begin work on delegate's ability to have a multi-step conversation

server/agents/chef.ts

@@ -3,7 +3,7 @@ import { Agent } from "../types.js";
 export const chefAgent: Agent = {
   id: "chef",
   name: "Chef",
-  modelName: "mistral/ministral-8b",
+  modelName: "mistralai/mistral-nemo",
   systemMessage:
     "You are a master chef who is famous for his creative and original recipes, but also knows many standard, tried-and-true recipes.",
   description:

server/agents/personalAssistant.ts

@@ -7,7 +7,8 @@ export const personalAssistantAgent: Agent = {
   name: "Personal Assistant",
   // modelName: "qwen/qwen3-32b:free",
   // modelName: "mistral/ministral-8b",
-  modelName: "google/gemini-2.5-flash-preview",
+  // modelName: "google/gemini-2.5-flash-preview",
+  modelName: "mistralai/mistral-nemo",
   systemMessage:
     singleSpace(`You are a personal assistant Agent who is helpful, friendly, and 
     responsible. You are my liason to other Agents who have specialized 

server/tools.ts

@@ -1,4 +1,10 @@
-import { streamText } from "ai";
+import {
+  streamText,
+  generateText,
+  generateObject,
+  type Message,
+  jsonSchema,
+} from "ai";
 import { getAgentById, openrouter } from "./agentRegistry.js";
 
 // Define the tools with explicit type
@@ -33,26 +39,59 @@ const tools: ToolFunctions = {
     }
 
     try {
-      // Generate a response from the agent using the prompt
-      const result = streamText({
-        model: openrouter(agent.modelName),
+      const conversation: { messages: Array<Omit<Message, "id">> } = {
         messages: [
           { role: "system", content: agent.systemMessage },
           { role: "user", content: prompt },
         ],
-        tools: agent.tools,
-      });
-
-      // Collect the response text
-      let responseText = "";
-
-      // The textStream is already an AsyncIterable, no need to call it as a function
-      for await (const chunk of result.textStream) {
-        responseText += chunk;
+      };
+      let isConversationDone = false;
+      while (!isConversationDone) {
+        // Generate a response from the agent using the prompt
+        const result = await generateText({
+          model: openrouter(agent.modelName),
+          messages: conversation.messages,
+          tools: agent.tools,
+        });
+        conversation.messages.push({ role: "assistant", content: result.text });
+        const sentimentIsConversationDone = await generateObject<{
+          isConversationDone: boolean;
+        }>({
+          model: openrouter("mistralai/mistral-nemo"),
+          messages: [
+            {
+              role: "system",
+              content:
+                "You are a tool to determine whether a conversation is done or should continue with another reply.",
+            },
+            {
+              role: "user",
+              content: conversation.messages
+                .map((message) => `${message.role}: ${message.content}`)
+                .join("\n"),
+            },
+          ],
+          schema: jsonSchema({
+            type: "object",
+            properties: {
+              isConversationDone: {
+                type: "boolean",
+                description:
+                  "Whether the conversation is done or should continue and requires a reply.",
+              },
+            },
+          }),
+        });
+        isConversationDone =
+          sentimentIsConversationDone.object.isConversationDone;
       }
 
-      // Return the agent's response
-      return responseText;
+      // const summaryText = await generateSummary();
+      // // Return the agent's response
+      // return summaryText;
+      return conversation.messages
+        .map((message) => `${message.role}: ${message.content}`)
+        .join("\n");
     } catch (error: unknown) {
       const errorMessage =
         error instanceof Error ? error.message : "Unknown error";