[Trivial] Generalize internal helper getModelStates

src/engine.ts

@@ -427,7 +427,7 @@
         pipeline.triggerStop();
         break;
       }
       counter += 1;
       await this.decode(pipeline, genConfig);
     }
     return pipeline.getMessage();
@@ -833,7 +833,7 @@
   ): Promise<AsyncIterable<Completion> | Completion> {
     // 0. Check model loaded and preprocess inputs
     const [selectedModelId, selectedPipeline, selectedChatConfig] =
-      this.getLLMStates("ChatCompletionRequest", request.model);
+      this.getLLMStates("CompletionCreateParams", request.model);
     API.postInitAndCheckFieldsCompletion(request, selectedModelId);
     const genConfig: GenerationConfig = {
       frequency_penalty: request.frequency_penalty,
@@ -930,28 +930,10 @@
     request: EmbeddingCreateParams,
   ): Promise<CreateEmbeddingResponse> {
     // 0. Preprocess inputs
-    const loadedModelIds: string[] = Array.from(
-      this.loadedModelIdToPipeline.keys(),
-    );
-    const selectedModelId: string = getModelIdToUse(
-      loadedModelIds,
-      request.model,
+    const [selectedModelId, selectedPipeline] = this.getEmbeddingStates(
       "EmbeddingCreateParams",
+      request.model,
     );
-    const selectedPipeline = this.loadedModelIdToPipeline.get(selectedModelId);
-    if (!(selectedPipeline instanceof EmbeddingPipeline)) {
-      throw new IncorrectPipelineLoadedError(
-        selectedModelId,
-        "EmbeddingPipeline",
-        "EmbeddingCreateParams",
-      );
-    }
-    if (
-      findModelRecord(selectedModelId, this.appConfig).model_type !==
-      ModelType.embedding
-    ) {
-      throw new EmbeddingUnsupportedModelError(selectedModelId);
-    }
     API.postInitAndCheckFieldsEmbedding(request, selectedModelId);
 
     // 1. Call EmbeddingPipeline to get embeddings
@@ -1031,19 +1013,42 @@
   // Needed due to possibly multiple loaded models.
   //---------------------------------------------------------------
 
+  private getLLMStates(
+    requestName: string,
+    modelId?: string | null,
+  ): [string, LLMChatPipeline, ChatConfig] {
+    return this.getModelStates(requestName, ModelType.LLM, modelId) as [
+      string,
+      LLMChatPipeline,
+      ChatConfig,
+    ];
+  }
+
+  private getEmbeddingStates(
+    requestName: string,
+    modelId?: string | null,
+  ): [string, EmbeddingPipeline, ChatConfig] {
+    return this.getModelStates(requestName, ModelType.embedding, modelId) as [
+      string,
+      EmbeddingPipeline,
+      ChatConfig,
+    ];
+  }
+
   /**
    * Return the model, its LLMChatPipeline, and ChatConfig to use. Throws error when unclear which
-   * model to load.
+   * model to load. Ensure all loadedModelIdToXXX maps contain entry for the selected modelId.
    * @param requestName The type of request or API to load the model for. Needed for error throwing.
+   * @param modelType The typ of model, determining what type of pipeline to expect.
    * @param modelId Model the user specified to load via the request. Required when multiple
    *   models are loaded
    */
-  private getLLMStates(
+  private getModelStates(
     requestName: string,
+    modelType: ModelType,
     modelId?: string | null,
-  ): [string, LLMChatPipeline, ChatConfig] {
-    // TODO(webllm-team): when more modalities/pipelines are supported, make this method
-    // generic for different pipelines. e.g. currently embedding() does not use this method
+  ): [string, LLMChatPipeline | EmbeddingPipeline, ChatConfig] {
+    // 0. Select model based on request.model and loadedModelIds
     const loadedModelIds: string[] = Array.from(
       this.loadedModelIdToPipeline.keys(),
     );
@@ -1052,14 +1057,35 @@
       modelId,
       requestName,
     );
+
+    // 1. Retrieve pipeline
     const selectedPipeline = this.loadedModelIdToPipeline.get(selectedModelId);
-    if (!(selectedPipeline instanceof LLMChatPipeline)) {
-      throw new IncorrectPipelineLoadedError(
-        selectedModelId,
-        "LLMChatPipeline",
-        requestName,
-      );
+    if (modelType === ModelType.LLM) {
+      if (!(selectedPipeline instanceof LLMChatPipeline)) {
+        throw new IncorrectPipelineLoadedError(
+          selectedModelId,
+          "LLMChatPipeline",
+          requestName,
+        );
+      }
+    } else {
+      // ModelType.Embedding
+      if (!(selectedPipeline instanceof EmbeddingPipeline)) {
+        throw new IncorrectPipelineLoadedError(
+          selectedModelId,
+          "EmbeddingPipeline",
+          requestName,
+        );
+      }
+      if (
+        findModelRecord(selectedModelId, this.appConfig).model_type !==
+        ModelType.embedding
+      ) {
+        throw new EmbeddingUnsupportedModelError(selectedModelId);
+      }
     }
+
+    // 2. Retrieve chat config
     const selectedChatConfig =
       this.loadedModelIdToChatConfig.get(selectedModelId);
     if (selectedChatConfig === undefined) {

src/error.ts

@@ -524,7 +524,7 @@ export class IncorrectPipelineLoadedError extends Error {
     requestName: string,
   ) {
     super(
-      `${requestName} expects model be loaded with ${expectedPipeline}. However, ` +
+      `${requestName} expects model to be loaded with ${expectedPipeline}. However, ` +
         `${selectedModelId} is not loaded with this pipeline.`,
     );
     this.name = "IncorrectPipelineLoadedError";