Upload 4 files

app.py

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+# app.py
+import gradio as gr
+import joblib
+import pandas as pd
+from sklearn.metrics.pairwise import cosine_similarity
+
+# ==============================
+# Load Saved Files
+# ==============================
+df = joblib.load("restaurants.pkl")
+vectorizer = joblib.load("vectorizer.pkl")
+similarity_matrix = joblib.load("similarity.pkl")
+
+# ==============================
+# Prepare Dropdown Lists
+# ==============================
+
+# Cities
+cities = sorted(df["Location"].unique())
+
+# Extract cuisines
+cuisines = sorted(
+    set(
+        cuisine.strip()
+        for sublist in df["Cuisine"].astype(str).str.split(",")
+        for cuisine in sublist
+    )
+)
+
+# ==============================
+# Recommendation Function
+# ==============================
+
+def recommend_restaurants(cuisine, city, veg_pref):
+
+    filtered = df[df["Location"] == city]
+
+    if veg_pref != "Any":
+        filtered = filtered[filtered["Pure Veg"] == veg_pref]
+
+    if len(filtered) == 0:
+        return "No restaurants found for this selection."
+
+    # Vectorize selected cuisine
+    cuisine_vec = vectorizer.transform([cuisine.lower()])
+    tfidf_filtered = vectorizer.transform(filtered["Cuisine"])
+
+    sim_scores = cosine_similarity(cuisine_vec, tfidf_filtered).flatten()
+
+    top_idx = sim_scores.argsort()[-5:][::-1]
+
+    recs = filtered.iloc[top_idx]
+
+    result = ""
+
+    for _, row in recs.iterrows():
+        result += f"""
+🍽 Restaurant: {row['Restaurant Name']}
+🍜 Cuisine: {row['Cuisine']}
+⭐ Rating: {row['Rating']}
+💰 Price: ₹{row['Average Price']}
+📍 Area: {row['Area']}
+
+-------------------------
+"""
+
+    return result
+
+
+# ==============================
+# Gradio UI
+# ==============================
+
+interface = gr.Interface(
+    fn=recommend_restaurants,
+    inputs=[
+        gr.Dropdown(cuisines, label="Select Cuisine"),
+        gr.Dropdown(cities, label="Select City"),
+        gr.Dropdown(["Any", "Yes", "No"], label="Pure Veg Preference"),
+    ],
+    outputs=gr.Textbox(label="Recommended Restaurants"),
+    title="🍔 AI Food Recommendation System",
+    description="Select cuisine and city to get restaurant recommendations."
+)
+
+interface.launch()

restaurants.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:002dbca40009fb6528432ca5db2e8e3ad0866f38e7c79616526742b6d3281b5f
+size 1312083

similarity.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2045533bf9316677d719501e66229e00f8f5a600f01005572c979b9257134ecf
+size 421544889

vectorizer.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b9532e1b4fa8593f8e82124a6d5c58487f78281d4b31b0ed58a510077d1e699c
+size 2720