Update app.py

app.py

@@ -3,42 +3,6 @@ import os
 from groq import Groq 
 import gradio as gr 
 
-DESCRIPTION = '''
-<div>
-<h1 style="text-align: center;">Meta Llama3 8B</h1>
-<p>This Space demonstrates the instruction-tuned model <a href="https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct"><b>Meta Llama3 8b Chat</b></a>. Meta Llama3 is the new open LLM and comes in two sizes: 8b and 70b. Feel free to play with it, or duplicate to run privately!</p>
-<p>🔎 For more details about the Llama3 release and how to use the model with <code>transformers</code>, take a look <a href="https://huggingface.co/blog/llama3">at our blog post</a>.</p>
-<p>🦕 Looking for an even more powerful model? Check out the <a href="https://huggingface.co/chat/"><b>Hugging Chat</b></a> integration for Meta Llama 3 70b</p>
-</div>
-'''
-
-LICENSE = """
-<p/>
----
-Built with Meta Llama 3
-"""
-
-PLACEHOLDER = """
-<div style="padding: 30px; text-align: center; display: flex; flex-direction: column; align-items: center;">
-   <img src="https://ysharma-dummy-chat-app.hf.space/file=/tmp/gradio/8e75e61cc9bab22b7ce3dec85ab0e6db1da5d107/Meta_lockup_positive%20primary_RGB.jpg" style="width: 80%; max-width: 550px; height: auto; opacity: 0.55;  "> 
-   <h1 style="font-size: 28px; margin-bottom: 2px; opacity: 0.55;">Meta llama3</h1>
-   <p style="font-size: 18px; margin-bottom: 2px; opacity: 0.65;">Ask me anything related to Ayur Veda</p>
-</div>
-"""
-
-
-css = """
-h1 {
-  text-align: center;
-  display: block;
-}
-#duplicate-button {
-  margin: auto;
-  color: white;
-  background: #1565c0;
-  border-radius: 100vh;
-}
-"""
 
 client = Groq(
     api_key =os.getenv('api_key_gorq')
@@ -61,48 +25,14 @@ def response_from_llam3(query):
 
   )
   return response.choices[0].message.content
-# iface = gr.Interface(
-#     fn=response_from_llam3,
-#     inputs="text",
-#     outputs="text",
-#        examples=[
-#             ['What is importance of fasting according to Ayurveda?'],
-#             ['What are the medicinal values of Tusli?'],
-#             ['What are the three different doshas?'],
-#             ['What is the ideal diet according to ayurveda?']
-#             ],
-#         cache_examples=False,
-#     )
-# iface.launch()
 
-# Gradio block
-chatbot=gr.Chatbot(height=450, placeholder=PLACEHOLDER, label='Gradio ChatInterface')
-
-with gr.Blocks(fill_height=True, css=css) as demo:
     
-    gr.Markdown(DESCRIPTION)
-    gr.DuplicateButton(value="Duplicate Space for private use", elem_id="duplicate-button")
-    gr.ChatInterface(
-        fn=response_from_llam3,
-        chatbot=chatbot,
-        fill_height=True,
-        inputs="text",
-        outputs="text",
-        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 ),
-        #     ],
+iface = gr.Interface(
+    gr.Markdown("<h1>🚀 Ayurveda Mate 🦙</h1>")
+    gr.Markdown("<h3> 🕹️ Type your questions or prompts below and see how each model responds to the same input 👾 </h3>")
+    fn=response_from_llam3,
+    inputs="text",
+    outputs="text",
        examples=[
             ['What is importance of fasting according to Ayurveda?'],
             ['What are the medicinal values of Tusli?'],
@@ -110,9 +40,19 @@ with gr.Blocks(fill_height=True, css=css) as demo:
             ['What is the ideal diet according to ayurveda?']
             ],
         cache_examples=False,
-                     )
-    
-    gr.Markdown(LICENSE)
+    )
+iface.launch()
+
+# with gr.Blocks() as demo:
+#     gr.Markdown("<h1>🚀 Ayurveda Mate 🦙</h1>")
+#     gr.Markdown("<h3> 🕹️ Type your questions or prompts below and see how each model responds to the same input 👾 </h3>")
+#     with gr.Row():
+#         input_text = gr.Textbox(label="Enter your prompt here:", placeholder="Type something...", lines=2)
+#         submit_button = gr.Button("Submit")
+#     output_llama = gr.Textbox(label="Llama 3 8B 👾", placeholder="", lines=10, interactive=False)
+#     output_mistral = gr.Textbox(label="Mistral 7B 🌠", placeholder="", lines=10, interactive=False)
     
-if __name__ == "__main__":
-    demo.launch()
+#     submit_button.click(fn=chat_with_models, inputs=input_text, outputs=[output_llama, output_mistral])
+
+# if __name__ == "__main__":
+#     demo.launch()