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import base64
import os
from datetime import datetime
from openai import OpenAI
import gradio as gr
# === 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(files):
if not files:
return "No images uploaded."
results = []
for file in files:
encoded_image = encode_image_to_base64(file)
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 using UploadButton ===
with gr.Blocks() as app:
with gr.Row():
uploader = gr.UploadButton(
label="Upload handwritten note images",
file_types=[".jpg", ".jpeg", ".png"],
file_types_multiple=True
)
output_box = gr.Textbox(label="Transcribed Output", lines=30)
uploader.change(fn=transcribe_images, inputs=uploader, outputs=output_box)
# === Launch ===
if __name__ == "__main__":
app.launch()
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