cli.py

from gaianet_rag_api_pipeline.config import ENV_FILE_PATH

import click
import dotenv
import errno
import importlib
import pathlib
import re
import requests
import shutil
import socket
import subprocess
import typing


class LazyGroup(click.Group):
    """
    Utility class to lazily load Pipeline sub-commands within a click.Group
    
    Source: https://click.palletsprojects.com/en/stable/complex/#using-lazygroup-to-define-a-cli
    """

    def __init__(self, *args, lazy_subcommands=None, **kwargs):
        """
        Set the list of sub-commands to be lazily load
        
        lazy_subcommands is a map of the form:
            {command-name} -> {module-name}.{command-object-name}
        """
        super().__init__(*args, **kwargs)
        
        self.lazy_subcommands = lazy_subcommands or {}

    def list_commands(self, ctx):
        """
        List all available sub-commands
        """
        base = super().list_commands(ctx)
        lazy = sorted(self.lazy_subcommands.keys())
        return base + lazy

    def get_command(self, ctx, cmd_name):
        """
        Load a sub-command using the correct function according to its type
        """
        if cmd_name in self.lazy_subcommands:
            return self._lazy_load(cmd_name)
        return super().get_command(ctx, cmd_name)

    def _lazy_load(self, cmd_name):
        """
        Lazily loads a sub-command
        """
        # lazily loading a command, first get the module name and attribute name
        import_path = self.lazy_subcommands[cmd_name]
        modname, cmd_object_name = import_path.rsplit(".", 1)
        # do the import
        mod = importlib.import_module(modname)
        # get the Command object from that module
        cmd_object = getattr(mod, cmd_object_name)
        # check the result to make debugging easier
        if not isinstance(cmd_object, click.BaseCommand):
            raise ValueError(
                f"Lazy loading of {import_path} failed by returning "
                "a non-command object"
            )
        return cmd_object


def ping_service(url: str, service_name: str, headers: typing.Dict[str, any] = dict(), debug: bool = False) -> bool:
    """
    Ping a service to check its availability.

    Sends a GET request to a specified URL to verify if a service is reachable and responds correctly. 
    Outputs a success or error message based on the response status, and optionally displays response details in debug mode.

    Args:
        url (str): The URL of the service to ping.
        service_name (str): The name of the service being checked.
        headers: (dict, optional): dictionary of HTTP Headers.
        debug (bool, optional): If True, outputs the JSON response of the service. Defaults to False.

    Returns:
        bool: True if the service is reachable and responds with a successful status code, False otherwise.

    Raises:
        Exception: If the service response is not successful (i.e., non-OK HTTP status).
    """
    try:
        ping = requests.get(url, headers=headers)
        if not ping.ok:
            raise Exception(f"ERROR: {service_name} (@ {url}). Reason: {ping.reason}")
        if debug:
            click.echo(click.style(ping.headers, fg="blue"))
            click.echo(click.style(ping.json(), fg="blue"))
        click.echo(click.style(f"{service_name} connection OK!", fg="green"))
    except Exception as e:
        click.echo(click.style(f"ERROR: {service_name} (@ {url}) is down. {e}", fg="red"), err=True)
        click.echo(click.style(ping.headers, fg="blue")) if debug else None
        click.echo("Try again...")
        return False
    return True


def check_port(port: int) -> bool:
    """
    Check if a given port on localhost is available for use.

    This function attempts to bind to the specified port on the local machine to determine its availability.
    If the port is already in use or an error occurs during the check, it logs an appropriate error message.

    Args:
        port (int): The port number to check.

    Returns:
        bool: `True` if the port is available, `False` otherwise.

    Raises:
        socket.error: Captures errors during socket binding.
    """
    is_available = True
    s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
    try:
        s.bind(("127.0.0.1", port))
    except socket.error as e:
        if e.errno == errno.EADDRINUSE:
            click.echo(click.style(f"ERROR: Port {port} is already in use", fg="red"), err=True)
        else:
            click.echo(click.style(f"ERROR: An error ocurred when checking port ({port}) availability: {e}", fg="red"), err=True)
        is_available = False
    s.close()
    return is_available


def check_docker(debug: bool = False) -> bool:
    """
    Verify that Docker is installed and its daemon is running.

