Update app.py
Browse files
app.py
CHANGED
@@ -5,30 +5,32 @@ from typing import List, Dict, Tuple
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import pandas as pd
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from datetime import datetime
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import os
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# Set up logging
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logging.basicConfig(
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level=logging.
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format='%(
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datefmt='%Y-%m-%d %H:%M:%S'
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)
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logger = logging.getLogger(__name__)
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# Get
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NEO4J_URL = os.
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NEO4J_USER = os.
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NEO4J_PASSWORD = os.
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def format_neo4j_datetime(dt) -> str:
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"""Convert Neo4j datetime to string format."""
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if dt is None:
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logger.info("Received None datetime")
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return 'Unknown date'
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try:
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logger.info(f"Formatting datetime: {dt} of type {type(dt)}")
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if hasattr(dt, 'to_native'):
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dt = dt.to_native()
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logger.info(f"Converted to native: {dt} of type {type(dt)}")
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return dt.strftime('%Y-%m-%d')
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except Exception as e:
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logger.warning(f"Error formatting datetime: {e}")
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@@ -43,6 +45,85 @@ def format_interest_list(interests: set, max_items: int = 10) -> str:
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return ', '.join(sorted_interests)
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return f"{', '.join(sorted_interests[:max_items])} (+{len(sorted_interests) - max_items} more)"
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class QuestionRecommender:
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def __init__(self):
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try:
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@@ -50,126 +131,12 @@ class QuestionRecommender:
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NEO4J_URL,
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auth=(NEO4J_USER, NEO4J_PASSWORD)
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)
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logger.info("Initializing QuestionRecommender with debug database")
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# Test connection immediately
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self.driver.verify_connectivity()
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logger.info("Successfully connected to Neo4j database")
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self.verify_connection()
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# Inspect question types on initialization
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self.inspect_question_types()
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except Exception as e:
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logger.error(f"Failed to initialize database connection: {str(e)}")
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raise
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def verify_connection(self):
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"""Verify database connection and log basic statistics."""
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try:
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with self.driver.session() as session:
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# First try a simple query to verify connection
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test_result = session.run("MATCH (n) RETURN count(n) as count").single()
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if not test_result:
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raise Exception("Could not execute test query")
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logger.info(f"Database contains {test_result['count']} total nodes")
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# Get database statistics with relationship counts
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stats = session.run("""
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// Count nodes
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MATCH (u:User)
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WITH COUNT(u) as user_count
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MATCH (k:Keyword)
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WITH user_count, COUNT(k) as keyword_count
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MATCH (q:Question)
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WITH user_count, keyword_count, COUNT(q) as question_count
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MATCH (t:Topic)
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WITH user_count, keyword_count, question_count, COUNT(t) as topic_count
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// Count relationships
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OPTIONAL MATCH ()-[r:INTERESTED_IN_KEYWORD]->()
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WITH user_count, keyword_count, question_count, topic_count, COUNT(r) as keyword_rel_count
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OPTIONAL MATCH ()-[r:INTERESTED_IN_TOPIC]->()
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WITH user_count, keyword_count, question_count, topic_count, keyword_rel_count, COUNT(r) as topic_rel_count
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OPTIONAL MATCH ()-[r:HAS_KEYWORD]->()
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WITH user_count, keyword_count, question_count, topic_count, keyword_rel_count, topic_rel_count, COUNT(r) as question_keyword_count
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OPTIONAL MATCH ()-[r:HAS_TOPIC]->()
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RETURN
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user_count, keyword_count, question_count, topic_count,
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keyword_rel_count, topic_rel_count,
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question_keyword_count, COUNT(r) as question_topic_count
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""").single()
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if not stats:
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raise Exception("Could not retrieve database statistics")
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logger.info("=== Database Statistics ===")
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logger.info(f"Nodes:")
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logger.info(f" Users: {stats['user_count']}")
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logger.info(f" Keywords: {stats['keyword_count']}")
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logger.info(f" Questions: {stats['question_count']}")
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logger.info(f" Topics: {stats['topic_count']}")
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logger.info(f"\nRelationships:")
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logger.info(f" User->Keyword (INTERESTED_IN_KEYWORD): {stats['keyword_rel_count']}")
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logger.info(f" User->Topic (INTERESTED_IN_TOPIC): {stats['topic_rel_count']}")
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logger.info(f" Question->Keyword (HAS_KEYWORD): {stats['question_keyword_count']}")
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logger.info(f" Question->Topic (HAS_TOPIC): {stats['question_topic_count']}")
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except Exception as e:
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logger.error(f"Database verification failed: {str(e)}")
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logger.error(f"URL: {NEO4J_URL}")
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logger.error(f"User: {NEO4J_USER}")
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raise Exception(f"Failed to verify database connection: {str(e)}")
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def inspect_question_types(self):
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"""Inspect different types of questions and their attributes in the database."""
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with self.driver.session() as session:
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try:
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# Get all distinct question types and their properties
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result = session.run("""
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MATCH (q:Question)
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WITH DISTINCT keys(q) as props, labels(q) as types
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RETURN types, props, count(*) as count
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ORDER BY count DESC
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""")
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logger.info("\n=== Question Types and Properties ===")
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for record in result:
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types = record["types"]
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props = record["props"]
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count = record["count"]
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logger.info(f"\nType: {types}")
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logger.info(f"Count: {count}")
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logger.info("Properties:")
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for prop in props:
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# Get a sample value for this property
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sample = session.run("""
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MATCH (q:Question)
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WHERE $prop in keys(q)
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RETURN q[$prop] as value
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LIMIT 1
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""", prop=prop).single()
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value = sample["value"] if sample else None
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value_type = type(value).__name__ if value is not None else "None"
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logger.info(f" - {prop}: {value_type} (example: {str(value)[:100]}{'...' if str(value)[100:] else ''})")
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# Get relationships specific to different question types
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result = session.run("""
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MATCH (q:Question)-[r]->(target)
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WITH DISTINCT type(r) as rel_type, labels(target) as target_labels, count(*) as count
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RETURN rel_type, target_labels, count
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ORDER BY count DESC
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""")
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logger.info("\n=== Question Relationships ===")
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for record in result:
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rel_type = record["rel_type"]
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target_labels = record["target_labels"]
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count = record["count"]
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logger.info(f"Relationship: {rel_type} -> {target_labels} (Count: {count})")
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except Exception as e:
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logger.error(f"Error inspecting question types: {str(e)}")
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raise
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def close(self):
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self.driver.close()
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"""Get list of all users with interest counts."""
