Use @inngest/ai and optional step tooling

package.json

@@ -44,8 +44,9 @@
     }
   },
   "dependencies": {
+    "@inngest/ai": "^0.0.0",
     "express": "^4.21.1",
-    "inngest": "^3.29.0",
+    "inngest": "3.29.4-pr-802.0",
     "openai-zod-to-json-schema": "^1.0.3",
     "zod": "^3.23.8"
   },

src/adapters/anthropic.ts

@@ -7,7 +7,7 @@ import {
   type AiAdapter,
   type Anthropic,
   type AnthropicAiAdapter,
-} from "inngest";
+} from "@inngest/ai";
 import { zodToJsonSchema } from "openai-zod-to-json-schema";
 import { z } from "zod";
 import { type AgenticModel } from "../model";
@@ -21,12 +21,12 @@ export const requestParser: AgenticModel.RequestParser<Anthropic.AiModel> = (
   model,
   messages,
   tools,
-  tool_choice = "auto",
+  tool_choice = "auto"
 ) => {
   // Note that Anthropic has a top-level system prompt, then a series of prompts
   // for assistants and users.
   const systemMessage = messages.find(
-    (m) => m.role === "system" && m.type === "text",
+    (m) => m.role === "system" && m.type === "text"
   ) as TextMessage;
   const system =
     typeof systemMessage?.content === "string" ? systemMessage.content : "";
@@ -79,7 +79,7 @@ export const requestParser: AgenticModel.RequestParser<Anthropic.AiModel> = (
               ];
           }
         },
-        [] as AiAdapter.Input<Anthropic.AiModel>["messages"],
+        [] as AiAdapter.Input<Anthropic.AiModel>["messages"]
       );
 
   const request: AiAdapter.Input<Anthropic.AiModel> = {
@@ -97,7 +97,7 @@ export const requestParser: AgenticModel.RequestParser<Anthropic.AiModel> = (
         input_schema: (t.parameters
           ? zodToJsonSchema(t.parameters)
           : zodToJsonSchema(
-              z.object({}),
+              z.object({})
             )) as AnthropicAiAdapter.Tool.InputSchema,
       };
     });
@@ -111,7 +111,7 @@ export const requestParser: AgenticModel.RequestParser<Anthropic.AiModel> = (
  * Parse a response from Anthropic output to internal network messages.
  */
 export const responseParser: AgenticModel.ResponseParser<Anthropic.AiModel> = (
-  input,
+  input
 ) => {
   return (input?.content ?? []).reduce<Message[]>((acc, item) => {
     if (!item.type) {
@@ -165,7 +165,7 @@ export const responseParser: AgenticModel.ResponseParser<Anthropic.AiModel> = (
 };
 
 const toolChoice = (
-  choice: Tool.Choice,
+  choice: Tool.Choice
 ): AiAdapter.Input<Anthropic.AiModel>["tool_choice"] => {
   switch (choice) {
     case "auto":

src/adapters/index.ts

@@ -1,4 +1,4 @@
-import { type AiAdapter, type AiAdapters } from "inngest";
+import { type AiAdapter, type AiAdapters } from "@inngest/ai";
 import { type AgenticModel } from "../model";
 import * as anthropic from "./anthropic";
 import * as openai from "./openai";

src/adapters/openai.ts

@@ -4,7 +4,7 @@
  * @module
  */
 
-import { type AiAdapter, type OpenAi } from "inngest";
+import { type AiAdapter, type OpenAi } from "@inngest/ai";
 import { zodToJsonSchema } from "openai-zod-to-json-schema";
 import { type AgenticModel } from "../model";
 import {
@@ -23,7 +23,7 @@ export const requestParser: AgenticModel.RequestParser<OpenAi.AiModel> = (
   model,
   messages,
   tools,
-  tool_choice = "auto",
+  tool_choice = "auto"
 ) => {
   const request: AiAdapter.Input<OpenAi.AiModel> = {
     messages: messages.map((m) => {
@@ -82,7 +82,7 @@ export const requestParser: AgenticModel.RequestParser<OpenAi.AiModel> = (
  * Parse a response from OpenAI output to internal network messages.
  */
 export const responseParser: AgenticModel.ResponseParser<OpenAi.AiModel> = (
-  input,
+  input
 ) => {
   return (input?.choices ?? []).reduce<Message[]>((acc, choice) => {
     const { message, finish_reason } = choice;
@@ -149,12 +149,12 @@ const safeParseOpenAIJson = (str: string): unknown => {
       // Replace backtick strings with regular JSON strings
       // Match content between backticks, preserving newlines
       const withQuotes = trimmed.replace(/`([\s\S]*?)`/g, (_, content) =>
-        JSON.stringify(content),
+        JSON.stringify(content)
       );
       return JSON.parse(withQuotes);
     } catch (e) {
       throw new Error(
-        `Failed to parse JSON with backticks: ${stringifyError(e)}`,
+        `Failed to parse JSON with backticks: ${stringifyError(e)}`
       );
     }
   }

