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‎.gitignore‎

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/downloaded_images
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/issues_with_comments_and_images.json

‎fetch_issues.py‎

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import os
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import json
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import subprocess
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import requests
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import re
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import time # ✅ Import time for delays
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from urllib.parse import urlparse
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# Prompt for user input
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OWNER = input("Enter GitHub repository owner: ")
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REPO = input("Enter GitHub repository name: ")
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TOKEN = input("Enter your GitHub token: ")
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LIMIT = input("Enter the number of issues to fetch (default 10): ") or "10"
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STATE = input("Enter issue state (open, closed, all - default all): ") or "all"
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HEADERS = {"Authorization": f"token {TOKEN}", "Accept": "application/vnd.github.v3+json"}
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# Ensure the image download directory exists
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IMAGE_DIR = "downloaded_images"
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os.makedirs(IMAGE_DIR, exist_ok=True)
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# Function to download an image and return the local path
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def download_image(image_url):
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try:
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print(f"Attempting to download image from URL: {image_url}")
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image_name = os.path.basename(urlparse(image_url).path)
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local_image_path = os.path.join(IMAGE_DIR, image_name)
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if os.path.exists(local_image_path):
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print(f"Image already downloaded: {image_name}")
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return local_image_path
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headers = {"Authorization": f"token {TOKEN}"}
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img_data = requests.get(image_url, headers=headers)
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if img_data.status_code == 200:
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with open(local_image_path, 'wb') as f:
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f.write(img_data.content)
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print(f"Downloaded image: {image_name}")
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return local_image_path
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else:
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print(f"Failed to download image. HTTP Status: {img_data.status_code} for URL: {image_url}")
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return None
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except Exception as e:
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print(f"Failed to download image from {image_url}: {e}")
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return None
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# Step 1: Get all issues (open and closed) using GitHub CLI
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print("\nFetching issues...")
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issues_json = subprocess.run(
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["gh", "issue", "list", "--repo", f"{OWNER}/{REPO}", "--limit", LIMIT, "--state", STATE, "--json", "number,title,body,state"],
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capture_output=True,
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text=True
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).stdout
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issues = json.loads(issues_json)
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# ✅ Add sleep to prevent hitting CLI request limits
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time.sleep(2)
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# Step 2: Fetch comments for each issue using GitHub API
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for issue in issues:
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issue_number = issue["number"]
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print(f"Fetching comments for issue #{issue_number}...")
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comments_url = f"https://api.github.com/repos/{OWNER}/{REPO}/issues/{issue_number}/comments"
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response = requests.get(comments_url, headers=HEADERS)
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if response.status_code == 200:
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comments = response.json()
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issue["comments"] = [{"author": c["user"]["login"], "body": c["body"], "date": c["created_at"]} for c in comments]
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else:
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print(f"Failed to fetch comments for issue #{issue_number} (HTTP {response.status_code})")
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issue["comments"] = []
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# ✅ Sleep after each comment fetch (prevents API rate limits)
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time.sleep(1.5)
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# Step 3: Download images from the issue body and comments (if any)
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body = issue.get("body", "")
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for comment in issue["comments"]:
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body += comment["body"]
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# Regex to find image URLs in Markdown and HTML formats
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img_urls = re.findall(r'!\[.*?\]\((https?://[^\)]+)\)', body)
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img_urls += re.findall(r'<img[^>]+src="(https?://[^\"]+)"', body)
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for img_url in img_urls:
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local_image_path = download_image(img_url)
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# ✅ Sleep after each image download (avoids too many requests)
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time.sleep(1)
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issue["body"] = body
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# ✅ Final sleep before saving (ensures all requests complete safely)
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time.sleep(2)
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# Save the issues with comments and updated image paths to a JSON file
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with open("issues_with_comments_and_images.json", "w", encoding="utf-8") as f:
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json.dump(issues, f, indent=4)
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print("✅ Export completed! Data saved in issues_with_comments_and_images.json")