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with self.driver.session() as session:
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try:
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# Get users with their interest counts using proper relationship patterns
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result = session.run("""
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MATCH (u:User)
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OPTIONAL MATCH (u)-[r:INTERESTED_IN_KEYWORD|INTERESTED_IN_TOPIC]->(interest)
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) for record in result if record["username"]]
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if not users_with_counts:
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logger.warning("No users found with interests")
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return []
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logger.info(f"Retrieved {len(users_with_counts)} users with interests")
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logger.info("Top 5 users by interest count:")
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for username, kw_count, topic_count in users_with_counts[:5]:
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logger.info(f" - {username}: {kw_count} keywords, {topic_count} topics")
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# Format usernames with their counts
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return [
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f"{username} ({kw_count} keywords, {topic_count} topics)"
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for username, kw_count, topic_count in users_with_counts
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def get_user_interests(self, username: str) -> Dict[str, set]:
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"""Get keywords and topics a user is interested in."""
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with self.driver.session() as session:
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# Get keywords the user is interested in
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keyword_result = session.run("""
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MATCH (u:User {name: $username})-[:INTERESTED_IN_KEYWORD]->(k:Keyword)
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RETURN DISTINCT k.keyword as keyword
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""", username=username)
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keywords = {str(record["keyword"]) for record in keyword_result if record["keyword"]}
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# Log keyword count for debugging
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logger.debug(f"Found {len(keywords)} keywords for user {username}")
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# Get topics the user is interested in
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topic_result = session.run("""
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MATCH (u:User {name: $username})-[:INTERESTED_IN_TOPIC]->(t:Topic)
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RETURN DISTINCT t.topic as topic
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""", username=username)
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topics = {str(record["topic"]) for record in topic_result if record["topic"]}
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# Log topic count for debugging
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logger.debug(f"Found {len(topics)} topics for user {username}")
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return {"keywords": keywords or set(), "topics": topics or set()}
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def find_common_questions(self, user1: str, user2: str, max_questions: int = 5) -> List[Dict]:
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"""Find questions to recommend based on common interests
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with self.driver.session() as session:
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user_check = session.run("""
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MATCH (u1:User {name: $user1})
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MATCH (u2:User {name: $user2})
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OPTIONAL MATCH (u1)-[r1:INTERESTED_IN_KEYWORD|INTERESTED_IN_TOPIC]->(interest1)
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OPTIONAL MATCH (u2)-[r2:INTERESTED_IN_KEYWORD|INTERESTED_IN_TOPIC]->(interest2)
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RETURN
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COUNT(DISTINCT u1) as user1_exists,
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COUNT(DISTINCT u2) as user2_exists,
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COUNT(DISTINCT interest1) as user1_interests,
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COUNT(DISTINCT interest2) as user2_interests
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""", user1=user1, user2=user2).single()
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if not (user_check and user_check['user1_exists'] and user_check['user2_exists']):
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logger.error(f"One or both users not found: {user1}, {user2}")
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return []
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logger.info(f"User {user1} has {user_check['user1_interests']} total interests")
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logger.info(f"User {user2} has {user_check['user2_interests']} total interests")
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# Advanced question recommendation query using Neo4j path finding and scoring
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questions_query = """
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// Find all interests (both keywords and topics) for both users
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MATCH (u1:User {name: $user1})
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MATCH (u2:User {name: $user2})
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// Get all interests for both users
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OPTIONAL MATCH (u1)-[r1:INTERESTED_IN_KEYWORD|INTERESTED_IN_TOPIC]->(interest1)
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OPTIONAL MATCH (u2)-[r2:INTERESTED_IN_KEYWORD|INTERESTED_IN_TOPIC]->(interest2)
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WITH u1, u2,
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COLLECT(DISTINCT interest1) as u1_interests,
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COLLECT(DISTINCT interest2) as u2_interests
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WITH q, interest, type(r) as rel_type,
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CASE WHEN interest IN u1_interests AND interest IN u2_interests THEN 2.0 ELSE 1.0 END as interest_weight
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WITH q, collect({interest: interest, weight: interest_weight, type: rel_type}) as interests,
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sum(interest_weight) as base_score
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RETURN q, interests, base_score
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ORDER BY base_score * rand() DESC
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LIMIT 15 // Increased from 10 to get more variety
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UNION
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WITH u1, u2, u1_interests, u2_interests
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UNWIND u1_interests + u2_interests as interest
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MATCH (q:Question)-[r:HAS_KEYWORD|HAS_TOPIC]->(interest)
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WHERE
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q.source = 'trivia' AND
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(
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(interest IN u1_interests AND interest IN u2_interests) OR
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(interest IN u1_interests AND EXISTS((q)-[:HAS_KEYWORD|HAS_TOPIC]->()<-[:INTERESTED_IN_KEYWORD|INTERESTED_IN_TOPIC]-(u2))) OR
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(interest IN u2_interests AND EXISTS((q)-[:HAS_KEYWORD|HAS_TOPIC]->()<-[:INTERESTED_IN_KEYWORD|INTERESTED_IN_TOPIC]-(u1)))
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)
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WITH q, interest, type(r) as rel_type,
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CASE WHEN interest IN u1_interests AND interest IN u2_interests THEN 2.0 ELSE 1.0 END as interest_weight
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WITH q, collect({interest: interest, weight: interest_weight, type: rel_type}) as interests,
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sum(interest_weight) as base_score
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RETURN q, interests, base_score
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ORDER BY base_score * rand() DESC
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LIMIT 15 // Increased from 10 to get more variety
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UNION
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WITH u1, u2, u1_interests, u2_interests
