Initial commit

main.py

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+from pathlib import Path
+import requests
+import llama_cpp_python as llm
+from rich.console import Console
+from rich.layout import Layout
+from rich.panel import Panel
+from rich.text import Text
+
+def download_model(url, model_path):
+    """
+    Download the GGUF model from the given URL if it's not present locally.
+
+    Parameters:
+        url (str): URL to download the model from.
+        model_path (Path): Local path to save the downloaded model.
+    """
+    if not model_path.exists():
+        try:
+            response = requests.get(url, allow_redirects=True)
+            response.raise_for_status()
+            model_path.write_bytes(response.content)
+            print(f"Model downloaded to {model_path}")
+        except requests.RequestException as e:
+            print(f"Error downloading the model: {e}")
+
+def load_model(model_path):
+    """
+    Load a GGUF format model for the chatbot.
+
+    Parameters:
+        model_path (Path): Path to the GGUF model file.
+
+    Returns:
+        Model: The loaded GGUF model.
+    """
+    return llm.load(str(model_path))
+
+def generate_text(model, prompt, max_tokens=256, temperature=0.1, top_p=0.5, echo=False, stop=None):
+    """
+    Generate a response from the LLM based on the given prompt.
+
+    Parameters:
+        model: The loaded GGUF model.
+        prompt (str): The input prompt for the model.
+        max_tokens (int): Maximum number of tokens for the response.
+        temperature (float): Token sampling temperature.
+        top_p (float): Nucleus sampling parameter.
+        echo (bool): If True, the prompt is included in the response.
+        stop (list): Tokens at which the model should stop generating text.
+
+    Returns:
+        str: The generated text response.
+    """
+    if stop is None:
+        stop = ["#"]
+    output = model.generate(
+        prompt,
+        max_tokens=max_tokens,
+        temperature=temperature,
+        top_p=top_p,
+        echo=echo,
+        stop=stop,
+    )
+    return output["choices"][0]["text"].strip()
+
+def generate_prompt_from_template(user_input):
+    """
+    Format the user input into a prompt suitable for the chatbot.
+
+    Parameters:
+        user_input (str): The user's input message.
+
+    Returns:
+        str: The formatted prompt for the chatbot.
+    """
+    return f"You are a helpful chatbot.\n{user_input}"
+
+def create_chat_layout():
+    """
+    Create the layout for the chatbot interface using rich.
+
+    Returns:
+        Layout: The layout object for the chat interface.
+    """
+    layout = Layout()
+
+    layout.split(
+        Layout(name="header", size=3),
+        Layout(ratio=1, name="main"),
+        Layout(name="footer", size=3)
+    )
+
+    layout["header"].update(Panel("[bold magenta]Llama.cpp Chatbot[/]", style="bold blue"))
+    layout["footer"].update(Text("Type your message and press [bold green]Enter[/]. Type 'exit' to end the chat.", justify="center"))
+    return layout
+
+def main():
+    """
+    The main function to run the chatbot.
+    """
+    model_path = Path("zephyr-7b-alpha.Q3_K_M.gguf")
+    model_url = "https://huggingface.co/TheBloke/zephyr-7B-alpha-GGUF/raw/main/zephyr-7b-alpha.Q3_K_M.gguf"
+
+    if not model_path.exists():
+        print("Model not found locally. Downloading...")
+        download_model(model_url, model_path)
+
+    model = load_model(model_path)
+
+    console = Console()
+    layout = create_chat_layout()
+    console.print(layout)
+
+    chat_history = ""
+
+    while True:
+        user_input = console.input("[bold green]You: [/]")
+        if user_input.lower() == "exit":
+            break
+
+        prompt = generate_prompt_from_template(user_input)
+        bot_response = generate_text(model, prompt, max_tokens=356)
+        
+        chat_history += f"[bold green]You:[/] {user_input}\n[bold yellow]Bot:[/] {bot_response}\n"
+        chat_panel = Panel(chat_history, title="Chat History")
+        layout["main"].update(chat_panel)
+        console.print(layout)
+
+if __name__ == "__main__":
+    main()