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| from flask import Flask, request, render_template_string, Response | |
| from openai import OpenAI | |
| import os | |
| import json | |
| from urllib.parse import quote | |
| import html | |
| app = Flask(__name__) | |
| # Initialize OpenAI client with API key and base URL from environment variables | |
| client = OpenAI( | |
| api_key=os.environ["OPENAI_API_KEY"], | |
| base_url=os.environ["OPENAI_BASE_URL"] | |
| ) | |
| # Define constants for pagination | |
| RESULTS_PER_PAGE = 10 | |
| TOTAL_RESULTS = 30 # Generate 30 results to allow pagination | |
| def fetch_search_results(query, stream=False): | |
| """Fetch search results from the LLM, with optional streaming.""" | |
| if not query.strip(): | |
| return None, "Please enter a search query." | |
| prompt = f""" | |
| You are a search engine that provides informative and relevant results. For the given query '{query}', | |
| generate {TOTAL_RESULTS} search results. Each result should include: | |
| - 'title': A concise, descriptive title of the result. | |
| - 'snippet': A short summary (2-3 sentences) of the content. | |
| - 'url': A plausible, clickable URL where the information might be found (e.g., a real or hypothetical website). | |
| Format the response as a JSON array of objects, where each object has 'title', 'snippet', and 'url' fields. | |
| Ensure the results are diverse, relevant to the query, and the URLs are realistic (e.g., https://example.com/page). | |
| """ | |
| try: | |
| response = client.chat.completions.create( | |
| model="gemini-2.0-flash-lite", # Updated model name | |
| messages=[ | |
| {"role": "system", "content": "You are a helpful search engine."}, | |
| {"role": "user", "content": prompt} | |
| ], | |
| response_format={"type": "json_object"}, | |
| stream=stream # Enable streaming if requested | |
| ) | |
| if stream: | |
| return response, None # Return raw streaming response | |
| else: | |
| content = response.choices[0].message.content | |
| results = json.loads(content) | |
| # Handle different possible JSON structures | |
| if isinstance(results, dict) and "results" in results: | |
| results = results["results"] | |
| elif isinstance(results, list): | |
| pass | |
| else: | |
| return None, "Error: Unexpected JSON structure." | |
| return results, None | |
| except Exception as e: | |
| error_msg = str(e) | |
| if "404" in error_msg: | |
| return None, f"Error 404: Model or endpoint not found. Check OPENAI_BASE_URL ({os.environ['OPENAI_BASE_URL']}) and model name." | |
| elif "401" in error_msg: | |
| return None, "Error 401: Invalid API key. Check OPENAI_API_KEY." | |
| else: | |
| return None, f"Error: {error_msg}" | |
| def stream_search_results(query, page): | |
| """Stream search results incrementally.""" | |
| stream_response, error = fetch_search_results(query, stream=True) | |
| if error: | |
| yield f"<p style='color: red; text-align: center;'>{error}</p>" | |
| return | |
| # Generate header | |
| header = """ | |
| <html> | |
| <head> | |
| <title>LLM Search Engine</title> | |
| <style> | |
| body { font-family: Arial, sans-serif; margin: 0; padding: 0; color: #202124; } | |
| .header { text-align: center; padding: 20px 0; } | |
| .logo { font-size: 36px; font-weight: bold; } | |
| .logo span:nth-child(1) { color: #4285f4; } | |
| .logo span:nth-child(2) { color: #ea4335; } | |
| .logo span:nth-child(3) { color: #fbbc05; } | |
| .logo span:nth-child(4) { color: #4285f4; } | |
| .logo span:nth-child(5) { color: #34a853; } | |
| .search-box { max-width: 584px; margin: 0 auto 20px; } | |
