Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,50 +1,73 @@
-# app.py
-import streamlit as st
-import pandas as pd
-from analyze import analyze_csv
-from plan import generate_cleaning_plan
-from execute import execute_plan
-from insight import generate_insights
-from visual_insight import generate_visual_plan
-import matplotlib.pyplot as plt
-import seaborn as sns
-import os
-
-st.set_page_config(page_title="Smart Data Cleaning Agent", layout="wide")
-st.title("🧠 Smart Data Cleaning Agent")
-
-uploaded_file = st.file_uploader("Upload your CSV file", type=["csv"])
-
-if uploaded_file:
-    with st.spinner("Reading file..."):
-        df = pd.read_csv(uploaded_file)
-        st.write("### 🔍 Original Data Preview", df.head())
-
-    with st.spinner("🔎 Analyzing..."):
-        analysis = analyze_csv(uploaded_file)
-
-    with st.spinner("🛠 Generating Cleaning Plan..."):
-        plan, explanation = generate_cleaning_plan(analysis)
-        st.json(plan)
-        st.markdown(f"**Plan Summary:** {explanation}")
-
-    with st.spinner("✨ Applying Cleaning..."):
-        cleaned_df = execute_plan(df.copy(), plan)
-        st.write("### ✅ Cleaned Data Preview", cleaned_df.head())
-        st.download_button("⬇️ Download Cleaned CSV", cleaned_df.to_csv(index=False), "cleaned.csv")
-
-    with st.spinner("📊 Generating Insights..."):
-        insight_text = generate_insights(analysis["columns"])
-        st.markdown("### 📄 Insights")
-        st.text(insight_text)
-
-    with st.spinner("📈 Generating Visuals..."):
-        visuals = generate_visual_plan(analysis["columns"])
-        for vis in visuals:
-            st.markdown(f"**{vis['title']}** — {vis['description']}")
-            try:
-                exec(vis["code"])
-                st.pyplot(plt.gcf())
-                plt.clf()
-            except Exception as e:
-                st.error(f"⚠️ Failed to render: {e}")
+# app.py
+import streamlit as st
+import pandas as pd
+import matplotlib.pyplot as plt
+import seaborn as sns
+import os
+
+from analyze import analyze_csv
+from plan import generate_cleaning_plan
+from execute import execute_plan
+from insight import generate_insights
+from visual_insight import generate_visual_plan
+from report import ReportBuilder
+
+st.set_page_config(page_title="Smart Data Cleaning Agent", layout="wide")
+st.title("🧠 Smart Data Cleaning Agent")
+
+os.makedirs("charts", exist_ok=True)
+
+uploaded_file = st.file_uploader("📂 Upload a CSV file", type=["csv"])
+
+if uploaded_file:
+    df = pd.read_csv(uploaded_file)
+    st.subheader("🔍 Original Data Preview")
+    st.dataframe(df.head())
+
+    with st.spinner("📊 Analyzing CSV..."):
+        analysis = analyze_csv(uploaded_file)
+
+    with st.spinner("🧼 Generating Cleaning Plan..."):
+        cleaning_plan, cleaning_summary = generate_cleaning_plan(analysis)
+        st.subheader("🧹 Cleaning Plan")
+        st.json(cleaning_plan)
+        st.markdown("### ✅ Cleaning Summary")
+        st.markdown(cleaning_summary)
+
+    with st.spinner("🧪 Applying cleaning..."):
+        cleaned_df = execute_plan(df.copy(), cleaning_plan)
+        st.subheader("🧼 Cleaned Data Preview")
+        st.dataframe(cleaned_df.head())
+        st.download_button("⬇️ Download Cleaned CSV", cleaned_df.to_csv(index=False), file_name="cleaned.csv")
+
+    with st.spinner("🧠 Deriving insights..."):
+        insights = generate_insights(analysis["columns"])
+        st.subheader("📄 EDA Insights")
+        st.text(insights)
+
+    with st.spinner("📈 Generating recommended plots..."):
+        visuals = generate_visual_plan(analysis["columns"])
+        for vis in visuals:
+            st.markdown(f"#### {vis['title']}")
+            st.markdown(vis['description'])
+            try:
+                exec(vis["code"], {"df": cleaned_df, "plt": plt, "sns": sns, "os": os})
+                st.pyplot(plt.gcf())
+                plt.clf()
+            except Exception as e:
+                st.error(f"❌ Failed to render: {e}")
+
+    if st.button("📝 Generate PDF Report"):
+        report = ReportBuilder("report.pdf")
+        report.add_title("📊 Smart Data Cleaning Report")
+        report.add_text("Cleaning Summary", cleaning_summary)
+        report.add_text("EDA Insights", insights)
+
+        for vis in visuals:
+            if "savefig('" in vis['code']:
+                path = vis['code'].split("savefig('")[-1].split("')")[0]
+                report.add_image(path, vis['description'])
+
+        report.save()
+        with open("report.pdf", "rb") as f:
+            st.download_button("⬇️ Download PDF Report", f, file_name="smart_data_report.pdf")