Update app.py
Browse files
app.py
CHANGED
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@@ -6,6 +6,7 @@ import os
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import numpy as np
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from sklearn.feature_extraction.text import TfidfVectorizer
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from sklearn.metrics.pairwise import cosine_similarity
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# Function to extract text from a PDF file
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def extract_text_from_pdf(pdf_file):
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@@ -28,6 +29,9 @@ def search_similar(query_embedding, index, stored_texts, top_k=3):
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# Function to generate HTML with nice styling
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def generate_html(response_content):
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html_template = f"""
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<!DOCTYPE html>
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<html lang="en">
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@@ -77,7 +81,7 @@ def generate_html(response_content):
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<h1>Course Query Response</h1>
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<div class="response">
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<h3>Answer:</h3>
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<p>{
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</div>
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<footer>
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<p>Generated by Course Query Assistant</p>
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@@ -150,7 +154,7 @@ if openai_api_key:
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# Get the response content
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response_content = response['choices'][0]['message']['content']
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# Display the response in Streamlit
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st.write("### Intelligent Reply:")
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st.write(response_content)
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import numpy as np
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from sklearn.feature_extraction.text import TfidfVectorizer
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from sklearn.metrics.pairwise import cosine_similarity
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import html
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# Function to extract text from a PDF file
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def extract_text_from_pdf(pdf_file):
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# Function to generate HTML with nice styling
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def generate_html(response_content):
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# Escape any HTML special characters to prevent unwanted rendering issues
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safe_content = html.escape(response_content)
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html_template = f"""
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<!DOCTYPE html>
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<html lang="en">
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<h1>Course Query Response</h1>
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<div class="response">
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<h3>Answer:</h3>
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<p>{safe_content}</p>
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</div>
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<footer>
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<p>Generated by Course Query Assistant</p>
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# Get the response content
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response_content = response['choices'][0]['message']['content']
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# Display the response in Streamlit (Intelligent Reply)
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st.write("### Intelligent Reply:")
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st.write(response_content)
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