feat: add /v1/models endpoint (#2433)
* feat: add /v1/models endpoint * feat: add /v1/models endpoint * fix: remove unused type import * fix: revert route typo * fix: update docs with new endpoint * fix: add to redocly ignore and lint
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@ -77,3 +77,4 @@ docs/openapi.json:
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- '#/paths/~1tokenize/post'
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- '#/paths/~1v1~1chat~1completions/post'
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- '#/paths/~1v1~1completions/post'
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- '#/paths/~1v1~1models/get'
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@ -556,6 +556,37 @@
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}
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}
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}
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},
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"/v1/models": {
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"get": {
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"tags": [
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"Text Generation Inference"
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],
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"summary": "Get model info",
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"operationId": "openai_get_model_info",
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"responses": {
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"200": {
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"description": "Served model info",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/ModelInfo"
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}
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}
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}
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},
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"404": {
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"description": "Model not found",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/ErrorResponse"
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}
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}
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}
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}
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}
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}
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}
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},
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"components": {
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@ -1747,6 +1778,35 @@
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}
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]
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},
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"ModelInfo": {
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"type": "object",
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"required": [
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"id",
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"object",
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"created",
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"owned_by"
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],
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"properties": {
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"created": {
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"type": "integer",
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"format": "int64",
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"example": 1686935002,
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"minimum": 0
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},
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"id": {
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"type": "string",
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"example": "gpt2"
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},
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"object": {
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"type": "string",
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"example": "model"
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},
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"owned_by": {
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"type": "string",
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"example": "openai"
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}
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}
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},
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"OutputMessage": {
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"oneOf": [
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{
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@ -1261,6 +1261,34 @@ pub(crate) struct ErrorResponse {
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pub error_type: String,
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}
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#[derive(Serialize, Deserialize, ToSchema)]
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pub(crate) struct ModelInfo {
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#[schema(example = "gpt2")]
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pub id: String,
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#[schema(example = "model")]
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pub object: String,
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#[schema(example = 1686935002)]
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pub created: u64,
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#[schema(example = "openai")]
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pub owned_by: String,
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}
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#[derive(Serialize, Deserialize, ToSchema)]
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pub(crate) struct ModelsInfo {
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#[schema(example = "list")]
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pub object: String,
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pub data: Vec<ModelInfo>,
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}
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impl Default for ModelsInfo {
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fn default() -> Self {
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ModelsInfo {
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object: "list".to_string(),
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data: Vec::new(),
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}
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}
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}
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#[cfg(test)]
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mod tests {
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use super::*;
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@ -24,6 +24,7 @@ use crate::{
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VertexResponse,
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};
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use crate::{FunctionDefinition, HubPreprocessorConfig, ToolCall, ToolChoice, ToolType};
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use crate::{ModelInfo, ModelsInfo};
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use async_stream::__private::AsyncStream;
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use axum::extract::Extension;
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use axum::http::{HeaderMap, HeaderValue, Method, StatusCode};
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@ -116,6 +117,29 @@ async fn get_model_info(info: Extension<Info>) -> Json<Info> {
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Json(info.0)
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}
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#[utoipa::path(
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get,
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tag = "Text Generation Inference",
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path = "/v1/models",
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responses(
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(status = 200, description = "Served model info", body = ModelInfo),
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(status = 404, description = "Model not found", body = ErrorResponse),
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)
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)]
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#[instrument(skip(info))]
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/// Get model info
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async fn openai_get_model_info(info: Extension<Info>) -> Json<ModelsInfo> {
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Json(ModelsInfo {
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data: vec![ModelInfo {
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id: info.0.model_id.clone(),
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object: "model".to_string(),
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created: 0, // TODO: determine how to get this
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owned_by: info.0.model_id.clone(),
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}],
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..Default::default()
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})
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}
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#[utoipa::path(
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post,
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tag = "Text Generation Inference",
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@ -1505,6 +1529,7 @@ chat_completions,
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completions,
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tokenize,
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metrics,
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openai_get_model_info,
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),
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components(
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schemas(
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@ -1557,6 +1582,7 @@ ToolCall,
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Function,
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FunctionDefinition,
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ToolChoice,
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ModelInfo,
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)
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),
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tags(
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@ -2250,7 +2276,8 @@ async fn start(
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.route("/info", get(get_model_info))
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.route("/health", get(health))
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.route("/ping", get(health))
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.route("/metrics", get(metrics));
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.route("/metrics", get(metrics))
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.route("/v1/models", get(openai_get_model_info));
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// Conditional AWS Sagemaker route
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let aws_sagemaker_route = if messages_api_enabled {
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