Create app.py

app.py

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+import torch
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+from PIL import Image
+import gradio as gr
+
+# Load text-to-image model
+text_to_image_model = torch.hub.load("ProPerNounpYK/texttoimage", map_location=torch.device("cuda" if torch.cuda.is_available() else "cpu"))
+
+# Load chat model
+chat_model = AutoModelForSeq2SeqLM.from_pretrained("ProPerNounpYK/chat")
+chat_tokenizer = AutoTokenizer.from_pretrained("ProPerNounpYK/chat")
+
+# Create multimodal interface
+interface = gr.Interface(
+    fn=lambda input_text, input_image: generate_response(input_text, input_image),
+    inputs=["text", "image"],
+    outputs=["text", "image"],
+    title="Multimodal Conversational AI",
+    description="Talk to me, and I'll respond with images!"
+)
+
+def generate_response(input_text, input_image):
+    # Process input text using chat model
+    chat_output = chat_model(input_text)
+    chat_response = chat_tokenizer.decode(chat_output, skip_special_tokens=True)
+
+    # Process input image using text-to-image model
+    generated_image = text_to_image_model(input_text, input_image)
+
+    # Return response as a tuple of text and image
+    return chat_response, generated_image
+
+# Launch the interface
+interface.launch()