docs(agent-kit): favor createAgent() instead of new Agent()

inngest · Nov 25, 2024 · 5bd771e · 5bd771e
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Showing 3 changed files with 4 additions and 4 deletions.
diff --git a/pages/docs/agent-kit/ai-agent-network-state-routing.mdx b/pages/docs/agent-kit/ai-agent-network-state-routing.mdx
@@ -76,7 +76,7 @@ The history system maintains a chronological record of all agent interactions in
 The network state keeps track of every agent interaction, building a chronological list of messages in memory.  When the network runs, it calls the `onStart` lifecycle hook with the given agent, network, user input, system, and history from memory:
 
 ```jsx
-const agent = new Agent({
+const agent = createAgent({
   name: "Code writer",
   lifecycles: {
     onStart: ({

diff --git a/pages/docs/agent-kit/ai-agents-tools.mdx b/pages/docs/agent-kit/ai-agents-tools.mdx
@@ -22,7 +22,7 @@ Here’s a simple agent, which makes a single model call using system prompts an
 ```jsx
 import { Agent, agenticOpenai as openai } from "@inngest/agent-kit";
 
-const agent = new Agent({
+const agent = createAgent({
   name: "Code writer",
   system: "You are an expert TypeScript programmer.  Given a set of asks, you think step-by-step to plan clean, " +
     "idiomatic TypeScript code, with comments and tests as necessary." +
@@ -84,7 +84,7 @@ const systemPrompt =
     "You are an expert TypeScript programmer.  Given a set of asks, think step-by-step to plan clean, " +
     "idiomatic TypeScript code, with comments and tests as necessary."
 
-const agent = new Agent({
+const agent = createAgent({
   name: "Code writer",
 
   // description helps LLM routers choose the right agents to run.

diff --git a/pages/docs/features/inngest-functions/steps-workflows/step-ai-orchestration.mdx b/pages/docs/features/inngest-functions/steps-workflows/step-ai-orchestration.mdx
@@ -45,7 +45,7 @@ export default inngest.createFunction(
   async ({ event, step }) => {
 
     // Create a new agent with a system prompt (you can add optional tools, too)
-    const writer = new Agent({
+    const writer = createAgent({
       name: "writer",
       system: "You are an expert writer.  You write readable, concise, simple content.",
       model: openai({ model: "gpt-4o", step }),