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Update app.py
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app.py
CHANGED
@@ -2,11 +2,8 @@ import streamlit as st
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import pandas as pd
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import sqlite3
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import os
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import io
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import json
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from pathlib import Path
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import tempfile
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from fpdf import FPDF
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import plotly.express as px
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from datetime import datetime, timezone
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from crewai import Agent, Crew, Process, Task
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@@ -86,94 +83,6 @@ if st.session_state.df is not None and st.session_state.show_preview:
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st.subheader("π Dataset Preview")
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st.dataframe(st.session_state.df.head())
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# Helper Function to Create a PDF Report with Visualizations and Descriptions
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def create_pdf_report_with_viz(report, conclusion, visualizations):
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pdf = FPDF()
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pdf.set_auto_page_break(auto=True, margin=15)
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pdf.add_page()
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pdf.set_font("Arial", size=12)
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# Title
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pdf.set_font("Arial", style="B", size=18)
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pdf.cell(0, 10, "π Analysis Report", ln=True, align="C")
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pdf.ln(10)
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# Report Content
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pdf.set_font("Arial", style="B", size=14)
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pdf.cell(0, 10, "Analysis", ln=True)
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pdf.set_font("Arial", size=12)
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pdf.multi_cell(0, 10, report)
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pdf.ln(10)
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pdf.set_font("Arial", style="B", size=14)
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pdf.cell(0, 10, "Conclusion", ln=True)
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pdf.set_font("Arial", size=12)
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pdf.multi_cell(0, 10, conclusion)
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# Add Visualizations
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pdf.add_page()
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pdf.set_font("Arial", style="B", size=16)
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pdf.cell(0, 10, "π Visualizations", ln=True)
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pdf.ln(5)
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with tempfile.TemporaryDirectory() as temp_dir:
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for i, fig in enumerate(visualizations, start=1):
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fig_title = fig.layout.title.text if fig.layout.title.text else f"Visualization {i}"
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x_axis = fig.layout.xaxis.title.text if fig.layout.xaxis.title.text else "X-axis"
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y_axis = fig.layout.yaxis.title.text if fig.layout.yaxis.title.text else "Y-axis"
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# Save each visualization as a PNG image
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img_path = os.path.join(temp_dir, f"viz_{i}.png")
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fig.write_image(img_path)
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# Insert Title and Description
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pdf.set_font("Arial", style="B", size=14)
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pdf.multi_cell(0, 10, f"{i}. {fig_title}")
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pdf.set_font("Arial", size=12)
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pdf.multi_cell(0, 10, f"X-axis: {x_axis} | Y-axis: {y_axis}")
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pdf.ln(3)
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# Embed Visualization
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pdf.image(img_path, w=170)
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pdf.ln(10)
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# Save PDF
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temp_pdf = tempfile.NamedTemporaryFile(delete=False, suffix=".pdf")
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pdf.output(temp_pdf.name)
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return temp_pdf
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# Helper function to create a plain text report with visualization summaries
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def create_text_report_with_viz(report, conclusion, visualizations):
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content = f"### Analysis Report\n\n{report}\n\n### Conclusion\n\n{conclusion}\n\n### Visualizations\n"
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# Dynamically add descriptions for each visualization
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for i, fig in enumerate(visualizations, start=1):
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# Extract the title of the Plotly figure if available
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fig_title = fig.layout.title.text if fig.layout.title.text else f"Visualization {i}"
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# Add title and figure details
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content += f"\n{i}. {fig_title}\n"
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# Extract x and y axis titles if available
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x_axis = fig.layout.xaxis.title.text if fig.layout.xaxis.title.text else "X-axis"
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y_axis = fig.layout.yaxis.title.text if fig.layout.yaxis.title.text else "Y-axis"
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content += f" - X-axis: {x_axis}\n"
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content += f" - Y-axis: {y_axis}\n"
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# If figure has data, summarize it
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if fig.data:
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trace_types = set(trace.type for trace in fig.data)
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content += f" - Chart Type(s): {', '.join(trace_types)}\n"
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else:
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content += " - No data available in this visualization.\n"
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# Return the content as a downloadable text stream
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return io.BytesIO(content.encode("utf-8"))
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# SQL-RAG Analysis
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if st.session_state.df is not None:
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temp_dir = tempfile.TemporaryDirectory()
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@@ -220,7 +129,7 @@ if st.session_state.df is not None:
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report_writer = Agent(
