Delete main.py

main.py

@@ -1,65 +0,0 @@
-# main.py
-import gradio as gr
-from gradio.themes import Soft
-
-from question_runner import run_tool
-from config import MODEL_PRIORITY, SYNTAX_DOC_URL, MORPHOLOGY_DOC_URL, SEMANTICS_DOC_URL
-from doc_utils import get_questions_from_doc
-
-# Estimate runtime based on # of questions
-def estimate_runtime(passage, doc_type):
-    if not passage or not doc_type:
-        return ""
-    if doc_type.lower() == "syntax":
-        doc_url = SYNTAX_DOC_URL
-    elif doc_type.lower() == "morphology":
-        doc_url = MORPHOLOGY_DOC_URL
-    else:  # semantics
-        doc_url = SEMANTICS_DOC_URL
-    questions = get_questions_from_doc(doc_url)
-    if not questions or (isinstance(questions, list) and questions and str(questions[0]).startswith("Error")):
-        return "Unable to load questions."
-    est_seconds = round(len(questions) * 2.5, 1)
-    return f"Estimated generation time: ~{est_seconds} seconds"
-
-# Build the Gradio interface at module level (required for HF Spaces)
-with gr.Blocks(theme=Soft()) as demo:
-    gr.Markdown("""
-    ## **Classical Language Query Assistant**
-    Submit a Latin or Greek passage and select the question type.
-    Answers are generated using a rotating chain of hosted AI models via OpenRouter.
-    """)
-
-    with gr.Row():
-        passage_input = gr.Textbox(label="Latin or Greek Passage", lines=4)
-        question_type = gr.Radio(["Syntax", "Morphology", "Semantics"], label="Question Type")
-
-    top_model = MODEL_PRIORITY[0]
-    full_model_list = "\n".join(f"- `{m}`" for m in MODEL_PRIORITY)
-    gr.Markdown(f"""
-**Currently prioritized model:** `{top_model}`  
-**Model fallback chain (if needed):**  
-{full_model_list}
-""")
-
-    estimated_time_box = gr.Textbox(label="Estimated Time", interactive=False)
-
-    with gr.Row():
-        output_text = gr.Textbox(label="Generated Answers", lines=25, interactive=False)
-        output_file = gr.File(label="Download Answers (.txt)", interactive=False)
-
-    passage_input.change(fn=estimate_runtime, inputs=[passage_input, question_type], outputs=estimated_time_box)
-    question_type.change(fn=estimate_runtime, inputs=[passage_input, question_type], outputs=estimated_time_box)
-
-    submit_button = gr.Button("Generate Answers")
-
-    # Connect the button to run_tool function directly
-    submit_button.click(
-        fn=run_tool,
-        inputs=[passage_input, question_type],
-        outputs=[output_text, output_file, estimated_time_box],
-        api_name="generate"
-    )
-
-if __name__ == "__main__":
-    demo.launch()