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UNWIND u1_interests + u2_interests as interest
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MATCH (q:Question)-[r:HAS_KEYWORD|HAS_TOPIC]->(interest)
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WHERE
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q.source = 'wikipedia' AND
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(
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(interest IN u1_interests AND interest IN u2_interests) OR
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(interest IN u1_interests AND EXISTS((q)-[:HAS_KEYWORD|HAS_TOPIC]->()<-[:INTERESTED_IN_KEYWORD|INTERESTED_IN_TOPIC]-(u2))) OR
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(interest IN u2_interests AND EXISTS((q)-[:HAS_KEYWORD|HAS_TOPIC]->()<-[:INTERESTED_IN_KEYWORD|INTERESTED_IN_TOPIC]-(u1)))
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)
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WITH q, interest, type(r) as rel_type,
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CASE WHEN interest IN u1_interests AND interest IN u2_interests THEN 2.0 ELSE 1.0 END as interest_weight
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WITH q, collect({interest: interest, weight: interest_weight, type: rel_type}) as interests,
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sum(interest_weight) as base_score
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RETURN q, interests, base_score
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ORDER BY base_score * rand() DESC
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LIMIT 15 // Increased from 10 to get more variety
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UNION
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WITH u1, u2, u1_interests, u2_interests
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UNWIND u1_interests + u2_interests as interest
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MATCH (q:Question)-[r:HAS_KEYWORD|HAS_TOPIC]->(interest)
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WHERE
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q.source = 'reddit' AND
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(
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(interest IN u1_interests AND interest IN u2_interests) OR
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(interest IN u1_interests AND EXISTS((q)-[:HAS_KEYWORD|HAS_TOPIC]->()<-[:INTERESTED_IN_KEYWORD|INTERESTED_IN_TOPIC]-(u2))) OR
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(interest IN u2_interests AND EXISTS((q)-[:HAS_KEYWORD|HAS_TOPIC]->()<-[:INTERESTED_IN_KEYWORD|INTERESTED_IN_TOPIC]-(u1)))
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)
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WITH q, interest, type(r) as rel_type,
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CASE WHEN interest IN u1_interests AND interest IN u2_interests THEN 2.0 ELSE 1.0 END as interest_weight
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WITH q, collect({interest: interest, weight: interest_weight, type: rel_type}) as interests,
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sum(interest_weight) as base_score
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RETURN q, interests, base_score
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ORDER BY base_score * rand() DESC
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LIMIT 15 // Increased from 10 to get more variety
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}
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// Calculate temporal relevance for the combined results
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WITH q, interests, base_score,
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CASE
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WHEN q.created_utc_ts IS NOT NULL
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THEN base_score * (1.0 + 0.1 * (1.0 - duration.between(q.created_utc_ts, datetime()).days / 365.0))
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ELSE base_score
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END as temporal_score
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// Add source-specific random boost to ensure better mixing
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CASE q.source
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WHEN 'stack_exchange' THEN rand() * 0.4
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WHEN 'trivia' THEN rand() * 0.4
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WHEN 'wikipedia' THEN rand() * 0.4
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WHEN 'reddit' THEN rand() * 0.4
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ELSE rand() * 0.4
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END as source_random_boost
|
379 |
-
|
380 |
-
// Return results with all metadata
|
381 |
-
WITH q, interests, temporal_score, source_random_boost,
|
382 |
-
temporal_score * (0.6 + 0.8 * rand()) + source_random_boost as final_score
|
383 |
RETURN DISTINCT
|
384 |
q.title as title,
|
385 |
q.body as body,
|
@@ -399,131 +245,25 @@ class QuestionRecommender:
|
|
399 |
WHEN i.type = 'HAS_KEYWORD' THEN 'keyword'
|
400 |
ELSE 'topic'
|
401 |
END] as interest_types,
|
402 |
-
|
403 |
-
ORDER BY
|
404 |
LIMIT $max_questions
|
405 |
-
"""
|
406 |
-
|
407 |
-
questions = [dict(record) for record in session.run(questions_query,
|
408 |
-
user1=user1,
|
409 |
-
user2=user2,
|
410 |
-
max_questions=max_questions)]
|
411 |
|
412 |
-
|
413 |
-
first_q = questions[0]
|
414 |
-
logger.info(f"Sample question:")
|
415 |
-
logger.info(f"Title: {first_q.get('title', 'No title')}")
|
416 |
-
logger.info(f"Author: {first_q.get('author', 'No author')}")
|
417 |
-
logger.info(f"Score: {first_q.get('relevance_score', 0)}")
|
418 |
-
logger.info(f"Interests: {first_q.get('matching_interests', [])}")
|
419 |
-
|
420 |
-
logger.info(f"Found {len(questions)} questions with common interests")
|
421 |
-
return questions
|
422 |
-
|
423 |
-
def process_body(text, title):
|
424 |
-
"""Process question body to handle images and HTML."""
|
425 |
-
if not text:
|
426 |
-
logger.warning(f"Empty body for question: {title}")
|
427 |
-
return ""
|
428 |
-
|
429 |
-
try:
|
430 |
-
from bs4 import BeautifulSoup
|
431 |
-
|
432 |
-
# Parse the HTML content
|
433 |
-
soup = BeautifulSoup(str(text), 'html.parser')
|
434 |
-
|
435 |
-
# Function to fix Stack Exchange URLs
|
436 |
-
def fix_stack_exchange_url(url):
|
437 |
-
if not url:
|
438 |
-
return url
|
439 |
-
if url.startswith(('http://', 'https://')):
|
440 |
-
return url
|
441 |
-
if url.startswith('//'):
|
442 |
-
return 'https:' + url
|
443 |
-
if url.startswith('/'):
|
444 |
-
return 'https://i.stack.imgur.com' + url
|
445 |
-
return 'https://i.stack.imgur.com/' + url
|
446 |
-
|
447 |
-
# Find all img tags and replace with preview cards
|
448 |
-
for img in soup.find_all('img'):
|
449 |
-
src = img.get('src', '')
|
450 |
-
if not src:
|
451 |
-
continue
|
452 |
-
|
453 |
-
fixed_src = fix_stack_exchange_url(src)
|
454 |
-
alt_text = img.get('alt', '').strip()
|
455 |
-
if not alt_text or alt_text.lower() == 'enter image description here':
|
456 |
-
alt_text = 'Question image'
|
457 |
-
|
458 |
-
# Create an image preview card
|
459 |
-
preview_html = f"""
|
460 |
-
<div class="image-preview" style="margin: 10px 0; padding: 10px; background: rgba(30, 41, 59, 0.4); border-radius: 6px;">
|
461 |
-
<div style="display: flex; align-items: center; margin-bottom: 8px;">
|
462 |
-
<span style="font-size: 20px; margin-right: 8px;">πΌοΈ</span>
|
463 |
-
<span style="color: #93c5fd;">{alt_text}</span>
|
464 |
-
</div>
|
465 |
-
<a href="{fixed_src}" target="_blank" rel="noopener noreferrer"
|
466 |
-
style="color: #60a5fa; text-decoration: none;">View image</a>
|
467 |
-
</div>
|
468 |
-
"""
|
469 |
-
|
470 |
-
new_soup = BeautifulSoup(preview_html, 'html.parser')
|
471 |
-
img.replace_with(new_soup)
|
472 |
-
|
473 |
-
# Style other elements
|
474 |
-
for link in soup.find_all('a'):
|
475 |
-
if 'View Image' not in (link.get_text() or ''):
|
476 |
-
href = link.get('href', '')
|
477 |
-
if href and not href.startswith(('http://', 'https://')):
|
478 |
-
link['href'] = fix_stack_exchange_url(href)
|
479 |
-
link['target'] = '_blank'
|
480 |
-
link['rel'] = 'noopener noreferrer'
|
481 |
-
link['style'] = 'color: #60a5fa; text-decoration: none;'
|
482 |
-
|
483 |
-
# Add paragraph styling
|
484 |
-
for p in soup.find_all(['p', 'div']):
|
485 |
-
if not any(cls in (p.get('class', []) or []) for cls in ['image-preview', 'question-card']):
|
486 |
-
current_style = p.get('style', '')
|
487 |
-
p['style'] = f"{current_style}; margin: 0.8em 0; line-height: 1.6; color: #e2e8f0;"
|
488 |
-
|
489 |
-
# Add list styling
|
490 |
-
for ul in soup.find_all(['ul', 'ol']):
|
491 |
-
ul['style'] = 'margin: 0.8em 0; padding-left: 1.5em; color: #e2e8f0;'
|
492 |
-
|
493 |
-
for li in soup.find_all('li'):
|
494 |
-
li['style'] = 'margin: 0.4em 0; line-height: 1.6; color: #e2e8f0;'
|
495 |
-
|
496 |
-
# Add code block styling
|
497 |
-
for code in soup.find_all(['code', 'pre']):
|
498 |
-
code['style'] = 'background: rgba(30, 41, 59, 0.5); padding: 0.2em 0.4em; border-radius: 4px; font-family: monospace; color: #e2e8f0;'
|
499 |
-
|
500 |
-
return str(soup)
|
501 |
-
|
502 |
-
except Exception as e:
|
503 |
-
logger.error(f"Error processing question body: {str(e)}")
|
504 |
-
return str(text) if text else ""
|
505 |
|
506 |
def format_question(q: Dict) -> str:
|
507 |
"""Format a question for display based on its source."""
