Create app.py

app.py

@@ -0,0 +1,60 @@
+from huggingface_hub import InferenceClient
+import gradio as gr
+
+client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
+
+def format_prompt(new_message, history):
+  prompt = "<s>"
+  for user_msg, bot_msg in history:
+    prompt += f"[INST] {user_msg} [/INST]"
+    prompt += f" {bot_msg}</s> "
+  prompt += f"[INST] {new_message} [/INST]"
+  return prompt
+
+def generate(prompt, history,
+             temperature=0.25,
+             max_new_tokens=512,
+             top_p=0.95,
+             repetition_penalty=1.0,):
+                 
+    temperature = float(temperature)
+                 
+    if temperature < 1e-2:
+        temperature = 1e-2
+        
+    top_p = float(top_p)
+
+    generate_kwargs = dict(
+        temperature=temperature,
+        max_new_tokens=max_new_tokens,
+        top_p=top_p,
+        repetition_penalty=repetition_penalty,
+        do_sample=True,
+        seed=727,
+    )
+
+    formatted_prompt = format_prompt(prompt, history)
+
+    stream = client.text_generation(formatted_prompt,
+                                    **generate_kwargs,
+                                    stream=True,
+                                    details=True,
+                                    return_full_text=False)
+    output = ""
+
+    for response in stream:
+        output += response.token.text
+        yield output
+    return output
+
+samir_chatbot = gr.Chatbot(avatar_images=["./user.png", "./bot.png"],
+                       bubble_full_width=False,
+                       show_label=False, 
+                       show_copy_button=True,
+                       likeable=True,)
+
+demo = gr.ChatInterface(fn=generate, 
+                        chatbot=samir_chatbot,
+                        title="Samir's Mixtral 8x7b Chat",)
+
+demo.queue().launch(show_api=False)