main.rs

use axum::http::HeaderValue;
use clap::Parser;
use hf_hub::api::tokio::{Api, ApiBuilder, ApiRepo};
use hf_hub::{Repo, RepoType};
use opentelemetry::sdk::propagation::TraceContextPropagator;
use opentelemetry::sdk::trace;
use opentelemetry::sdk::trace::Sampler;
use opentelemetry::sdk::Resource;
use opentelemetry::{global, KeyValue};
use opentelemetry_otlp::WithExportConfig;
/// Text Generation Inference webserver entrypoint
use std::fs::File;
use std::io::BufReader;
use std::net::{IpAddr, Ipv4Addr, SocketAddr};
use std::path::Path;
use text_generation_client::{ClientError, ShardedClient};
use text_generation_router::{server, HubModelInfo};
use thiserror::Error;
use tokenizers::Tokenizer;
use tower_http::cors::AllowOrigin;
use tracing_subscriber::layer::SubscriberExt;
use tracing_subscriber::util::SubscriberInitExt;
use tracing_subscriber::{EnvFilter, Layer};

/// App Configuration
#[derive(Parser, Debug)]
#[clap(author, version, about, long_about = None)]
struct Args {
    #[clap(default_value = "128", long, env)]
    max_concurrent_requests: usize,
    #[clap(default_value = "2", long, env)]
    max_best_of: usize,
    #[clap(default_value = "4", long, env)]
    max_stop_sequences: usize,
    #[clap(default_value = "5", long, env)]
    max_top_n_tokens: u32,
    #[clap(default_value = "1024", long, env)]
    max_input_length: usize,
    #[clap(default_value = "2048", long, env)]
    max_total_tokens: usize,
    #[clap(default_value = "1.2", long, env)]
    waiting_served_ratio: f32,
    #[clap(default_value = "4096", long, env)]
    max_batch_prefill_tokens: u32,
    #[clap(long, env)]
    max_batch_total_tokens: Option<u32>,
    #[clap(default_value = "20", long, env)]
    max_waiting_tokens: usize,
    #[clap(default_value = "0.0.0.0", long, env)]
    hostname: String,
    #[clap(default_value = "3000", long, short, env)]
    port: u16,
    #[clap(default_value = "/tmp/text-generation-server-0", long, env)]
    master_shard_uds_path: String,
    #[clap(default_value = "bigscience/bloom", long, env)]
    tokenizer_name: String,
    #[clap(long, env)]
    revision: Option<String>,
    #[clap(default_value = "2", long, env)]
    validation_workers: usize,
    #[clap(long, env)]
    json_output: bool,
    #[clap(long, env)]
    otlp_endpoint: Option<String>,
    #[clap(long, env)]
    cors_allow_origin: Option<Vec<String>>,
    #[clap(long, env)]
    ngrok: bool,
    #[clap(long, env)]
    ngrok_authtoken: Option<String>,
    #[clap(long, env)]
    ngrok_edge: Option<String>,
}

#[tokio::main]
async fn main() -> Result<(), RouterError> {
    // Get args
    let args = Args::parse();
    // Pattern match configuration
    let Args {
        max_concurrent_requests,
        max_best_of,
        max_stop_sequences,
        max_top_n_tokens,
        max_input_length,
        max_total_tokens,
        waiting_served_ratio,
        max_batch_prefill_tokens,
        max_batch_total_tokens,
        max_waiting_tokens,
        hostname,
        port,
        master_shard_uds_path,
        tokenizer_name,
        revision,
        validation_workers,
        json_output,
        otlp_endpoint,
        cors_allow_origin,
        ngrok,
        ngrok_authtoken,
        ngrok_edge,
    } = args;

    // Launch Tokio runtime
    init_logging(otlp_endpoint, json_output);

    // Validate args
    if max_input_length >= max_total_tokens {
        return Err(RouterError::ArgumentValidation(
            "`max_input_length` must be < `max_total_tokens`".to_string(),
        ));
    }
    if max_input_length as u32 > max_batch_prefill_tokens {
        return Err(RouterError::ArgumentValidation(format!("`max_batch_prefill_tokens` must be >= `max_input_length`. Given: {max_batch_prefill_tokens} and {max_input_length}")));
    }

    if validation_workers == 0 {
        return Err(RouterError::ArgumentValidation(
            "`validation_workers` must be > 0".to_string(),
        ));
    }

    if let Some(ref max_batch_total_tokens) = max_batch_total_tokens {
        if max_batch_prefill_tokens > *max_batch_total_tokens {
            return Err(RouterError::ArgumentValidation(format!("`max_batch_prefill_tokens` must be <= `max_batch_total_tokens`. Given: {max_batch_prefill_tokens} and {max_batch_total_tokens}")));
        }
        if max_total_tokens as u32 > *max_batch_total_tokens {
            return Err(RouterError::ArgumentValidation(format!("`max_total_tokens` must be <= `max_batch_total_tokens`. Given: {max_total_tokens} and {max_batch_total_tokens}")));
        }
    }

