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feat: handle batch completions requests

This commit is contained in:
drbh 2024-04-10 04:07:03 +00:00
parent b08038cc81
commit 70e8d2aaa9
6 changed files with 344 additions and 135 deletions
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9
docs/source/basic_tutorials/launcher.md
View File

@ -393,6 +393,15 @@ Options:
-e, --env
Display a lot of information about your runtime environment
```
## MAX_CLIENT_BATCH_SIZE
```shell
--max-client-batch-size <MAX_CLIENT_BATCH_SIZE>
Control the maximum number of inputs that a client can send in a single request
[env: MAX_CLIENT_BATCH_SIZE=]
[default: 32]
```
## HELP
```shell

56
integration-tests/models/test_completion_prompts.py Normal file
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@ -0,0 +1,56 @@
import pytest
import requests
@pytest.fixture(scope="module")
def flash_llama_completion_handle(launcher):
with launcher(
"TinyLlama/TinyLlama-1.1B-Chat-v1.0", num_shard=2, disable_grammar_support=False
) as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_llama_completion(flash_llama_completion_handle):
await flash_llama_completion_handle.health(300)
return flash_llama_completion_handle.client
# NOTE: since `v1/completions` is a deprecated inferface/endpoint we do not provide a convience
# method for it. Instead, we use the `requests` library to make the HTTP request directly.
def test_flash_llama_grammar_single_prompt(flash_llama_completion, response_snapshot):
response = requests.post(
f"{flash_llama_completion.base_url}/v1/completions",
json={
"model": "tgi",
"prompt": "Say this is a test",
"max_tokens": 5,
"seed": 0,
},
headers=flash_llama_completion.headers,
stream=False,
)
response = response.json()
assert len(response["choices"]) == 1
def test_flash_llama_grammar_many_prompts(flash_llama_completion, response_snapshot):
response = requests.post(
f"{flash_llama_completion.base_url}/v1/completions",
json={
"model": "tgi",
"prompt": ["Say", "this", "is", "a", "test"],
"max_tokens": 5,
"seed": 0,
},
headers=flash_llama_completion.headers,
stream=False,
)
response = response.json()
assert len(response["choices"]) == 5
all_indexes = [choice["index"] for choice in response["choices"]]
all_indexes.sort()
assert all_indexes == [0, 1, 2, 3, 4]

6
launcher/src/main.rs
View File

@ -396,6 +396,10 @@ struct Args {
/// Display a lot of information about your runtime environment
#[clap(long, short, action)]
env: bool,
/// Control the maximum number of inputs that a client can send in a single request
#[clap(default_value = "32", long, env)]
max_client_batch_size: usize,
}
#[derive(Debug)]
@ -1044,6 +1048,8 @@ fn spawn_webserver(
// Start webserver
tracing::info!("Starting Webserver");
let mut router_args = vec![
"--max-client-batch-size".to_string(),
args.max_client_batch_size.to_string(),
"--max-concurrent-requests".to_string(),
args.max_concurrent_requests.to_string(),
"--max-best-of".to_string(),

