Update README.md

README.md

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-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# LLM Search Engine
+
+This is a Flask-based web application that uses a large language model (LLM) to generate search engine-like results, styled to resemble Google’s classic search results page. Instead of querying an external search API, it prompts an LLM to create titles, snippets, and URLs for a given query, delivering a paginated, familiar interface.
+
+## Why We Built It
+
+We created this app to explore how LLMs can mimic traditional search engines by generating results directly from their training data. It offers:
+- A nostalgic, Google-like pagination design with clickable links.
+- A proof-of-concept for LLM-driven search without real-time web access.
+- A simple, self-contained alternative for queries within the model’s knowledge base.
+
+## Features
+- **Google-Styled Interface**: Search bar, result list, and pagination styled with Google’s colors and layout.
+- **Generated Results**: Titles, snippets, and URLs are fully produced by the LLM.
+- **Pagination**: Displays 10 results per page, up to 30 total results across 3 pages.
+
+## Limitations
+- **Static Knowledge**: Results are limited to the LLM’s training cutoff (e.g., pre-2025).
+- **Generated Content**: URLs and snippets may not correspond to real web pages—use as a starting point.
+- **No Real-Time Data**: Best for historical or established topics, not breaking news.
+
+## Using It on Hugging Face Spaces
+
+### Try the Demo
+Deployed on Hugging Face Spaces, you can test it at [https://codelion-llmsearchengine.hf.space](https://codelion-llmsearchengine.hf.space):
+1. Open the URL in your browser.
+2. Type a query (e.g., "best Python libraries") in the search bar and press Enter or click "LLM Search".
+3. Browse the paginated results, styled like Google, using "Previous" and "Next" links.