Spaces:
Sleeping
Sleeping
app.py
CHANGED
@@ -14,7 +14,6 @@ st.set_page_config(page_title="📑 Contract Analyzer", layout="wide")
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# ========== FUNCTIONS ==========
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# Tải mô hình Hugging Face từ Hub
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@st.cache_resource
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def load_inference_client():
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return InferenceClient(repo_id="HuggingFaceH4/zephyr-7b-beta") # Mô hình Zephyr
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@@ -23,19 +22,23 @@ inference_client = load_inference_client()
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def extract_text_from_pdf(uploaded_file):
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try:
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with pdfplumber.open(uploaded_file) as pdf:
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return ""
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def load_text(file):
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if not file:
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return ""
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try:
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ext = file.name.split('.')[-1].lower()
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if ext == 'txt':
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return StringIO(file.getvalue().decode("utf-8")).read()
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@@ -79,7 +82,11 @@ def query_zephyr_model(text1, text2, question):
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prompt = f"Compare the following two contracts and answer the question:\nText 1: {text1}\nText 2: {text2}\nQuestion: {question}"
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try:
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result = inference_client(inputs=prompt)
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except Exception as e:
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st.error(f"Error querying the model: {e}")
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return None
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@@ -129,16 +136,15 @@ def main():
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user_question = st.text_input("Enter your question about the contracts:")
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if user_question and st.button("Analyze Question"):
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with st.spinner("Analyzing..."):
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try:
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pred = query_zephyr_model(text1, text2, user_question)
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st.success(pred)
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st.error(
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if __name__ == "__main__":
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main()
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# ========== FUNCTIONS ==========
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# Tải mô hình Hugging Face từ Hub
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def load_inference_client():
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return InferenceClient(repo_id="HuggingFaceH4/zephyr-7b-beta") # Mô hình Zephyr
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def extract_text_from_pdf(uploaded_file):
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try:
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with pdfplumber.open(uploaded_file) as pdf:
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text = "\n".join(page.extract_text() or "" for page in pdf.pages)
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if not text.strip():
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raise ValueError("No extractable text found in the PDF")
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return text
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except Exception as e:
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st.error(f"Error reading PDF: {e}")
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return ""
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def load_text(file):
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if not file:
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return ""
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try:
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# Check file size (e.g., limit to 10MB)
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if file.size > 10 * 1024 * 1024: # 10MB
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st.warning("File is too large. Please upload a smaller file.")
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return ""
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ext = file.name.split('.')[-1].lower()
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if ext == 'txt':
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return StringIO(file.getvalue().decode("utf-8")).read()
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prompt = f"Compare the following two contracts and answer the question:\nText 1: {text1}\nText 2: {text2}\nQuestion: {question}"
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try:
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result = inference_client(inputs=prompt)
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if 'generated_text' in result:
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return result['generated_text']
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else:
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st.error("No generated text found in the response.")
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return None
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except Exception as e:
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st.error(f"Error querying the model: {e}")
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return None
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user_question = st.text_input("Enter your question about the contracts:")
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if user_question and st.button("Analyze Question"):
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with st.spinner("Analyzing..."):
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try:
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pred = query_zephyr_model(text1, text2, user_question)
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if pred:
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st.success(pred)
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else:
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st.error("Failed to get a valid answer from the model.")
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except Exception as e:
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st.error(f"Failed on Document: {e}")
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if __name__ == "__main__":
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main()
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