Update app.py

app.py

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+import streamlit as st
+import pandas as pd
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import speech_recognition as sr
+from pydub import AudioSegment
+
+# Load the Netflix dataset from CSV
+@st.cache_data
+def load_data():
+    return pd.read_csv("netflix_titles.csv")
+
+# Load DialoGPT model and tokenizer
+@st.cache_resource
+def load_model():
+    tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
+    model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")
+    return tokenizer, model
+
+# Function to search the dataset for movie details
+def search_movie_details(query, data):
+    query = query.lower()
+    results = data[
+        data["title"].str.lower().str.contains(query) |
+        data["cast"].str.lower().str.contains(query) |
+        data["director"].str.lower().str.contains(query)
+    ]
+    return results
+
+# Function to convert voice to text
+def voice_to_text():
+    recognizer = sr.Recognizer()
+    with sr.Microphone() as source:
+        st.write("Speak now...")
+        audio = recognizer.listen(source)
+        try:
+            text = recognizer.recognize_google(audio)
+            return text
+        except sr.UnknownValueError:
+            return "Sorry, I could not understand the audio."
+        except sr.RequestError:
+            return "Sorry, the speech service is down."
+
+# Streamlit App
+st.title("Netflix Movie Details Chatbot 🎬")
+
+# Load dataset and model
+data = load_data()
+tokenizer, model = load_model()
+
+# Input options: Text or Voice
+input_option = st.radio("Choose input method:", ("Text", "Voice"))
+
+user_input = ""
+if input_option == "Text":
+    user_input = st.text_input("Enter the movie name, director, or cast:")
+elif input_option == "Voice":
+    if st.button("Start Recording"):
+        user_input = voice_to_text()
+        st.write(f"You said: {user_input}")
+
+# Generate response
+if user_input:
+    # Search for movie details
+    movie_results = search_movie_details(user_input, data)
+    
+    if not movie_results.empty:
+        st.write("Here are the matching results:")
+        for _, row in movie_results.iterrows():
+            st.write(f"**Title:** {row['title']}")
+            st.write(f"**Type:** {row['type']}")
+            st.write(f"**Director:** {row['director']}")
+            st.write(f"**Cast:** {row['cast']}")
+            st.write(f"**Release Year:** {row['release_year']}")
+            st.write(f"**Rating:** {row['rating']}")
+            st.write(f"**Description:** {row['description']}")
+            st.write("---")
+    else:
+        # Use DialoGPT for general conversation
+        inputs = tokenizer.encode(user_input, return_tensors="pt")
+        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}")