ref_counter}] {item.get('title', 'No Title')}\n"
|
326 |
+
output += f"**Link**: {item.get('link')}\n"
|
327 |
+
output += "\n**Summary**:\n"
|
328 |
+
output += f"{item.get('detailed_summary', 'No summary available.')}\n\n"
|
329 |
+
ref_counter += 1
|
330 |
+
|
331 |
+
# Format News results
|
332 |
+
if news_results:
|
333 |
+
output += "## π° Recent News\n\n"
|
334 |
+
for item in news_results:
|
335 |
+
output += f"### [{ref_counter}] {item.get('title', 'No Title')}\n"
|
336 |
+
output += f"**Link**: {item.get('url')}\n"
|
337 |
+
if item.get('source', {}).get('name'):
|
338 |
+
output += f"**Source**: {item['source']['name']}\n"
|
339 |
+
if item.get('publishedAt'):
|
340 |
+
output += f"**Published**: {item['publishedAt'][:10]}\n"
|
341 |
+
output += "\n**Summary**:\n"
|
342 |
+
output += f"{item.get('detailed_summary', 'No summary available.')}\n\n"
|
343 |
+
ref_counter += 1
|
344 |
+
|
345 |
+
return output
|
346 |
+
|
347 |
def process_request(self, user_request: str) -> str:
|
348 |
"""Process the user request with enhanced content collection and analysis."""
|
349 |
try:
|
|
|
373 |
logger.error(f"Error processing request: {e}", exc_info=True)
|
374 |
return f"An error occurred while processing your request. Please try again."
|
375 |
|
376 |
+
def generate_search_query(self, user_request: str) -> str:
|
377 |
+
"""Convert user request to optimized search terms."""
|
378 |
+
logger.info(f"Generating search query for: {user_request}")
|
379 |
+
|
380 |
+
prompt = f"""
|
381 |
+
You are a search expert. Create a search query to find relevant documents about:
|
382 |
+
{user_request}
|
383 |
+
|
384 |
+
Guidelines:
|
385 |
+
- Focus on key concepts and synonyms
|
386 |
+
- Use simple keywords that would appear in titles or descriptions
|
387 |
+
- Avoid complex operators or special characters
|
388 |
+
- Return only the search terms, no explanation
|
389 |
+
- Include alternative phrasings
|
390 |
+
- Keep it concise (max 3-4 key terms/phrases)
|
391 |
+
|
392 |
+
Return only the search query terms.
|
393 |
+
"""
|
394 |
+
|
395 |
+
try:
|
396 |
+
response = self.client.chat.completions.create(
|
397 |
+
model="gpt-4o-mini",
|
398 |
+
messages=[{"role": "user", "content": prompt}],
|
399 |
+
temperature=0.3,
|
400 |
+
max_tokens=50
|
401 |
+
)
|
402 |
+
search_query = response.choices[0].message.content.strip()
|
403 |
+
logger.info(f"Generated search query: {search_query}")
|
404 |
+
return search_query
|
405 |
+
except Exception as e:
|
406 |
+
logger.error(f"Error generating search query: {e}")
|
407 |
+
return user_request
|
408 |
+
|
409 |
# Initialize bot
|
410 |
bot = RaindropSearchBot()
|
411 |
|
|
|
448 |
|
449 |
# Launch the interface
|
450 |
if __name__ == "__main__":
|
451 |
+
demo.launch(share=True)
|