Update app.py

app.py

@@ -1,11 +1,30 @@
 import spaces
+import json
+import subprocess
 import gradio as gr
-from huggingface_hub import InferenceClient
+from huggingface_hub import hf_hub_download
 
+subprocess.run('pip install llama-cpp-python==0.2.75 --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cu124', shell=True)
+subprocess.run('pip install llama-cpp-agent==0.2.10', shell=True)
+
+hf_hub_download(repo_id="bartowski/dolphin-2.9.1-yi-1.5-34b-GGUF", filename="dolphin-2.9.1-yi-1.5-34b-Q6_K.gguf",  local_dir = "./models")
+hf_hub_download(repo_id="bartowski/dolphin-2.9.1-yi-1.5-9b-GGUF", filename="dolphin-2.9.1-yi-1.5-9b-f32.gguf",  local_dir = "./models")
+
+css = """
+.message-row {
+    justify-content: space-evenly !important;
+}
+.message-bubble-border {
+    border-radius: 6px !important;
+    border-color: #343140 !important;
+}
+.user {
+    background: #1e1c26 !important;
+}
+.assistant, .pending {
+    background: #16141c !important;
+}
 """
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
 @spaces.GPU(duration=120)
 def respond(
@@ -15,39 +34,58 @@ def respond(
     max_tokens,
     temperature,
     top_p,
+    model,
 ):
-    messages = [{"role": "system", "content": system_message}]
+    from llama_cpp import Llama
+    from llama_cpp_agent import LlamaCppAgent
+    from llama_cpp_agent import 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
 
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
+    llm = Llama(
+        model_path=f"models/{model}",
+        n_gpu_layers=81,
+    )
+    provider = LlamaCppPythonProvider(llm)
 
-    messages.append({"role": "user", "content": message})
+    agent = LlamaCppAgent(
+        provider,
+        system_prompt="You are a helpful assistant.",
+        predefined_messages_formatter_type=MessagesFormatterType.CHATML,
+        debug_output=True
+    )
+    
+    settings = provider.get_provider_default_settings()
+    settings.max_tokens = max_tokens
+    settings.stream = True
 
-    response = ""
+    messages = BasicChatHistory()
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
+    for msn in history:
+        user = {
+            'role': Roles.user,
+            'content': msn[0]
+        }
+        assistant = {
+            'role': Roles.assistant,
+            'content': msn[1]
+        }
 
-        response += token
-        yield response
+        messages.add_message(user)
+        messages.add_message(assistant)
+    
+    stream = agent.get_chat_response(message, llm_sampling_settings=settings, chat_history=messages, returns_streaming_generator=True, print_output=False)
+    
+    outputs = ""
+    for output in stream:
+        outputs += output
+        yield outputs
 
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
+        gr.Slider(minimum=1, maximum=8192, value=8192, step=1, label="Max new tokens"),
         gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
         gr.Slider(
             minimum=0.1,
@@ -56,9 +94,24 @@ demo = gr.ChatInterface(
             step=0.05,
             label="Top-p (nucleus sampling)",
         ),
+        gr.Dropdown(['dolphin-2.9.1-yi-1.5-34b-Q6_K.gguf', 'dolphin-2.9.1-yi-1.5-9b-f32.gguf'], value="dolphin-2.9.1-yi-1.5-34b-Q6_K.gguf", label="Model"),
     ],
+    theme=gr.themes.Soft(primary_hue="violet", secondary_hue="violet", neutral_hue="gray",font=[gr.themes.GoogleFont("Exo"), "ui-sans-serif", "system-ui", "sans-serif"]).set(
+        body_background_fill_dark="#16141c",
+        block_background_fill_dark="#16141c",
+        block_title_background_fill_dark="#1e1c26",
+        input_background_fill_dark="#292733",
+        button_secondary_background_fill_dark="#24212b",
+        border_color_primary_dark="#343140",
+        background_fill_secondary_dark="#16141c"
+    ),
+    css=css,
+    retry_btn="Retry",
+    undo_btn="Undo",
+    clear_btn="Clear",
+    submit_btn="Send",
+    description="Llama-cpp-agent: Chat multi llm selection"
 )
 
-
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()