‎issue.html‎

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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>GitHub Issue List</title>
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<style>
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body {
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font-family: Arial, sans-serif;
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background-color: #f9f9f9;
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color: #333;
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padding: 20px;
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}
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h1 {
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text-align: center;
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color: #333;
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}
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.issue {
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background-color: #fff;
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border-radius: 8px;
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box-shadow: 0 2px 6px rgba(0, 0, 0, 0.1);
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padding: 20px;
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margin-bottom: 20px;
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border-left: 5px solid #4CAF50;
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}
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.issue h2 {
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color: #333;
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margin-top: 0;
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}
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.issue p {
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line-height: 1.6;
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}
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.issue .comments {
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margin-top: 15px;
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padding-left: 20px;
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border-left: 3px solid #ddd;
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}
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.comment {
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background-color: #f9f9f9;
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margin-bottom: 10px;
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padding: 10px;
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border-radius: 5px;
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}
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.comment p {
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margin: 5px 0;
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}
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.comment .author {
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font-weight: bold;
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color: #4CAF50;
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}
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.comment .date {
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font-size: 0.9em;
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color: #888;
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}
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.comment .body {
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margin-top: 5px;
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}
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img {
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max-width: 100%;
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height: auto;
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border-radius: 8px;
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}
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</style>
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</head>
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<body>
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<h1>GitHub Issue List</h1>
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<div id="issues-container"></div>
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<script>
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// Function to render issues dynamically
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async function fetchIssues() {
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try {
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const response = await fetch('issues_with_comments_and_images.json'); // Fetch the JSON file
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const issuesData = await response.json(); // Parse the JSON data
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// Now render the issues
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renderIssues(issuesData);
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} catch (error) {
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console.error("Error fetching the issues data:", error);
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alert("There was an error loading the issues.");
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}
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}
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// Function to render issues dynamically
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function renderIssues(issuesData) {
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const container = document.getElementById('issues-container');
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issuesData.forEach(issue => {
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// Create the issue container
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const issueDiv = document.createElement('div');
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issueDiv.classList.add('issue');
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const numberAndState = document.createElement('h3');
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numberAndState.innerHTML = `<strong>Issue #${issue.number}</strong> - State: ${issue.state==="OPEN" ? `<span style="color: green;">Open</span>` : `<span style="color: red;">Closed</span>`}`;
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issueDiv.appendChild(numberAndState);
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// Title and number
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const title = document.createElement('h2');
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title.textContent = issue.title;
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issueDiv.appendChild(title);
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// Body - converting Markdown images into HTML <img> tags
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const body = document.createElement('p');
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body.innerHTML = processBodyText(issue.body);
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issueDiv.appendChild(body);
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// Comments Section
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if (issue.comments.length > 0) {
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const commentsDiv = document.createElement('div');
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commentsDiv.classList.add('comments');
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issue.comments.forEach(comment => {
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const commentDiv = document.createElement('div');
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commentDiv.classList.add('comment');
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const author = document.createElement('p');
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author.classList.add('author');
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author.innerHTML = `${comment.author} <span class="date">(${comment.date})</span>`;
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commentDiv.appendChild(author);
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const body = document.createElement('p');
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body.classList.add('body');
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body.textContent = comment.body;
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commentDiv.appendChild(body);
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commentsDiv.appendChild(commentDiv);
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});
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issueDiv.appendChild(commentsDiv);
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}
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container.appendChild(issueDiv);
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});
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}
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// Function to process body text and convert Markdown-style images to <img> tags
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function processBodyText(text) {
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// Regex to match Markdown image syntax (e.g. ![Image](url))
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const regex = /!\[([^\]]+)\]\((https?:\/\/[^\)]+)\)/g;
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// Replace Markdown images with <img> tags pointing to the local 'downloaded_images' folder
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return text.replace(regex, (match, altText, url) => {
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// Extract image name from the URL
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const imageName = url.split('/').pop(); // Get the last part of the URL as the image file name
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// Check if the image has an extension and handle accordingly
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const imageExtension = imageName.split('.').pop();
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const imagePath = `./downloaded_images/${imageName}`;
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// Debugging: log the URL and local path to verify
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console.log("Original URL:", url); // Check the original URL
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console.log("Local Image Path:", imagePath); // Check the local image path
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// Return HTML <img> tag
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return `<img src="${imagePath}" alt="${altText}" style="max-width: 100%; height: auto;">`;
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}).replace(/\n/g, '<br>'); // Replace line breaks with <br> tags
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}
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// Call the fetchIssues function when the page loads
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fetchIssues();
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</script>
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</body>
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</html>

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