commit

.gitattributes

@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+movies_nonnull.csv filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,12 +1,12 @@
 ---
-title: Movie Recommender
-emoji: 🏢
-colorFrom: red
+title: Movie Recommendation
+emoji: 💻
+colorFrom: blue
 colorTo: indigo
 sdk: gradio
 sdk_version: 3.29.0
 app_file: app.py
-pinned: true
+pinned: false
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,35 @@
+import gradio as gr
+import pandas as pd
+import pickle
+import joblib
+kmeans = joblib.load('kmeans_model.joblib')
+
+movies_pred = pd.read_csv("movies_nonnull.csv")
+with open("movies_df.pkl", "rb") as f:
+    movies_df = pickle.load(f)
+
+with open("cosine.pkl", "rb") as f:
+    cosine_sim = pickle.load(f)
+
+def recommend_movies(name):
+
+    try:
+        
+        idx = movies_pred[movies_pred['title'] == name].index[0]
+    
+        prediction = kmeans.predict(movies_df.iloc[idx,:-1].to_numpy().reshape(1,-1))
+        ans = list(movies_pred[movies_df['KmeansCluster']==prediction[0]].index)
+        scores=[]
+
+        for i in ans:
+            scores.append((i,cosine_sim.at[idx,i]))
+        scores.sort(key = lambda x: x[1],reverse=True)
+        final_ans = []
+        for i in scores[:20]:
+            final_ans.append(movies_pred.iloc[i[0]]['title'])
+    
+        return final_ans
+    except Exception as e:
+            return "Sorry Movie does not exist in the database"
+iface = gr.Interface(fn=recommend_movies, inputs="text", outputs="text")
+iface.launch()

gitattributes.txt

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+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
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+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+movies_nonnull.csv filter=lfs diff=lfs merge=lfs -text

gitignore.txt

@@ -0,0 +1,2 @@
+venv/
+cosine.pkl

kmeans_model.joblib

@@ -0,0 +1,3 @@
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+size 3022295

movies_df.pkl

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+size 8142211

movies_nonnull.csv

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