Update app.py

app.py

@@ -1,84 +1,13 @@
-import base64
-import os
-from datetime import datetime
-from openai import OpenAI
 import gradio as gr
 
-import gradio
-print("Gradio version:", gradio.__version__)
+def echo(files):
+    return f"Received {len(files)} file(s)."
 
-
-# === Initialize OpenAI Client using Environment Variable ===
-openai_api_key = os.environ.get("OPENAI_API_KEY")
-if not openai_api_key:
-    raise ValueError("OPENAI_API_KEY environment variable is not set.")
-
-client = OpenAI(api_key=openai_api_key)
-
-# === Prompts ===
-system_prompt = (
-    "You are a detail-oriented assistant that specializes in transcribing and polishing "
-    "handwritten notes from images. Your goal is to turn rough, casual, or handwritten "
-    "content into clean, structured, and professional-looking text that sounds like it "
-    "was written by a human—not an AI. You do not include icons, emojis, or suggest next "
-    "steps unless explicitly instructed."
-)
-
-user_prompt_template = (
-    "You will receive an image of handwritten notes. Transcribe the content accurately, "
-    "correcting any spelling or grammar issues. Then, organize it clearly with headings, "
-    "bullet points, and proper formatting. Maintain the original intent and voice of the "
-    "author, but enhance readability and flow. Do not add embellishments or AI-style phrasing."
-)
-
-# === Image processing ===
-def encode_image_to_base64(image_file):
-    image_bytes = image_file.read()
-    return base64.b64encode(image_bytes).decode("utf-8")
-
-# === Transcription function ===
-def transcribe_images(images):
-    if not images:
-        return "No images uploaded."
-
-    results = []
-    for image in images:
-        encoded_image = encode_image_to_base64(image)
-        image_url = f"data:image/jpeg;base64,{encoded_image}"
-
-        response = client.chat.completions.create(
-            model="gpt-4-turbo",
-            messages=[
-                {"role": "system", "content": system_prompt},
-                {"role": "user", "content": [
-                    {"type": "text", "text": user_prompt_template},
-                    {"type": "image_url", "image_url": {"url": image_url}}
-                ]}
-            ],
-            max_tokens=1500
-        )
-
-        timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
-        result_text = f"🗓️ Transcribed on: {timestamp}\n\n{response.choices[0].message.content}"
-        results.append(result_text)
-
-    return "\n\n---\n\n".join(results)
-
-# === Gradio Interface ===
-app = gr.Interface(
-    fn=transcribe_images,
-    inputs=gr.File(
-        type="file",
-        label="Upload handwritten note images",
-        file_types=[".jpg", ".jpeg", ".png"],
-        multiple=True
-    ),
-    outputs=gr.Textbox(label="Transcribed Output", lines=30),
-    title="Handwritten Note Transcriber",
-    description="Upload one or more images of handwritten notes to receive clean, professional transcriptions."
+demo = gr.Interface(
+    fn=echo,
+    inputs=gr.File(label="Upload", file_types=[".jpg", ".jpeg", ".png"], type="file", multiple=True),
+    outputs="text"
 )
 
-# === Launch ===
-if __name__ == "__main__":
-    app.launch()
+demo.launch()