|
508 |
try:
|
509 |
-
# Extract and validate basic question data
|
510 |
title = q.get('title', 'Untitled')
|
511 |
-
source = q.get('source', '').lower()
|
512 |
|
513 |
-
# Log available fields for debugging
|
514 |
-
logger.info(f"Question fields: {list(q.keys())}")
|
515 |
-
if 'created_utc_ts' in q:
|
516 |
-
logger.info(f"Raw created_utc_ts value: {q['created_utc_ts']}")
|
517 |
-
|
518 |
-
# Format metadata section based on source
|
519 |
metadata_html = ""
|
520 |
content_html = ""
|
521 |
|
522 |
-
# Default metadata for questions with author/date
|
523 |
if 'author' in q or 'created_utc_ts' in q:
|
524 |
author = q.get('author', 'Unknown author')
|
525 |
created_date = format_neo4j_datetime(q.get('created_utc_ts'))
|
526 |
-
logger.info(f"Question {title}: author={author}, date={created_date}")
|
527 |
upvotes = q.get('upvotes', 0)
|
528 |
num_comments = q.get('num_comments', 0)
|
529 |
|
@@ -539,7 +279,6 @@ def format_question(q: Dict) -> str:
|
|
539 |
</div>
|
540 |
"""
|
541 |
|
542 |
-
# Handle content based on source and available fields
|
543 |
if source == "stack_exchange":
|
544 |
body = q.get('body', '')
|
545 |
if body:
|
@@ -548,12 +287,10 @@ def format_question(q: Dict) -> str:
|
|
548 |
{process_body(body, title)}
|
549 |
</div>
|
550 |
"""
|
551 |
-
|
552 |
elif source == "trivia":
|
553 |
correct_answer = q.get('correct_answer', '')
|
554 |
incorrect_answers = q.get('incorrect_answers', [])
|
555 |
|
556 |
-
# Create answer options HTML
|
557 |
answers = [correct_answer] + incorrect_answers if incorrect_answers else [correct_answer]
|
558 |
answers_html = "".join([
|
559 |
f"""
|
@@ -572,58 +309,21 @@ def format_question(q: Dict) -> str:
|
|
572 |
{answers_html}
|
573 |
</div>
|
574 |
"""
|
575 |
-
|
576 |
-
elif source == "wikipedia":
|
577 |
-
correct_answer = q.get('correct_answer', '')
|
578 |
-
if correct_answer:
|
579 |
-
content_html = f"""
|
580 |
-
<div class="answer" style="margin-top: 15px; padding: 15px; background: rgba(51, 65, 85, 0.4); border-radius: 6px; border-left: 3px solid #10b981;">
|
581 |
-
<div style="color: #94a3b8; margin-bottom: 10px;">Answer:</div>
|
582 |
-
<div style="color: #34d399;">{correct_answer}</div>
|
583 |
-
</div>
|
584 |
-
"""
|
585 |
-
|
586 |
-
elif source == "reddit":
|
587 |
-
# Add subreddit to metadata if available
|
588 |
-
if 'subreddit' in q:
|
589 |
-
subreddit = q.get('subreddit', '')
|
590 |
-
metadata_html = metadata_html.replace(
|
591 |
-
'posted on',
|
592 |
-
f'posted in <span style="color: #60a5fa; font-weight: 500;">r/{subreddit}</span> on'
|
593 |
-
)
|
594 |
|
595 |
-
# If no specific content is set, try to use any available content fields
|
596 |
-
if not content_html:
|
597 |
-
if 'body' in q:
|
598 |
-
content_html = f"""
|
599 |
-
<div class="question-content" style="margin-top: 20px; font-family: 'Segoe UI', system-ui, -apple-system, sans-serif; color: #e2e8f0; line-height: 1.6;">
|
600 |
-
{process_body(q['body'], title)}
|
601 |
-
</div>
|
602 |
-
"""
|
603 |
-
elif 'correct_answer' in q:
|
604 |
-
content_html = f"""
|
605 |
-
<div class="answer" style="margin-top: 15px; padding: 15px; background: rgba(51, 65, 85, 0.4); border-radius: 6px;">
|
606 |
-
<div style="color: #94a3b8; margin-bottom: 10px;">Answer:</div>
|
607 |
-
<div style="color: #e2e8f0;">{q['correct_answer']}</div>
|
608 |
-
</div>
|
609 |
-
"""
|
610 |
-
|
611 |
-
# Get source-specific icon and color
|
612 |
source_icon = {
|
613 |
-
'stack_exchange': 'β‘',
|
614 |
-
'reddit': 'πΈ',
|
615 |
-
'wikipedia': 'π',
|
616 |
-
'trivia': 'π―',
|
617 |
-
}.get(source, 'β')
|
618 |
|
619 |
source_color = {
|
620 |
-
'stack_exchange': '#60a5fa',
|
621 |
-
'reddit': '#f97316',
|
622 |
-
'wikipedia': '#22c55e',
|
623 |
-
'trivia': '#eab308',
|
624 |
-
}.get(source, '#60a5fa')
|
625 |
|
626 |
-
# Create the source badge with icon
|
627 |
source_display = source.title() if source else "Unknown"
|
628 |
source_badge = f"""
|
629 |
<div class="source-badge" style="display: inline-flex; align-items: center; padding: 4px 8px; background: rgba(51, 65, 85, 0.5); border-radius: 4px; margin-right: 10px; border: 1px solid {source_color}25;">
|
@@ -632,7 +332,6 @@ def format_question(q: Dict) -> str:
|
|
632 |
</div>
|
633 |
"""
|
634 |
|
635 |
-
# Handle matching interests display
|
636 |
matching_interests = q.get('matching_interests', [])
|
637 |
interest_types = q.get('interest_types', [])
|
638 |
interests_with_types = []
|
@@ -643,11 +342,9 @@ def format_question(q: Dict) -> str:
|
|
643 |
'type': type_
|
644 |
})
|
645 |
|
646 |
-
# Format interests by type
|
647 |
keywords = [i['name'] for i in interests_with_types if i['type'] == 'keyword']
|
648 |
