Upload 3 files

app (1).py

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+import gradio as gr
+import pandas as pd
+import numpy as np
+import ast
+from sentence_transformers import SentenceTransformer
+from sklearn.metrics.pairwise import cosine_similarity
+
+# --- 1. Load Data ---
+print("⏳ Loading Data...")
+try:
+    df = pd.read_pickle("apps_clustered.pkl")
+    print("✅ Data Loaded")
+except Exception as e:
+    print(f"❌ Error loading data: {e}")
+    df = pd.DataFrame() 
+
+# --- Column Setup ---
+def get_col_name(candidates, df_cols):
+    return next((col for col in candidates if col in df_cols), None)
+
+image_col = get_col_name(['artworkUrl512', 'artworkUrl100', 'artworkUrl60', 'image_url', 'icon'], df.columns)
+desc_col  = get_col_name(['description', 'longDescription', 'shortDescription', 'summary'], df.columns)
+lang_col  = get_col_name(['languageCodesISO2A', 'primaryLanguage', 'languages', 'language'], df.columns)
+rating_col = 'averageUserRating'
+
+print(f"🔍 Mapped Columns: Image='{image_col}', Desc='{desc_col}', Rating='{rating_col}', Lang='{lang_col}'")
+
+print("⏳ Loading AI Model...")
+model = SentenceTransformer('all-MiniLM-L6-v2')
+print("✅ Ready!")
+
+# --- 2. The Logic ---
+def search_apps(user_query):
+    if not user_query:
+        return ""
+        
+    try:
+        # Search
+        user_vector = model.encode(user_query).reshape(1, -1)
+        app_embeddings = np.vstack(df["text_embedding"].values)
+        scores = cosine_similarity(user_vector, app_embeddings).flatten()
+        
+        df_results = df.copy()
+        df_results["similarity_score"] = scores
+        top_results = df_results.sort_values(by="similarity_score", ascending=False).head(3)
+        
+        # --- HTML GENERATION ---
+        
+        # 1. The Header Message
+        html_content = """
+        <div style="margin-bottom: 20px; text-align: center;">
+            <h3 style="color: #374151; margin: 0;">Here is what our recommendation system found for you:</h3>
+        </div>
+        """
+        
+        # 2. The Cards Container
+        html_content += '<div style="display: flex; gap: 20px; justify-content: center; flex-wrap: wrap;">'
+        
+        for _, row in top_results.iterrows():
+            # Image Logic
+            img_url = row.get(image_col, "")
+            if pd.isna(img_url) or not isinstance(img_url, str):
+                img_tag = '<div style="width: 100%; height: 180px; background: #eee; border-radius: 15px; display: flex; align-items: center; justify-content: center;">No Image</div>'
+            else:
+                img_tag = f'<img src="{img_url}" style="width: 100%; height: auto; border-radius: 15px; margin-bottom: 12px; box-shadow: 0 4px 10px rgba(0,0,0,0.1);">'
+
+            # Rating Logic
+            score = row.get(rating_col, 0)
+            if pd.isna(score) or score == 0:
+                rating_text = "No ratings yet"
+            else:
+                rating_text = f"{float(score):.1f} ⭐"
+
+            # Language Logic
+            lang_val = row.get(lang_col, "N/A")
+            if pd.isna(lang_val): lang_val = "N/A"
+            if isinstance(lang_val, str) and lang_val.startswith('[') and lang_val.endswith(']'):
+                try: lang_val = ast.literal_eval(lang_val)
+                except: pass
+            
+            if isinstance(lang_val, list):
+                if len(lang_val) > 1:
+                    lang_text = f"{lang_val[0]} and more"
+                elif len(lang_val) == 1:
+                    lang_text = str(lang_val[0])
+                else:
+                    lang_text = "N/A"
+            else:
+                lang_text = str(lang_val)
+
+            # Description Logic
+            desc = str(row.get(desc_col, "No description"))
+            if len(desc) > 120: desc = desc[:120] + "..."
+
+            # Link Logic
+            url = row.get('trackViewUrl', '#')
+            if pd.isna(url) and 'trackId' in row: url = f"https://apps.apple.com/app/id{row['trackId']}"
+            
+            # Card HTML
+            card_html = f"""
+            <div style="
+                width: 280px;
+                padding: 20px;
+                background-color: white;
+                border: 1px solid #e5e7eb;
+                border-radius: 20px;
+                box-shadow: 0 10px 25px rgba(0,0,0,0.05);
+                display: flex;
+                flex-direction: column;
+                align-items: flex-start;
+                font-family: sans-serif;
+            ">
+                {img_tag}
+                <h3 style="margin: 0 0 5px 0; color: #1f2937; font-size: 18px;">{row['trackName']}</h3>
+                <p style="margin: 0 0 10px 0; color: #6b7280; font-size: 14px; font-weight: 500;">{row['primaryGenreName']}</p>
+                
+                <div style="display: flex; gap: 10px; margin-bottom: 10px; font-size: 13px; color: #4b5563;">
+                    <span style="background: #f3f4f6; padding: 4px 8px; border-radius: 6px;">{rating_text}</span>
+                    <span style="background: #f3f4f6; padding: 4px 8px; border-radius: 6px;">🗣️ {lang_text}</span>
+                </div>
+                
+                <p style="font-size: 13px; color: #6b7280; margin-bottom: 15px; line-height: 1.4;">{desc}</p>
+                
+                <a href="{url}" target="_blank" style="
+                    margin-top: auto;
+                    width: 100%;
+                    text-align: center;
+                    background-color: #2563eb;
+                    color: white;
+                    padding: 10px 0;
+                    border-radius: 10px;
+                    text-decoration: none;
+                    font-weight: bold;
+                    transition: background 0.2s;
+                ">Get App ↗️</a>
+            </div>
+            """
+            html_content += card_html
+
+        html_content += '</div>'
+        return html_content
+        
+    except Exception as e:
+        return f"<div style='color:red;'>Error: {str(e)}</div>"
+
+# --- 3. The UI ---
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    
+    gr.Markdown("# 📱 AI App Recommender")
+    gr.Markdown("Describe what you need, and the AI will find the best apps for you.")
+    
+    with gr.Column():
+        with gr.Row():
+            txt_input = gr.Textbox(
+                show_label=False, 
+                placeholder="Type here... (e.g., 'I need a puzzle game for kids')",
+                scale=4
+            )
+            btn_submit = gr.Button("🚀 Find Apps", variant="primary", scale=1)
+        
+        gr.Examples(
+            examples=[["I want a timer for my kitchen"], ["A game to learn math"]],
+            inputs=txt_input
+        )
+        
+        output_html = gr.HTML(label="Recommended Apps")
+    
+    # --- FOOTER ---
+    gr.Markdown(
+        """
+        <div style="text-align: center; margin-top: 40px; color: #9ca3af; font-size: 14px;">
+            app developed by Karin M & Lior F
+        </div>
+        """
+    )
+
+    btn_submit.click(fn=search_apps, inputs=txt_input, outputs=output_html)
+    txt_input.submit(fn=search_apps, inputs=txt_input, outputs=output_html)
+
+demo.launch()

apps_clustered (3).pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:dd952682cf9afbb479ab37046f51bf20ab8be317d13193124512e3c014449344
+size 33947133

requirements (3).txt

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+pandas
+numpy
+scikit-learn
+sentence-transformers
+gradio