Add image generation capabilities using Google DDPM

app.py

@@ -3,6 +3,7 @@ from transformers import pipeline
 import streamlit as st
 from huggingface_hub import InferenceClient
 import os
+from diffusers import DiffusionPipeline
 
 #Use an API endpoint to call in the MS inference client 
 apiToken = os.getenv("my_API_Key")
@@ -11,6 +12,9 @@ client = InferenceClient(api_key=apiToken)
 #Instantiate the summarization pipeline - this will be used for the image generation
 summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
 
+#Instantiate the image genereation pipeline
+imagePipeline = DiffusionPipeline.from_pretrained("google/ddpm-cifar10-32")
+
 #Input prompt
 writingPrompt = st.text_input("Paste a writing prompt here: ")
 
@@ -35,4 +39,7 @@ if writingPrompt:
     st.write(response_content)
 
     summary = summarizer(response_content, max_length=130, min_length=30, do_sample=False)
-    st.write(summary[0]['summary_text'])  # Displaying the summarized text in Streamlit
+    st.write(summary[0]['summary_text'])  # Displaying the summarized text in Streamlit
+
+    image = pipe(summary).images[0]
+    st.image(image)