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import gradio as gr
from docx import Document
from transformers import pipeline
import tempfile
import time
# Load Mistral model
chatbot = pipeline(
"text-generation",
model="mistralai/Mistral-7B-Instruct-v0.1",
device_map="auto",
trust_remote_code=True
)
# Read .docx file and extract questions
def read_questions_from_docx(document_path):
doc = Document(document_path)
return [p.text.strip() for p in doc.paragraphs if p.text.strip().endswith("?")]
# --- Load .docx once into memory ---
syntax_questions = read_questions_from_docx("Syntax Questions.docx")
morphology_questions = read_questions_from_docx("Morphology Questions.docx")
# Main function
def run_tool(passage, question_type):
if not passage.strip():
return "Please enter a passage to analyze.", None, None
try:
questions = syntax_questions if question_type.lower() == "syntax" else morphology_questions
if not questions:
return "No valid questions found.", None, None
est_seconds = round(len(questions) * 3.5, 1)
estimated_time = f"Estimated generation time: ~{est_seconds} seconds"
prompt = f"You are a classical language expert.\n\nHere is the passage:\n{passage}\n\n"
prompt += "Answer the following questions clearly and completely:\n\n"
for idx, q in enumerate(questions):
prompt += f"Q{idx+1}: {q}\n"
result = chatbot(prompt, max_new_tokens=1600, do_sample=False)[0]["generated_text"].strip()
# Save result to .txt
with tempfile.NamedTemporaryFile(delete=False, suffix=".txt", mode="w", encoding="utf-8") as f:
f.write(result)
file_path = f.name
return result, file_path, estimated_time
except Exception as e:
return f"An error occurred: {str(e)}", None, None
# --- Gradio UI ---
with gr.Blocks(theme="soft") as demo:
gr.Markdown("""
## **Classical Language Query Assistant**
Submit a Latin or Greek passage and select whether to analyze **syntax** or **morphology**.
Answers are generated using **Mistral-7B-Instruct**, hosted via Hugging Face.
""")
with gr.Row():
passage_input = gr.Textbox(label="Latin or Greek Passage", placeholder="Paste your passage here...", lines=4)
question_type = gr.Radio(["Syntax", "Morphology"], label="Select Question Set")
with gr.Row():
output_text = gr.Textbox(label="Generated Answers", lines=25, interactive=False)
output_file = gr.File(label="Download Answers (.txt)", interactive=False)
est_time = gr.Textbox(label="Estimated Time", interactive=False)
submit = gr.Button("Generate Answers")
submit.click(fn=run_tool, inputs=[passage_input, question_type], outputs=[output_text, output_file, est_time])
demo.launch()
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