Update app.py

app.py

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+import streamlit as st
+import requests
+import json
+from sentence_transformers import SentenceTransformer
+import chromadb
+from bs4 import BeautifulSoup
+
+# Initialize embedding model (Open-Source)
+model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
+
+# Connect to ChromaDB (Local Open-Source Vector DB)
+client = chromadb.PersistentClient(path="./recipe_db")
+collection = client.get_or_create_collection("recipes")
+
+# Function to scrape restaurant data (Alternative to API)
+def scrape_restaurant_info(city, recipe):
+    search_url = f"https://www.foodpanda.pk/restaurants?search={recipe}+{city}"
+    headers = {"User-Agent": "Mozilla/5.0"}
+    response = requests.get(search_url, headers=headers)
+
+    restaurant_list = []
+    if response.status_code == 200:
+        soup = BeautifulSoup(response.text, "html.parser")
+        items = soup.find_all("div", class_="vendor-info")
+        for item in items[:5]:  # Get top 5 restaurants
+            name = item.find("span", class_="name").text if item.find("span", class_="name") else "Unknown"
+            restaurant_list.append(name)
+    return restaurant_list
+
+# Streamlit UI
+st.title("Pakistani City Recipe Finder 🍛")
+
+city = st.selectbox("Select a City", ["Lahore", "Karachi", "Islamabad", "Peshawar", "Quetta"])
+query = st.text_input("Enter a Recipe Name")
+
+if st.button("Find Recipe"):
+    if query:
+        # Retrieve recipe info from vector DB
+        query_embedding = model.encode(query).tolist()
+        results = collection.query(query_embedding, n_results=3)
+
+        if results["documents"]:
+            st.subheader(f"Famous {query} Recipes in {city}")
+            for recipe in results["documents"][0]:
+                st.write(f"**Recipe:** {recipe['name']}")
+                st.image(recipe["image"], caption=recipe["name"], use_column_width=True)
+                st.write(f"Price: {recipe['price']} PKR")
+
+            # Fetch restaurant data via scraping
+            restaurants = scrape_restaurant_info(city, query)
+            if restaurants:
+                st.subheader("Available at These Restaurants:")
+                for r in restaurants:
+                    st.write(f"- {r}")
+            else:
+                st.write("No restaurant data found.")
+        else:
+            st.write("No matching recipes found.")
+    else:
+        st.warning("Please enter a recipe name.")