Update app.py

app.py

@@ -1,12 +1,61 @@
 import streamlit as st
-
 from transformers import pipeline
+from huggingface_hub import cached_download
+import torch
+from PIL import Image
+
+# Pre-trained models
+text_generator = pipeline("text-generation", model="gpt2")
+question_answering = pipeline("question-answering", model="distilbert-base-cased-squad2")
+image_generator = pipeline("image-generation", model="sd-v1-diffusion")
+
+# Download models if not already present
+models = ["gpt2", "distilbert-base-cased-squad2", "sd-v1-diffusion"]
+for model in models:
+    cached_download(repo_id=f"huggingface/transformers/{model}", force_download=True)
+
+# Story prompt input
+prompt = st.text_input("Start your story with...", value="Once upon a time...")
+
+# Generate story
+generated_text = text_generator(prompt, max_length=1024)[0]["generated_text"]
+
+# Text-to-speech and Text-to-text buttons
+st.button("Speak the story", on_click=lambda: speak(generated_text))
+generated_text_2 = st.button("Generate different story", on_click=lambda: generate_text(prompt))
+
+# Generate question from story
+question = st.text_input("Ask a question about the story...")
+answer = question_answering(question=question, context=generated_text)["answer"]
+
+# Generate image
+image = image_generator(prompt="Image related to the story:")
+image = Image.open(torch.ByteStorage.from_buffer(image[0]["image"]).read())
+
+# Streamlit layout
+st.title("Your Story")
+st.write(generated_text)
+st.image(image)
+
+# Question and answer section
+st.subheader("Ask and Learn")
+st.write(f"Question: {question}")
+st.write(f"Answer: {answer}")
+
+# Text-to-text functionality
+if generated_text_2:
+    generated_text_2 = text_generator(prompt, max_length=1024)[0]["generated_text"]
+    st.write("**New Story:**")
+    st.write(generated_text_2)
+
+# Text-to-speech functionality
+def speak(text):
+    # Your preferred text-to-speech implementation
+    # (e.g., ResponsiveVoice, gTTS) goes here
+    pass
+
+st.write("* This app is still under development and may not always generate accurate or coherent results.")
+st.write("* Please be mindful of the content generated by the AI models.")
 
-text_generator = pipeline("text-generation", model="EleutherAI/gpt-neo-1.3B", device=0)  # You can choose a different model if needed
 
-# Generate text
-prompt = "Once upon a time"
-generated_text = text_generator(prompt, max_length=100, num_return_sequences=1)[0]['generated_text']
 
-# Print the generated text
-print(generated_text)