Create app.py

app.py

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+import streamlit as st
+from transformers import AutoProcessor, MusicgenForConditionalGeneration
+import scipy.io.wavfile
+import openai
+import torch
+
+
+# Streamlit app setup
+st.set_page_config(
+    page_icon="https://soundboard.bilsimaging.com/faviconbilsimaging.png",
+    layout="wide",
+    page_title="Radio Imaging Audio Generator Beta 0.1",
+    initial_sidebar_state="expanded",
+)
+
+# App Header
+st.markdown("""
+    <h1 style=''>Radio Imaging Audio Generator 
+    <span style='font-size: 24px; color: #FDC74A;'>Beta 0.1</span></h1>
+    """, unsafe_allow_html=True)
+st.write("Welcome to the Radio Imaging & MusicGen AI audio generator. Easily create unique audio for your radio imaging projects or for music creation using cutting-edge AI technology.")
+st.markdown("---")
+
+# Instructions Section
+with st.expander("📘 How to Use This Web App"):
+    st.markdown("""
+        1. **Enter OpenAI API Key**: Provide your API key in the sidebar to access the GPT model.
+        2. **Select GPT Model**: Choose the desired model, such as `gpt-3.5-turbo-16k`.
+        3. **Write a Description**: Provide a detailed description of your desired audio.
+        4. **Generate and Review the Prompt**: Generate a description and review the output.
+        5. **Generate Audio**: Use the description to create your audio file.
+        6. **Playback and Download**: Listen to or download the generated audio.
+    """)
+
+# Sidebar Inputs
+with st.sidebar:
+    openai_api_key = st.text_input("🔑 OpenAI API Key", type="password", help="Enter your OpenAI API key.")
+    st.caption("Need an API key? Get one [here](https://platform.openai.com/account/api-keys).")
+    model = st.selectbox("🛠 Choose GPT Model", options=("gpt-3.5-turbo", "gpt-3.5-turbo-16k"))
+
+# Prompt Input
+st.markdown("## ✍🏻 Write Your Description")
+prompt = st.text_area(
+    "Describe the audio you'd like to generate.", 
+    help="Include details like mood, instruments, style, or purpose (e.g., calm background music for a morning show)."
+)
+
+# Generate Prompt
+if st.button("📄 Generate Prompt"):
+    if not openai_api_key.strip() or not prompt.strip():
+        st.error("Please provide both an OpenAI API key and a description.")
+    else:
+        with st.spinner("Generating your prompt... Please wait."):
+            try:
+                # Create a prompt and get response from OpenAI
+                full_prompt = {"role": "user", "content": f"Describe a radio imaging audio piece based on: {prompt}"}
+                response = openai.ChatCompletion.create(model=model, messages=[full_prompt], api_key=openai_api_key)
+                descriptive_text = response.choices[0].message['content'].strip()
+
+                # Append a credit line
+                descriptive_text += "\n\n© Created using Radio Imaging Audio Generator by Bilsimaging"
+
+                # Save to session state
+                st.session_state['generated_prompt'] = descriptive_text
+                st.success("Prompt successfully generated!")
+                st.write(descriptive_text)
+                st.download_button("📥 Download Prompt", descriptive_text, file_name="generated_prompt.txt")
+            except Exception as e:
+                st.error(f"Error while generating prompt: {e}")
+
+st.markdown("---")
+
+# Cache Model Loading
+@st.cache_resource
+def load_model():
+    """Load and cache the MusicGen model and processor."""
+    model = MusicgenForConditionalGeneration.from_pretrained("facebook/musicgen-small")
+    processor = AutoProcessor.from_pretrained("facebook/musicgen-small")
+    return model, processor
+
+# Generate Audio
+if st.button("▶ Generate Audio"):
+    if 'generated_prompt' not in st.session_state or not st.session_state['generated_prompt']:
+        st.error("Please generate and approve a prompt before creating audio.")
+    else:
+        descriptive_text = st.session_state['generated_prompt']
+        with st.spinner("Generating your audio... This might take a few moments."):
+            try:
+                # Load model and processor
+                musicgen_model, processor = load_model()
+
+                # Generate audio from the prompt
+                inputs = processor(text=[descriptive_text], padding=True, return_tensors="pt")
+                audio_values = musicgen_model.generate(**inputs, max_new_tokens=512)
+                sampling_rate = musicgen_model.config.audio_encoder.sampling_rate
+
+                # Save and display the audio
+                audio_filename = "Bilsimaging_radio_imaging_output.wav"
+                scipy.io.wavfile.write(audio_filename, rate=sampling_rate, data=audio_values[0, 0].numpy())
+                st.success("Audio successfully generated!")
+                st.audio(audio_filename)
+            except Exception as e:
+                st.error(f"Error while generating audio: {e}")
+
+# Footer Section
+st.markdown("---")
+st.markdown("""
+    ✔️ Made with ❤️ by [Bilsimaging](https://bilsimaging.com). Your feedback and support help us grow!
+    """)
+st.markdown("<style>#MainMenu {visibility: hidden;} footer {visibility: hidden;}</style>", unsafe_allow_html=True)