Create app.py

app.py

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+import streamlit as st
+from transformers import pipeline
+
+# Initialize a text generation pipeline
+generator = pipeline('text-generation', model='dbmdz/german-gpt2')
+
+st.title('German Medical Content Manager')
+
+# Sidebar for user input
+st.sidebar.header('User Input Options')
+input_topic = st.sidebar.text_input('Enter a medical topic', 'Type 1 Diabetes')
+
+# Main Page
+st.write(f"Creating social media content for: {input_topic}")
+
+# Function to generate text based on the input topic
+def generate_content(topic):
+    generated_text = generator(f"Letzte Nachrichten über {topic}:", max_length=50, num_return_sequences=1)
+    return generated_text[0]['generated_text']
+
+if st.button('Generate Social Media Post'):
+    with st.spinner('Generating...'):
+        post_content = generate_content(input_topic)
+        st.success('Generated Content:')
+        st.write(post_content)
+
+st.write('Generated social media posts will appear here after clicking the "Generate" button.')