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Update app.py
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app.py
CHANGED
@@ -1,3 +1,5 @@
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import os
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import tempfile
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import pandas as pd
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@@ -6,32 +8,38 @@ import google.generativeai as genai
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import plotly.graph_objects as go
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from tools.csv_parser import parse_csv_tool
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from tools.plot_generator import plot_sales_tool
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from tools.forecaster import forecast_tool
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from tools.visuals import (
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histogram_tool,
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scatter_matrix_tool,
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corr_heatmap_tool,
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)
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#
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genai.configure(api_key=os.getenv("GEMINI_APIKEY"))
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gemini = genai.GenerativeModel(
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"gemini-1.5-pro-latest",
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generation_config={
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"temperature": 0.7,
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"top_p": 0.9,
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"response_mime_type": "text/plain",
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},
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)
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#
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st.set_page_config(page_title="BizIntel AI Ultra โ Geminiย 1.5ย Pro", layout="wide")
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st.title("๐ BizIntelย AIย Ultraย โ Advanced Analytics")
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TEMP_DIR = tempfile.gettempdir()
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#
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csv_file = st.file_uploader("Upload CSV (โคโฏ200โฏMB)", type=["csv"])
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if csv_file is None:
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st.info("โฌ๏ธย Upload a CSV to begin.")
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@@ -42,49 +50,55 @@ with open(csv_path, "wb") as f:
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f.write(csv_file.read())
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st.success("CSV saved โ
")
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# Preview
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df_preview = pd.read_csv(csv_path, nrows=5)
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st.dataframe(df_preview)
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date_col = st.selectbox("Select date/time column for forecasting", df_preview.columns)
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#
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summary_text = parse_csv_tool(csv_path)
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with st.spinner("Generating sales trend chartโฆ"):
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sales_fig = plot_sales_tool(csv_path, date_col=date_col)
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st.plotly_chart(sales_fig, use_container_width=True)
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with st.spinner("Forecasting future metricsโฆ"):
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forecast_text = forecast_tool(csv_path, date_col=date_col)
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if os.path.exists("forecast_plot.png"):
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forecast_img = "forecast_plot.png"
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else:
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forecast_img = None
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#
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prompt = (
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f"You are **BizIntel Strategist AI**.\n\n"
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f"### CSV Summary\n```\n{summary_text}\n```\n\n"
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f"### Forecast Output\n```\n{forecast_text}\n```\n\n"
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"Return Markdown with:\n"
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"1.
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"2.
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"3.
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"4.
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)
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st.subheader("๐ Strategy Recommendations (Geminiย 1.5ย Pro)")
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with st.spinner("Geminiย 1.5ย Pro is generating insightsโฆ"):
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strategy_md = gemini.generate_content(prompt).text
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st.markdown(strategy_md)
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#
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# โโ Optional exploratory visuals โโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
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st.markdown("---")
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st.subheader("๐ Optional Exploratory Visuals")
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@@ -98,9 +112,11 @@ if st.checkbox("Show histogram"):
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# Scatterโmatrix
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if st.checkbox("Show scatterโmatrix"):
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st.plotly_chart(fig_scatter, use_container_width=True)
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# Correlation heatโmap
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fig_corr = corr_heatmap_tool(csv_path)
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st.plotly_chart(fig_corr, use_container_width=True)
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#
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st.markdown("---")
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st.subheader("๐ CSV Summary (full
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st.text(summary_text)
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# app.py โ BizIntelย AIย Ultra (Geminiโฏ1.5ย Pro, interactive Plotly visuals)
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import os
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import tempfile
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import pandas as pd
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import plotly.graph_objects as go
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from tools.csv_parser import parse_csv_tool
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from tools.plot_generator import plot_sales_tool # accepts date_col, returns Figure or str
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from tools.forecaster import forecast_tool # accepts date_col
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from tools.visuals import (
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histogram_tool,
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scatter_matrix_tool,
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corr_heatmap_tool,
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)
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# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
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# 1. GEMINI CONFIG (1.5โPro, temperature 0.7)
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# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
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genai.configure(api_key=os.getenv("GEMINI_APIKEY"))
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gemini = genai.GenerativeModel(
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"gemini-1.5-pro-latest",
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generation_config={
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"temperature": 0.7,
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"top_p": 0.9,
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"response_mime_type": "text/plain", # must be allowed type
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},
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)
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# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
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# 2. STREAMLIT PAGE SETUP
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# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
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st.set_page_config(page_title="BizIntel AI Ultra โ Geminiย 1.5ย Pro", layout="wide")
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st.title("๐ BizIntelย AIย Ultraย โ Advanced Analytics")
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TEMP_DIR = tempfile.gettempdir()
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# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
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# 3. CSV UPLOAD
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# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
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csv_file = st.file_uploader("Upload CSV (โคโฏ200โฏMB)", type=["csv"])
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if csv_file is None:
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st.info("โฌ๏ธย Upload a CSV to begin.")
