Create app.py

app.py

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+import streamlit as st
+from transformers import pipeline
+from gtts import gTTS
+import os
+
+# Load a text generation pipeline
+generator = pipeline('text-generation', model='gpt2')
+
+# Streamlit app
+st.title("Phone-Guy-Generator")
+st.subheader("Generate Custom FNaF Phone Calls")
+
+# User inputs
+night = st.selectbox("Select the Night", ["1", "2", "3", "4", "5", "6", "7"])
+tone = st.selectbox("Select the Tone of the Call", ["Friendly", "Warning", "Ominous", "Neutral"])
+length = st.slider("Select the Length of the Call (in words)", 50, 300, 150)
+include_phrase = st.text_input("Include a Specific Phrase (Optional)")
+
+# Generate phone call
+if st.button("Generate Phone Call"):
+    # Construct the prompt based on user input
+    prompt = f"Generate Custom FNaF Phone Call for night {night}. The tone should be {tone.lower()}."
+    if include_phrase:
+        prompt += f" Make sure to include the phrase: '{include_phrase}'."
+    
+    # Generate the text
+    result = generator(prompt, max_length=length, num_return_sequences=1)
+    generated_text = result[0]['generated_text']
+    
+    # Display the generated phone call
+    st.text(generated_text)
+    
+    # Convert the generated text to speech
+    tts = gTTS(generated_text, lang='en')
+    tts.save("phone_call.mp3")
+
+    # Provide a download link for the generated speech
+    audio_file = open("phone_call.mp3", "rb")
+    st.audio(audio_file.read(), format='audio/mp3')
+    audio_file.close()
+
+    # Optionally, remove the file after use
+    os.remove("phone_call.mp3")