44
router/src/lib.rs
View File

@ -141,6 +141,8 @@ pub struct Info {
pub max_batch_size: Option<usize>,
#[schema(example = "2")]
pub validation_workers: usize,
#[schema(example = "32")]
pub max_client_batch_size: usize,
/// Router Info
#[schema(example = "0.5.0")]
pub version: &'static str,
@ -270,28 +272,20 @@ mod prompt_serde {
use serde::{self, Deserialize, Deserializer};
use serde_json::Value;
pub fn deserialize<'de, D>(deserializer: D) -> Result<String, D::Error>
pub fn deserialize<'de, D>(deserializer: D) -> Result<Vec<String>, D::Error>
where
D: Deserializer<'de>,
{
let value = Value::deserialize(deserializer)?;
match value {
Value::String(s) => Ok(s),
Value::Array(arr) => {
if arr.len() == 1 {
match arr[0].as_str() {
Some(s) => Ok(s.to_string()),
None => Err(serde::de::Error::custom(
"Array contains non-string elements",
)),
}
} else {
Err(serde::de::Error::custom(
"Array contains non-string element. Expected string. In general arrays should not be used for prompts. Please use a string instead if possible.",
))
}
}
Value::String(s) => Ok(vec![s]),
Value::Array(arr) => arr
.iter()
.map(|v| match v {
Value::String(s) => Ok(s.to_owned()),
_ => Err(serde::de::Error::custom("Expected a string")),
})
.collect(),
_ => Err(serde::de::Error::custom(
"Expected a string or an array of strings",
)),
@ -309,7 +303,7 @@ pub struct CompletionRequest {
/// The prompt to generate completions for.
#[schema(example = "What is Deep Learning?")]
#[serde(deserialize_with = "prompt_serde::deserialize")]
pub prompt: String,
pub prompt: Vec<String>,
/// The maximum number of tokens that can be generated in the chat completion.
#[serde(default)]
@ -945,6 +939,20 @@ pub(crate) struct Details {
pub top_tokens: Vec<Vec<Token>>,
}
impl Default for Details {
fn default() -> Self {
Self {
finish_reason: FinishReason::Length,
generated_tokens: 0,
seed: None,
prefill: Vec::new(),
tokens: Vec::new(),
best_of_sequences: None,
top_tokens: Vec::new(),
}
}
}
#[derive(Serialize, ToSchema)]
pub(crate) struct GenerateResponse {
#[schema(example = "test")]

4
router/src/main.rs
View File

@ -77,6 +77,8 @@ struct Args {
messages_api_enabled: bool,
#[clap(long, env, default_value_t = false)]
disable_grammar_support: bool,
#[clap(default_value = "32", long, env)]
max_client_batch_size: usize,
}
#[tokio::main]
@ -111,6 +113,7 @@ async fn main() -> Result<(), RouterError> {
ngrok_edge,
messages_api_enabled,
disable_grammar_support,
max_client_batch_size,
} = args;
// Launch Tokio runtime
@ -372,6 +375,7 @@ async fn main() -> Result<(), RouterError> {
tokenizer_config,
messages_api_enabled,
disable_grammar_support,
max_client_batch_size,
)
.await?;
Ok(())