    This function performs a check to confirm that Docker is installed and that the Docker daemon is actively running. 
    If Docker is not detected or the daemon is not running, it prompts the user to try again or exit. 
    Optional debug output shows detailed subprocess output for troubleshooting.

    Args:
        debug (bool, optional): If True, displays detailed output from subprocess commands. Defaults to False.

    Returns:
        bool: True if Docker is installed and the daemon is running, False if the check fails and the user opts not to retry.

    Raises:
        SystemExit: Exits the function if Docker is not found or the daemon is not running, and the user chooses not to retry.
    """
    while True:
        docker_installed = True
        docker_running = True
        click.echo(click.style(f"Checking Docker settings...", fg="yellow"))
        # Check Docker is installed
        out = subprocess.run(["which", "docker"], capture_output=True)
        click.echo(click.style(out, fg="blue"), err=True) if debug else None
        if len(out.stdout) == 0 or len(out.stderr) > 0:
            click.echo(click.style(f"ERROR: Docker not found. Please install it before proceeding", fg="red"), err=True)
            docker_installed = False

        
        if docker_installed:
            # Check Docker daemon is running
            out = subprocess.run(["docker", "info"], capture_output=True)
            click.echo(click.style(out, fg="blue"), err=True) if debug else None
            if out.stderr.find(b"Is the docker daemon running?") > 0:
                click.echo(click.style(f"ERROR: Docker daemon is not running. Please start Docker before proceeding", fg="red"), err=True)
                docker_running = False

        if docker_running:
            break

        if not docker_installed or not docker_running:
            try_again = click.confirm(
                f"Do you want to try again?",
                default=True,
                show_default=True
            )
            if not try_again:
                return False

    click.echo(click.style(f"Docker requirements OK!", fg="green"))
    return True


def start_docker_service(service_id: str, service_name: str, debug: bool = False):
    """
    Start a Docker service using Docker Compose.

    This function attempts to start a specified Docker service in detached mode (`-d`) using Docker Compose. 
    If debug mode is enabled, it displays detailed output from the subprocess command, providing diagnostic information.

    Args:
        service_id (str): The ID of the service to start, as defined in the Docker Compose configuration.
        service_name (str): A human-readable name for the service to be started (used for user-friendly messages).
        debug (bool, optional): If True, displays detailed output from the Docker Compose command for debugging purposes. Defaults to False.

    Returns:
        None

    Side Effects:
        Outputs messages to the console to indicate the status of the service start operation.
    """
    click.echo(click.style(f"Starting a {service_name} instance using Docker....", fg="yellow"))
    out = subprocess.run(["docker", "compose", "up", service_id, "-d"], capture_output=True)
    click.echo(click.style(out, fg="blue"), err=True) if debug else None
    click.echo(f"{out.stdout.decode() if len(out.stdout) > 0 else ''}\n{out.stderr.decode()}")
    # click.echo(click.style(f"{service_name} instance running OK!", fg="green"))


@click.group(
    cls=LazyGroup,
    lazy_subcommands={"run": "run.cli"}
)
def cli():
    """
    Command-line interface (CLI) for the RAG API pipeline.
    """
    pass


@cli.command(help="Setup wizard to config the pipeline settings prior execution")
@click.option("--debug", is_flag=True, help="enable logging debug level")
@click.option(
    "--llm-provider",
    type=click.Choice(["gaia", "other"], case_sensitive=False),
    default="gaia",
    help="LLM provider",
    prompt="Which LLM provider you want to use?",
    show_choices=True,
    show_default=True
)
def setup(
    debug: bool,
    llm_provider: str    
):
    step = 1 # Wizard step counter
    total_steps = 3 # Total Wizard steps
    click.echo(click.style(f"Init pipeline...", fg="yellow"))

    env_file = pathlib.Path(ENV_FILE_PATH)
    init_setup = True
    if env_file.exists():
        click.echo(f"A .env file already exists in {ENV_FILE_PATH}")
        init_setup = click.confirm(
            f"Do you want to init the pipeline configuration from scratch?",
            default=False,
            show_default=True
        )
        if init_setup:
            env_file.unlink()

    if init_setup:
        env_vars = dict()

