mirror of
https://github.com/huggingface/text-generation-inference.git
synced 2025-04-21 23:12:07 +00:00
See #1049 --------- Signed-off-by: Wang, Yi A <yi.a.wang@intel.com> Co-authored-by: Wang, Yi <yi.a.wang@intel.com>
399 lines
15 KiB
Rust
399 lines
15 KiB
Rust
/// Text Generation Inference webserver entrypoint
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use axum::http::HeaderValue;
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use clap::Parser;
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use opentelemetry::sdk::propagation::TraceContextPropagator;
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use opentelemetry::sdk::trace;
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use opentelemetry::sdk::trace::Sampler;
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use opentelemetry::sdk::Resource;
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use opentelemetry::{global, KeyValue};
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use opentelemetry_otlp::WithExportConfig;
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use std::net::{IpAddr, Ipv4Addr, SocketAddr};
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use std::path::Path;
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use std::time::Duration;
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use text_generation_client::{ClientError, ShardedClient};
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use text_generation_router::{server, HubModelInfo};
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use thiserror::Error;
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use tokenizers::{FromPretrainedParameters, Tokenizer};
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use tower_http::cors::AllowOrigin;
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use tracing_subscriber::layer::SubscriberExt;
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use tracing_subscriber::util::SubscriberInitExt;
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use tracing_subscriber::{EnvFilter, Layer};
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/// App Configuration
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#[derive(Parser, Debug)]
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#[clap(author, version, about, long_about = None)]
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struct Args {
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#[clap(default_value = "128", long, env)]
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max_concurrent_requests: usize,
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#[clap(default_value = "2", long, env)]
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max_best_of: usize,
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#[clap(default_value = "4", long, env)]
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max_stop_sequences: usize,
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#[clap(default_value = "5", long, env)]
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max_top_n_tokens: u32,
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#[clap(default_value = "1024", long, env)]
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max_input_length: usize,
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#[clap(default_value = "2048", long, env)]
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max_total_tokens: usize,
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#[clap(default_value = "1.2", long, env)]
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waiting_served_ratio: f32,
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#[clap(default_value = "4096", long, env)]
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max_batch_prefill_tokens: u32,
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#[clap(long, env)]
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max_batch_total_tokens: Option<u32>,
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#[clap(default_value = "20", long, env)]
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max_waiting_tokens: usize,
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#[clap(default_value = "0.0.0.0", long, env)]
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hostname: String,
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#[clap(default_value = "3000", long, short, env)]
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port: u16,
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#[clap(default_value = "/tmp/text-generation-server-0", long, env)]
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master_shard_uds_path: String,
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#[clap(default_value = "bigscience/bloom", long, env)]
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tokenizer_name: String,
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#[clap(long, env)]
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revision: Option<String>,
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#[clap(default_value = "2", long, env)]
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validation_workers: usize,
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#[clap(long, env)]
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json_output: bool,
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#[clap(long, env)]
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otlp_endpoint: Option<String>,
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#[clap(long, env)]
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cors_allow_origin: Option<Vec<String>>,
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#[clap(long, env)]
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ngrok: bool,
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#[clap(long, env)]
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ngrok_authtoken: Option<String>,
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#[clap(long, env)]
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ngrok_edge: Option<String>,
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}
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fn main() -> Result<(), RouterError> {
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// Get args
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let args = Args::parse();
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// Pattern match configuration
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let Args {
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max_concurrent_requests,
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max_best_of,
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max_stop_sequences,
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max_top_n_tokens,
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max_input_length,
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max_total_tokens,
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waiting_served_ratio,
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max_batch_prefill_tokens,
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max_batch_total_tokens,
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max_waiting_tokens,
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hostname,
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port,
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master_shard_uds_path,
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tokenizer_name,
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revision,
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validation_workers,
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json_output,
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otlp_endpoint,
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cors_allow_origin,
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ngrok,
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ngrok_authtoken,
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ngrok_edge,
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} = args;
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// Validate args
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if max_input_length >= max_total_tokens {
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return Err(RouterError::ArgumentValidation(
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"`max_input_length` must be < `max_total_tokens`".to_string(),
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));
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}
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if max_input_length as u32 > max_batch_prefill_tokens {
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return Err(RouterError::ArgumentValidation(format!("`max_batch_prefill_tokens` must be >= `max_input_length`. Given: {max_batch_prefill_tokens} and {max_input_length}")));
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}
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if validation_workers == 0 {
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return Err(RouterError::ArgumentValidation(
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"`validation_workers` must be > 0".to_string(),
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));
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}