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f.write(csv_file.read())
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st.success("CSV saved โ
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# Preview & date column selection
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df_preview = pd.read_csv(csv_path, nrows=5)
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st.dataframe(df_preview)
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date_col = st.selectbox("Select date/time column for forecasting", df_preview.columns)
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# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
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# 4. LOCAL TOOL EXECUTION
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# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
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with st.spinner("๐ Parsing CSVโฆ"):
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summary_text = parse_csv_tool(csv_path)
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with st.spinner("๐ Generating sales trend chartโฆ"):
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sales_fig = plot_sales_tool(csv_path, date_col=date_col)
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# Show chart or warn
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if isinstance(sales_fig, go.Figure):
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st.plotly_chart(sales_fig, use_container_width=True)
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else: # returned error message
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st.warning(sales_fig)
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with st.spinner("๐ฎ Forecasting future metricsโฆ"):
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forecast_text = forecast_tool(csv_path, date_col=date_col)
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# Display forecast PNG if created
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if os.path.exists("forecast_plot.png"):
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st.image("forecast_plot.png", caption="Sales Forecast", use_column_width=True)
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# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
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# 5. GEMINI 1.5โPRO STRATEGY
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# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
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prompt = (
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f"You are **BizIntel Strategist AI**.\n\n"
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f"### CSV Summary\n```\n{summary_text}\n```\n\n"
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f"### Forecast Output\n```\n{forecast_text}\n```\n\n"
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"Return **Markdown** with:\n"
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"1. Five key insights (bullets)\n"
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"2. Three actionable strategies (with expected impact)\n"
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"3. Risk factors or anomalies\n"
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"4. Suggested additional visuals\n"
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)
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st.subheader("๐ Strategy Recommendations (Geminiย 1.5ย Pro)")
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with st.spinner("Geminiย 1.5ย Pro is generating insightsโฆ"):
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strategy_md = gemini.generate_content(prompt).text
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st.markdown(strategy_md)
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# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
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# 6. OPTIONAL EXPLORATORY VISUALS
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# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
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st.markdown("---")
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st.subheader("๐ Optional Exploratory Visuals")
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# Scatterโmatrix
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if st.checkbox("Show scatterโmatrix"):
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mult_cols = st.multiselect(
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"Choose up to 5 columns", num_cols, default=num_cols[:3], key="scatter"
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)
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if mult_cols:
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fig_scatter = scatter_matrix_tool(csv_path, mult_cols)
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st.plotly_chart(fig_scatter, use_container_width=True)
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# Correlation heatโmap
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fig_corr = corr_heatmap_tool(csv_path)
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st.plotly_chart(fig_corr, use_container_width=True)
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# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
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# 7. CSV SUMMARY TEXT
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# โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
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st.markdown("---")
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st.subheader("๐ CSV Summary (full stats)")
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st.text(summary_text)
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