| .search-box input[type="text"] { | |
| width: 100%; padding: 12px 20px; font-size: 16px; | |
| border: 1px solid #dfe1e5; border-radius: 24px; | |
| box-shadow: 0 1px 6px rgba(32,33,36,0.28); outline: none; | |
| } | |
| .search-box input[type="submit"] { | |
| background-color: #f8f9fa; border: 1px solid #f8f9fa; | |
| border-radius: 4px; color: #3c4043; font-size: 14px; | |
| padding: 10px 16px; margin: 11px 4px; cursor: pointer; | |
| } | |
| .search-box input[type="submit"]:hover { | |
| border: 1px solid #dadce0; box-shadow: 0 1px 2px rgba(0,0,0,0.1); | |
| } | |
| .search-buttons { text-align: center; } | |
| .results { max-width: 652px; margin: 0 auto; } | |
| .search-result { margin-bottom: 28px; } | |
| .search-result a { color: #1a0dab; font-size: 20px; text-decoration: none; } | |
| .search-result a:hover { text-decoration: underline; } | |
| .search-result .url { color: #006621; font-size: 14px; line-height: 20px; } | |
| .search-result p { color: #4d5156; font-size: 14px; line-height: 22px; margin: 0; } | |
| .pagination { text-align: center; margin: 40px 0; } | |
| .pagination a, .pagination span { | |
| color: #1a0dab; font-size: 14px; margin: 0 8px; text-decoration: none; | |
| } | |
| .pagination a:hover { text-decoration: underline; } | |
| </style> | |
| </head> | |
| <body> | |
| <div class="header"> | |
| <div class="logo"> | |
| <span>L</span><span>L</span><span>M</span><span> </span><span>Search</span> | |
| </div> | |
| </div> | |
| <div class="search-box"> | |
| <form method="get" action="/"> | |
| <input type="text" name="query" value="{{query}}"> | |
| <input type="hidden" name="page" value="1"> | |
| <div class="search-buttons"> | |
| <input type="submit" name="btn" value="LLM Search"> | |
| <input type="submit" name="btn" value="I'm Feeling Lucky"> | |
| </div> | |
| </form> | |
| </div> | |
| <div class="results"> | |
| <h2 style="font-size: 18px; color: #70757a; margin-bottom: 20px;">Results for '{{query}}' (Page {{page}})</h2> | |
| """.replace('{{query}}', html.escape(query)).replace('{{page}}', str(page)) | |
| yield header | |
| # Stream and parse results | |
| buffer = "" | |
| results = [] | |
| for chunk in stream_response: | |
| if chunk.choices[0].delta.content: | |
| buffer += chunk.choices[0].delta.content | |
| try: | |
| # Try to parse the buffer as JSON incrementally | |
| temp_results = json.loads(buffer) | |
| if isinstance(temp_results, list): | |
| results = temp_results | |
| elif isinstance(temp_results, dict) and "results" in temp_results: | |
| results = temp_results["results"] | |
| # Process only new results | |
| for i, result in enumerate(results[len(results) - (len(results) % RESULTS_PER_PAGE):]): | |
| if i >= start_idx and i < end_idx: | |
| title = html.escape(result.get("title", "No title")) | |
| snippet = html.escape(result.get("snippet", "No snippet")) | |
| url = html.escape(result.get("url", "#")) | |
| yield f""" | |
| <div class="search-result"> | |
| <a href="{url}" target="_blank">{title}</a> | |
| <div class="url">{url}</div> | |
| <p>{snippet}</p> | |
| </div> | |
| """ | |
| except json.JSONDecodeError: | |
| continue # Keep buffering until complete JSON | |
| # Calculate pagination | |
| start_idx = (page - 1) * RESULTS_PER_PAGE | |
| end_idx = start_idx + RESULTS_PER_PAGE | |
| total_pages = (len(results) + RESULTS_PER_PAGE - 1) // RESULTS_PER_PAGE | |
| # Pagination links | |
| encoded_query = quote(query) | |
| prev_link = f'<a href="/?query={encoded_query}&page={page-1}&btn=LLM+Search">Previous</a>' if page > 1 else '<span>Previous</span>' | |