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if let Some(ref max_batch_total_tokens) = max_batch_total_tokens {
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if max_batch_prefill_tokens > *max_batch_total_tokens {
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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}")));
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}
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if max_total_tokens as u32 > *max_batch_total_tokens {
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return Err(RouterError::ArgumentValidation(format!("`max_total_tokens` must be <= `max_batch_total_tokens`. Given: {max_total_tokens} and {max_batch_total_tokens}")));
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}
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}
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// CORS allowed origins
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// map to go inside the option and then map to parse from String to HeaderValue
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// Finally, convert to AllowOrigin
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let cors_allow_origin: Option<AllowOrigin> = cors_allow_origin.map(|cors_allow_origin| {
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AllowOrigin::list(
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cors_allow_origin
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.iter()
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.map(|origin| origin.parse::<HeaderValue>().unwrap()),
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)
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});
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// Parse Huggingface hub token
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let authorization_token = std::env::var("HUGGING_FACE_HUB_TOKEN").ok();
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// Tokenizer instance
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// This will only be used to validate payloads
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let local_path = Path::new(&tokenizer_name);
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let local_model = local_path.exists() && local_path.is_dir();
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let tokenizer = if local_model {
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// Load local tokenizer
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Tokenizer::from_file(local_path.join("tokenizer.json")).ok()
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} else {
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// Download and instantiate tokenizer
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// We need to download it outside of the Tokio runtime
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let params = FromPretrainedParameters {
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revision: revision.clone().unwrap_or("main".to_string()),
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auth_token: authorization_token.clone(),
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..Default::default()
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};
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Tokenizer::from_pretrained(tokenizer_name.clone(), Some(params)).ok()
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};
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// Launch Tokio runtime
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tokio::runtime::Builder::new_multi_thread()
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.enable_all()
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.build()?
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.block_on(async {
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init_logging(otlp_endpoint, json_output);
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if tokenizer.is_none() {
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tracing::warn!(
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"Could not find a fast tokenizer implementation for {tokenizer_name}"
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);
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tracing::warn!("Rust input length validation and truncation is disabled");
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}
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// Get Model info
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let model_info = match local_model {
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true => HubModelInfo {
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model_id: tokenizer_name.clone(),
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sha: None,
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pipeline_tag: None,
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},
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false => get_model_info(&tokenizer_name, revision, authorization_token)
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.await
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.unwrap_or_else(|| {
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tracing::warn!("Could not retrieve model info from the Hugging Face hub.");
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HubModelInfo {
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model_id: tokenizer_name.to_string(),
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sha: None,
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pipeline_tag: None,
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}
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}),
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};
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// if pipeline-tag == text-generation we default to return_full_text = true
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let compat_return_full_text = match &model_info.pipeline_tag {
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None => {
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tracing::warn!("no pipeline tag found for model {tokenizer_name}");
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false
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}
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Some(pipeline_tag) => pipeline_tag.as_str() == "text-generation",
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};
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// Instantiate sharded client from the master unix socket
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let mut sharded_client = ShardedClient::connect_uds(master_shard_uds_path)
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.await
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.map_err(RouterError::Connection)?;
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// Clear the cache; useful if the webserver rebooted
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sharded_client
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.clear_cache(None)
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.await
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.map_err(RouterError::Cache)?;
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// Get info from the shard
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let shard_info = sharded_client.info().await.map_err(RouterError::Info)?;
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// Warmup model
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tracing::info!("Warming up model");
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let max_supported_batch_total_tokens = match sharded_client
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.warmup(max_input_length as u32, max_batch_prefill_tokens, max_total_tokens as u32)
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.await
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.map_err(RouterError::Warmup)?
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{
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// Older models do not support automatic max-batch-total-tokens
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None => {
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let max_batch_total_tokens = max_batch_total_tokens.unwrap_or(
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16000.max((max_total_tokens as u32).max(max_batch_prefill_tokens)),
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);
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tracing::warn!("Model does not support automatic max batch total tokens");
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max_batch_total_tokens
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}
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// Flash attention models return their max supported total tokens
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Some(max_supported_batch_total_tokens) => {
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// Warn if user added his own max-batch-total-tokens as we will ignore it
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if max_batch_total_tokens.is_some() {
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tracing::warn!(
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"`--max-batch-total-tokens` is deprecated for Flash \
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Attention models."
