import gradio as gr from retrieval_leaderboard import create_retrieval_tab from reranking_leaderboard import create_reranking_tab from llm_in_context_leaderboard import create_llm_in_context_tab from dotenv import load_dotenv load_dotenv() HEADER = """

The Arabic RAG Leaderboard

The only leaderboard you will require for your RAG needs 🏆

This leaderboard presents the first comprehensive benchmark for Arabic RAG systems, evaluating both retrieval and re-ranking components. Our framework combines real-world queries with synthetic contexts in a dynamic evaluation cycle, ensuring fair and robust assessment of Arabic information retrieval systems.

For technical details, check our blog post here. """ CITATION_BUTTON_LABEL = """ Copy the following snippet to cite these results """ CITATION_BUTTON_TEXT = """ @misc{TARL, author = {Mohaned A. Rashad, Hamza Shahid}, title = {The Arabic RAG Leaderboard}, year = {2025}, publisher = {Navid-AI}, howpublished = "url{https://huggingface.co/spaces/Navid-AI/The-Arabic-Rag-Leaderboard}" } """ def main(): with gr.Blocks() as demo: gr.HTML(HEADER) with gr.Tabs(): with gr.Tab("🕵️‍♂️ Retrieval"): create_retrieval_tab() with gr.Tab("📊 Reranking"): create_reranking_tab() # with gr.Tab("📊 LLM in Context"): # create_llm_in_context_tab() with gr.Row(): with gr.Accordion("📙 Citation", open=False): gr.Textbox( value=CITATION_BUTTON_TEXT, label=CITATION_BUTTON_LABEL, lines=20, elem_id="citation-button", show_copy_button=True, ) demo.launch() if __name__ == "__main__": main()