        # ------------------------------------------------------------------------------------------------------

        click.echo(click.style(f"(Step {step}/{total_steps}) Setting Pipeline LLM provider settings...", fg="yellow"))

        # Set LLM_PROVIDER
        llm_provider_chosen = llm_provider
        if llm_provider != "gaia":
            available_llm_providers = ["openai", "ollama"]
            llm_provider = click.prompt(f"Select a custom LLM provider", type=click.Choice(available_llm_providers, case_sensitive=True), show_choices=True)
        else:
            llm_provider = "openai" # gaia uses an openai-like API server

        click.echo(f"LLM_PROVIDER={llm_provider}") if debug else None
        env_vars["LLM_PROVIDER"] = llm_provider

        # Set LLM_API_BASE_URL
        llm_api_base_url_default = "http://127.0.0.1:11434" if llm_provider == "ollama" else "http://127.0.0.1:8080/v1"
        llm_api_server_url = llm_api_base_url_default
        llm_api_key = 'empty-api-key'
        llm_api_key_set = False
        while True:
            llm_api_server_url = click.prompt(
                "LLM provider API URL",
                type=click.STRING,
                default=llm_api_base_url_default,
                show_default=True
            )

            # Set LLM_API_KEY
            if not llm_api_key_set and llm_provider_chosen == "other" and llm_provider == "openai":
                llm_api_key = click.prompt("LLM provider API Key", type=click.STRING, hide_input=True)
                llm_api_key_set = True
                click.echo(f"LLM_API_KEY value updated") if debug else None
                env_vars["LLM_API_KEY"] = llm_api_key
            
            service_url = llm_api_server_url if re.search("(v1)|(v1/)$", llm_api_server_url) else f"{llm_api_server_url}/v1"
            service_url += "/models"
            headers = {
                "Authorization": f"Bearer {llm_api_key}"
            }
            if ping_service(service_url, "LLM Provider API", headers=headers, debug=debug):
                break
        click.echo(f"LLM_API_BASE_URL={llm_api_server_url}") if debug else None
        env_vars["LLM_API_BASE_URL"] = llm_api_server_url
        
        # Set LLM_EMBEDDINGS_*
        llm_embeddings_model = click.prompt("Embeddings model Name", type=click.STRING, default="Nomic-embed-text-v1.5", show_default=True)
        click.echo(f"LLM_EMBEDDINGS_MODEL={llm_embeddings_model}") if debug else None
        env_vars["LLM_EMBEDDINGS_MODEL"] = llm_embeddings_model
        llm_embeddings_vector_size = click.prompt("Embeddings Vector Size", type=click.IntRange(min=0, min_open=True), default=768, show_default=True)
        click.echo(f"LLM_EMBEDDINGS_VECTOR_SIZE={llm_embeddings_vector_size}") if debug else None
        env_vars["LLM_EMBEDDINGS_VECTOR_SIZE"] = int(llm_embeddings_vector_size)
        if llm_provider == "ollama":
            # check Ollama is installed
            out = subprocess.run(["which", "ollama"], capture_output=True)
            if len(out.stdout) == 0 or len(out.stderr) > 0:
                click.echo(click.style(out, fg="red"), err=True) if debug else None
                click.echo(click.style(f"ERROR: Ollama not found. Please install it before proceeding", fg="red"), err=True)
                return
            # check ollama is running
            out = subprocess.run(["ollama", "-v"], capture_output=True)
            click.echo(click.style(out, fg="blue"), err=True) if debug else None
            if out.stdout.find(b"could not connect to a running Ollama instance") > 0:
                click.echo(click.style(f"ERROR: Ollama is not running. Please start Ollama before proceeding", fg="red"), err=True)
                return
            # check if model name is loaded into ollama
            model_info = subprocess.run(["ollama", "show", llm_embeddings_model], capture_output=True)
            click.echo(click.style(model_info, fg="blue"), err=True) if debug else None
            if model_info.stderr.find(b"not found") > 0:
                # request model file and load model
                embeddings_model_file = click.prompt("Enter the Absolute Path to the Embeddings model file", type=click.Path(exists=True, dir_okay=False))
                # create Modelfile
                with open("./models/Modelfile", "w") as f:
                    f.write(f"FROM {embeddings_model_file}")
                    f.close()
                # import embeddings model into Ollama
                click.echo(click.style(f"Importing embeddings model into Ollama...", fg="yellow"))
                out = subprocess.run(["ollama", "create", llm_embeddings_model, "-f", "./models/Modelfile"], capture_output=True)
                click.echo(click.style(out, fg="blue"), err=True) if debug else None
                if out.stderr.find(b"success") == -1:
                    click.echo(click.style(f"ERROR: Something went wrong. Check Ollama logs", fg="red"), err=True)
                    return
            else:
                click.echo(f"{llm_embeddings_model} model is already loaded into Ollama")

