Implement a first version of a streamed chat API

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Clément Renault 2025-05-14 11:18:21 +02:00 committed by Kerollmops
parent 11ace7f209
commit 0f75ae9f25
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@ -1,14 +1,50 @@
use std::mem;
use actix_web::web::{self, Data};
use actix_web::HttpResponse;
use actix_web::{Either, HttpResponse, Responder};
use actix_web_lab::sse::{self, Event};
use async_openai::config::OpenAIConfig;
use async_openai::types::CreateChatCompletionRequest;
use async_openai::types::{
ChatCompletionRequestAssistantMessageArgs, ChatCompletionRequestMessage,
ChatCompletionRequestToolMessage, ChatCompletionRequestToolMessageContent,
ChatCompletionToolArgs, ChatCompletionToolType, CreateChatCompletionRequest, FinishReason,
FunctionObjectArgs,
};
use async_openai::Client;
use futures::StreamExt;
use index_scheduler::IndexScheduler;
use meilisearch_types::error::ResponseError;
use meilisearch_types::keys::actions;
use meilisearch_types::milli::index::IndexEmbeddingConfig;
use meilisearch_types::milli::prompt::PromptData;
use meilisearch_types::milli::vector::EmbeddingConfig;
use meilisearch_types::{Document, Index};
use serde::{Deserialize, Serialize};
use serde_json::json;
use crate::extractors::authentication::policies::ActionPolicy;
use crate::extractors::authentication::GuardedData;
use crate::metrics::MEILISEARCH_DEGRADED_SEARCH_REQUESTS;
use crate::routes::indexes::search::search_kind;
use crate::search::{
add_search_rules, perform_search, HybridQuery, RetrieveVectors, SearchQuery, SemanticRatio,
};
use crate::search_queue::SearchQueue;
/// The default description of the searchInIndex tool provided to OpenAI.
const DEFAULT_SEARCH_IN_INDEX_TOOL_DESCRIPTION: &str =
"Search the database for relevant JSON documents using an optional query.";
/// The default description of the searchInIndex `q` parameter tool provided to OpenAI.
const DEFAULT_SEARCH_IN_INDEX_Q_PARAMETER_TOOL_DESCRIPTION: &str =
"The search query string used to find relevant documents in the index. \
This should contain keywords or phrases that best represent what the user is looking for. \
More specific queries will yield more precise results.";
/// The default description of the searchInIndex `index` parameter tool provided to OpenAI.
const DEFAULT_SEARCH_IN_INDEX_INDEX_PARAMETER_TOOL_DESCRIPTION: &str =
"The name of the index to search within. An index is a collection of documents organized for search. \
Selecting the right index ensures the most relevant results for the user query";
const EMBEDDER_NAME: &str = "openai";
pub fn configure(cfg: &mut web::ServiceConfig) {
cfg.service(web::resource("").route(web::post().to(chat)));
@ -16,17 +52,240 @@ pub fn configure(cfg: &mut web::ServiceConfig) {
/// Get a chat completion
async fn chat(
_index_scheduler: GuardedData<ActionPolicy<{ actions::CHAT_GET }>, Data<IndexScheduler>>,
web::Json(chat_completion): web::Json<CreateChatCompletionRequest>,
) -> Result<HttpResponse, ResponseError> {
index_scheduler: GuardedData<ActionPolicy<{ actions::CHAT_GET }>, Data<IndexScheduler>>,
search_queue: web::Data<SearchQueue>,
web::Json(mut chat_completion): web::Json<CreateChatCompletionRequest>,
) -> impl Responder {
// To enable later on, when the feature will be experimental
// index_scheduler.features().check_chat("Using the /chat route")?;
if chat_completion.stream.unwrap_or(false) {
Either::Right(streamed_chat(index_scheduler, search_queue, chat_completion).await)
} else {
Either::Left(non_streamed_chat(index_scheduler, search_queue, chat_completion).await)
}
}
async fn non_streamed_chat(
index_scheduler: GuardedData<ActionPolicy<{ actions::CHAT_GET }>, Data<IndexScheduler>>,
search_queue: web::Data<SearchQueue>,
mut chat_completion: CreateChatCompletionRequest,
) -> Result<HttpResponse, ResponseError> {
let api_key = std::env::var("MEILI_OPENAI_API_KEY")
.expect("cannot find OpenAI API Key (MEILI_OPENAI_API_KEY)");
let config = OpenAIConfig::default().with_api_key(&api_key); // we can also change the API base
let client = Client::with_config(config);
assert_eq!(
chat_completion.n.unwrap_or(1),
1,
"Meilisearch /chat only support one completion at a time (n = 1, n = null)"
);
let rtxn = index_scheduler.read_txn().unwrap();
let search_in_index_description = index_scheduler
.chat_prompts(&rtxn, "searchInIndex-description")
.unwrap()
.unwrap_or(DEFAULT_SEARCH_IN_INDEX_TOOL_DESCRIPTION)
.to_string();
let search_in_index_q_param_description = index_scheduler
.chat_prompts(&rtxn, "searchInIndex-q-param-description")
.unwrap()
.unwrap_or(DEFAULT_SEARCH_IN_INDEX_Q_PARAMETER_TOOL_DESCRIPTION)
.to_string();
let search_in_index_index_description = index_scheduler
.chat_prompts(&rtxn, "searchInIndex-index-param-description")
.unwrap()
.unwrap_or(DEFAULT_SEARCH_IN_INDEX_INDEX_PARAMETER_TOOL_DESCRIPTION)
