Update app.py

app.py

@@ -1,97 +1,38 @@
 import gradio as gr
-import os
-import spaces
-from transformers import GemmaTokenizer, AutoModelForCausalLM
-from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
-from threading import Thread
+from spaces import spaces
 
-# Set an environment variable
-HF_TOKEN = os.environ.get("HF_TOKEN", None)
+# Assign GPU to the overall spaces
+def main():
 
+    # Define the components using the specified URLs
+    with gr.Blocks() as chatbot:
+        gr.HTML("<iframe src='https://huggingface.co/spaces/prithivMLmods/Mistral-7B-Instruct-v0.3' width='100%' height='1000px' style='border-radius: 8px;'></iframe>")
 
-# Load the tokenizer and model
-tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.3")
-model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.3", device_map="auto")
-terminators = [
-    tokenizer.eos_token_id,
-    tokenizer.convert_tokens_to_ids("<|eot_id|>")
-]
+    with gr.Blocks() as imagegpt:
+        gr.HTML("<iframe src='https://huggingface.co/spaces/prithivMLmods/ImageGPT-4XL' width='100%' height='1000px' style='border-radius: 8px;'></iframe>")
 
-@spaces.GPU(duration=120)
-def gpt4o_mistral(message: str, 
-              history: list, 
-              temperature: float, 
-              max_new_tokens: int
-             ) -> str:
-   
-    conversation = []
-    for user, assistant in history:
-        conversation.extend([{"role": "user", "content": user}, {"role": "assistant", "content": assistant}])
-    conversation.append({"role": "user", "content": message})
+    with gr.Blocks() as imageengine4k:
+        gr.HTML("<iframe src='https://huggingface.co/spaces/prithivMLmods/DALLE-4K' width='100%' height='1000px' style='border-radius: 8px;'></iframe>")
 
-    input_ids = tokenizer.apply_chat_template(conversation, return_tensors="pt").to(model.device)
-    
-    streamer = TextIteratorStreamer(tokenizer, timeout=10.0, skip_prompt=True, skip_special_tokens=True)
+    with gr.Blocks() as imageengine2k:
+        gr.HTML("<iframe src='https://huggingface.co/spaces/prithivMLmods/DALLE-2K' width='100%' height='1000px' style='border-radius: 8px;'></iframe>")
 
-    generate_kwargs = dict(
-        input_ids= input_ids,
-        streamer=streamer,
-        max_new_tokens=max_new_tokens,
-        do_sample=True,
-        temperature=temperature,
-        eos_token_id=terminators,
-    )
-    # This will enforce greedy generation (do_sample=False) when the temperature is passed 0, avoiding the crash.             
-    if temperature == 0:
-        generate_kwargs['do_sample'] = False
-        
-    t = Thread(target=model.generate, kwargs=generate_kwargs)
-    t.start()
+    with gr.Blocks() as mediadownloader:
+        gr.HTML("<iframe src='https://huggingface.co/spaces/prithivMLmods/All-In-One-Downloader' width='100%' height='1000px' style='border-radius: 8px;'></iframe>")
 
-    outputs = []
-    for text in streamer:
-        outputs.append(text)
-        #print(outputs)
-        yield "".join(outputs)
-        
+    with gr.Blocks() as photofakes:
+        gr.HTML("<iframe src='https://huggingface.co/spaces/prithivMLmods/Face-Swap-Roop' width='100%' height='1000px' style='border-radius: 8px;'></iframe>")
 
-# Gradio block
-chatbot=gr.Chatbot(height=450, label='Gradio ChatInterface')
+    # Assemble the components into a single Gradio interface
+    with gr.Blocks(theme=gr.themes.Soft(), title="ChatGPT-Omni") as demo:
+        gr.Markdown("# ChatGPT-Omni")
+        gr.TabbedInterface(
+            [chatbot, imagegpt, imageengine4k, imageengine2k, mediadownloader, photofakes], 
+            ['ChatBot', 'ImageGPT', 'Image Engine 4K', 'Image Engine 2K', 'Media Downloader', 'PhotoFakes']
+        )
 
-with gr.Blocks(fill_height=True) as demo:
-    
+    # Launch the demo
+    demo.queue().launch(debug=True)
 
-    gr.ChatInterface(
-        fn=gpt4o_mistral,
-         theme="xiaobaiyuan/theme_brief",
-        chatbot=chatbot,
-        fill_height=True,
-        additional_inputs_accordion=gr.Accordion(label="⚙️ Parameters", open=False, render=False),
-        additional_inputs=[
-            gr.Slider(minimum=0,
-                      maximum=1, 
-                      step=0.1,
-                      value=0.95, 
-                      label="Temperature", 
-                      render=False),
-            gr.Slider(minimum=128, 
-                      maximum=4096,
-                      step=1,
-                      value=512, 
-                      label="Max new tokens", 
-                      render=False ),
-            ],
-        examples=[
-            ['How to setup a human base on Mars? Give short answer.'],
-            ['Explain theory of relativity to me like I’m 8 years old.'],
-            ['What is 9,000 * 9,000?'],
-            ['Write a pun-filled happy birthday message to my friend Alex.'],
-            ['Justify why a penguin might make a good king of the jungle.']
-            ],
-        cache_examples=False,
-       
-                     )
-    
-  
-if __name__ == "__main__":
-    demo.launch()
+# Run the main function
+main()