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Systematic-Research-Paper-Review

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shukdevdatta123 commited on 20 days ago

Commit

06265a9

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1 Parent(s): 4f49a0e

Update app.py

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Files changed (1) hide show

app.py +11 -67

app.py CHANGED Viewed

@@ -5,7 +5,6 @@ import os
 import tempfile
 import base64
 from datetime import datetime
-import re
 # Variable to store API key
 api_key = ""
@@ -26,7 +25,7 @@ def extract_text_from_pdf(pdf_path):
         return f"Error extracting text from PDF: {str(e)}"
 # Function to interact with OpenAI API for systematic review
-def generate_systematic_review(pdf_files, review_question, include_tables=True, include_figures=True):
     if not api_key:
         return "Please enter your OpenAI API key first."
@@ -98,15 +97,11 @@ def generate_systematic_review(pdf_files, review_question, include_tables=True,
             pdf_names.append(pdf_name)
         # Prepare the user prompt with the review question and instructions
-        visual_instruction = ""
-        if include_tables and include_figures:
-            visual_instruction = " Please include important new generated tables and create essential figures (using SVG format) to illustrate key findings, trends, or conceptual frameworks in your review. Create at least 2-3 figures that help visualize the most important insights."
-        elif include_tables:
-            visual_instruction = " Please include important new generated tables in your review."
-        elif include_figures:
-            visual_instruction = " Please create essential figures (using SVG format) to illustrate key findings, trends, or conceptual frameworks in your review. Create at least 2-3 figures that help visualize the most important insights."
-        user_prompt = f"Please generate a systematic review of the following {len(pdf_files)} papers: {', '.join(pdf_names)}.{visual_instruction}\n\nReview Question: {review_question}"
         # Create the messages for the API call
         messages = [
@@ -126,9 +121,6 @@ def generate_systematic_review(pdf_files, review_question, include_tables=True,
         # Get the AI response
         review_content = response["choices"][0]["message"]["content"]
-        # Process and replace any SVG content with properly formatted SVG
-        review_content = process_svg_content(review_content)
         # Apply professional academic paper styling
         styled_html = f"""
         <!DOCTYPE html>
@@ -240,26 +232,18 @@ def generate_systematic_review(pdf_files, review_question, include_tables=True,
                     margin: 25px 0;
                     text-align: center;
                 }}
-                .figure svg {{
                     max-width: 100%;
-                    height: auto;
                 }}
                 .figure-caption {{
                     font-size: 14px;
                     color: #666;
                     margin-top: 10px;
-                    text-align: center;
                 }}
                 .footnote {{
                     font-size: 12px;
                     color: #777;
                 }}
-                svg {{
-                    display: block;
-                    margin: 0 auto;
-                    max-width: 100%;
-                    height: auto;
-                }}
                 @media print {{
                     body {{
                         background-color: white;
@@ -289,33 +273,6 @@ def generate_systematic_review(pdf_files, review_question, include_tables=True,
         </div>
         """
-# Function to clean up and format SVG content
-def process_svg_content(content):
-    # Find SVG blocks
-    svg_pattern = r'```svg\s*([\s\S]*?)\s*```'
-    def replace_svg(match):
-        svg_content = match.group(1).strip()
-        # Ensure proper SVG structure
-        if not svg_content.startswith('<svg'):
-            svg_content = f'<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 800 500">{svg_content}</svg>'
-        # Wrap in figure div with caption if not already
-        if '<div class="figure">' not in svg_content:
-            figure_number = len(re.findall(r'<div class="figure">', content[:match.start()])) + 1
-            return f"""
-            <div class="figure">
-                {svg_content}
-                <div class="figure-caption">Figure {figure_number}: Generated visualization of key findings.</div>
-            </div>
-            """
-        return svg_content
-    # Replace SVG code blocks with properly formatted SVG elements
-    processed_content = re.sub(svg_pattern, replace_svg, content)
-    return processed_content
 # Function to save uploaded files
 def save_uploaded_files(files):
     if not files:
@@ -465,13 +422,6 @@ custom_css = """
         border-radius: 8px;
     }
-    /* Checkbox Group */
-    .checkbox-group {
-        display: flex;
-        gap: 20px;
-        margin: 15px 0;
-    }
     /* Responsive adjustments */
     @media screen and (max-width: 768px) {
         .gradio-container {
@@ -491,7 +441,7 @@ with gr.Blocks(css=custom_css) as demo:
         1. Enter your OpenAI API key in the field below and click "Set API Key"
         2. Upload multiple PDF research papers (2 or more recommended)
         3. Enter your review question or topic
-        4. Choose visual elements to include (tables and/or figures)
         5. Click "Generate Systematic Review" to start the process
         6. After generation, you can download the review as HTML
@@ -500,8 +450,6 @@ with gr.Blocks(css=custom_css) as demo:
         - Be specific in your review question to get more focused results
         - The generated review will follow a systematic structure including research field identification, data extraction, analysis, and conclusions
         - The more papers you upload, the more comprehensive the review will be
-        - Tables help organize and compare findings across studies
-        - Figures help visualize key trends, frameworks, or relationships identified in the review
         - The review will be formatted as a professional academic paper with proper sections and citations
         """)
@@ -523,11 +471,7 @@ with gr.Blocks(css=custom_css) as demo:
                 value="Please generate a systematic review of the following papers.",
                 placeholder="e.g., What are the effects of mindfulness meditation on stress reduction?"
             )
-            with gr.Row(elem_classes="checkbox-group"):
-                include_tables = gr.Checkbox(label="Include Comparison Tables", value=True)
-                include_figures = gr.Checkbox(label="Include Visual Figures", value=True)
             generate_button = gr.Button("Generate Systematic Review", elem_id="generate_button", size="large")
     # Download link container
@@ -541,7 +485,7 @@ with gr.Blocks(css=custom_css) as demo:
     api_key_button.click(set_api_key, inputs=[api_key_input], outputs=[api_key_output])
     # Generate systematic review
-    def process_files_and_generate_review(files, question, include_tables, include_figures):
         if not files:
             return ("""
             <div style="padding: 20px; border: 1px solid #e0e0e0; border-radius: 5px; background-color: #f9f9f9;">
@@ -573,7 +517,7 @@ with gr.Blocks(css=custom_css) as demo:
         yield loading_message, ""
         # Generate review
-        review = generate_systematic_review(saved_paths, question, include_tables, include_figures)
         # Create HTML download link
         html_link = create_html_download_link(review)
@@ -599,7 +543,7 @@ with gr.Blocks(css=custom_css) as demo:
     generate_button.click(
         process_files_and_generate_review,
-        inputs=[pdf_files, review_question, include_tables, include_figures],
         outputs=[review_output, download_html_output]
     )

