Create app.py

app.py

@@ -0,0 +1,171 @@
+import gradio as gr
+import openai
+import os
+import json
+
+# Set OpenAI API key and base URL from environment variables
+openai.api_key = os.environ["OPENAI_API_KEY"]
+openai.base_url = os.environ["OPENAI_BASE_URL"]
+
+# Define the number of results per page and total results to generate
+RESULTS_PER_PAGE = 10
+TOTAL_RESULTS = 30  # Generate 30 results to allow pagination
+
+def fetch_search_results(query):
+    """Fetch search results from the LLM based on the user's query."""
+    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 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 = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo",  # Adjust model name as needed
+            messages=[
+                {"role": "system", "content": "You are a helpful search engine."},
+                {"role": "user", "content": prompt}
+            ],
+            response_format="json_object"
+        )
+        
+        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 openai.error.OpenAIError as e:
+        return None, f"Error: {str(e)}"
+    except json.JSONDecodeError:
+        return None, "Error: Failed to parse JSON response."
+    except Exception as e:
+        return None, f"Unexpected error: {str(e)}"
+
+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
+    end_idx = start_idx + RESULTS_PER_PAGE
+    total_pages = (len(results) + RESULTS_PER_PAGE - 1) // RESULTS_PER_PAGE
+    
+    # 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 (simulated with buttons)
+    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>'
+    
+    # Note: Gradio doesn't support interactive JS directly in HTML outputs,
+    # so we return page numbers for button functionality
+    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.")
+    
+    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
+    
+    search_button.click(
+        fn=on_submit,
+        inputs=[query_input, page_state],
+        outputs=[output_html, page_state]
+    )
+    
+    # Note: For full pagination, we simulate Previous/Next with additional 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
+    search_button.click(
+        fn=lambda q, p: (search_handler(q, p), p, gr.update(visible=p > 1), gr.update(visible=True)),
+        inputs=[query_input, page_state],
+        outputs=[output_html, page_state, prev_button, next_button]
+    )
+
+app.launch()