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import gradio as gr
from llama_cpp import Llama
from paddleocr import PaddleOCR
from PIL import Image
# Load GGUF model
llm = Llama(
model_path="./deepseek-v3-0324.Q4_K_M.gguf", # Make sure this file is in your repo
n_ctx=2048,
n_threads=8,
n_gpu_layers=20 # Set to 0 if you are on CPU-only
)
# OCR Function
def ocr_inference(img, lang):
ocr = PaddleOCR(use_angle_cls=True, lang=lang, use_gpu=False)
result = ocr.ocr(img, cls=True)[0]
txts = [line[1][0] for line in result]
return " ".join(txts)
# Step 1: Convert text to base form words
def text_inference(text, language):
prompt = (
f"Given the following {language} text, convert each word into its base form. "
f"Remove all duplicates. Return the base form words as a comma-separated list.\n\n"
f"Text:\n{text}"
)
response = llm(prompt, max_tokens=256, stop=["</s>"])
output_text = response["choices"][0]["text"].strip()
words = [w.strip() for w in output_text.split(",") if w.strip()]
return words
# Step 2: Generate flashcards for those words
def make_flashcards(words, language):
prompt = (
f"For each {language} word in the list, write a flashcard in this format:\n"
f"word - definition - example sentence - translated sentence.\n\n"
f"Words:\n{', '.join(words)}"
)
response = llm(prompt, max_tokens=512, stop=["</s>"])
return response["choices"][0]["text"].strip()
# Wrapper logic to handle OCR or text
def flashcard_pipeline(text, image, language):
if image:
text = ocr_inference(image, language)
if not text:
return "", "Please provide either text or an image."
words = text_inference(text, language)
flashcards = make_flashcards(words, language)
return "\n".join(words), flashcards
# Gradio UI
demo = gr.Interface(
fn=flashcard_pipeline,
inputs=[
gr.Textbox(label="Input Text (leave empty to use image)", lines=4, placeholder="Type or paste sentence here..."),
gr.Image(label="Upload Image for OCR (optional)", type="filepath"),
gr.Dropdown(choices=["korean", "japan", "french", "ch"], label="Language (for OCR and LLM)")
],
outputs=[
gr.Textbox(label="Base Form Words"),
gr.Textbox(label="Flashcards"),
],
title="Language Flashcard Generator (with OCR + DeepSeek GGUF)",
description="Either input text or upload an image. The app will extract words, lemmatize them, and generate flashcards."
)
if __name__ == "__main__":
demo.launch()
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