topics = [i['name'] for i in interests_with_types if i['type'] == 'topic']
|
649 |
|
650 |
-
# Create interests display string
|
651 |
interests_display = []
|
652 |
if keywords:
|
653 |
interests_display.append(f"Keywords: {format_interest_list(set(keywords), max_items=3)}")
|
@@ -655,7 +352,6 @@ def format_question(q: Dict) -> str:
|
|
655 |
interests_display.append(f"Topics: {format_interest_list(set(topics), max_items=3)}")
|
656 |
interests_str = " | ".join(interests_display) if interests_display else "No common interests found"
|
657 |
|
658 |
-
# Calculate relevance score display
|
659 |
relevance_score = q.get('relevance_score', 0)
|
660 |
score_display = f"""
|
661 |
<div class="relevance-score" style="display: inline-block; padding: 4px 8px; background: rgba(59, 130, 246, 0.2); border-radius: 4px; margin-left: 10px;">
|
@@ -663,8 +359,7 @@ def format_question(q: Dict) -> str:
|
|
663 |
</div>
|
664 |
""" if relevance_score > 0 else ""
|
665 |
|
666 |
-
|
667 |
-
question_html = f"""
|
668 |
<div class="question-card" style="background: rgba(51, 65, 85, 0.5); padding: 20px; border-radius: 8px; margin: 15px 0; border: 1px solid rgba(148, 163, 184, 0.2);">
|
669 |
<div class="question-header" style="display: flex; justify-content: space-between; align-items: flex-start; margin-bottom: 15px;">
|
670 |
<div style="flex: 1; display: flex; align-items: center;">
|
@@ -685,8 +380,6 @@ def format_question(q: Dict) -> str:
|
|
685 |
</div>
|
686 |
"""
|
687 |
|
688 |
-
return question_html
|
689 |
-
|
690 |
except Exception as e:
|
691 |
logger.error(f"Error formatting question: {str(e)}")
|
692 |
return f"""
|
@@ -695,35 +388,19 @@ def format_question(q: Dict) -> str:
|
|
695 |
</div>
|
696 |
"""
|
697 |
|
698 |
-
def loading_message() -> Tuple[str, str, str]:
|
699 |
-
"""Return loading message in proper HTML format."""
|
700 |
-
loading_html = """
|
701 |
-
<div class="loading-spinner">
|
702 |
-
<div style="text-align: center;">
|
703 |
-
<div style="border: 4px solid #60a5fa; border-top: 4px solid transparent; border-radius: 50%; width: 40px; height: 40px; animation: spin 1s linear infinite; margin: 20px auto;"></div>
|
704 |
-
<div style="color: #60a5fa; margin-top: 10px;">Analyzing interests and finding recommendations...</div>
|
705 |
-
</div>
|
706 |
-
</div>
|
707 |
-
"""
|
708 |
-
return loading_html, loading_html, loading_html
|
709 |
-
|
710 |
def recommend_questions(user1: str, user2: str) -> Tuple[str, str, str, List[Dict]]:
|
711 |
"""Main function to get recommendations and user interests."""
|
712 |
-
# Extract actual usernames from the formatted strings
|
713 |
user1 = user1.split(" (")[0] if " (" in user1 else user1
|
714 |
user2 = user2.split(" (")[0] if " (" in user2 else user2
|
715 |
|
716 |
recommender = QuestionRecommender()
|
717 |
try:
|
718 |
-
# Get interests for both users
|
719 |
user1_interests = recommender.get_user_interests(user1)
|
720 |
user2_interests = recommender.get_user_interests(user2)
|
721 |
|
722 |
-
# Find common interests
|
723 |
common_keywords = user1_interests['keywords'] & user2_interests['keywords']
|
724 |
common_topics = user1_interests['topics'] & user2_interests['topics']
|
725 |
|
726 |
-
# Format interests summary
|
727 |
interests_summary = f"""
|
728 |
<div class="interests-summary">
|
729 |
<div class="user-interests">
|
@@ -758,7 +435,6 @@ def recommend_questions(user1: str, user2: str) -> Tuple[str, str, str, List[Dic
|
|
758 |
</div>
|
759 |
"""
|
760 |
|
761 |
-
# Get all recommended questions
|
762 |
questions = recommender.find_common_questions(user1, user2, max_questions=50)
|
763 |
|
764 |
if questions:
|
@@ -784,7 +460,7 @@ def recommend_questions(user1: str, user2: str) -> Tuple[str, str, str, List[Dic
|
|
784 |
finally:
|
785 |
recommender.close()
|
786 |
|
787 |
-
# Custom CSS for
|
788 |
custom_css = """
|
789 |
.gradio-container {
|
790 |
max-width: 1200px !important;
|
@@ -962,17 +638,14 @@ strong {
|
|
962 |
"""
|
963 |
|
964 |
def main():
|
965 |
-
# Create Gradio interface
|
966 |
recommender = QuestionRecommender()
|
967 |
users = recommender.get_all_users()
|
968 |
recommender.close()
|
969 |
|
970 |
-
with gr.Blocks(title="Question Recommender
|
971 |
gr.Markdown("""
|
972 |
-
# π€ Question Recommender
|
973 |
Find questions that two users might be interested in discussing together based on their common interests.
|
974 |
-
|
975 |
-
> This is the local debug version using the test database.
|
976 |
""")
|
977 |
|
978 |
with gr.Row(equal_height=True):
|
@@ -1003,29 +676,13 @@ def main():
|
|
1003 |
recommendation_type = gr.HTML()
|
1004 |
questions_output = gr.HTML()
|
1005 |
|
1006 |
-
def recommend_and_store(user1, user2):
|
1007 |
-
"""Get recommendations and store questions."""
