First commit

app.py

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+from transformers import MusicgenForConditionalGeneration
+from transformers import AutoProcessor
+import scipy
+
+import streamlit as st
+
+st.set_page_config(
+    page_title="Plant Orchestra with GenAI",
+    page_icon="🎵"
+)
+
+# initialise model
+@st.cache_resource
+def initialise_model():
+    try:
+        #processor = AutoProcessor.from_pretrained("musicgen-small")
+        processor = AutoProcessor.from_pretrained("facebook/musicgen-small")
+        # model = MusicgenForConditionalGeneration.from_pretrained("musicgen-small")
+        model = MusicgenForConditionalGeneration.from_pretrained("facebook/musicgen-small")
+        return processor, model
+    except Exception as e:
+        st.error(f"Error initializing the model: {str(e)}")
+        return None, None
+    
+processor, model = initialise_model()
+    
+
+# Generate audio with given prompt
+def generate_audio(processor, model, prompt):
+    if processor is not None and model is not None:
+        try:
+            inputs = processor(
+                text=[prompt],
+                padding=True,
+                return_tensors="pt",
+            )
+            audio_values = model.generate(**inputs.to("cpu"), do_sample=True, guidance_scale=3, max_new_tokens=256)
+            return audio_values
+        except Exception as e:
+            st.error(f"Error generating audio: {str(e)}")
+    return None
+
+# save audio file with scipy
+def save_file(model, audio_values, filename):
+    sampling_rate = model.config.audio_encoder.sampling_rate
+    scipy.io.wavfile.write(filename, rate=sampling_rate, data=audio_values[0, 0].cpu().numpy())
+
+
+
+st.title("Plant Orchestra 🌻")
+st.markdown("Generate music based on your own plant orchestra.")
+
+
+prompt = st.text_input(label='Prompt:', value='Sunflower temperature: 32.5C UV light intensity: 50% Soil water level: 3cm/h')
+if st.button("Generate Music"):
+    #with st.spinner("Initialising model..."):
+    #    processor, model = initialise_model()
+    if processor is not None and model is not None:
+        with st.spinner("Generating audio..."):
+            results = generate_audio(processor, model, prompt)
+        if results is not None:
+            with st.spinner("Saving audio..."):
+                filename = "plant_orchestra" + ".wav"
+                save_file(model, results, filename)
+            with st.spinner("Displaying audio..."):
+                with open(filename, "rb") as f:
+                    generation = f.read()
+                    st.write("Listen to the generated music:")
+                st.audio(generation)
+            
+# Add additional information and instructions for users
+st.sidebar.subheader("How to Use:")
+st.sidebar.write("1. Enter a plant condition prompt in the text input.")
+st.sidebar.write("2. Click the 'Generate Music' button to create music based on the provided prompt.")
+st.sidebar.write("3. You can listen to the generated music and download it.")
+
+# Footer
+st.write()
+st.write()
+st.write()
+st.markdown("---")
+st.markdown("Created with ❤️ by HS2912 W4 Group 2")

requirements.txt

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+streamlit
+transformers
+scipy
+torch