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);
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tracing::warn!(
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"Inferred max batch total tokens: {max_supported_batch_total_tokens}"
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);
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}
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if max_total_tokens as u32 > max_supported_batch_total_tokens {
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return Err(RouterError::ArgumentValidation(format!("`max_total_tokens` must be <= `max_batch_total_tokens`. Given: {max_total_tokens} and {max_supported_batch_total_tokens}")));
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}
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max_supported_batch_total_tokens
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}
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};
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tracing::info!("Setting max batch total tokens to {max_supported_batch_total_tokens}");
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tracing::info!("Connected");
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let addr = match hostname.parse() {
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Ok(ip) => SocketAddr::new(ip, port),
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Err(_) => {
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tracing::warn!("Invalid hostname, defaulting to 0.0.0.0");
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SocketAddr::new(IpAddr::V4(Ipv4Addr::new(0, 0, 0, 0)), port)
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}
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};
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// Run server
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server::run(
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model_info,
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shard_info,
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compat_return_full_text,
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max_concurrent_requests,
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max_best_of,
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max_stop_sequences,
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max_top_n_tokens,
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max_input_length,
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max_total_tokens,
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waiting_served_ratio,
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max_batch_prefill_tokens,
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max_supported_batch_total_tokens,
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max_waiting_tokens,
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sharded_client,
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tokenizer,
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validation_workers,
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addr,
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cors_allow_origin,
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ngrok,
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ngrok_authtoken,
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ngrok_edge,
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)
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.await?;
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Ok(())
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})
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}
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/// Init logging using env variables LOG_LEVEL and LOG_FORMAT:
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/// - otlp_endpoint is an optional URL to an Open Telemetry collector
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/// - LOG_LEVEL may be TRACE, DEBUG, INFO, WARN or ERROR (default to INFO)
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/// - LOG_FORMAT may be TEXT or JSON (default to TEXT)
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fn init_logging(otlp_endpoint: Option<String>, json_output: bool) {
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let mut layers = Vec::new();
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// STDOUT/STDERR layer
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let fmt_layer = tracing_subscriber::fmt::layer()
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.with_file(true)
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.with_line_number(true);
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let fmt_layer = match json_output {
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true => fmt_layer.json().flatten_event(true).boxed(),
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false => fmt_layer.boxed(),
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};
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layers.push(fmt_layer);
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// OpenTelemetry tracing layer
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if let Some(otlp_endpoint) = otlp_endpoint {
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global::set_text_map_propagator(TraceContextPropagator::new());
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let tracer = opentelemetry_otlp::new_pipeline()
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.tracing()
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.with_exporter(
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opentelemetry_otlp::new_exporter()
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.tonic()
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.with_endpoint(otlp_endpoint),
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)
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.with_trace_config(
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trace::config()
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.with_resource(Resource::new(vec![KeyValue::new(
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"service.name",
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"text-generation-inference.router",
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)]))
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.with_sampler(Sampler::AlwaysOn),
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)
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.install_batch(opentelemetry::runtime::Tokio);
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if let Ok(tracer) = tracer {
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layers.push(tracing_opentelemetry::layer().with_tracer(tracer).boxed());
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init_tracing_opentelemetry::init_propagator().unwrap();
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};
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}
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// Filter events with LOG_LEVEL
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let env_filter =
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EnvFilter::try_from_env("LOG_LEVEL").unwrap_or_else(|_| EnvFilter::new("info"));
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tracing_subscriber::registry()
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.with(env_filter)
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.with(layers)
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.init();
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}
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/// get model info from the Huggingface Hub
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pub async fn get_model_info(
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model_id: &str,
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revision: Option<String>,
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token: Option<String>,
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) -> Option<HubModelInfo> {
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let revision = match revision {
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None => {
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tracing::warn!("`--revision` is not set");
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tracing::warn!("We strongly advise to set it to a known supported commit.");
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"main".to_string()
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}
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Some(revision) => revision,
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};
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let client = reqwest::Client::new();
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// Poor man's urlencode
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let revision = revision.replace('/', "%2F");
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let url = format!("https://huggingface.co/api/models/{model_id}/revision/{revision}");
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let mut builder = client.get(url).timeout(Duration::from_secs(5));
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if let Some(token) = token {
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builder = builder.bearer_auth(token);
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}
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let response = builder.send().await.ok()?;
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if response.status().is_success() {
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let hub_model_info: HubModelInfo =
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serde_json::from_str(&response.text().await.ok()?).ok()?;
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if let Some(sha) = &hub_model_info.sha {
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tracing::info!(
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"Serving revision {sha} of model {}",
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hub_model_info.model_id
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);
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}
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Some(hub_model_info)
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} else {
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None
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}
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}
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#[derive(Debug, Error)]
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enum RouterError {
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#[error("Argument validation error: {0}")]
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ArgumentValidation(String),
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#[error("Unable to connect to the Python model shards: {0}")]
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Connection(ClientError),
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#[error("Unable to clear the Python model shards cache: {0}")]
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Cache(ClientError),
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#[error("Unable to get the Python model shards info: {0}")]
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Info(ClientError),
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#[error("Unable to warmup the Python model shards: {0}")]
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Warmup(ClientError),
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#[error("Tokio runtime failed to start: {0}")]
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Tokio(#[from] std::io::Error),
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#[error("Axum webserver failed: {0}")]
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Axum(#[from] axum::BoxError),
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}
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