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role="Technical Report Writer",
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goal="Write a structured report with Introduction
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backstory="Specializes in detailed analytical reports without conclusions.",
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llm=llm,
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)
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@@ -247,16 +156,16 @@ if st.session_state.df is not None:
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)
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write_report = Task(
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description="Write the analysis report with Introduction
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expected_output="Markdown-formatted report excluding Conclusion.",
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agent=report_writer,
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context=[analyze_data],
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)
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write_conclusion = Task(
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description="
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expected_output="Markdown-formatted Conclusion section with key insights and statistics.",
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agent=conclusion_writer,
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context=[analyze_data],
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)
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visualizations.append(fig_employment)
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# Step 5: Insert Visual Insights
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st.markdown("
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for fig in visualizations:
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st.plotly_chart(fig, use_container_width=True)
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@@ -323,28 +232,6 @@ if st.session_state.df is not None:
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#st.markdown("#### 6. Conclusion")
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st.markdown(conclusion_result if conclusion_result else "β οΈ No Conclusion Generated.")
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# Step 7: PDF and TXT Download Buttons for Query Insights + Viz
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if report_result and conclusion_result and visualizations:
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# PDF Download
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pdf_file = create_pdf_report_with_viz(report_result, conclusion_result, visualizations)
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with open(pdf_file.name, "rb") as f:
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st.download_button(
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label="π₯ Download Full Report (PDF)",
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data=f,
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file_name="query_insights_report.pdf",
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mime="application/pdf"
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)
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# TXT Download
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text_file = create_text_report_with_viz(report_result, conclusion_result, visualizations)
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st.download_button(
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label="π₯ Download Full Report (TXT)",
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data=text_file,
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file_name="query_insights_report.txt",
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mime="text/plain"
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)
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# Full Data Visualization Tab
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with tab2:
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st.subheader("π Comprehensive Data Visualizations")
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import pandas as pd
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import sqlite3
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import os
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import json
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from pathlib import Path
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import plotly.express as px
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from datetime import datetime, timezone
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from crewai import Agent, Crew, Process, Task
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st.subheader("π Dataset Preview")
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st.dataframe(st.session_state.df.head())
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# SQL-RAG Analysis
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if st.session_state.df is not None:
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temp_dir = tempfile.TemporaryDirectory()
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report_writer = Agent(
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role="Technical Report Writer",
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goal="Write a structured report with Introduction, Key Insights, and Analysis. DO NOT include any Conclusion or Summary.",
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backstory="Specializes in detailed analytical reports without conclusions.",
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llm=llm,
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)
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)
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write_report = Task(
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description="Write the analysis report with Introduction, Key Insights, and Analysis. DO NOT include any Conclusion or Summary.",
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expected_output="Markdown-formatted report excluding Conclusion.",
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agent=report_writer,
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context=[analyze_data],
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)
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write_conclusion = Task(
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description="Write a brief and impactful 3-5 line Conclusion summarizing only the most important insights/findings. Include the max, min, and average salary"
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"and highlight the most impactful insights.",
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expected_output="Markdown-formatted Conclusion/Summary section with key insights and statistics.",
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agent=conclusion_writer,
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context=[analyze_data],
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)
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visualizations.append(fig_employment)
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# Step 5: Insert Visual Insights
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st.markdown("#### 5. Visual Insights")
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for fig in visualizations:
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st.plotly_chart(fig, use_container_width=True)
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#st.markdown("#### 6. Conclusion")
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st.markdown(conclusion_result if conclusion_result else "β οΈ No Conclusion Generated.")
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# Full Data Visualization Tab
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with tab2:
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st.subheader("π Comprehensive Data Visualizations")
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