360
router/src/server.rs
View File

@ -595,126 +595,250 @@ async fn completions(
));
}
// build the request passing some parameters
let generate_request = GenerateRequest {
inputs: req.prompt.to_string(),
parameters: GenerateParameters {
best_of: None,
temperature: req.temperature,
repetition_penalty: req.repetition_penalty,
frequency_penalty: req.frequency_penalty,
top_k: None,
top_p: req.top_p,
typical_p: None,
do_sample: true,
max_new_tokens,
return_full_text: None,
stop: Vec::new(),
truncate: None,
watermark: false,
details: true,
decoder_input_details: !stream,
seed,
top_n_tokens: None,
grammar: None,
if req.prompt.len() > info.max_client_batch_size {
metrics::increment_counter!("tgi_request_failure", "err" => "validation");
return Err((
StatusCode::UNPROCESSABLE_ENTITY,
Json(ErrorResponse {
error: format!(
"Number of prompts exceeds the maximum allowed batch size of {}",
info.max_client_batch_size
),
error_type: "batch size exceeded".to_string(),
}),
));
}
let mut generate_requests = Vec::new();
for prompt in req.prompt.iter() {
// build the request passing some parameters
let generate_request = GenerateRequest {
inputs: prompt.to_string(),
parameters: GenerateParameters {
best_of: None,
temperature: req.temperature,
repetition_penalty: req.repetition_penalty,
frequency_penalty: req.frequency_penalty,
top_k: None,
top_p: req.top_p,
typical_p: None,
do_sample: true,
max_new_tokens,
return_full_text: None,
stop: Vec::new(),
truncate: None,
watermark: false,
details: true,
decoder_input_details: !stream,
seed,
top_n_tokens: None,
grammar: None,
},
};
generate_requests.push(generate_request);
}
if stream {
let response_streams = FuturesUnordered::new();
for (index, generate_request) in generate_requests.into_iter().enumerate() {
let model_id = info.model_id.clone();
let system_fingerprint =
format!("{}-{}", info.version, info.docker_label.unwrap_or("native"));
let on_message_callback = move |stream_token: StreamResponse| {
let event = Event::default();
let current_time = std::time::SystemTime::now()
.duration_since(std::time::UNIX_EPOCH)
.unwrap_or_else(|_| std::time::Duration::from_secs(0))
.as_secs();
event
.json_data(CompletionCompleteChunk {
id: "".to_string(),
object: "text_completion".to_string(),
created: current_time,
choices: vec![CompletionComplete {
finish_reason: "".to_string(),
index: index as u32,
logprobs: None,
text: stream_token.token.text,
}],
model: model_id.clone(),
system_fingerprint: system_fingerprint.clone(),
})
.map_or_else(
|e| {
println!("Failed to serialize ChatCompletionChunk: {:?}", e);
Event::default()
},
|data| data,
)
};
let (headers, response_stream) = generate_stream_internal(
infer.clone(),
compute_type.clone(),
Json(generate_request),
on_message_callback,
)
.await;
response_streams.push((headers, Box::pin(response_stream)));
}
let stream = async_stream::stream! {
for response_stream in response_streams {
let (_headers, mut inner_stream) = response_stream;
while let Some(event) = inner_stream.next().await {
yield event;
}
}
};
let sse = Sse::new(stream).keep_alive(KeepAlive::default());
return Ok((HeaderMap::new(), sse).into_response());
}
let current_time = std::time::SystemTime::now()
.duration_since(std::time::UNIX_EPOCH)
.unwrap_or_else(|_| std::time::Duration::from_secs(0))
.as_secs();
let responses = FuturesUnordered::new();
for generate_request in generate_requests.into_iter() {
responses.push(generate(
Extension(infer.clone()),
Extension(compute_type.clone()),
Json(generate_request),
));
}
let generate_responses = responses.try_collect::<Vec<_>>().await?;
let mut prompt_tokens = 0u32;
let mut completion_tokens = 0u32;
let mut total_tokens = 0u32;
let mut headers = HeaderMap::new();
let mut x_compute_type: Option<String> = None;
let mut x_compute_time = 0u32;
let mut x_compute_characters = 0u32;
let mut x_total_time = 0u32;
let mut x_validation_time = 0u32;
let mut x_queue_time = 0u32;
let mut x_inference_time = 0u32;
let mut x_time_per_token = 0u32;
let mut x_prompt_tokens = 0u32;
let mut x_generated_tokens = 0u32;
// helper closure to extract a header value or default to 0
let extract_or_zero = |headers: &HeaderMap, key: &str| {
headers
.get(key)
.and_then(|v| v.to_str().ok())
.unwrap_or("0")
.parse::<u32>()
.unwrap_or(0)
};
let choices = generate_responses
.into_iter()
.enumerate()
.map(|(index, (headers, Json(generation)))| {
let details = generation.details.unwrap_or_default();
if x_compute_type.is_none() {
x_compute_type = Some(
headers
.get("x-compute-type")
.unwrap()
.to_str()
.unwrap()
.to_string(),
);
}
// update headers
x_compute_time += extract_or_zero(&headers, "x-compute-time");
x_compute_characters += extract_or_zero(&headers, "x-compute-characters");