|
1008 |
-
interests, rec_type, questions_html, questions_data = recommend_questions(user1, user2)
|
1009 |
-
return interests, rec_type, questions_html
|
1010 |
-
|
1011 |
-
# Wire up the components
|
1012 |
recommend_btn.click(
|
1013 |
-
fn=
|
1014 |
-
outputs=[interests_output, recommendation_type, questions_output],
|
1015 |
-
queue=False
|
1016 |
-
).then(
|
1017 |
-
fn=recommend_and_store,
|
1018 |
inputs=[user1_dropdown, user2_dropdown],
|
1019 |
outputs=[interests_output, recommendation_type, questions_output]
|
1020 |
)
|
1021 |
|
1022 |
-
|
1023 |
-
logger.info("Starting local debug version of Question Recommender")
|
1024 |
-
iface.launch(
|
1025 |
-
show_error=True,
|
1026 |
-
server_name="127.0.0.1",
|
1027 |
-
server_port=7860
|
1028 |
-
)
|
1029 |
|
1030 |
if __name__ == "__main__":
|
1031 |
-
main()
|
|
|
5 |
import pandas as pd
|
6 |
from datetime import datetime
|
7 |
import os
|
8 |
+
import re
|
9 |
+
from html import escape
|
10 |
+
from bs4 import BeautifulSoup
|
11 |
|
12 |
+
# Set up basic logging
|
13 |
logging.basicConfig(
|
14 |
+
level=logging.WARNING,
|
15 |
+
format='%(levelname)s: %(message)s'
|
|
|
16 |
)
|
17 |
logger = logging.getLogger(__name__)
|
18 |
|
19 |
+
# Get database credentials from environment variables
|
20 |
+
NEO4J_URL = os.getenv("NEO4J_URL")
|
21 |
+
NEO4J_USER = os.getenv("NEO4J_USER")
|
22 |
+
NEO4J_PASSWORD = os.getenv("NEO4J_PASSWORD")
|
23 |
+
|
24 |
+
if not all([NEO4J_URL, NEO4J_USER, NEO4J_PASSWORD]):
|
25 |
+
raise ValueError("Missing required environment variables for database connection")
|
26 |
|
27 |
def format_neo4j_datetime(dt) -> str:
|
28 |
"""Convert Neo4j datetime to string format."""
|
29 |
if dt is None:
|
|
|
30 |
return 'Unknown date'
|
31 |
try:
|
|
|
32 |
if hasattr(dt, 'to_native'):
|
33 |
dt = dt.to_native()
|
|
|
34 |
return dt.strftime('%Y-%m-%d')
|
35 |
except Exception as e:
|
36 |
logger.warning(f"Error formatting datetime: {e}")
|
|
|
45 |
return ', '.join(sorted_interests)
|
46 |
return f"{', '.join(sorted_interests[:max_items])} (+{len(sorted_interests) - max_items} more)"
|
47 |
|
48 |
+
def process_body(text, title):
|
49 |
+
"""Process question body to handle images and HTML."""
|
50 |
+
if not text:
|
51 |
+
return ""
|
52 |
+
|
53 |
+
try:
|
54 |
+
# Parse the HTML content
|
55 |
+
soup = BeautifulSoup(str(text), 'html.parser')
|
56 |
+
|
57 |
+
# Function to fix Stack Exchange URLs
|
58 |
+
def fix_stack_exchange_url(url):
|
59 |
+
if not url:
|
60 |
+
return url
|
61 |
+
if url.startswith(('http://', 'https://')):
|
62 |
+
return url
|
63 |
+
if url.startswith('//'):
|
64 |
+
return 'https:' + url
|
65 |
+
if url.startswith('/'):
|
66 |
+
return 'https://i.stack.imgur.com' + url
|
67 |
+
return 'https://i.stack.imgur.com/' + url
|
68 |
+
|
69 |
+
# Find all img tags and replace with preview cards
|
70 |
+
for img in soup.find_all('img'):
|
71 |
+
src = img.get('src', '')
|
72 |
+
if not src:
|
73 |
+
continue
|
74 |
+
|
75 |
+
fixed_src = fix_stack_exchange_url(src)
|
76 |
+
alt_text = img.get('alt', '').strip()
|
77 |
+
if not alt_text or alt_text.lower() == 'enter image description here':
|
78 |
+
alt_text = 'Question image'
|
79 |
+
|
80 |
+
preview_html = f"""
|
81 |
+
<div class="image-preview" style="margin: 10px 0; padding: 10px; background: rgba(30, 41, 59, 0.4); border-radius: 6px;">
|
82 |
+
<div style="display: flex; align-items: center; margin-bottom: 8px;">
|
83 |
+
<span style="font-size: 20px; margin-right: 8px;">πΌοΈ</span>
|
84 |
+
<span style="color: #93c5fd;">{alt_text}</span>
|
85 |
+
</div>
|
86 |
+
<a href="{fixed_src}" target="_blank" rel="noopener noreferrer"
|
87 |
+
style="color: #60a5fa; text-decoration: none;">View image</a>
|
88 |
+
</div>
|
89 |
+
"""
|
90 |
+
|
91 |
+
new_soup = BeautifulSoup(preview_html, 'html.parser')
|
92 |
+
img.replace_with(new_soup)
|
93 |
+
|
94 |
+
# Style other elements
|
95 |
+
for link in soup.find_all('a'):
|
96 |
+
if 'View Image' not in (link.get_text() or ''):
|
97 |
+
href = link.get('href', '')
|
98 |
+
if href and not href.startswith(('http://', 'https://')):
|
99 |
+
link['href'] = fix_stack_exchange_url(href)
|
100 |
+
link['target'] = '_blank'
|
101 |
+
link['rel'] = 'noopener noreferrer'
|
102 |
+
link['style'] = 'color: #60a5fa; text-decoration: none;'
|
103 |
+
|
104 |
+
# Add paragraph styling
|
105 |
+
for p in soup.find_all(['p', 'div']):
|
106 |
+
if not any(cls in (p.get('class', []) or []) for cls in ['image-preview', 'question-card']):
|
107 |
+
current_style = p.get('style', '')
|
108 |
+
p['style'] = f"{current_style}; margin: 0.8em 0; line-height: 1.6; color: #e2e8f0;"
|
109 |
+
|
110 |
+
# Add list styling
|
111 |
+
for ul in soup.find_all(['ul', 'ol']):
|
112 |
+
ul['style'] = 'margin: 0.8em 0; padding-left: 1.5em; color: #e2e8f0;'
|
113 |
+
|
114 |
+
for li in soup.find_all('li'):
|
115 |
+
li['style'] = 'margin: 0.4em 0; line-height: 1.6; color: #e2e8f0;'
|
116 |
+
|
117 |
+
# Add code block styling
|
118 |
+
for code in soup.find_all(['code', 'pre']):
|
119 |
+
code['style'] = 'background: rgba(30, 41, 59, 0.5); padding: 0.2em 0.4em; border-radius: 4px; font-family: monospace; color: #e2e8f0;'
|
120 |
+
|
121 |
+
return str(soup)
|
122 |
+
|
123 |
+
except Exception as e:
|
124 |
+
logger.warning(f"Error processing question body: {str(e)}")
|
125 |
+
return str(text) if text else ""
|
126 |
+
|
127 |
class QuestionRecommender:
|
128 |
def __init__(self):
|
129 |
try:
|
|
|
131 |
NEO4J_URL,
|
132 |
auth=(NEO4J_USER, NEO4J_PASSWORD)
|
133 |
)
|
|
|
134 |
# Test connection immediately
|
135 |
self.driver.verify_connectivity()
|
|
|
|
|
|
|
|
|
136 |
except Exception as e:
|
137 |
logger.error(f"Failed to initialize database connection: {str(e)}")
|
138 |
raise
|
139 |
|
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|
140 |
def close(self):
|
141 |
self.driver.close()
|
142 |
|
|
|
144 |
"""Get list of all users with interest counts."""
