Files
oak-gpui/crates/collab/src/llm.rs
T
Marshall Bowers 7f6d0919c9 collab: Setup database for LLM service (#15882)
This PR puts the initial infrastructure for the LLM service's database
in place.

The LLM service will be using a separate Postgres database, with its own
set of migrations.

Currently we only connect to the database in development, as we don't
yet have the database setup for the staging/production environments.

Release Notes:

- N/A
2024-08-06 17:18:08 -04:00

248 lines
7.9 KiB
Rust

mod authorization;
pub mod db;
mod token;
use crate::api::CloudflareIpCountryHeader;
use crate::llm::authorization::authorize_access_to_language_model;
use crate::llm::db::LlmDatabase;
use crate::{executor::Executor, Config, Error, Result};
use anyhow::{anyhow, Context as _};
use axum::TypedHeader;
use axum::{
body::Body,
http::{self, HeaderName, HeaderValue, Request, StatusCode},
middleware::{self, Next},
response::{IntoResponse, Response},
routing::post,
Extension, Json, Router,
};
use futures::StreamExt as _;
use http_client::IsahcHttpClient;
use rpc::{LanguageModelProvider, PerformCompletionParams, EXPIRED_LLM_TOKEN_HEADER_NAME};
use std::sync::Arc;
pub use token::*;
pub struct LlmState {
pub config: Config,
pub executor: Executor,
pub db: Option<Arc<LlmDatabase>>,
pub http_client: IsahcHttpClient,
}
impl LlmState {
pub async fn new(config: Config, executor: Executor) -> Result<Arc<Self>> {
// TODO: This is temporary until we have the LLM database stood up.
let db = if config.is_development() {
let database_url = config
.llm_database_url
.as_ref()
.ok_or_else(|| anyhow!("missing LLM_DATABASE_URL"))?;
let max_connections = config
.llm_database_max_connections
.ok_or_else(|| anyhow!("missing LLM_DATABASE_MAX_CONNECTIONS"))?;
let mut db_options = db::ConnectOptions::new(database_url);
db_options.max_connections(max_connections);
let db = LlmDatabase::new(db_options, executor.clone()).await?;
Some(Arc::new(db))
} else {
None
};
let user_agent = format!("Zed Server/{}", env!("CARGO_PKG_VERSION"));
let http_client = IsahcHttpClient::builder()
.default_header("User-Agent", user_agent)
.build()
.context("failed to construct http client")?;
let this = Self {
config,
executor,
db,
http_client,
};
Ok(Arc::new(this))
}
}
pub fn routes() -> Router<(), Body> {
Router::new()
.route("/completion", post(perform_completion))
.layer(middleware::from_fn(validate_api_token))
}
async fn validate_api_token<B>(mut req: Request<B>, next: Next<B>) -> impl IntoResponse {
let token = req
.headers()
.get(http::header::AUTHORIZATION)
.and_then(|header| header.to_str().ok())
.ok_or_else(|| {
Error::http(
StatusCode::BAD_REQUEST,
"missing authorization header".to_string(),
)
})?
.strip_prefix("Bearer ")
.ok_or_else(|| {
Error::http(
StatusCode::BAD_REQUEST,
"invalid authorization header".to_string(),
)
})?;
let state = req.extensions().get::<Arc<LlmState>>().unwrap();
match LlmTokenClaims::validate(&token, &state.config) {
Ok(claims) => {
req.extensions_mut().insert(claims);
Ok::<_, Error>(next.run(req).await.into_response())
}
Err(ValidateLlmTokenError::Expired) => Err(Error::Http(
StatusCode::UNAUTHORIZED,
"unauthorized".to_string(),
[(
HeaderName::from_static(EXPIRED_LLM_TOKEN_HEADER_NAME),
HeaderValue::from_static("true"),
)]
.into_iter()
.collect(),
)),
Err(_err) => Err(Error::http(
StatusCode::UNAUTHORIZED,
"unauthorized".to_string(),
)),
}
}
async fn perform_completion(
Extension(state): Extension<Arc<LlmState>>,
Extension(claims): Extension<LlmTokenClaims>,
country_code_header: Option<TypedHeader<CloudflareIpCountryHeader>>,
Json(params): Json<PerformCompletionParams>,
) -> Result<impl IntoResponse> {
authorize_access_to_language_model(
&state.config,
&claims,
country_code_header.map(|header| header.to_string()),
params.provider,
&params.model,
)?;
match params.provider {
LanguageModelProvider::Anthropic => {
let api_key = state
.config
.anthropic_api_key
.as_ref()
.context("no Anthropic AI API key configured on the server")?;
let chunks = anthropic::stream_completion(
&state.http_client,
anthropic::ANTHROPIC_API_URL,
api_key,
serde_json::from_str(&params.provider_request.get())?,
None,
)
.await?;
let stream = chunks.map(|event| {
let mut buffer = Vec::new();
event.map(|chunk| {
buffer.clear();
serde_json::to_writer(&mut buffer, &chunk).unwrap();
buffer.push(b'\n');
buffer
})
});
Ok(Response::new(Body::wrap_stream(stream)))
}
LanguageModelProvider::OpenAi => {
let api_key = state
.config
.openai_api_key
.as_ref()
.context("no OpenAI API key configured on the server")?;
let chunks = open_ai::stream_completion(
&state.http_client,
open_ai::OPEN_AI_API_URL,
api_key,
serde_json::from_str(&params.provider_request.get())?,
None,
)
.await?;
let stream = chunks.map(|event| {
let mut buffer = Vec::new();
event.map(|chunk| {
buffer.clear();
serde_json::to_writer(&mut buffer, &chunk).unwrap();
buffer.push(b'\n');
buffer
})
});
Ok(Response::new(Body::wrap_stream(stream)))
}
LanguageModelProvider::Google => {
let api_key = state
.config
.google_ai_api_key
.as_ref()
.context("no Google AI API key configured on the server")?;
let chunks = google_ai::stream_generate_content(
&state.http_client,
google_ai::API_URL,
api_key,
serde_json::from_str(&params.provider_request.get())?,
)
.await?;
let stream = chunks.map(|event| {
let mut buffer = Vec::new();
event.map(|chunk| {
buffer.clear();
serde_json::to_writer(&mut buffer, &chunk).unwrap();
buffer.push(b'\n');
buffer
})
});
Ok(Response::new(Body::wrap_stream(stream)))
}
LanguageModelProvider::Zed => {
let api_key = state
.config
.qwen2_7b_api_key
.as_ref()
.context("no Qwen2-7B API key configured on the server")?;
let api_url = state
.config
.qwen2_7b_api_url
.as_ref()
.context("no Qwen2-7B URL configured on the server")?;
let chunks = open_ai::stream_completion(
&state.http_client,
&api_url,
api_key,
serde_json::from_str(&params.provider_request.get())?,
None,
)
.await?;
let stream = chunks.map(|event| {
let mut buffer = Vec::new();
event.map(|chunk| {
buffer.clear();
serde_json::to_writer(&mut buffer, &chunk).unwrap();
buffer.push(b'\n');
buffer
})
});
Ok(Response::new(Body::wrap_stream(stream)))
}
}
}