fixed example based on new interface

examples/llm_stream.ts

@@ -7,7 +7,9 @@ import {
 import { ChatMessage, MessageType, OpenAI } from "../packages/core/src/llm/LLM";
 
 async function main() {
-  const query: string = "Where is Istanbul?";
+  const query: string = `
+Where is Istanbul?
+  `;
 
   const llm = new OpenAI({ model: "gpt-3.5-turbo", temperature: 0.1 });
   const message: ChatMessage = { content: query, role: "user" };
@@ -19,26 +21,14 @@ async function main() {
   //GPT 3.5 Turbo uses CL100K_Base encodings, check your LLM to see which tokenizer it uses.
   const encoding = tiktoken.getEncoding("cl100k_base");
 
-  const callback: CallbackManager = new CallbackManager();
-  callback.onLLMStream = (callback_response) => {
-    //Token text
-    const text = callback_response.token.choices[0].delta.content
-      ? callback_response.token.choices[0].delta.content
-      : "";
-    //Increment total number of tokens
-    total_tokens += encoding.encode(text).length;
-  };
-
-  llm.callbackManager = callback;
+  //Stream Complete
+  //Note: Setting streaming flag to true or false will auto-set your return type to
+  //either an AsyncGenerator or a Response.
+  // Omitting the streaming flag automatically sets streaming to false
 
-  //Create a dummy event to trigger our Stream Callback
-  const dummy_event: Event = {
-    id: "something",
-    type: "intermediate" as EventType,
-  };
+  // const stream2 = await llm.chat([message], undefined);
+  const stream = await llm.complete(query, undefined, true);
 
-  //Stream Complete
-  const stream = llm.stream_complete(query, dummy_event);
 
   for await (const part of stream) {
     //This only gives you the string part of a stream
@@ -49,13 +39,11 @@ async function main() {
   const correct_total_tokens: number =
     encoding.encode(accumulated_result).length;
 
+  console.log(accumulated_result);
   //Check if our stream token counter works
   console.log(
     `Output token total using tokenizer on accumulated output: ${correct_total_tokens}`,
   );
-  console.log(
-    `Output token total using tokenizer on stream output: ${total_tokens}`,
-  );
 }
 
 main();