        click.echo(click.style(f"Pipeline LLM Provider settings OK!", fg="green"))

        step += 1

        # ------------------------------------------------------------------------------------------------------

        click.echo(click.style(f"(Step {step}/{total_steps}) Setting API Source settings...", fg="yellow"))

        api_key_file = "config/secrets/api_key"
        api_key = click.prompt("REST API Key", type=click.STRING, hide_input=True)
        click.echo(f"API Key value set") if debug else None
        with open(api_key_file, mode="w") as f:
            f.write(api_key)
            f.close()

        click.echo(click.style(f"API Key stored in {api_key_file}", fg="green"))

        step += 1

        # ------------------------------------------------------------------------------------------------------

        click.echo(click.style(f"(Step {step}/{total_steps}) Setting Vector DB settings...", fg="yellow"))

        while True:
            external_qdrant = click.confirm(
                f"Do you have a running QdrantDB instance?",
                default=False,
                show_default=True
            )
            if not external_qdrant:
                # TODO: check port is not in use
                port_available = check_port(6333)
                if not port_available:
                    click.echo(click.style(f"Cannot deploy a QdrantDB instance", fg="red"), err=True)
                    continue
            break

        qdrantdb_url = "http://127.0.0.1:6333"
        if external_qdrant:
            while True:
                qdrantdb_url = click.prompt(
                    "Enter your Qdrant Server URL",
                    type=click.STRING,
                    default="http://127.0.0.1:6333",
                    show_default=True
                )
                if ping_service(qdrantdb_url, "QdrantDB", debug=debug):
                    break
        else:
            docker_running = check_docker(debug)
            if not docker_running:
                return
            out = subprocess.run(["docker", "compose", "-f", "ps"], capture_output=True)
            click.echo(click.style(out, fg="blue"), err=True) if debug else None
            if out.stdout.find(b"qdrant/qdrant:v1.10.0") == -1:
                start_docker_service("qdrant", "QdrantDB", debug)
                # TODO: ping service loop to check is qdrant is up
            else:
                click.echo(click.style(f"A QdrantDB Doker container is already running", fg="yellow"))

        click.echo(f"QDRANTDB_URL={qdrantdb_url}") if debug else None
        env_vars["QDRANTDB_URL"] = qdrantdb_url

        step += 1

        # ------------------------------------------------------------------------------------------------------

        # Set .env file
        click.echo(click.style(f"Saving Pipeline settings in {ENV_FILE_PATH}...", fg="yellow"))
        shutil.copyfile(f"{ENV_FILE_PATH}.sample", ENV_FILE_PATH)

        for key, val in env_vars.items():
            dotenv.set_key(ENV_FILE_PATH, key_to_set=key, value_to_set=val, quote_mode="always" if type(val) == str else "never")

        # ------------------------------------------------------------------------------------------------------

        click.echo(click.style(f"Pipeline Setup completed!", fg="green"))
        click.echo(
            f"""
            You can use the pipeline by running either {click.style("rag-api-pipeline run --help", fg="yellow")}
            or {click.style("docker compose run pipeline --help", fg="yellow")}
            """
        )


def entrypoint():
    """Entry point for the CLI application. Initializes and invokes the CLI interface."""
    cli(obj={})


if __name__ == "__main__":
    entrypoint()