| next_link = f'<a href="/?query={encoded_query}&page={page+1}&btn=LLM+Search">Next</a>' if page < total_pages else '<span>Next</span>' | |
| yield f""" | |
| </div> | |
| <div class="pagination"> | |
| {prev_link} | |
| <span>Page {page} of {total_pages}</span> | |
| {next_link} | |
| </div> | |
| </body> | |
| </html> | |
| """ | |
| def search_page(): | |
| """Generate and serve the search results page styled like Google.""" | |
| query = request.args.get('query', '') | |
| page = request.args.get('page', '1') | |
| btn = request.args.get('btn', 'LLM Search') | |
| try: | |
| page = int(page) | |
| except ValueError: | |
| page = 1 | |
| if not query.strip(): | |
| html_content = """ | |
| <html> | |
| <head> | |
| <title>LLM Search Engine</title> | |
| <style> | |
| body { font-family: Arial, sans-serif; margin: 0; padding: 20px; } | |
| .header { text-align: center; margin-bottom: 20px; } | |
| .logo { font-size: 36px; font-weight: bold; } | |
| .logo span:nth-child(1) { color: #4285f4; } | |
| .logo span:nth-child(2) { color: #ea4335; } | |
| .logo span:nth-child(3) { color: #fbbc05; } | |
| .logo span:nth-child(4) { color: #4285f4; } | |
| .logo span:nth-child(5) { color: #34a853; } | |
| .search-box { max-width: 584px; margin: 0 auto; } | |
| .search-box input[type="text"] { | |
| width: 100%; padding: 12px 20px; font-size: 16px; | |
| border: 1px solid #dfe1e5; border-radius: 24px; | |
| box-shadow: 0 1px 6px rgba(32,33,36,0.28); | |
| } | |
| .search-box input[type="submit"] { | |
| background-color: #f8f9fa; border: 1px solid #f8f9fa; | |
| border-radius: 4px; color: #3c4043; font-size: 14px; | |
| padding: 10px 16px; margin: 11px 4px; cursor: pointer; | |
| } | |
| .search-box input[type="submit"]:hover { | |
| border: 1px solid #dadce0; box-shadow: 0 1px 2px rgba(0,0,0,0.1); | |
| } | |
| .search-buttons { text-align: center; } | |
| </style> | |
| </head> | |
| <body> | |
| <div class="header"> | |
| <div class="logo"> | |
| <span>L</span><span>L</span><span>M</span><span> </span><span>Search</span> | |
| </div> | |
| </div> | |
| <div class="search-box"> | |
| <form method="get" action="/"> | |
| <input type="text" name="query" placeholder="Search..."> | |
| <input type="hidden" name="page" value="1"> | |
| <div class="search-buttons"> | |
| <input type="submit" name="btn" value="LLM Search"> | |
| <input type="submit" name="btn" value="I'm Feeling Lucky"> | |
| </div> | |
| </form> | |
| </div> | |
| </body> | |
| </html> | |
| """ | |
| return render_template_string(html_content) | |
| if btn == "I'm Feeling Lucky": | |
| results, error = fetch_search_results(query, stream=False) | |
| if error: | |
| return render_template_string(f""" | |
| <html> | |
| <head><title>LLM Search Engine</title></head> | |
| <body style="font-family: Arial, sans-serif;"> | |
| <h1>LLM Search Engine</h1> | |
| <form method="get" action="/"> | |
| <input type="text" name="query" value="{html.escape(query)}"> | |
| <input type="submit" value="Search"> | |
| </form> | |
| <p style="color: red;">{error}</p> | |
| </body> | |
| </html> | |
| """) | |
| first_url = results[0].get("url", "#") if results else "#" | |
| return Response(f""" | |
| <html> | |
| <head> | |
| <meta http-equiv="refresh" content="0; url={first_url}"> | |
| </head> | |
| <body> | |
| <p>Redirecting to {first_url}...</p> | |
| </body> | |
| </html> | |
| """, mimetype="text/html") | |
| # Stream results for "LLM Search" | |
| return Response(stream_search_results(query, page), mimetype="text/html") | |
| if __name__ == '__main__': | |
| app.run(debug=True, host='0.0.0.0', port=int(os.environ.get("PORT", 5000))) |