Create app.py

app.py

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+import base64
+import os
+from datetime import datetime
+from openai import OpenAI
+import gradio as gr
+import oci
+
+# === OpenAI API Setup ===
+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)
+
+# === OCI Object Storage Setup ===
+oci_config = {
+    "user": os.environ.get("OCI_USER"),
+    "tenancy": os.environ.get("OCI_TENANCY"),
+    "fingerprint": os.environ.get("OCI_FINGERPRINT"),
+    "region": os.environ.get("OCI_REGION"),
+    "key_content": os.environ.get("OCI_PRIVATE_KEY")
+}
+
+# Optional: access OCI Object Storage (if needed)
+try:
+    object_storage = oci.object_storage.ObjectStorageClient(oci_config)
+except Exception as e:
+    print("Failed to initialize OCI Object Storage client:", e)
+
+# === 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."
+)
+
+# === Encode uploaded bytes ===
+def encode_image_to_base64(file_bytes):
+    return base64.b64encode(file_bytes).decode("utf-8")
+
+# === Transcription logic ===
+def transcribe_image(file_bytes):
+    if not file_bytes:
+        return "No image uploaded."
+
+    encoded = encode_image_to_base64(file_bytes)
+    image_url = f"data:image/jpeg;base64,{encoded}"
+
+    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")
+    return f"🗓️ Transcribed on: {timestamp}\n\n{response.choices[0].message.content}"
+
+# === Gradio Interface ===
+with gr.Blocks() as app:
+    gr.Markdown("## Handwritten Note Transcriber\nUpload a handwritten note image for professional transcription.")
+    input_file = gr.File(label="Upload image", type="binary", file_types=[".jpg", ".jpeg", ".png"])
+    output_text = gr.Textbox(label="Transcription Output", lines=30)
+    input_file.change(fn=transcribe_image, inputs=input_file, outputs=output_text)
+
+# === Launch App ===
+if __name__ == "__main__":
+        app.launch(share=True)