Update app.py

app.py

@@ -1,201 +1,48 @@
-import spaces
-import subprocess
-from llama_cpp import Llama
-from llama_cpp_agent import LlamaCppAgent, MessagesFormatterType
-from llama_cpp_agent.providers import LlamaCppPythonProvider
-from llama_cpp_agent.chat_history import BasicChatHistory
-from llama_cpp_agent.chat_history.messages import Roles
-import gradio as gr
-from huggingface_hub import hf_hub_download
 import os
-import cv2
-
-huggingface_token = os.environ.get('HF_TOKEN')
-
-# Download the Meta-Llama-3.1-8B-Instruct model
-hf_hub_download(
-    repo_id="bartowski/Meta-Llama-3.1-8B-Instruct-GGUF",
-    filename="Meta-Llama-3.1-8B-Instruct-Q5_K_M.gguf",
-    local_dir="./models",
-    token=huggingface_token
-)
-
-hf_hub_download(
-    repo_id="bartowski/Mistral-Nemo-Instruct-2407-GGUF",
-    filename="Mistral-Nemo-Instruct-2407-Q5_K_M.gguf",
-    local_dir="./models",
-    token=huggingface_token
-)
-
-hf_hub_download(
-    repo_id="bartowski/gemma-2-2b-it-GGUF",
-    filename="gemma-2-2b-it-Q6_K_L.gguf",
-    local_dir="./models",
-    token=huggingface_token
-)
-
-hf_hub_download(
-    repo_id="bartowski/openchat-3.6-8b-20240522-GGUF",
-    filename="openchat-3.6-8b-20240522-Q6_K.gguf",
-    local_dir="./models",
-    token=huggingface_token
-)
-
-hf_hub_download(
-    repo_id="bartowski/Llama-3-Groq-8B-Tool-Use-GGUF",
-    filename="Llama-3-Groq-8B-Tool-Use-Q6_K.gguf",
-    local_dir="./models",
-    token=huggingface_token
-)
-
-hf_hub_download(
-    repo_id="bartowski/MiniCPM-V-2_6-GGUF",
-    filename="MiniCPM-V-2_6-Q6_K.gguf",
-    local_dir="./models",
-    token=huggingface_token
-)
-
-hf_hub_download(
-    repo_id="CaioXapelaum/Llama-3.1-Storm-8B-Q5_K_M-GGUF",
-    filename="llama-3.1-storm-8b-q5_k_m.gguf",
-    local_dir="./models",
-    token=huggingface_token
-)
-
-hf_hub_download(
-    repo_id="CaioXapelaum/Orca-2-7b-Patent-Instruct-Llama-2-Q5_K_M-GGUF",
-    filename="orca-2-7b-patent-instruct-llama-2-q5_k_m.gguf",
-    local_dir="./models",
-    token=huggingface_token
-)
-
-
-
-llm = None
-llm_model = None
+import gradio as gr
+from llama_cpp import Llama
+import spaces
 
-cv2.setNumThreads(1)
+llm = None  # Global model variable
 
 @spaces.GPU()
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    model,
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-    top_k,
-    repeat_penalty,
-):
-    chat_template = MessagesFormatterType.GEMMA_2
-
+def chat(message, history):
     global llm
-    global llm_model
 
-    # Load model only if it's not already loaded or if a new model is selected
-    if llm is None or llm_model != model:
+    # Initialize Llama model if not already loaded
+    if llm is None:
         try:
-            llm = Llama(
-                model_path=f"models/{model}",
-                flash_attn=True,
-                n_gpu_layers=81,  # Adjust based on available GPU resources
-                n_batch=1024,
-                n_ctx=8192,
+            llm = Llama.from_pretrained(
+                repo_id="bartowski/Meta-Llama-3.1-70B-Instruct-GGUF",
+                filename="Meta-Llama-3.1-70B-Instruct-Q4_K_S.gguf",
+                verbose=False  # Set to True if you need debug information
             )
-            llm_model = model
         except Exception as e:
             return f"Error loading model: {str(e)}"
 
-    provider = LlamaCppPythonProvider(llm)
-
-    agent = LlamaCppAgent(
-        provider,
-        system_prompt=f"{system_message}",
-        predefined_messages_formatter_type=chat_template,
-        debug_output=True
-    )
-
-    settings = provider.get_provider_default_settings()
-    settings.temperature = temperature
-    settings.top_k = top_k
-    settings.top_p = top_p
-    settings.max_tokens = max_tokens
-    settings.repeat_penalty = repeat_penalty
-    settings.stream = True
-
-    messages = BasicChatHistory()
+    # Prepare the chat history
+    chat_history = [{"role": "user", "content": user_input} for user_input, _ in history]
+    chat_history.append({"role": "user", "content": message})
 
-    # Add user and assistant messages to the history
-    for msn in history:
-        user = {'role': Roles.user, 'content': msn[0]}
-        assistant = {'role': Roles.assistant, 'content': msn[1]}
-        messages.add_message(user)
-        messages.add_message(assistant)
-
-    # Stream the response
+    # Stream the response back as it's generated
     try:
-        stream = agent.get_chat_response(
-            message,
-            llm_sampling_settings=settings,
-            chat_history=messages,
-            returns_streaming_generator=True,
-            print_output=False
+        response_stream = llm.create_chat_completion_stream(
+            messages=chat_history,
+            stream=True  # Ensure streaming is enabled
         )
 
-        outputs = ""
-        for output in stream:
-            outputs += output
-            yield outputs
+        output = ""
+        for chunk in response_stream:
+            output += chunk['text']  # Collect and stream text chunks
+            yield output  # Stream each updated response chunk
+
     except Exception as e:
-        yield f"Error during response generation: {str(e)}"
+        yield f"Error generating response: {str(e)}"
 
+# Gradio Chat Interface setup
 demo = gr.ChatInterface(
-    fn=respond,
-    additional_inputs=[
-        gr.Dropdown([
-                'Meta-Llama-3.1-8B-Instruct-Q5_K_M.gguf',
-                'Mistral-Nemo-Instruct-2407-Q5_K_M.gguf',
-                'gemma-2-2b-it-Q6_K_L.gguf',
-                'openchat-3.6-8b-20240522-Q6_K.gguf',
-                'Llama-3-Groq-8B-Tool-Use-Q6_K.gguf',
-                'MiniCPM-V-2_6-Q6_K.gguf',
-                'llama-3.1-storm-8b-q5_k_m.gguf',
-                'orca-2-7b-patent-instruct-llama-2-q5_k_m.gguf'
-            ],
-            value="gemma-2-2b-it-Q6_K_L.gguf",
-            label="Model"
-        ),
-        gr.Textbox(value="You are a helpful assistant.", label="System message"),
-        gr.Slider(minimum=1, maximum=4096, value=2048, step=1, label="Max tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p",
-        ),
-        gr.Slider(
-            minimum=0,
-            maximum=100,
-            value=40,
-            step=1,
-            label="Top-k",
-        ),
-        gr.Slider(
-            minimum=0.0,
-            maximum=2.0,
-            value=1.1,
-            step=0.1,
-            label="Repetition penalty",
-        ),
-    ],
-    retry_btn="Retry",
-    undo_btn="Undo",
-    clear_btn="Clear",
-    submit_btn="Send",
-    title="Chat with lots of Models and LLMs using llama.cpp",
+    fn=chat,  # Function to call when the user sends a message
+    title="Chat with Meta-Llama 3.1 70B",  # Title for the chat interface
     chatbot=gr.Chatbot(
         scale=1,
         likeable=False,