 import tempfile
 import base64
 from datetime import datetime
 # Variable to store API key
 api_key = ""
         return f"Error extracting text from PDF: {str(e)}"
 # Function to interact with OpenAI API for systematic review
+def generate_systematic_review(pdf_files, review_question, include_tables=True):
     if not api_key:
         return "Please enter your OpenAI API key first."
             pdf_names.append(pdf_name)
         # Prepare the user prompt with the review question and instructions
+        table_instruction = ""
+        if include_tables:
+            table_instruction = " Please include important new generated tables in your review."
+        user_prompt = f"Please generate a systematic review of the following {len(pdf_files)} papers: {', '.join(pdf_names)}.{table_instruction}\n\nReview Question: {review_question}"
         # Create the messages for the API call
         messages = [
         # Get the AI response
         review_content = response["choices"][0]["message"]["content"]
         # Apply professional academic paper styling
         styled_html = f"""
         <!DOCTYPE html>
                     margin: 25px 0;
                     text-align: center;
                 }}
+                .figure img {{
                     max-width: 100%;
                 }}
                 .figure-caption {{
                     font-size: 14px;
                     color: #666;
                     margin-top: 10px;
                 }}
                 .footnote {{
                     font-size: 12px;
                     color: #777;
                 }}
                 @media print {{
                     body {{
                         background-color: white;
         </div>
         """
 # Function to save uploaded files
 def save_uploaded_files(files):
     if not files:
         border-radius: 8px;
     }
     /* Responsive adjustments */
     @media screen and (max-width: 768px) {
         .gradio-container {
         1. Enter your OpenAI API key in the field below and click "Set API Key"
         2. Upload multiple PDF research papers (2 or more recommended)
         3. Enter your review question or topic
+        4. Check the "Include Tables" option if you want the review to include comparison tables
         5. Click "Generate Systematic Review" to start the process
         6. After generation, you can download the review as HTML
         - Be specific in your review question to get more focused results
         - The generated review will follow a systematic structure including research field identification, data extraction, analysis, and conclusions
         - The more papers you upload, the more comprehensive the review will be
         - The review will be formatted as a professional academic paper with proper sections and citations
         """)
                 value="Please generate a systematic review of the following papers.",
                 placeholder="e.g., What are the effects of mindfulness meditation on stress reduction?"
             )
+            include_tables = gr.Checkbox(label="Include Comparison Tables", value=True)
             generate_button = gr.Button("Generate Systematic Review", elem_id="generate_button", size="large")
     # Download link container
     api_key_button.click(set_api_key, inputs=[api_key_input], outputs=[api_key_output])
     # Generate systematic review
+    def process_files_and_generate_review(files, question, include_tables):
         if not files:
             return ("""
             <div style="padding: 20px; border: 1px solid #e0e0e0; border-radius: 5px; background-color: #f9f9f9;">
         yield loading_message, ""
         # Generate review
+        review = generate_systematic_review(saved_paths, question, include_tables)
         # Create HTML download link
         html_link = create_html_download_link(review)
     generate_button.click(
         process_files_and_generate_review,
+        inputs=[pdf_files, review_question, include_tables],
         outputs=[review_output, download_html_output]
     )