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LLMSearchEngine

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codelion commited on Feb 28

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1cc26a0

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1 Parent(s): c12e9a4

Update app.py

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app.py +144 -105

app.py CHANGED Viewed

@@ -2,6 +2,7 @@ import gradio as gr
 from openai import OpenAI
 import os
 import json
 # Initialize OpenAI client with API key and base URL from environment variables
 client = OpenAI(
@@ -20,14 +21,17 @@ def fetch_search_results(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 with a title and a snippet that summarizes the information.
-    Format the response as a JSON array of objects, where each object has 'title' and 'snippet' fields.
-    Ensure the results are diverse and relevant to the query.
     """
     try:
         response = client.chat.completions.create(
-            model="gemini-2.0-flash-lite",  # Adjust model name as needed (e.g., 'xai-model-name')
             messages=[
                 {"role": "system", "content": "You are a helpful search engine."},
                 {"role": "user", "content": prompt}
@@ -57,12 +61,20 @@ def fetch_search_results(query):
         else:
             return None, f"Error: {error_msg}"
-def display_search_results(query, page=1):
-    """Display search results for the given query and page number."""
     results, error = fetch_search_results(query)
     if error:
-        return error, None, None
     # Calculate pagination boundaries
     start_idx = (page - 1) * RESULTS_PER_PAGE
@@ -71,118 +83,145 @@ def display_search_results(query, page=1):
     # Ensure indices are within bounds
     if start_idx >= len(results):
-        return "No more results to display.", None, None
     paginated_results = results[start_idx:end_idx]
-    # Format results into HTML
     html = """
-    <style>
-    .search-result {
-        margin-bottom: 20px;
-    }
-    .search-result h3 {
-        color: blue;
-        font-size: 18px;
-        margin: 0;
-    }
-    .search-result p {
-        font-size: 14px;
-        margin: 5px 0 0 0;
-    }
-    .pagination {
-        margin-top: 20px;
-    }
-    </style>
-    <div>
     """
-    html += f"<h2>Search Results for '{query}' (Page {page} of {total_pages})</h2>"
-    html += "<ul>"
     for result in paginated_results:
         title = result.get("title", "No title")
         snippet = result.get("snippet", "No snippet")
-        html += f'<li class="search-result"><h3>{title}</h3><p>{snippet}</p></li>'
-    html += "</ul>"
-    # Add pagination controls
     html += '<div class="pagination">'
     if page > 1:
-        html += f'<button onclick="update_page({page - 1})">Previous</button>'
     if page < total_pages:
-        html += f'<button onclick="update_page({page + 1})">Next</button>'
-    html += '</div></div>'
-    return html, page - 1 if page > 1 else None, page + 1 if page < total_pages else None
-def search_handler(query, page):
-    """Handle search submission and pagination."""
-    html, prev_page, next_page = display_search_results(query, page)
     return html
-# Build Gradio interface with Blocks for state management
 with gr.Blocks(title="LLM Search Engine") as app:
-    gr.Markdown("# LLM Search Engine")
-    gr.Markdown("Enter a query below to search using a large language model (press Enter or click Search).")
-    query_input = gr.Textbox(label="Search Query", placeholder="Type your search here...")
-    search_button = gr.Button("Search")
-    output_html = gr.HTML()
-    # Hidden state to track current page
-    page_state = gr.State(value=1)
-    # Define submit behavior
-    def on_submit(query, page):
-        return search_handler(query, page), page
-    # Trigger search on Enter key or button click
-    query_input.submit(
-        fn=on_submit,
-        inputs=[query_input, page_state],
-        outputs=[output_html, page_state]
-    )
-    search_button.click(
-        fn=on_submit,
-        inputs=[query_input, page_state],
-        outputs=[output_html, page_state]
-    )
-    # Pagination buttons
-    with gr.Row():
-        prev_button = gr.Button("Previous", visible=False)
-        next_button = gr.Button("Next", visible=False)
-    def update_page(query, page, direction):
-        new_page = page + direction
-        html, prev_page, next_page = display_search_results(query, new_page)
-        return html, new_page, gr.update(visible=prev_page is not None), gr.update(visible=next_page is not None)
-    prev_button.click(
-        fn=lambda q, p: update_page(q, p, -1),
-        inputs=[query_input, page_state],
-        outputs=[output_html, page_state, prev_button, next_button]
-    )
-    next_button.click(
-        fn=lambda q, p: update_page(q, p, 1),
-        inputs=[query_input, page_state],
-        outputs=[output_html, page_state, prev_button, next_button]
-    )
-    # Update button visibility after search
-    def update_visibility(query, page):
-        html, prev_page, next_page = display_search_results(query, page)
-        return html, page, gr.update(visible=prev_page is not None), gr.update(visible=next_page is not None)
-    query_input.submit(
-        fn=update_visibility,
-        inputs=[query_input, page_state],
-        outputs=[output_html, page_state, prev_button, next_button]
-    )
-    search_button.click(
-        fn=update_visibility,
-        inputs=[query_input, page_state],
-        outputs=[output_html, page_state, prev_button, next_button]
-    )
 app.launch()

