cloud version

app_cloud.py

@@ -0,0 +1,180 @@
+import llama_cpp
+import os
+import json
+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
+
+huggingface_token = os.getenv("HUGGINGFACE_TOKEN")
+
+hf_hub_download(
+    repo_id="Qwen/Qwen2-0.5B-Instruct-GGUF",
+    filename="qwen2-0_5b-instruct-q4_k_m.gguf",
+    local_dir="./models"
+)
+
+hf_hub_download(
+    repo_id="TobDeBer/Meta-Llama-3.1-8B-Instruct-Q4_K_M-GGUF",
+    filename="meta-llama-3.1-8b-instruct-q4_k_m.gguf",
+    local_dir="./models",
+    token=huggingface_token
+)
+# 5GB
+
+# RichardErkhov/ibm-granite_-_granite-7b-base-gguf
+# granite-7b-base.Q4_K_M.gguf
+hf_hub_download(
+    repo_id="RichardErkhov/ibm-granite_-_granite-7b-base-gguf",
+    filename="granite-7b-base.Q4_K_M.gguf",
+    local_dir="./models",
+    token=huggingface_token
+)# 4GB
+
+# TobDeBer/granite-8b-code-instruct-128k-Q4_K_M-GGUF
+# granite-8b-code-instruct-128k-q4_k_m.gguf
+hf_hub_download(
+    repo_id="TobDeBer/granite-8b-code-instruct-128k-Q4_K_M-GGUF",
+    filename="granite-8b-code-instruct-128k-q4_k_m.gguf",
+    local_dir="./models",
+    token=huggingface_token
+)# 5GB
+
+# Dropdown for Model Selection
+model_dropdown = gr.Dropdown(
+    [
+        'qwen2-0_5b-instruct-q4_k_m.gguf',
+        'meta-llama-3.1-8b-instruct-q4_k_m.gguf',
+        'granite-7b-base.Q4_K_M.gguf',
+		'granite-8b-code-instruct-128k-q4_k_m.gguf',
+    ],
+    value="qwen2-0_5b-instruct-q4_k_m.gguf",
+    label="Model"
+)
+
+llm = None
+llm_model = None
+
+def respond(
+    message,
+    history: list[tuple[str, str]],
+        system_message,
+    max_tokens,
+    temperature,
+    top_p,
+    top_k,
+    repeat_penalty,
+	selected_model,  # This is now a parameter received from the interface
+):
+    chat_template = MessagesFormatterType.GEMMA_2
+
+    global llm
+    global llm_model
+    
+    # Update the model if it has changed
+    if llm is None or llm_model != selected_model:
+        llm = Llama(
+            model_path=f"models/{selected_model}",
+            flash_attn=True,
+            n_gpu_layers=81,
+            n_batch=1024,
+            n_ctx=8192,
+        )
+        llm_model = selected_model
+
+    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()
+
+    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 = 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
+
+description = """<p align="center">Defaults to Qwen 500M</p>
+"""
+
+# Create the Gradio interface
+with gr.Blocks() as demo:  # Create a Gradio Blocks context
+    
+    # Model selection dropdown above the chat
+    model_dropdown.render()
+
+    # Main chat interface
+    chat_interface = gr.ChatInterface(
+        respond,
+        additional_inputs=[
+            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",
+            ),
+            model_dropdown  # Pass the dropdown directly
+        ],
+        retry_btn="Retry",
+        undo_btn="Undo",
+        clear_btn="Clear",
+        submit_btn="Send",
+        title="Chat with Qwen 2 and friends using llama.cpp",
+        description=description,
+    )
+
+demo.queue().launch()