Update app.py

app.py

@@ -1,40 +1,37 @@
-# app.py  —  BizIntel AI Ultra  (Gemini 1.5 Pro, selectable date column)
-
 import os
 import tempfile
 import pandas as pd
 import streamlit as st
 import google.generativeai as genai
+import plotly.graph_objects as go
 
 from tools.csv_parser import parse_csv_tool
 from tools.plot_generator import plot_sales_tool
-from tools.forecaster import forecast_tool   # must accept date_col
+from tools.forecaster import forecast_tool
+from tools.visuals import (
+    histogram_tool,
+    scatter_matrix_tool,
+    corr_heatmap_tool,
+)
 
-# ──────────────────────────────────────────────────────────────
-# 1.  GEMINI CONFIG  (1.5‑Pro, temperature 0.7)
-# ──────────────────────────────────────────────────────────────
+# ── Gemini 1.5‑Pro configuration ─────────────────────────────
 genai.configure(api_key=os.getenv("GEMINI_APIKEY"))
 gemini = genai.GenerativeModel(
     "gemini-1.5-pro-latest",
     generation_config={
         "temperature": 0.7,
         "top_p": 0.9,
-        # Allowed types: text/plain, application/json, etc.
         "response_mime_type": "text/plain",
     },
 )
 
-# ──────────────────────────────────────────────────────────────
-# 2.  STREAMLIT PAGE SETUP
-# ──────────────────────────────────────────────────────────────
+# ── Streamlit page setup ─────────────────────────────────────
 st.set_page_config(page_title="BizIntel AI Ultra – Gemini 1.5 Pro", layout="wide")
-st.title("📊 BizIntel AI Ultra – Advanced Analytics Pipeline")
+st.title("📊 BizIntel AI Ultra – Advanced Analytics")
 
 TEMP_DIR = tempfile.gettempdir()
 
-# ──────────────────────────────────────────────────────────────
-# 3.  CSV UPLOAD
-# ──────────────────────────────────────────────────────────────
+# ── CSV upload ───────────────────────────────────────────────
 csv_file = st.file_uploader("Upload CSV (≤ 200 MB)", type=["csv"])
 if csv_file is None:
     st.info("⬆️ Upload a CSV to begin.")
@@ -43,34 +40,34 @@ if csv_file is None:
 csv_path = os.path.join(TEMP_DIR, csv_file.name)
 with open(csv_path, "wb") as f:
     f.write(csv_file.read())
-st.success("CSV saved to temporary storage ✅")
+st.success("CSV saved ✅")
 
-# Preview first rows and choose date column
+# Preview + date column selection
 df_preview = pd.read_csv(csv_path, nrows=5)
 st.dataframe(df_preview)
-date_col = st.selectbox("Select the date/time column for forecasting", df_preview.columns)
+date_col = st.selectbox("Select date/time column for forecasting", df_preview.columns)
 
-# ──────────────────────────────────────────────────────────────
-# 4.  LOCAL TOOL EXECUTION
-# ──────────────────────────────────────────────────────────────
-with st.spinner("🔍 Parsing CSV…"):
+# ── Local tools: summary, sales trend, forecast ──────────────
+with st.spinner("Parsing CSV…"):
     summary_text = parse_csv_tool(csv_path)
 
-with st.spinner("📈 Generating sales trend chart…"):
-    _ = plot_sales_tool(csv_path)   # generates sales_plot.png
+with st.spinner("Generating sales trend chart…"):
+    sales_fig = plot_sales_tool(csv_path, date_col=date_col)
+    st.plotly_chart(sales_fig, use_container_width=True)
 
-with st.spinner("🔮 Forecasting future metrics…"):
-    forecast_text = forecast_tool(csv_path, date_col=date_col)  # uses chosen column
+with st.spinner("Forecasting future metrics…"):
+    forecast_text = forecast_tool(csv_path, date_col=date_col)
+    if os.path.exists("forecast_plot.png"):
+        forecast_img = "forecast_plot.png"
+    else:
+        forecast_img = None
 
-# ──────────────────────────────────────────────────────────────
-# 5.  GEMINI 1.5‑PRO STRATEGY (sync call)
-# ─────────────────��────────────────────────────────────────────
+# ── Gemini strategy insights ─────────────────────────────────
 prompt = (
     f"You are **BizIntel Strategist AI**.\n\n"
-    f"## CSV Summary\n```\n{summary_text}\n```\n\n"
-    f"## Forecast Output\n```\n{forecast_text}\n```\n\n"
-    "### Task\n"
-    "Return **Markdown** with:\n"
+    f"### CSV Summary\n```\n{summary_text}\n```\n\n"
+    f"### Forecast Output\n```\n{forecast_text}\n```\n\n"
+    "Return Markdown with:\n"
     "1. **Five key insights** (bullet list)\n"
     "2. **Three actionable strategies** (with expected impact)\n"
     "3. **Risk factors or anomalies**\n"
@@ -78,21 +75,40 @@ prompt = (
 )
 
 st.subheader("🚀 Strategy Recommendations (Gemini 1.5 Pro)")
-with st.spinner("Gemini 1.5 Pro is thinking…"):
-    response = gemini.generate_content(prompt)
+with st.spinner("Gemini 1.5 Pro is generating insights…"):
+    strategy_md = gemini.generate_content(prompt).text
 
-strategy_md = response.text
 st.markdown(strategy_md)
 
-# ──────────────────────────────────────────────────────────────
-# 6.  DISPLAY SUMMARY & CHARTS
-# ──────────────────────────────────────────────────────────────
+# Display forecast image if exists
+if forecast_img:
+    st.image(forecast_img, caption="Sales Forecast", use_column_width=True)
+
+# ── Optional exploratory visuals ─────────────────────────────
 st.markdown("---")
-st.subheader("📑 CSV Summary")
-st.text(summary_text)
+st.subheader("🔍 Optional Exploratory Visuals")
+
+num_cols = df_preview.select_dtypes("number").columns
 
-if os.path.exists("sales_plot.png"):
-    st.image("sales_plot.png", caption="Sales Trend", use_column_width=True)
+# Histogram
+if st.checkbox("Show histogram"):
+    hist_col = st.selectbox("Histogram variable", num_cols, key="hist")
+    fig_hist = histogram_tool(csv_path, hist_col)
+    st.plotly_chart(fig_hist, use_container_width=True)
 
-if os.path.exists("forecast_plot.png"):
-    st.image("forecast_plot.png", caption="Forecast Chart", use_column_width=True)
+# Scatter‑matrix
+if st.checkbox("Show scatter‑matrix"):
+    multi_cols = st.multiselect("Choose up to 5 columns", num_cols, default=num_cols[:3])
+    if multi_cols:
+        fig_scatter = scatter_matrix_tool(csv_path, multi_cols)
+        st.plotly_chart(fig_scatter, use_container_width=True)
+
+# Correlation heat‑map
+if st.checkbox("Show correlation heat‑map"):
+    fig_corr = corr_heatmap_tool(csv_path)
+    st.plotly_chart(fig_corr, use_container_width=True)
+
+# ── CSV summary text at bottom ───────────────────────────────
+st.markdown("---")
+st.subheader("📑 CSV Summary (full Stats)")
+st.text(summary_text)