x_total_time += extract_or_zero(&headers, "x-total-time");
x_validation_time += extract_or_zero(&headers, "x-validation-time");
x_queue_time += extract_or_zero(&headers, "x-queue-time");
x_inference_time += extract_or_zero(&headers, "x-inference-time");
x_time_per_token += extract_or_zero(&headers, "x-time-per-token");
x_prompt_tokens += extract_or_zero(&headers, "x-prompt-tokens");
x_generated_tokens += extract_or_zero(&headers, "x-generated-tokens");
// update usage
prompt_tokens += details.prefill.len() as u32;
completion_tokens += details.generated_tokens;
total_tokens += details.prefill.len() as u32 + details.generated_tokens;
CompletionComplete {
finish_reason: details.finish_reason.to_string(),
index: index as u32,
logprobs: None,
text: generation.generated_text,
}
})
.collect::<Vec<_>>();
// Headers similar to `generate` but aggregated
headers.insert(
"x-compute-type",
x_compute_type
.unwrap_or("unknown".to_string())
.parse()
.unwrap(),
);
headers.insert(
"x-compute-time",
x_compute_time.to_string().parse().unwrap(),
);
headers.insert(
"x-compute-characters",
x_compute_characters.to_string().parse().unwrap(),
);
headers.insert("x-total-time", x_total_time.to_string().parse().unwrap());
headers.insert(
"x-validation-time",
x_validation_time.to_string().parse().unwrap(),
);
headers.insert("x-queue-time", x_queue_time.to_string().parse().unwrap());
headers.insert(
"x-inference-time",
x_inference_time.to_string().parse().unwrap(),
);
headers.insert(
"x-time-per-token",
x_time_per_token.to_string().parse().unwrap(),
);
headers.insert(
"x-prompt-tokens",
x_prompt_tokens.to_string().parse().unwrap(),
);
headers.insert(
"x-generated-tokens",
x_generated_tokens.to_string().parse().unwrap(),
);
let response = Completion {
id: "".to_string(),
object: "text_completion".to_string(),
created: current_time,
model: info.model_id.clone(),
system_fingerprint: format!("{}-{}", info.version, info.docker_label.unwrap_or("native")),
choices,
usage: Usage {
prompt_tokens,
completion_tokens,
total_tokens,
},
};
if stream {
let on_message_callback = move |stream_token: StreamResponse| {
let event = Event::default();
let current_time = std::time::SystemTime::now()
.duration_since(std::time::UNIX_EPOCH)
.unwrap_or_else(|_| std::time::Duration::from_secs(0))
.as_secs();
event
.json_data(CompletionCompleteChunk {
id: "".to_string(),
object: "text_completion".to_string(),
created: current_time,
choices: vec![CompletionComplete {
finish_reason: "".to_string(),
index: 0,
logprobs: None,
text: stream_token.token.text,
}],
model: info.model_id.clone(),
system_fingerprint: format!(
"{}-{}",
info.version,
info.docker_label.unwrap_or("native")
),
})
.map_or_else(
|e| {
println!("Failed to serialize ChatCompletionChunk: {:?}", e);
Event::default()
},
|data| data,
)
};
let (headers, response_stream) = generate_stream_internal(
infer,
compute_type,
Json(generate_request),
on_message_callback,
)
.await;
let sse = Sse::new(response_stream).keep_alive(KeepAlive::default());
Ok((headers, sse).into_response())
} else {
let (headers, Json(generation)) = generate(
Extension(infer),
Extension(compute_type),
Json(generate_request),
)
.await?;
let current_time = std::time::SystemTime::now()
.duration_since(std::time::UNIX_EPOCH)
.unwrap_or_else(|_| std::time::Duration::from_secs(0))
.as_secs();
let details = generation.details.ok_or((
// this should never happen but handle if details are missing unexpectedly
StatusCode::INTERNAL_SERVER_ERROR,
Json(ErrorResponse {
error: "No details in generation".to_string(),
error_type: "no details".to_string(),
}),
))?;
let response = Completion {
id: "".to_string(),
object: "text_completion".to_string(),
created: current_time,
model: info.model_id.clone(),
system_fingerprint: format!(
"{}-{}",
info.version,
info.docker_label.unwrap_or("native")
),
choices: vec![CompletionComplete {
finish_reason: details.finish_reason.to_string(),
index: 0,
logprobs: None,
text: generation.generated_text,
}],
usage: Usage {
prompt_tokens: details.prefill.len() as u32,
completion_tokens: details.generated_tokens,
total_tokens: details.prefill.len() as u32 + details.generated_tokens,
},
};
Ok((headers, Json(response)).into_response())
}
Ok((headers, Json(response)).into_response())
}
/// Generate tokens
@ -1163,6 +1287,7 @@ pub async fn run(
tokenizer_config: HubTokenizerConfig,
messages_api_enabled: bool,
grammar_support: bool,
max_client_batch_size: usize,
) -> Result<(), axum::BoxError> {
// OpenAPI documentation
#[derive(OpenApi)]
@ -1336,6 +1461,7 @@ pub async fn run(
max_waiting_tokens,
max_batch_size,
validation_workers,
max_client_batch_size,
version: env!("CARGO_PKG_VERSION"),
sha: option_env!("VERGEN_GIT_SHA"),
docker_label: option_env!("DOCKER_LABEL"),