Update app.py

app.py

@@ -7,7 +7,9 @@ import speech_recognition as sr
 # Load the Netflix dataset from CSV
 @st.cache_data
 def load_data():
-    return pd.read_csv("https://huggingface.co/spaces/mfraz/Netflix-data/resolve/main/netflix_titles.csv")
+    df = pd.read_csv("https://huggingface.co/spaces/mfraz/Netflix-data/resolve/main/netflix_titles.csv")
+    df.fillna("N/A", inplace=True)  # Replace NaN values with "N/A"
+    return df
 
 # Load DialoGPT model and tokenizer
 @st.cache_resource
@@ -19,12 +21,14 @@ def load_model():
 # Function to search the dataset for movie details
 def search_movie_details(query, data):
     query = query.lower()
-    filtered_data = data.dropna(subset=["title", "cast", "director", "country"])  # Remove NaN values
-    results = filtered_data[
-        filtered_data["title"].str.lower().str.contains(query, na=False) |
-        filtered_data["cast"].str.lower().str.contains(query, na=False) |
-        filtered_data["director"].str.lower().str.contains(query, na=False)
+    
+    # Filtering: Ensure column names exist and search query is in title, cast, or director
+    results = data[
+        data["title"].str.lower().str.contains(query, na=False) |
+        data["cast"].str.lower().str.contains(query, na=False) |
+        data["director"].str.lower().str.contains(query, na=False)
     ]
+    
     return results
 
 # Function to convert voice to text
@@ -70,7 +74,7 @@ if user_input:
             st.write(f"**Director:** {row['director']}")
             st.write(f"**Cast:** {row['cast']}")
             st.write(f"**Release Year:** {row['release_year']}")
-            st.write(f"**Country:** {row['country']}")  # ✅ Now country is displayed correctly
+            st.write(f"**Country:** {row['country']}")  # ✅ Now displays Country correctly
             st.write(f"**Rating:** {row['rating']}")
             st.write(f"**Description:** {row['description']}")
             st.write("---")
@@ -80,3 +84,4 @@ if user_input:
         outputs = model.generate(inputs, max_length=100, num_return_sequences=1)
         response = tokenizer.decode(outputs[0], skip_special_tokens=True)
         st.write(f"Chatbot: {response}")
+