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jblitzar
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github-python-corpus

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# "requests",
# "beautifulsoup4",
# "html2text",
# "networkx",
# "pyvis",
# ]
# ///
"""
Search Graph Generator Script
This script takes a question as input and generates a knowledge graph by:
1. Understanding the question and setting up assumptions
2. Generating search queries
3. Running searches and processing results
4. Building and displaying a graph structure
Usage:
./search_graph.py -h
./search_graph.py -q "What is machine learning?" -v # For INFO logging
./search_graph.py -q "What is machine learning?" -vv # For DEBUG logging
"""
import logging
import time
from argparse import ArgumentParser, RawDescriptionHelpFormatter
from concurrent.futures import ThreadPoolExecutor
from threading import Lock
from urllib.parse import quote_plus
import networkx as nx
import requests
from bs4 import BeautifulSoup
from html2text import HTML2Text
from pyvis.network import Network
class SearchGraph:
def __init__(self, question):
self.question = question
self.graph = nx.Graph(title=question)
self.search_queries = []
self.graph_lock = Lock()
def generate_search_queries(self):
"""Generate 10 search queries based on the input question"""
logging.debug(f"Generating search queries for question: {self.question}")
base_queries = [
self.question,
f"how to {self.question}",
f"what is {self.question}",
f"explain {self.question}",
f"{self.question} tutorial",
f"{self.question} guide",
f"{self.question} examples",
f"{self.question} best practices",
f"{self.question} overview",
f"{self.question} detailed explanation",
]
self.search_queries = base_queries
return base_queries
def visualize_graph(self, output_file="search_graph.html"):
"""
Create an interactive visualization of the graph
"""
logging.info(f"Generating interactive visualization: {output_file}")
net = Network(
height="750px",
width="100%",
bgcolor="#ffffff",
font_color="#000000",
notebook=False,
)
net.force_atlas_2based(
gravity=-50,
central_gravity=0.01,
spring_length=100,
spring_strength=0.08,
damping=0.4,
overlap=0,
)
color_map = {"question": "#ff7675", "query": "#74b9ff", "result": "#55efc4"}
net.add_node(
self.question,
label=self.question[:30] + "..."
if len(self.question) > 30
else self.question,
color=color_map["question"],
size=20,
title=self.question,
)
for node, data in self.graph.nodes(data=True):
if node == self.question:
continue