Create app.py

app.py

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+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+import json
+
+# Load words and languages from JSON files
+with open("top_500_quran_lemmas_fixed.json", encoding="utf-8") as f:
+    word_list = json.load(f)
+
+with open("language_list.json", encoding="utf-8") as f:
+    language_list = json.load(f)
+
+# Format dropdown options
+word_options = [f"{word['text']} ({word['english']})" for word in word_list]
+language_options = [f"{lang['name']} ({lang['code']})" for lang in language_list]
+
+# Load DeepSeek-V3 model
+model_id = "deepseek-ai/DeepSeek-V3"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", device_map="auto")
+generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+# Generate prompt
+def create_prompt(word_entry, language_code):
+    prompt = f"""
+You are a friendly Quranic AI assistant.
+
+The word is: {word_entry['text']} ({word_entry['english']})
+
+Please provide the following in simple, easy-to-understand language, translated into {language_code}:
+1. Translation of the word.
+2. Its root word and any related words (derivatives).
+3. Where it appears in the Qur'an — list the Surah and Ayah numbers.
+4. Give an explanation of each appearance (based on context), in {language_code}.
+
+Avoid technical terms. Make it feel like a helpful teacher explaining to a student.
+"""
+    return prompt.strip()
+
+# Function to call the model
+def process(word_label, lang_label):
+    # Extract selected word data
+    selected_word = next((w for w in word_list if w['text'] in word_label), None)
+    language_code = lang_label.split("(")[-1].strip(")")
+
+    if not selected_word:
+        return "Word not found in list."
+
+    prompt = create_prompt(selected_word, language_code)
+    result = generator(prompt, max_new_tokens=800, do_sample=True, temperature=0.7)[0]["generated_text"]
+
+    return result.replace(prompt, "").strip()
+
+# Gradio UI
+with gr.Blocks() as demo:
+    gr.Markdown("## 📖 Quran Word Explorer with DeepSeek-V3")
+    with gr.Row():
+        word_input = gr.Dropdown(choices=word_options, label="Select a Quran Word")
+        lang_input = gr.Dropdown(choices=language_options, label="Select Language")
+
+    output = gr.Textbox(label="DeepSeek-V3 Output", lines=20)
+    run_btn = gr.Button("Get Info")
+
+    run_btn.click(fn=process, inputs=[word_input, lang_input], outputs=output)
+
+demo.launch()