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Update app.py
Browse files
app.py
CHANGED
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@@ -1,3 +1,6 @@
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import gradio as gr
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import torch
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import re
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@@ -56,6 +59,34 @@ model = AutoModelForCausalLM.from_pretrained(
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print("Model loaded successfully!")
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@spaces.GPU
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def extract_arguments(text, temperature=0.1):
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if not text or not text.strip():
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@@ -82,6 +113,7 @@ Extract arguments from historical text. Arguments in historical texts are often
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temperature = 0.3
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except:
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temperature = 0.1
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with torch.no_grad():
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outputs = model.generate(
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**inputs,
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@@ -96,8 +128,6 @@ Extract arguments from historical text. Arguments in historical texts are often
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generated_tokens = outputs[0][input_length:]
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response = tokenizer.decode(generated_tokens, skip_special_tokens=True)
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-
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# Fix XML start
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if not response.startswith('<argument>'):
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arg_start = response.find('<argument>')
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@@ -107,31 +137,6 @@ Extract arguments from historical text. Arguments in historical texts are often
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formatted = format_output(response)
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return response, formatted
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'''def format_output(xml_response):
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def extract_field(field_name):
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pattern = f'<{field_name}>(.*?)</{field_name}>'
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match = re.search(pattern, xml_response, re.DOTALL)
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return match.group(1).strip() if match else 'ERROR'
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argument = extract_field('argument')
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claim = extract_field('claim')
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explanation = extract_field('explanation')
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verification = extract_field('human_verification_needed')
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if argument != 'NA' and argument != 'ERROR':
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return f"""✅ **Argument Found**
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**Argument:** {argument}
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**Claim:** {claim}
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**Explanation:** {explanation}
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**Verification Needed:** {verification}"""
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else:
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return """❌ **No Argument Found**
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The text does not contain an argumentative unit."""'''
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# Gradio interface
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demo = gr.Interface(
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@@ -153,6 +158,5 @@ demo = gr.Interface(
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]
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)
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-
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if __name__ == "__main__":
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demo.launch()
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import os
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os.environ["OMP_NUM_THREADS"] = "1"
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import gradio as gr
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import torch
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import re
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)
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print("Model loaded successfully!")
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def format_output(xml_response):
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def extract_field(field_name):
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pattern = f'<{field_name}>(.*?)</{field_name}>'
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match = re.search(pattern, xml_response, re.DOTALL)
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return match.group(1).strip() if match else 'ERROR'
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argument = extract_field('argument')
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claim = extract_field('claim')
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explanation = extract_field('explanation')
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verification = extract_field('human_verification_needed')
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if argument != 'NA' and argument != 'ERROR':
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return f"""✅ **Argument Found**
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**Argument:** {argument}
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**Claim:** {claim}
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**Explanation:** {explanation}
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**Verification Needed:** {verification}"""
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else:
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return """❌ **No Argument Found**
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The text does not contain an argumentative unit."""
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@spaces.GPU
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def extract_arguments(text, temperature=0.1):
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if not text or not text.strip():
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temperature = 0.3
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except:
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temperature = 0.1
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with torch.no_grad():
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outputs = model.generate(
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**inputs,
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generated_tokens = outputs[0][input_length:]
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response = tokenizer.decode(generated_tokens, skip_special_tokens=True)
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# Fix XML start
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if not response.startswith('<argument>'):
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arg_start = response.find('<argument>')
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formatted = format_output(response)
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return response, formatted
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# Gradio interface
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demo = gr.Interface(
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]
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)
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if __name__ == "__main__":
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demo.launch()
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