Create app.py

app.py

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+import streamlit as st
+import random
+import pandas as pd
+import matplotlib.pyplot as plt
+
+# ---- UI Layout ----
+st.set_page_config(page_title="StreetStyle Trends Dashboard", layout="wide")
+st.title("👕 StreetStyle Trends - Business Analytics & Insights Hub")
+
+# Sidebar for navigation
+st.sidebar.header("Navigation")
+page = st.sidebar.radio("Go to", ["Business Overview", "Dashboard Features", "Competitor Analysis", "Chatbot"])
+
+# Business Overview Section
+if page == "Business Overview":
+    st.header("🏢 Business Overview")
+    st.markdown("""
+    **Business Name:** StreetStyle Trends  
+    **Industry:** Fashion & Apparel  
+    **Specialty:** Affordable, trendy streetwear for young adults  
+    **Mission:** To provide stylish, budget-friendly streetwear that resonates with the youth culture.
+    """)
+
+    st.subheader("Key Highlights")
+    st.markdown("""
+    - 🚀 Rapidly growing brand with a strong social media presence.  
+    - 💡 Focused on fast-fashion trends and affordability.  
+    - 📈 High customer engagement and repeat purchase rates.  
+    """)
+
+# Dashboard Features Section
+elif page == "Dashboard Features":
+    st.header("📊 Dashboard Features for StreetStyle Trends")
+    st.markdown("""
+    Here are the key features of the StreetStyle Trends analytics dashboard:
+    """)
+
+    col1, col2 = st.columns(2)
+
+    with col1:
+        st.success("✅ **Trending Products Section**")
+        st.write("Shows what’s popular based on recent sales data.")
+        st.success("✅ **Social Media Buzz Tracker**")
+        st.write("Fetches keywords and trends from Instagram and Twitter to keep you updated on what’s hot.")
+
+    with col2:
+        st.success("✅ **Stock & Inventory Updates**")
+        st.write("Notifies you when popular items are low on stock to avoid missed sales opportunities.")
+        st.success("✅ **Customer Engagement Metrics**")
+        st.write("Tracks reviews, feedback, and repeat customer statistics to measure brand loyalty.")
+
+# Competitor Analysis Section
+elif page == "Competitor Analysis":
+    st.header("🔍 Competitor Analysis")
+    st.markdown("""
+    Here’s a breakdown of StreetStyle Trends' key competitors in the fashion and apparel industry:
+    """)
+
+    competitors = {
+        "Competitor": ["H&M", "Zara", "Uniqlo", "Forever 21"],
+        "Specialty": [
+            "Affordable, stylish clothing",
+            "Fast-fashion brand with trend-driven apparel",
+            "Minimalist, high-quality casual wear",
+            "Budget-friendly fashion for youth"
+        ],
+        "Market Position": ["Global", "Global", "Global", "Global"]
+    }
+
+    df_competitors = pd.DataFrame(competitors)
+    st.dataframe(df_competitors, hide_index=True)
+
+    st.subheader("Competitor Insights")
+    st.markdown("""
+    - **H&M:** Known for affordability and wide variety, but lacks exclusivity.  
+    - **Zara:** Excels in fast-fashion but often at a higher price point.  
+    - **Uniqlo:** Focuses on quality and minimalism, but less trendy.  
+    - **Forever 21:** Targets youth with budget-friendly options, but struggles with brand perception.  
+    """)
+
+# Chatbot Section
+elif page == "Chatbot":
+    st.header("🤖 AI-Powered Business Insights Chatbot")
+
+    chat_history = st.session_state.get("chat_history", [])
+
+    user_input = st.text_input("💬 Ask a question about StreetStyle Trends, competitors, or the fashion industry:")
+
+    if st.button("Ask AI"):
+        responses = [
+            "StreetStyle Trends is well-positioned to capture the youth market with its affordable pricing and trendy designs.",
+            "Consider leveraging social media influencers to boost brand visibility among young adults.",
+            "H&M and Zara are strong competitors, but StreetStyle Trends can differentiate itself through exclusive designs.",
+            "Focus on sustainability to appeal to eco-conscious consumers in the fashion industry."
+        ]
+        bot_response = random.choice(responses)
+
+        chat_history.append(f"🧑 You: {user_input}")
+        chat_history.append(f"🤖 AI: {bot_response}")
+        st.session_state["chat_history"] = chat_history
+
+    for chat in chat_history[-5:]:  # Show last 5 messages
+        st.write(chat)
+
+    if st.button("Clear Chat"):
+        st.session_state["chat_history"] = []
+
+# Sample Data Analytics Section (Placeholder)
+if page == "Business Overview" or page == "Dashboard Features":
+    st.sidebar.write("---")
+    st.sidebar.header("Sample Analytics")
+    if st.sidebar.button("Generate Sample Data"):
+        data = {
+            "Category": ["Tops", "Bottoms", "Accessories", "Footwear", "Outerwear"],
+            "Revenue (in thousands)": [random.randint(50, 200) for _ in range(5)],
+            "Growth (%)": [random.randint(5, 25) for _ in range(5)]
+        }
+
+        df = pd.DataFrame(data)
+
+        st.subheader("📈 Revenue by Product Category")
+        fig, ax = plt.subplots()
+        ax.bar(df["Category"], df["Revenue (in thousands)"], color=["blue", "green", "orange", "red", "purple"])
+        st.pyplot(fig)
+
+        st.subheader("🧠 AI Insights")
+        fake_insight = random.choice([
+            "Tops are the best-selling category this quarter!",
+            "Footwear sales are expected to grow by 20% next month.",
+            "Accessories have seen a 15% increase in customer engagement."
+        ])
+        st.success(fake_insight)
+
+st.sidebar.write("🚀 Built with ❤️ using Streamlit")