Improve execute-model to include some client references, and improve …

…function description

src/functions/execute-model.ts

@@ -1,11 +1,26 @@
 import OpenAI from "openai";
 import { RunnerResponse, Tool } from "../functions";
 
+type MessageWithReferences = OpenAI.ChatCompletionMessageParam & {
+  copilot_references: Reference[];
+};
+
+interface Reference {
+  type: string;
+  data: any;
+  id: string;
+  metadata: any;
+}
+
 export class executeModel extends Tool {
   static definition = {
     name: "execute_model",
-    description:
-      'Executes a model. This will often be used by saying something like "using <model>: <instruction>".',
+    description: `This function sends the prompt from the user's message to the specified model.".
+Example Queries (IMPORTANT: Phrasing doesn't have to match):
+- using gpt-4o-mini: what is 1+1?
+- using Mistral-large: what is the capital of France?
+- using cohere-command-r-plus: explain this code.
+  `,
     parameters: {
       type: "object",
       properties: {
@@ -24,19 +39,36 @@ export class executeModel extends Tool {
   };
 
   async execute(
-    _: OpenAI.ChatCompletionMessageParam[],
+    messages: MessageWithReferences[],
     args: {
       model: string;
       instruction: string;
     }
   ): Promise<RunnerResponse> {
+    // Check if the user included any code references in their last message
+    const lastMessage = messages[messages.length - 1];
+    const importantRefs = lastMessage.copilot_references.filter(
+      (ref) => ref.type === "client.selection" || ref.type === "client.file"
+    );
+
+    const content = [
+      `The user has chosen to use the model named ${args.model}. Begin your response with the following phrase: "The model you've selected is ${args.model}".`,
+      "Do not include any additional information about the selected model in this first sentence - ONLY the name.",
+    ];
+
+    if (importantRefs) {
+      content.push(
+        "The user included the following context - you may find information in this context useful for your response:",
+        JSON.stringify(importantRefs)
+      );
+    }
+
     return {
       model: args.model,
       messages: [
         {
           role: "system",
-          content:
-            "Begin your response by telling the user the name of your language model.",
+          content: content.join("\n"),
         },
         { role: "user", content: args.instruction },
       ],