    // CORS allowed origins
    // map to go inside the option and then map to parse from String to HeaderValue
    // Finally, convert to AllowOrigin
    let cors_allow_origin: Option<AllowOrigin> = cors_allow_origin.map(|cors_allow_origin| {
        AllowOrigin::list(
            cors_allow_origin
                .iter()
                .map(|origin| origin.parse::<HeaderValue>().unwrap()),
        )
    });

    // Parse Huggingface hub token
    let authorization_token = std::env::var("HUGGING_FACE_HUB_TOKEN").ok();

    // Tokenizer instance
    // This will only be used to validate payloads
    let local_path = Path::new(&tokenizer_name);
    let local_model = local_path.exists() && local_path.is_dir();

    let (tokenizer, model_info) = if local_model {
        // Get Model info
        let model_info = HubModelInfo {
            model_id: tokenizer_name.clone(),
            sha: None,
            pipeline_tag: None,
        };

        // Load local tokenizer
        let tokenizer = Tokenizer::from_file(local_path.join("tokenizer.json")).ok();

        (tokenizer, model_info)
    } else {
        let mut builder = ApiBuilder::new()
            .with_progress(false)
            .with_token(authorization_token);

        if let Some(cache_dir) = std::env::var("HUGGINGFACE_HUB_CACHE").ok() {
            builder = builder.with_cache_dir(cache_dir.into());
        }

        if revision.is_none() {
            tracing::warn!("`--revision` is not set");
            tracing::warn!("We strongly advise to set it to a known supported commit.");
        }

        let api = builder.build().unwrap();
        let api_repo = api.repo(Repo::with_revision(
            tokenizer_name.clone(),
            RepoType::Model,
            revision.clone().unwrap_or("main".to_string()),
        ));

        // Get Model info
        let model_info = get_model_info(&api_repo).await.unwrap_or_else(|| {
            tracing::warn!("Could not retrieve model info from the Hugging Face hub.");
            HubModelInfo {
                model_id: tokenizer_name.to_string(),
                sha: None,
                pipeline_tag: None,
            }
        });

        let tokenizer = match api_repo.get("tokenizer.json").await {
            Ok(tokenizer_filename) => Tokenizer::from_file(tokenizer_filename).ok(),
            Err(_) => get_base_tokenizer(&api, &api_repo).await,
        };

        (tokenizer, model_info)
    };

    if tokenizer.is_none() {
        tracing::warn!("Could not find a fast tokenizer implementation for {tokenizer_name}");
        tracing::warn!("Rust input length validation and truncation is disabled");
    }

    // if pipeline-tag == text-generation we default to return_full_text = true
    let compat_return_full_text = match &model_info.pipeline_tag {
        None => {
            tracing::warn!("no pipeline tag found for model {tokenizer_name}");
            false
        }
        Some(pipeline_tag) => pipeline_tag.as_str() == "text-generation",
    };

    // Instantiate sharded client from the master unix socket
    let mut sharded_client = ShardedClient::connect_uds(master_shard_uds_path)
        .await
        .map_err(RouterError::Connection)?;
    // Clear the cache; useful if the webserver rebooted
    sharded_client
        .clear_cache(None)
        .await
        .map_err(RouterError::Cache)?;
    // Get info from the shard
    let shard_info = sharded_client.info().await.map_err(RouterError::Info)?;

    // Warmup model
    tracing::info!("Warming up model");
    let max_supported_batch_total_tokens = match sharded_client
        .warmup(
            max_input_length as u32,
            max_batch_prefill_tokens,
            max_total_tokens as u32,
        )
        .await
        .map_err(RouterError::Warmup)?
    {
        // Older models do not support automatic max-batch-total-tokens
        None => {
            let max_batch_total_tokens = max_batch_total_tokens
                .unwrap_or(16000.max((max_total_tokens as u32).max(max_batch_prefill_tokens)));
            tracing::warn!("Model does not support automatic max batch total tokens");
            max_batch_total_tokens
        }
        // Flash attention models return their max supported total tokens
        Some(max_supported_batch_total_tokens) => {
            // Warn if user added his own max-batch-total-tokens as we will ignore it
            if max_batch_total_tokens.is_some() {
                tracing::warn!(
                    "`--max-batch-total-tokens` is deprecated for Flash \
                        Attention models."
                );
                tracing::warn!(
                    "Inferred max batch total tokens: {max_supported_batch_total_tokens}"
                );
            }
            if max_total_tokens as u32 > max_supported_batch_total_tokens {
                return Err(RouterError::ArgumentValidation(format!("`max_total_tokens` must be <= `max_batch_total_tokens`. Given: {max_total_tokens} and {max_supported_batch_total_tokens}")));
            }

            max_supported_batch_total_tokens
        }
    };
    tracing::info!("Setting max batch total tokens to {max_supported_batch_total_tokens}");
    tracing::info!("Connected");

    let addr = match hostname.parse() {
        Ok(ip) => SocketAddr::new(ip, port),
        Err(_) => {
            tracing::warn!("Invalid hostname, defaulting to 0.0.0.0");
            SocketAddr::new(IpAddr::V4(Ipv4Addr::new(0, 0, 0, 0)), port)
        }
    };

