Update main.py

main.py

@@ -1,51 +1,60 @@
 from ctransformers import AutoModelForCausalLM
-from gradio import Chatbot, Interface
 import gradio as gr
 
-# Load the GGUF model
-llm = AutoModelForCausalLM.from_pretrained(
-    "zephyr-7b-beta.Q4_K_S.gguf",
-    model_type="mistral",
-    max_new_tokens=1096,
-    threads=3
+greety = """
+Follow us [Gathnex](https://medium.com/@gathnex), [linkedin](https://www.linkedin.com/company/gathnex/) and [Github](https://github.com/gathnexadmin) for  more update on Genrative AI, LLM,etc. A special thanks to the Gathnex team members who made a significant contribution to this project.
+"""
+
+llm = AutoModelForCausalLM.from_pretrained("zephyr-7b-beta.Q4_K_S.gguf",
+model_type='mistral',
+max_new_tokens = 1096,
+threads = 3,
 )
 
-# Format prompt with system message and chat history
-def format_prompt(message, chat_history):
-    system_prompt = "Below is an instruction that describes a task. Write a response that appropriately completes the request."
+def stream(prompt, UL):
+    system_prompt = 'You are a helpful AI assistant'
     E_INST = "</s>"
     user, assistant = "<|user|>", "<|assistant|>"
-    prompt = f"{system_prompt}{E_INST}\n"
-    for user_msg, bot_msg in chat_history:
-        prompt += f"{user}\n{user_msg}{E_INST}\n{assistant}\n{bot_msg}{E_INST}\n"
-    prompt += f"{user}\n{message}{E_INST}\n{assistant}\n"
-    return prompt
-
-# Define chatbot function
-def respond(message, chat_history):
-    formatted_prompt = format_prompt(message, chat_history)
-    response = llm(formatted_prompt)
-    chat_history.append((message, response))
-    return chat_history, chat_history
-
-# Create Gradio Chatbot UI
-chatbot = Chatbot(
-    bubble_full_width=False,
-    height=500
+    prompt = f"{system_prompt}{E_INST}\n{user}\n{prompt.strip()}{E_INST}\n{assistant}\n"
+    return llm(prompt)
+
+css = """
+  h1 {
+  text-align: center;
+}
+#duplicate-button {
+  margin: auto;
+  color: white;
+  background: #1565c0;
+  border-radius: 100vh;
+}
+.contain {
+  max-width: 900px;
+  margin: auto;
+  padding-top: 1.5rem;
+}
+"""
+
+chat_interface = gr.ChatInterface(
+    fn=stream,
+    #additional_inputs_accordion_name = "Credentials",
+    #additional_inputs=[
+    #     gr.Textbox(label="OpenAI Key", lines=1),
+    #     gr.Textbox(label="Linkedin Access Token", lines=1),
+    #],
+    stop_btn=None,
+    examples=[
+        ["explain Large language model"],
+        ["what is quantum computing"]
+    ],
 )
 
-# Launch interface
-with gr.Blocks() as demo:
-    gr.Markdown("## Zephyr LLM Chat Interface")
-    chatbot = gr.Chatbot()
-    msg = gr.Textbox(label="Your Message")
-    clear = gr.Button("Clear Chat")
-
-    state = gr.State([])
-
-    msg.submit(respond, [msg, state], [chatbot, state])
-    clear.click(lambda: ([], []), None, [chatbot, state])
-
-# Launch Gradio app
+with gr.Blocks(css=css) as demo:
+    gr.HTML("<h1><center>Gathnex Free LLM Deployment Space<h1><center>")
+    gr.HTML("<h3><center><a href='https://medium.com/@gathnex'>Gathnex AI</a>💬<h3><center>")
+    gr.DuplicateButton(value="Duplicate Space for private use", elem_id="duplicate-button")
+    chat_interface.render()
+    gr.Markdown(greety)
+    
 if __name__ == "__main__":
-    demo.launch(share=True)
+    demo.queue(max_size=10).launch()