src/agent.ts

@@ -1,4 +1,4 @@
-import { type AiAdapter } from "inngest";
+import { type AiAdapter } from "@inngest/ai";
 import { createAgenticModelFromAiAdapter, type AgenticModel } from "./model";
 import { NetworkRun } from "./networkRun";
 import {
@@ -8,7 +8,7 @@ import {
   type ToolResultMessage,
 } from "./state";
 import { type Tool } from "./types";
-import { getStepTools, type AnyZodType, type MaybePromise } from "./util";
+import { type AnyZodType, type MaybePromise } from "./util";
 
 /**
  * createTool is a helper that properly types the input argument for a handler
@@ -108,7 +108,7 @@ export class Agent {
    */
   async run(
     input: string,
-    { model, network, state, maxIter = 0 }: Agent.RunOptions | undefined = {},
+    { model, network, state, maxIter = 0 }: Agent.RunOptions | undefined = {}
   ): Promise<InferenceResult> {
     const rawModel = model || this.model || network?.defaultModel;
     if (!rawModel) {
@@ -152,7 +152,7 @@ export class Agent {
         p,
         prompt,
         history,
-        run,
+        run
       );
 
       hasMoreActions =
@@ -183,13 +183,13 @@ export class Agent {
     p: AgenticModel.Any,
     prompt: Message[],
     history: Message[],
-    network?: NetworkRun,
+    network?: NetworkRun
   ): Promise<InferenceResult> {
     const { output, raw } = await p.infer(
       this.name,
       prompt.concat(history),
       Array.from(this.tools.values()),
-      this.tool_choice || "auto",
+      this.tool_choice || "auto"
     );
 
     // Now that we've made the call, we instantiate a new InferenceResult for
@@ -201,7 +201,7 @@ export class Agent {
       history,
       output,
       [],
-      typeof raw === "string" ? raw : JSON.stringify(raw),
+      typeof raw === "string" ? raw : JSON.stringify(raw)
     );
     if (this.lifecycles?.onResponse) {
       result = await this.lifecycles.onResponse({
@@ -223,7 +223,7 @@ export class Agent {
   private async invokeTools(
     msgs: Message[],
     p: AgenticModel.Any,
-    network?: NetworkRun,
+    network?: NetworkRun
   ): Promise<ToolResultMessage[]> {
     const output: ToolResultMessage[] = [];
 
@@ -240,7 +240,7 @@ export class Agent {
         const found = this.tools.get(tool.name);
         if (!found) {
           throw new Error(
-            `Inference requested a non-existent tool: ${tool.name}`,
+            `Inference requested a non-existent tool: ${tool.name}`
           );
         }
 
@@ -254,7 +254,7 @@ export class Agent {
         const result = await found.handler(tool.input, {
           agent: this,
           network,
-          step: await getStepTools(),
+          // step: await getStepTools(),
         });
 
         // TODO: handle error and send them back to the LLM
@@ -280,7 +280,7 @@ export class Agent {
 
   private async agentPrompt(
     input: string,
-    network?: NetworkRun,
+    network?: NetworkRun
   ): Promise<Message[]> {
     // Prompt returns the full prompt for the current agent.  This does NOT
     // include the existing network's state as part of the prompt.
@@ -401,7 +401,7 @@ export namespace Agent {
      * running tools.
      */
     onResponse?: (
-      args: Agent.LifecycleArgs.Result,
+      args: Agent.LifecycleArgs.Result
     ) => MaybePromise<InferenceResult>;
 
     /**
@@ -411,7 +411,7 @@ export namespace Agent {
      *
      */
     onFinish?: (
-      args: Agent.LifecycleArgs.Result,
+      args: Agent.LifecycleArgs.Result
     ) => MaybePromise<InferenceResult>;
   }