|
145 |
with self.driver.session() as session:
|
146 |
try:
|
|
|
147 |
result = session.run("""
|
148 |
MATCH (u:User)
|
149 |
OPTIONAL MATCH (u)-[r:INTERESTED_IN_KEYWORD|INTERESTED_IN_TOPIC]->(interest)
|
|
|
166 |
) for record in result if record["username"]]
|
167 |
|
168 |
if not users_with_counts:
|
|
|
169 |
return []
|
|
|
|
|
|
|
|
|
|
|
170 |
|
|
|
171 |
return [
|
172 |
f"{username} ({kw_count} keywords, {topic_count} topics)"
|
173 |
for username, kw_count, topic_count in users_with_counts
|
|
|
179 |
def get_user_interests(self, username: str) -> Dict[str, set]:
|
180 |
"""Get keywords and topics a user is interested in."""
|
181 |
with self.driver.session() as session:
|
|
|
182 |
keyword_result = session.run("""
|
183 |
MATCH (u:User {name: $username})-[:INTERESTED_IN_KEYWORD]->(k:Keyword)
|
184 |
RETURN DISTINCT k.keyword as keyword
|
185 |
""", username=username)
|
186 |
keywords = {str(record["keyword"]) for record in keyword_result if record["keyword"]}
|
|
|
|
|
|
|
187 |
|
|
|
188 |
topic_result = session.run("""
|
189 |
MATCH (u:User {name: $username})-[:INTERESTED_IN_TOPIC]->(t:Topic)
|
190 |
RETURN DISTINCT t.topic as topic
|
191 |
""", username=username)
|
192 |
topics = {str(record["topic"]) for record in topic_result if record["topic"]}
|
|
|
|
|
|
|
193 |
|
194 |
return {"keywords": keywords or set(), "topics": topics or set()}
|
195 |
|
196 |
def find_common_questions(self, user1: str, user2: str, max_questions: int = 5) -> List[Dict]:
|
197 |
+
"""Find questions to recommend based on common interests."""
|
198 |
with self.driver.session() as session:
|
199 |
+
questions = session.run("""
|
|
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|
200 |
MATCH (u1:User {name: $user1})
|
201 |
MATCH (u2:User {name: $user2})
|
202 |
|
|
|
203 |
OPTIONAL MATCH (u1)-[r1:INTERESTED_IN_KEYWORD|INTERESTED_IN_TOPIC]->(interest1)
|
204 |
OPTIONAL MATCH (u2)-[r2:INTERESTED_IN_KEYWORD|INTERESTED_IN_TOPIC]->(interest2)
|
205 |
WITH u1, u2,
|
206 |
COLLECT(DISTINCT interest1) as u1_interests,
|
207 |
COLLECT(DISTINCT interest2) as u2_interests
|
208 |
|
209 |
+
UNWIND u1_interests + u2_interests as interest
|
210 |
+
MATCH (q:Question)-[r:HAS_KEYWORD|HAS_TOPIC]->(interest)
|
211 |
+
WHERE
|
212 |
+
q.author <> $user1 AND
|
213 |
+
q.author <> $user2 AND
|
214 |
+
(
|
215 |
+
(interest IN u1_interests AND interest IN u2_interests) OR
|
216 |
+
(interest IN u1_interests AND EXISTS((q)-[:HAS_KEYWORD|HAS_TOPIC]->()<-[:INTERESTED_IN_KEYWORD|INTERESTED_IN_TOPIC]-(u2))) OR
|
217 |
+
(interest IN u2_interests AND EXISTS((q)-[:HAS_KEYWORD|HAS_TOPIC]->()<-[:INTERESTED_IN_KEYWORD|INTERESTED_IN_TOPIC]-(u1)))
|
218 |
+
)
|
219 |
+
WITH q, interest, type(r) as rel_type,
|
220 |
+
CASE WHEN interest IN u1_interests AND interest IN u2_interests THEN 2.0 ELSE 1.0 END as interest_weight
|
221 |
+
WITH q, collect({interest: interest, weight: interest_weight, type: rel_type}) as interests,
|
222 |
+
sum(interest_weight) as base_score
|
|
|
|
|
|
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|
|
223 |
WITH q, interests, base_score,
|
224 |
CASE
|
225 |
WHEN q.created_utc_ts IS NOT NULL
|
226 |
THEN base_score * (1.0 + 0.1 * (1.0 - duration.between(q.created_utc_ts, datetime()).days / 365.0))
|
227 |
ELSE base_score
|
228 |
+
END as temporal_score
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
229 |
RETURN DISTINCT
|
230 |
q.title as title,
|
231 |
q.body as body,
|
|
|
245 |
WHEN i.type = 'HAS_KEYWORD' THEN 'keyword'
|
246 |
ELSE 'topic'
|
247 |
END] as interest_types,
|
248 |
+
temporal_score as relevance_score
|
249 |
+
ORDER BY temporal_score DESC
|
250 |
LIMIT $max_questions
|
251 |
+
""", user1=user1, user2=user2, max_questions=max_questions)
|
|
|
|
|
|
|
|
|
|
|
252 |
|
253 |
+
return [dict(record) for record in questions]
|
|
|
|
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|
|
254 |
|
255 |
def format_question(q: Dict) -> str:
|
256 |
"""Format a question for display based on its source."""
