Create app/app.py

app/app.py

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+# This Gradio app allows users to interact with a chatbot that can generate text and images based on user prompts.
+import gradio as gr
+import numpy as np
+from transformers_js import pipeline  # Corrected import to use transformers_js instead of transformers_js_py
+
+# Define the available models
+AVAILABLE_MODELS = {
+    "GPT-2": "gpt2",
+    "DALL-E": "dalle-mini/dalle-mini-1.3B"
+}
+
+# Initialize the text generation pipeline
+text_generator = pipeline("text-generation", model=AVAILABLE_MODELS["GPT-2"])
+
+# Initialize the image generation pipeline
+image_generator = pipeline("image-generation", model=AVAILABLE_MODELS["DALL-E"])
+
+# Function to generate text
+def generate_text(prompt, model):
+    np.random.seed(42)  # Set a seed for reproducibility
+    if model == "GPT-2":
+        return text_generator(prompt, max_length=50, num_return_sequences=1)[0]['generated_text']
+    else:
+        return "Model not supported for text generation"
+
+# Function to generate images
+def generate_image(prompt, model):
+    if model == "DALL-E":
+        image = image_generator(prompt, num_inference_steps=50, guidance_scale=7.5).images[0]
+        return image
+    else:
+        return "Model not supported for image generation"
+
+# Create the Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Chatbot with Text and Image Generation")
+    
+    with gr.Tab("Text Generation"):
+        text_prompt = gr.Textbox(label="Enter your text prompt")
+        text_model = gr.Radio(choices=list(AVAILABLE_MODELS.keys()), label="Choose a model", value="GPT-2")
+        text_output = gr.Textbox(label="Generated Text")
+        text_button = gr.Button("Generate Text")
+        text_button.click(generate_text, inputs=[text_prompt, text_model], outputs=text_output)
+    
+    with gr.Tab("Image Generation"):
+        image_prompt = gr.Textbox(label="Enter your image prompt")
+        image_model = gr.Radio(choices=list(AVAILABLE_MODELS.keys()), label="Choose a model", value="DALL-E")
+        image_output = gr.Image(label="Generated Image")
+        image_button = gr.Button("Generate Image")
+        image_button.click(generate_image, inputs=[image_prompt, image_model], outputs=image_output)
+
+# Launch the interface
+demo.launch(show_error=True)