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README.md

@@ -1,11 +1,14 @@
 ---
-title: Mixtral 8x7B Chatbot
-emoji: 🏃
-colorFrom: pink
-colorTo: yellow
+title: Mixtral Chat
+emoji: 🐙
+colorFrom: green
+colorTo: blue
 sdk: gradio
-sdk_version: 4.41.0
+sdk_version: 4.37.2
 app_file: app.py
+models:
+  - mistralai/Mixtral-8x7B-v0.1
+  - mistralai/Mixtral-8x7B-Instruct-v0.1
 pinned: false
 ---
 

app.py

@@ -0,0 +1,84 @@
+from huggingface_hub import InferenceClient
+import gradio as gr
+
+client = InferenceClient(model="mistralai/Mixtral-8x7B-Instruct-v0.1")
+
+def format_prompt(message, history):
+    prompt = "<s>"
+    for user_prompt, bot_response in history:
+        prompt += f"[INST] {user_prompt} [/INST]"
+        prompt += f" {bot_response}</s> "
+    prompt += f"[INST] {message} [/INST]"
+    return prompt
+
+def should_stop_generation(output, stop_patterns):
+    for pattern in stop_patterns:
+        if pattern in output:
+            return True
+    return False
+
+async def generate(
+    prompt, history, temperature=0.7, max_new_tokens=1024, top_p=0.95, repetition_penalty=1.0,
+    stop_patterns=None, max_loops=5
+):
+    if stop_patterns is None:
+        stop_patterns = ["\n\n", ".", "The end", "Thank you"]
+
+    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=42,
+    )
+
+    formatted_prompt = format_prompt(prompt, history)
+
+    output = ""
+    loop_count = 0
+    while loop_count < max_loops:
+        try:
+            stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
+            async for response in stream:
+                output += response.token.text
+                yield output
+                if should_stop_generation(output, stop_patterns):
+                    return  # Stop if end pattern is detected
+
+            loop_count += 1  # Increment loop count to avoid infinite loops
+
+            # If the text isn't complete, use the last segment as a new prompt
+            formatted_prompt = format_prompt(output.split("\n")[-1], history)
+        
+        except Exception as e:
+            print(f"Error during streaming: {e}")
+            break
+
+    # Non-streaming fallback
+    try:
+        response = client.text_generation(formatted_prompt, **generate_kwargs, stream=False, return_full_text=False)
+        output = response  # Use response as a string if streaming failed
+        if not should_stop_generation(output, stop_patterns):
+            output += " [Additional text required to complete the response.]"
+        yield output
+    except Exception as e:
+        print(f"Error during non-streaming generation: {e}")
+
+mychatbot = gr.Chatbot(
+    avatar_images=["./user.png", "./botm.png"], bubble_full_width=False, show_label=False, show_copy_button=True, likeable=True,
+)
+
+demo = gr.ChatInterface(fn=generate, 
+                        chatbot=mychatbot,
+                        title="Mixtral 8x7b AI Chatbot By wifix199",
+                        retry_btn=None,
+                        undo_btn=None
+                       )
+
+demo.queue().launch(server_name="10.172.2.37", server_port=5002, show_api=False, share=True)

readme.txt

@@ -0,0 +1,2 @@
+Thanks to the Mistral AI Team for developing this awesome model.
+Wifix199