Delete app.py

app.py

@@ -1,87 +0,0 @@
-import gradio as gr
-import google.generativeai as genai
-from transformers import pipeline
-import json
-from tempfile import NamedTemporaryFile
-from app import transfer_to_structure  # from your pptx-parser
-
-# ✅ Use your Gemini API Key
-GOOGLE_API_KEY = "AIzaSyA8fWpwJE21zxpuN8Fi8Qx9-iwx3d_AZiw"
-genai.configure(api_key=GOOGLE_API_KEY)
-
-# ✅ Load Summarization Model
-summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
-gemini_model = genai.GenerativeModel("models/gemini-1.5-flash")
-
-# ✅ Global text storage
-extracted_text = ""
-
-# ✅ Function to flatten PPTX-parsed JSON into readable text
-def extract_text_from_pptx_json(parsed_json: dict) -> str:
-    extracted_text = ""
-    for slide_key, slide in parsed_json.items():
-        for shape_key, shape in slide.items():
-            if shape.get('type') == 'group':
-                group = shape.get('group_content', {})
-                for _, group_shape in group.items():
-                    if group_shape.get('type') == 'text':
-                        for para_key, para in group_shape.items():
-                            if para_key.startswith("paragraph_"):
-                                extracted_text += para.get("text", "") + "\n"
-            elif shape.get('type') == 'text':
-                for para_key, para in shape.items():
-                    if para_key.startswith("paragraph_"):
-                        extracted_text += para.get("text", "") + "\n"
-    return extracted_text.strip()
-
-# ✅ Handler for file upload & parsing
-def handle_pptx_upload(pptx_file):
-    global extracted_text
-    with NamedTemporaryFile(delete=False, suffix=".pptx") as tmp:
-        tmp.write(pptx_file.read())
-        tmp_path = tmp.name
-
-    parsed_json_str, _, _ = transfer_to_structure(tmp_path, "images")
-    parsed_json = json.loads(parsed_json_str)
-    extracted_text = extract_text_from_pptx_json(parsed_json)
-    return extracted_text or "No readable text found in slides."
-
-# ✅ Summarization function
-def summarize_text():
-    global extracted_text
-    if not extracted_text:
-        return "Please upload and extract text from a PPTX file first."
-    summary = summarizer(extracted_text, max_length=200, min_length=50, do_sample=False)[0]['summary_text']
-    return summary
-
-# ✅ Gemini-powered Q&A
-def clarify_concept(question):
-    global extracted_text
-    if not extracted_text:
-        return "Please upload and extract text from a PPTX file first."
-    prompt = f"Context:\n{extracted_text}\n\nQuestion: {question}"
-    response = gemini_model.generate_content(prompt)
-    return response.text if response else "No response from Gemini."
-
-# ✅ Gradio UI
-with gr.Blocks() as demo:
-    gr.Markdown("## 🧠 AI-Powered Study Assistant for PowerPoint Lectures")
-
-    pptx_input = gr.File(label="📂 Upload PPTX File")
-    extract_btn = gr.Button("📜 Extract & Summarize")
-
-    extracted_output = gr.Textbox(label="📄 Extracted Text", lines=10, interactive=False)
-    summary_output = gr.Textbox(label="📝 Summary", interactive=False)
-
-    extract_btn.click(handle_pptx_upload, inputs=[pptx_input], outputs=[extracted_output])
-    extract_btn.click(summarize_text, outputs=[summary_output])
-
-    question = gr.Textbox(label="❓ Ask a Question")
-    ask_btn = gr.Button("💬 Ask Gemini")
-    ai_answer = gr.Textbox(label="🤖 Gemini Answer", lines=4)
-
-    ask_btn.click(clarify_concept, inputs=[question], outputs=[ai_answer])
-
-# ✅ Run Gradio app
-if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7860, share=True)