    // Run server
    server::run(
        model_info,
        shard_info,
        compat_return_full_text,
        max_concurrent_requests,
        max_best_of,
        max_stop_sequences,
        max_top_n_tokens,
        max_input_length,
        max_total_tokens,
        waiting_served_ratio,
        max_batch_prefill_tokens,
        max_supported_batch_total_tokens,
        max_waiting_tokens,
        sharded_client,
        tokenizer,
        validation_workers,
        addr,
        cors_allow_origin,
        ngrok,
        ngrok_authtoken,
        ngrok_edge,
    )
    .await?;
    Ok(())
}

/// Init logging using env variables LOG_LEVEL and LOG_FORMAT:
///     - otlp_endpoint is an optional URL to an Open Telemetry collector
///     - LOG_LEVEL may be TRACE, DEBUG, INFO, WARN or ERROR (default to INFO)
///     - LOG_FORMAT may be TEXT or JSON (default to TEXT)
fn init_logging(otlp_endpoint: Option<String>, json_output: bool) {
    let mut layers = Vec::new();

    // STDOUT/STDERR layer
    let fmt_layer = tracing_subscriber::fmt::layer()
        .with_file(true)
        .with_line_number(true);

    let fmt_layer = match json_output {
        true => fmt_layer.json().flatten_event(true).boxed(),
        false => fmt_layer.boxed(),
    };
    layers.push(fmt_layer);

    // OpenTelemetry tracing layer
    if let Some(otlp_endpoint) = otlp_endpoint {
        global::set_text_map_propagator(TraceContextPropagator::new());

        let tracer = opentelemetry_otlp::new_pipeline()
            .tracing()
            .with_exporter(
                opentelemetry_otlp::new_exporter()
                    .tonic()
                    .with_endpoint(otlp_endpoint),
            )
            .with_trace_config(
                trace::config()
                    .with_resource(Resource::new(vec![KeyValue::new(
                        "service.name",
                        "text-generation-inference.router",
                    )]))
                    .with_sampler(Sampler::AlwaysOn),
            )
            .install_batch(opentelemetry::runtime::Tokio);

        if let Ok(tracer) = tracer {
            layers.push(tracing_opentelemetry::layer().with_tracer(tracer).boxed());
            init_tracing_opentelemetry::init_propagator().unwrap();
        };
    }

    // Filter events with LOG_LEVEL
    let env_filter =
        EnvFilter::try_from_env("LOG_LEVEL").unwrap_or_else(|_| EnvFilter::new("info"));

    tracing_subscriber::registry()
        .with(env_filter)
        .with(layers)
        .init();
}

/// get model info from the Huggingface Hub
pub async fn get_model_info(api: &ApiRepo) -> Option<HubModelInfo> {
    let response = api.info_request().send().await.ok()?;

    if response.status().is_success() {
        let hub_model_info: HubModelInfo =
            serde_json::from_str(&response.text().await.ok()?).ok()?;
        if let Some(sha) = &hub_model_info.sha {
            tracing::info!(
                "Serving revision {sha} of model {}",
                hub_model_info.model_id
            );
        }
        Some(hub_model_info)
    } else {
        None
    }
}

/// get base tokenizer
pub async fn get_base_tokenizer(api: &Api, api_repo: &ApiRepo) -> Option<Tokenizer> {
    let config_filename = api_repo.get("config.json").await.ok()?;

    // Open the file in read-only mode with buffer.
    let file = File::open(config_filename).ok()?;
    let reader = BufReader::new(file);

    // Read the JSON contents of the file as an instance of `User`.
    let config: serde_json::Value = serde_json::from_reader(reader).ok()?;

    if let Some(serde_json::Value::String(base_model_id)) = config.get("base_model_name_or_path") {
        let api_base_repo = api.repo(Repo::with_revision(
            base_model_id.to_string(),
            RepoType::Model,
            "main".to_string(),
        ));

        let tokenizer_filename = api_base_repo.get("tokenizer.json").await.ok()?;
        Tokenizer::from_file(tokenizer_filename).ok()
    } else {
        None
    }
}

#[derive(Debug, Error)]
enum RouterError {
    #[error("Argument validation error: {0}")]
    ArgumentValidation(String),
    #[error("Unable to connect to the Python model shards: {0}")]
    Connection(ClientError),
    #[error("Unable to clear the Python model shards cache: {0}")]
    Cache(ClientError),
    #[error("Unable to get the Python model shards info: {0}")]
    Info(ClientError),
    #[error("Unable to warmup the Python model shards: {0}")]
    Warmup(ClientError),
    #[error("Tokio runtime failed to start: {0}")]
    Tokio(#[from] std::io::Error),
    #[error("Axum webserver failed: {0}")]
    Axum(#[from] axum::BoxError),
}