Create app.py

app.py

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+%%writefile app.py
+import streamlit as st
+import pandas as pd
+import plotly.express as px
+import os
+from groq import Groq
+
+os.environ["GROQ_API_KEY"] = "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"
+
+st.set_page_config(page_title="Personal Expense Analyzer", layout="wide")
+st.title("💰 Personal Expense Analyzer")
+
+if "expenses" not in st.session_state:
+    st.session_state["expenses"] = pd.DataFrame(columns=["Name", "Description", "Date", "Amount"])
+
+st.sidebar.header("➕ Add New Expense")
+with st.sidebar.form("expense_form", clear_on_submit=True):
+    name = st.text_input("Expense Name")
+    desc = st.text_area("Description")
+    date = st.date_input("Date of Expense")
+    amount = st.number_input("Amount (SAR)", min_value=0.0, step=1.0)
+    submitted = st.form_submit_button("Add Expense")
+
+    if submitted:
+        if name and amount > 0:
+            new_exp = pd.DataFrame(
+                {"Name": [name], "Description": [desc], "Date": [pd.to_datetime(date)], "Amount": [amount]}
+            )
+            st.session_state["expenses"] = pd.concat([st.session_state["expenses"], new_exp], ignore_index=True)
+            st.success("Expense added successfully!")
+        else:
+            st.error("Please enter both name and amount.")
+
+df = st.session_state["expenses"]
+
+if not df.empty:
+    st.subheader("📊 Expense Summary")
+    st.dataframe(df.sort_values("Date", ascending=False), use_container_width=True)
+
+    col1, col2 = st.columns(2)
+    with col1:
+        st.markdown("### 💸 Expense Distribution (Pie Chart)")
+        fig1 = px.pie(df, names="Name", values="Amount", title="Expenses by Category", hole=0.4)
+        st.plotly_chart(fig1, use_container_width=True)
+
+    with col2:
+        st.markdown("### 📈 Expense Trend (Bar Chart)")
+        df_sorted = df.groupby("Date")["Amount"].sum().reset_index()
+        fig2 = px.bar(df_sorted, x="Date", y="Amount", title="Daily Spending Trend")
+        st.plotly_chart(fig2, use_container_width=True)
+
+    st.markdown("## 🧠 Expense Insights (Powered by Groq Llama Model)")
+    if st.button("🔍 Analyze My Spending"):
+        with st.spinner("Analyzing your expenses using Groq..."):
+            try:
+                client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
+                summary_text = df.to_string(index=False)
+                prompt = f"""
+                Analyze the following expense records and provide:
+                1. Spending patterns (e.g., high spend periods or frequent categories)
+                2. Financial control recommendations
+                3. Suggestions for saving or budgeting
+
+                Expense data:
+                {summary_text}
+                """
+                response = client.chat.completions.create(
+                    messages=[
+                        {"role": "system", "content": "You are a financial advisor analyzing personal expenses."},
+                        {"role": "user", "content": prompt}
+                    ],
+                    model="llama-3.3-70b-versatile"
+                )
+                result = response.choices[0].message.content
+                st.success("✅ Analysis Complete!")
+                st.markdown(f"### 🪄 AI Recommendations:\n{result}")
+            except Exception as e:
+                st.error(f"Error while analyzing: {e}")
+else:
+    st.info("No expenses added yet. Use the sidebar to start adding your expenses!")
+
+st.markdown("---")
+st.caption("Built with ❤️ using Streamlit + Groq LLM")