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Update app.py
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app.py
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import base64
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from datetime import datetime
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from openai import OpenAI
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import gradio as gr
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# === Initialize OpenAI Client ===
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# === Prompts ===
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system_prompt = (
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@@ -28,37 +33,48 @@ def encode_image_to_base64(image_file):
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return base64.b64encode(image_bytes).decode("utf-8")
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# === Transcription function ===
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def
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if
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return "No
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": [
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{"type": "text", "text": user_prompt_template},
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{"type": "image_url", "image_url": {"url": image_url}}
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]}
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],
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max_tokens=1500
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)
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return f"🗓️ Transcribed on: {timestamp}\n\n{response.choices[0].message.content}"
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# === Gradio Interface ===
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app = gr.Interface(
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fn=
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inputs=gr.
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title="Handwritten Note Transcriber",
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description="Upload
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)
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# === Launch ===
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if __name__ == "__main__":
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app.launch()
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import base64
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import os
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from datetime import datetime
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from openai import OpenAI
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import gradio as gr
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# === Initialize OpenAI Client using Environment Variable ===
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openai_api_key = os.environ.get("OPENAI_API_KEY")
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if not openai_api_key:
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raise ValueError("OPENAI_API_KEY environment variable is not set.")
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client = OpenAI(api_key=openai_api_key)
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# === Prompts ===
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system_prompt = (
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return base64.b64encode(image_bytes).decode("utf-8")
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# === Transcription function ===
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def transcribe_images(images):
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if not images:
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return "No images uploaded."
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results = []
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for image in images:
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encoded_image = encode_image_to_base64(image)
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image_url = f"data:image/jpeg;base64,{encoded_image}"
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response = client.chat.completions.create(
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model="gpt-4-turbo",
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messages=[
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": [
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{"type": "text", "text": user_prompt_template},
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{"type": "image_url", "image_url": {"url": image_url}}
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]}
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],
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max_tokens=1500
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)
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timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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result_text = f"🗓️ Transcribed on: {timestamp}\n\n{response.choices[0].message.content}"
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results.append(result_text)
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return "\n\n---\n\n".join(results)
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# === Gradio Interface ===
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app = gr.Interface(
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fn=transcribe_images,
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inputs=gr.File(
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type="file",
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label="Upload handwritten note images",
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file_types=[".jpg", ".jpeg", ".png"],
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multiple=True
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),
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outputs=gr.Textbox(label="Transcribed Output", lines=30),
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title="Handwritten Note Transcriber",
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description="Upload one or more images of handwritten notes to receive clean, professional transcriptions."
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)
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# === Launch ===
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if __name__ == "__main__":
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app.launch()
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