tab_search.py

import gradio as gr
from config import SEARCH_SYSTEM_PROMPT

def handle_web_search(query):
    """Handle the logic for the 'Web Search' tab"""
    # Simulate Ring model for web search and summarization
    # In a real application, SEARCH_SYSTEM_PROMPT would be used here
    summary = f"Based on a web search, here is a summary about '{query}':\n\nThis is a summary answer simulated by the Ring model. In a real application, the model would access the internet, retrieve relevant information, and generate a high-quality summary.\n\n### Key Points:\n- **Point 1**: This is the first key piece of information.\n- **Point 2**: This is the second key piece of information.\n- **Point 3**: This is the third key piece of information."

    sources = """### Sources:
* [Source 1: Example Domain](https://example.com)
* [Source 2: Another Example](https://example.com)
* [Source 3: Wikipedia](https://wikipedia.org)"""

    full_response = f"{summary}\n\n{sources}"
    
    return gr.update(value=full_response, visible=True)

def create_search_tab():
    gr.Markdown("<p align='center'>work in progress XD</p>")
    with gr.Column():
        search_input = gr.Textbox(label="Search Input", placeholder="Enter a question to search and summarize...")
        gr.Examples(
            examples=["What are the latest advancements in AI?", "Explain the Transformer architecture", "Summarize today's news headlines"],
            label="Example Prompts",
            inputs=[search_input]
        )
        search_button = gr.Button("✨ Search")
        search_results_output = gr.Markdown(label="Results Display", visible=False)

    return {
        "search_input": search_input,
        "search_button": search_button,
        "search_results_output": search_results_output
    }