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for log, one output simplified
Browse files
app.py
CHANGED
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@@ -43,8 +43,18 @@ tax_deductions = '''Extract the following information in the given format:
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'''
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{
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"role": "user",
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"content": [
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@@ -92,27 +102,11 @@ def demo(image_path, prompt):
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json = literal_eval(almost_json)
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except:
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json = output_text[0] # Return raw output if JSON parsing fails
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return json
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def process_document(image):
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# Save the uploaded image to a temporary file
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with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as tmp_file:
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image = Image.fromarray(image) # Convert NumPy array to PIL Image
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image.save(tmp_file.name) # Save the image to the temporary file
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image_path = tmp_file.name # Get the path of the saved file
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# Process the image with your model
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one = demo(image_path, other_benifits)
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two = demo(image_path, tax_deductions)
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json_op = {
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"tax_deductions": one,
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"other_benifits": two
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}
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# Optionally, you can delete the temporary file after use
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os.remove(image_path)
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return
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# Create Gradio interface
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demo = gr.Interface(
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}
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'''
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def process_document(image):
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# Save the uploaded image to a temporary file
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with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as tmp_file:
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image = Image.fromarray(image) # Convert NumPy array to PIL Image
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image.save(tmp_file.name) # Save the image to the temporary file
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image_path = tmp_file.name # Get the path of the saved file
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messages = [
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{
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"role": "user",
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"content": [
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json = literal_eval(almost_json)
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except:
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json = output_text[0] # Return raw output if JSON parsing fails
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# Optionally, you can delete the temporary file after use
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os.remove(image_path)
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return json
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# Create Gradio interface
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demo = gr.Interface(
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