|
257 |
try:
|
|
|
258 |
title = q.get('title', 'Untitled')
|
259 |
+
source = q.get('source', '').lower()
|
260 |
|
|
|
|
|
|
|
|
|
|
|
|
|
261 |
metadata_html = ""
|
262 |
content_html = ""
|
263 |
|
|
|
264 |
if 'author' in q or 'created_utc_ts' in q:
|
265 |
author = q.get('author', 'Unknown author')
|
266 |
created_date = format_neo4j_datetime(q.get('created_utc_ts'))
|
|
|
267 |
upvotes = q.get('upvotes', 0)
|
268 |
num_comments = q.get('num_comments', 0)
|
269 |
|
|
|
279 |
</div>
|
280 |
"""
|
281 |
|
|
|
282 |
if source == "stack_exchange":
|
283 |
body = q.get('body', '')
|
284 |
if body:
|
|
|
287 |
{process_body(body, title)}
|
288 |
</div>
|
289 |
"""
|
|
|
290 |
elif source == "trivia":
|
291 |
correct_answer = q.get('correct_answer', '')
|
292 |
incorrect_answers = q.get('incorrect_answers', [])
|
293 |
|
|
|
294 |
answers = [correct_answer] + incorrect_answers if incorrect_answers else [correct_answer]
|
295 |
answers_html = "".join([
|
296 |
f"""
|
|
|
309 |
{answers_html}
|
310 |
</div>
|
311 |
"""
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
312 |
|
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|
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|
|
|
|
|
|
|
|
|
|
|
313 |
source_icon = {
|
314 |
+
'stack_exchange': 'β‘',
|
315 |
+
'reddit': 'πΈ',
|
316 |
+
'wikipedia': 'π',
|
317 |
+
'trivia': 'π―',
|
318 |
+
}.get(source, 'β')
|
319 |
|
320 |
source_color = {
|
321 |
+
'stack_exchange': '#60a5fa',
|
322 |
+
'reddit': '#f97316',
|
323 |
+
'wikipedia': '#22c55e',
|
324 |
+
'trivia': '#eab308',
|
325 |
+
}.get(source, '#60a5fa')
|
326 |
|
|
|
327 |
source_display = source.title() if source else "Unknown"
|
328 |
source_badge = f"""
|
329 |
<div class="source-badge" style="display: inline-flex; align-items: center; padding: 4px 8px; background: rgba(51, 65, 85, 0.5); border-radius: 4px; margin-right: 10px; border: 1px solid {source_color}25;">
|
|
|
332 |
</div>
|
333 |
"""
|
334 |
|
|
|
335 |
matching_interests = q.get('matching_interests', [])
|
336 |
interest_types = q.get('interest_types', [])
|
337 |
interests_with_types = []
|
|
|
342 |
'type': type_
|
343 |
})
|
344 |
|
|
|
345 |
keywords = [i['name'] for i in interests_with_types if i['type'] == 'keyword']
|
346 |
topics = [i['name'] for i in interests_with_types if i['type'] == 'topic']
|
347 |
|
|
|
348 |
interests_display = []
|
349 |
if keywords:
|
350 |
interests_display.append(f"Keywords: {format_interest_list(set(keywords), max_items=3)}")
|
|
|
352 |
interests_display.append(f"Topics: {format_interest_list(set(topics), max_items=3)}")
|
353 |
interests_str = " | ".join(interests_display) if interests_display else "No common interests found"
|
354 |
|
|
|
355 |
relevance_score = q.get('relevance_score', 0)
|
356 |
score_display = f"""
|
357 |
<div class="relevance-score" style="display: inline-block; padding: 4px 8px; background: rgba(59, 130, 246, 0.2); border-radius: 4px; margin-left: 10px;">
|
|
|
359 |
</div>
|
360 |
""" if relevance_score > 0 else ""
|
361 |
|
362 |
+
return f"""
|
|
|
363 |
<div class="question-card" style="background: rgba(51, 65, 85, 0.5); padding: 20px; border-radius: 8px; margin: 15px 0; border: 1px solid rgba(148, 163, 184, 0.2);">
|
364 |
<div class="question-header" style="display: flex; justify-content: space-between; align-items: flex-start; margin-bottom: 15px;">
|
365 |
<div style="flex: 1; display: flex; align-items: center;">
|
|
|
380 |
</div>
|
381 |
"""
|
382 |
|
|
|
|
|
383 |
except Exception as e:
|
384 |
logger.error(f"Error formatting question: {str(e)}")
|
385 |
return f"""
|
|
|
388 |
</div>
|
389 |
"""
|
390 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
391 |
def recommend_questions(user1: str, user2: str) -> Tuple[str, str, str, List[Dict]]:
|
392 |
"""Main function to get recommendations and user interests."""
|
|
|
393 |
user1 = user1.split(" (")[0] if " (" in user1 else user1
|
394 |
user2 = user2.split(" (")[0] if " (" in user2 else user2
|
395 |
|
396 |
recommender = QuestionRecommender()
|
397 |
try:
|
|
|
398 |
user1_interests = recommender.get_user_interests(user1)
|
399 |
user2_interests = recommender.get_user_interests(user2)
|
400 |
|
|
|
401 |
common_keywords = user1_interests['keywords'] & user2_interests['keywords']
|
402 |
common_topics = user1_interests['topics'] & user2_interests['topics']
|
403 |
|
|
|
404 |
interests_summary = f"""
|
405 |
<div class="interests-summary">
|
406 |
<div class="user-interests">
|
|
|
435 |
</div>
|
436 |
"""
|
437 |
|
|
|
438 |
questions = recommender.find_common_questions(user1, user2, max_questions=50)
|
439 |
|
440 |
if questions:
|
|
|
460 |
finally:
|
461 |
recommender.close()
|
462 |
|
463 |
+
# Custom CSS for styling
|
464 |
custom_css = """
|
465 |
.gradio-container {
|
466 |
max-width: 1200px !important;
|
|
|
638 |
"""
|
639 |
|
640 |
def main():
|
|
|
641 |
recommender = QuestionRecommender()
|
642 |
users = recommender.get_all_users()
|
643 |
recommender.close()
|
644 |
|
645 |
+
with gr.Blocks(title="Question Recommender", theme=gr.themes.Soft(), css=custom_css) as iface:
|
646 |
gr.Markdown("""
|
647 |
+
# π€ Question Recommender
|
648 |
Find questions that two users might be interested in discussing together based on their common interests.
|
|
|
|
|
649 |
""")
|
650 |
|
651 |
with gr.Row(equal_height=True):
|
|
|
676 |
recommendation_type = gr.HTML()
|
677 |
questions_output = gr.HTML()
|
678 |
|
|
|
|
|
|
|
|
|
|
|
|
|
679 |
recommend_btn.click(
|
680 |
+
fn=recommend_questions,
|
|
|
|
|
|
|
|
|
681 |
inputs=[user1_dropdown, user2_dropdown],
|
682 |
outputs=[interests_output, recommendation_type, questions_output]
|
683 |
)
|
684 |
|
685 |
+
iface.launch()
|
|
|
|
|
|
|
|
|
|
|
|
|
686 |
|
687 |
if __name__ == "__main__":
|
688 |
+
main()
|