 from openai import OpenAI
 import os
 import json
+from functools import partial
 # Initialize OpenAI client with API key and base URL from environment variables
 client = OpenAI(
     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}
         else:
             return None, f"Error: {error_msg}"
+def generate_search_page(query, page=1):
+    """Generate a full HTML search results page."""
     results, error = fetch_search_results(query)
     if error:
+        return f"""
+        <html>
+        <head><title>LLM Search Engine</title></head>
+        <body style="font-family: Arial, sans-serif;">
+            <h1>LLM Search Engine</h1>
+            <p style="color: red;">{error}</p>
+        </body>
+        </html>
+        """
     # Calculate pagination boundaries
     start_idx = (page - 1) * RESULTS_PER_PAGE
     # Ensure indices are within bounds
     if start_idx >= len(results):
+        return """
+        <html>
+        <head><title>LLM Search Engine</title></head>
+        <body style="font-family: Arial, sans-serif;">
+            <h1>LLM Search Engine</h1>
+            <p>No more results to display.</p>
+        </body>
+        </html>
+        """
     paginated_results = results[start_idx:end_idx]
+    # Generate full HTML page
     html = """
+    <html>
+    <head>
+        <title>LLM Search Engine</title>
+        <style>
+            body {
+                font-family: Arial, sans-serif;
+                margin: 0;
+                padding: 20px;
+                max-width: 800px;
+                margin-left: auto;
+                margin-right: auto;
+            }
+            .search-box {
+                margin-bottom: 20px;
+            }
+            .search-box input[type="text"] {
+                width: 70%;
+                padding: 8px;
+                font-size: 16px;
+                border: 1px solid #dfe1e5;
+                border-radius: 4px;
+            }
+            .search-box input[type="submit"] {
+                padding: 8px 16px;
+                font-size: 14px;
+                background-color: #f8f9fa;
+                border: 1px solid #dfe1e5;
+                border-radius: 4px;
+                cursor: pointer;
+            }
+            .search-result {
+                margin-bottom: 20px;
+            }
+            .search-result a {
+                color: #1a0dab;
+                font-size: 18px;
+                text-decoration: none;
+            }
+            .search-result a:hover {
+                text-decoration: underline;
+            }
+            .search-result .url {
+                color: #006621;
+                font-size: 14px;
+                margin: 2px 0;
+            }
+            .search-result p {
+                color: #545454;
+                font-size: 14px;
+                margin: 2px 0;
+            }
+            .pagination {
+                margin-top: 20px;
+                text-align: center;
+            }
+            .pagination a {
+                color: #1a0dab;
+                margin: 0 10px;
+                text-decoration: none;
+            }
+            .pagination a:hover {
+                text-decoration: underline;
+            }
+            .pagination span {
+                color: #545454;
+                margin: 0 10px;
+            }
+        </style>
+    </head>
+    <body>
+        <h1>LLM Search Engine</h1>
+        <form class="search-box" method="get" action="/">
+            <input type="text" name="query" value="{query}" placeholder="Type your search here...">
+            <input type="submit" value="Search">
+            <input type="hidden" name="page" value="1">
+        </form>
+        <h2>Results for '{query}' (Page {page} of {total_pages})</h2>
     """
+    # Add search results
     for result in paginated_results:
         title = result.get("title", "No title")
         snippet = result.get("snippet", "No snippet")
+        url = result.get("url", "#")
+        html += f"""
+        <div class="search-result">
+            <a href="{url}" target="_blank">{title}</a>
+            <div class="url">{url}</div>
+            <p>{snippet}</p>
+        </div>
+        """
+    # Add pagination
     html += '<div class="pagination">'
     if page > 1:
+        html += f'<a href="/?query={query}&page={page - 1}">Previous</a>'
+    else:
+        html += '<span>Previous</span>'
+    html += f'<span>Page {page} of {total_pages}</span>'
     if page < total_pages:
+        html += f'<a href="/?query={query}&page={page + 1}">Next</a>'
+    else:
+        html += '<span>Next</span>'
+    html += '</div>'
+    html += """
+    </body>
+    </html>
+    """
     return html
+# Define the app with Blocks
 with gr.Blocks(title="LLM Search Engine") as app:
+    # Custom route handler
+    def handle_request(query, page):
+        try:
+            page = int(page) if page else 1
+        except (ValueError, TypeError):
+            page = 1
+        return generate_search_page(query, page)
+    # Use a Route to serve raw HTML
+    app.route("/", inputs=[gr.Textbox(visible=False, value=""), gr.Number(visible=False, value=1)],
+               outputs=gr.HTML(), _js="() => [new URLSearchParams(window.location.search).get('query') || '', new URLSearchParams(window.location.search).get('page') || '1']",
+               fn=handle_request)
 app.launch()