.to_string();
drop(rtxn);
let mut response;
loop {
let tools = chat_completion.tools.get_or_insert_default();
tools.push(
ChatCompletionToolArgs::default()
.r#type(ChatCompletionToolType::Function)
.function(
FunctionObjectArgs::default()
.name("searchInIndex")
.description(&search_in_index_description)
.parameters(json!({
"type": "object",
"properties": {
"index_uid": {
"type": "string",
"enum": ["main"],
"description": search_in_index_index_description,
},
"q": {
"type": ["string", "null"],
"description": search_in_index_q_param_description,
}
},
"required": ["index_uid", "q"],
"additionalProperties": false,
}))
.strict(true)
.build()
.unwrap(),
)
.build()
.unwrap(),
);
response = client.chat().create(chat_completion.clone()).await.unwrap();
let choice = &mut response.choices[0];
match choice.finish_reason {
Some(FinishReason::ToolCalls) => {
let tool_calls = mem::take(&mut choice.message.tool_calls).unwrap_or_default();
let (meili_calls, other_calls): (Vec<_>, Vec<_>) =
tool_calls.into_iter().partition(|call| call.function.name == "searchInIndex");
chat_completion.messages.push(
ChatCompletionRequestAssistantMessageArgs::default()
.tool_calls(meili_calls.clone())
.build()
.unwrap()
.into(),
);
for call in meili_calls {
let SearchInIndexParameters { index_uid, q } =
serde_json::from_str(&call.function.arguments).unwrap();
let mut query = SearchQuery {
q,
hybrid: Some(HybridQuery {
semantic_ratio: SemanticRatio::default(),
embedder: EMBEDDER_NAME.to_string(),
}),
limit: 20,
..Default::default()
};
// Tenant token search_rules.
if let Some(search_rules) =
index_scheduler.filters().get_index_search_rules(&index_uid)
{
add_search_rules(&mut query.filter, search_rules);
}
// TBD
// let mut aggregate = SearchAggregator::<SearchPOST>::from_query(&query);
let index = index_scheduler.index(&index_uid)?;
let search_kind = search_kind(
&query,
index_scheduler.get_ref(),
index_uid.to_string(),
&index,
)?;
let permit = search_queue.try_get_search_permit().await?;
let features = index_scheduler.features();
let index_cloned = index.clone();
let search_result = tokio::task::spawn_blocking(move || {
perform_search(
index_uid.to_string(),
&index_cloned,
query,
search_kind,
RetrieveVectors::new(false),
features,
)
})
.await;
permit.drop().await;
let search_result = search_result?;
if let Ok(ref search_result) = search_result {
// aggregate.succeed(search_result);
if search_result.degraded {
MEILISEARCH_DEGRADED_SEARCH_REQUESTS.inc();
}
}
// analytics.publish(aggregate, &req);
let search_result = search_result?;
let formatted = format_documents(
&index,
search_result.hits.into_iter().map(|doc| doc.document),
);
let text = formatted.join("\n");
chat_completion.messages.push(ChatCompletionRequestMessage::Tool(
ChatCompletionRequestToolMessage {
tool_call_id: call.id,
content: ChatCompletionRequestToolMessageContent::Text(text),
},
));
}
// Let the client call other tools by themselves
if !other_calls.is_empty() {
response.choices[0].message.tool_calls = Some(other_calls);
break;
}
}
_ => break,
}
}
Ok(HttpResponse::Ok().json(response))
}
async fn streamed_chat(
index_scheduler: GuardedData<ActionPolicy<{ actions::CHAT_GET }>, Data<IndexScheduler>>,
search_queue: web::Data<SearchQueue>,
mut chat_completion: CreateChatCompletionRequest,
) -> impl Responder {
assert!(chat_completion.stream.unwrap_or(false));
let api_key = std::env::var("MEILI_OPENAI_API_KEY")
.expect("cannot find OpenAI API Key (MEILI_OPENAI_API_KEY)");
let config = OpenAIConfig::default().with_api_key(&api_key); // we can also change the API base
let client = Client::with_config(config);
let response = client.chat().create(chat_completion).await.unwrap();
Ok(HttpResponse::Ok().json(response))
let response = client.chat().create_stream(chat_completion).await.unwrap();
actix_web_lab::sse::Sse::from_stream(response.map(|response| {
response
.map(|mut r| Event::Data(sse::Data::new_json(r.choices.pop().unwrap().delta).unwrap()))
}))
}
#[derive(Deserialize)]
struct SearchInIndexParameters {
/// The index uid to search in.
index_uid: String,
/// The query parameter to use.
q: Option<String>,
}
fn format_documents(index: &Index, documents: impl Iterator<Item = Document>) -> Vec<String> {
let rtxn = index.read_txn().unwrap();
let IndexEmbeddingConfig { name: _, config, user_provided: _ } = index
.embedding_configs(&rtxn)
.unwrap()
.into_iter()
.find(|conf| conf.name == EMBEDDER_NAME)
.unwrap();
let EmbeddingConfig {
embedder_options: _,
prompt: PromptData { template, max_bytes },
quantized: _,
} = config;
#[derive(Serialize)]
struct Doc<T: Serialize> {
doc: T,
}
let template = liquid::ParserBuilder::with_stdlib().build().unwrap().parse(&template).unwrap();
documents
.map(|doc| {
let object = liquid::to_object(&Doc { doc }).unwrap();
template.render(&object).unwrap()
})
.collect()
}