File size: 2,322 Bytes
d675a30
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
import base64
from datetime import datetime
from openai import OpenAI
import gradio as gr

# === Initialize OpenAI Client ===
client = OpenAI()

# === 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_image(image):
    if image is None:
        return "No image uploaded."

    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")
    return f"🗓️ Transcribed on: {timestamp}\n\n{response.choices[0].message.content}"

# === Gradio Interface ===
app = gr.Interface(
    fn=transcribe_image,
    inputs=gr.Image(type="file", label="Upload handwritten note (image)"),
    outputs=gr.Textbox(label="Transcribed Output"),
    title="Handwritten Note Transcriber",
    description="Upload an image of handwritten notes to receive a clean, professional transcription."
)

# === Launch ===
if __name__ == "__main__":
    app.launch()