ci: linting, type checking and testing - fix

.changeset/floppy-carrots-fold.md

@@ -0,0 +1,9 @@
+---
+"@llamaindex/workflow": minor
+"@llamaindex/tools": minor
+"@llamaindex/core": minor
+"@llamaindex/resolution-tests": patch
+"@llamaindex/e2e": patch
+---
+
+Moving tools from zod to zod/v4; adding responseFormat to llm.exec

e2e/examples/vite-import-llamaindex/tsconfig.tsbuildinfo

@@ -1 +1 @@
-{"root":["./src/main.ts","./vite.config.ts"],"version":"5.7.3"}
+{"root":["./src/main.ts","./vite.config.ts"],"version":"5.8.3"}

e2e/node/fixtures/tools.ts

@@ -1,5 +1,5 @@
 import { FunctionTool } from "llamaindex";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 function sumNumbers({ a, b }: { a: number; b: number }) {
   return `${a + b}`;
@@ -13,12 +13,8 @@ export const sumNumbersTool = FunctionTool.from(sumNumbers, {
   name: "sumNumbers",
   description: "Use this function to sum two numbers",
   parameters: z.object({
-    a: z.number({
-      description: "The first number",
-    }),
-    b: z.number({
-      description: "The second number",
-    }),
+    a: z.number({}).describe("The first number"),
+    b: z.number({}).describe("The second number"),
   }),
 });
 
@@ -26,12 +22,8 @@ export const divideNumbersTool = FunctionTool.from(divideNumbers, {
   name: "divideNumbers",
   description: "Use this function to divide two numbers",
   parameters: z.object({
-    a: z.number({
-      description: "The first number",
-    }),
-    b: z.number({
-      description: "The second number",
-    }),
+    a: z.number({}).describe("The first number"),
+    b: z.number({}).describe("The second number"),
   }),
 });
 
@@ -44,9 +36,7 @@ export const getWeatherTool = FunctionTool.from(
     name: "getWeather",
     description: "Get the weather for a city",
     parameters: z.object({
-      city: z.string({
-        description: "The city to get the weather for",
-      }),
+      city: z.string({}).describe("The city to get the weather for"),
     }),
   },
 );

e2e/npm/test/workflow.e2e.ts

@@ -3,7 +3,7 @@ import { agent } from "@llamaindex/workflow";
 import { Settings, tool } from "llamaindex";
 import { ok } from "node:assert";
 import { test } from "node:test";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 Settings.llm = new OpenAI({ model: "gpt-4-0613" });
 

examples/agents/agent/blog-writer.ts

@@ -8,7 +8,7 @@ import {
 import fs from "fs";
 import { tool } from "llamaindex";
 import os from "os";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 import { wiki } from "@llamaindex/tools";
 const llm = openai({
@@ -20,9 +20,7 @@ const saveFileTool = tool({
   description:
     "Save the written content into a file that can be downloaded by the user",
   parameters: z.object({
-    content: z.string({
-      description: "The content to save into a file",
-    }),
+    content: z.string().describe("The content to save into a file"),
   }),
   execute: ({ content }: { content: string }) => {
     const filePath = os.tmpdir() + "/report.md";

examples/agents/agent/large-toolcall.ts

@@ -1,7 +1,7 @@
 import { OpenAI } from "@llamaindex/openai";
 import { agent } from "@llamaindex/workflow";
 import { tool } from "llamaindex";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 const csvData =
   "TITLE,RELEASE_YEAR,SCORE,NUMBER_OF_VOTES,DURATION,MAIN_GENRE,MAIN_PRODUCTION\nDavid Attenborough: A Life on Our Planet,2020,9,31180,83,documentary,GB\nInception,2010,8.8,2268288,148,scifi,GB\nForrest Gump,1994,8.8,1994599,142,drama,US\nAnbe Sivam,2003,8.7,20595,160,comedy,IN\nBo Burnham: Inside,2021,8.7,44074,87,comedy,US\nSaving Private Ryan,1998,8.6,1346020,169,drama,US\nDjango Unchained,2012,8.4,1472668,165,western,US\nDangal,2016,8.4,180247,161,action,IN\nBo Burnham: Make Happy,2016,8.4,14356,60,comedy,US\nLouis C.K.: Hilarious,2010,8.4,11973,84,comedy,US\nDave Chappelle: Sticks & Stones,2019,8.4,25687,65,comedy,US\n3 Idiots,2009,8.4,385782,170,comedy,IN\nBlack Friday,2004,8.4,20611,143,crime,IN\nSuper Deluxe,2019,8.4,13680,176,thriller,IN\nWinter on Fire: Ukraine's Fight for Freedom,2015,8.3,17710,98,documentary,UA\nOnce Upon a Time in America,1984,8.3,342335,229,drama,US\nTaxi Driver,1976,8.3,795222,113,crime,US\nLike Stars on Earth,2007,8.3,188234,165,drama,IN\nBo Burnham: What.,2013,8.3,11488,60,comedy,US\nFull Metal Jacket,1987,8.3,723306,116,drama,GB\nWarrior,2011,8.2,463276,140,drama,US\nDrishyam,2015,8.2,79075,163,thriller,IN\nQueen,2014,8.2,64805,146,drama,IN\nPaan Singh Tomar,2012,8.2,35888,135,drama,IN";
@@ -17,9 +17,7 @@ const userQuestion = "which are the best comedies after 2010?";
     description:
       "Execute python code in a Jupyter notebook cell and return any result, stdout, stderr, display_data, and error.",
     parameters: z.object({
-      code: z.string({
-        description: "The python code to execute in a single cell.",
-      }),
+      code: z.string().describe("The python code to execute in a single cell."),
     }),
     execute: ({ code }) => {
       console.log(

examples/agents/agent/multiple-agents.ts

@@ -15,7 +15,7 @@ import {
   stopAgentEvent,
 } from "@llamaindex/workflow";
 import { tool } from "llamaindex";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 const llm = openai({
   model: "gpt-4o-mini",
@@ -26,9 +26,7 @@ const temperatureConverterTool = tool({
   description: "Convert a temperature from Fahrenheit to Celsius",
   name: "fahrenheitToCelsius",
   parameters: z.object({
-    temperature: z.number({
-      description: "The temperature in Fahrenheit",
-    }),
+    temperature: z.number().describe("The temperature in Fahrenheit"),
   }),
   execute: ({ temperature }) => {
     return ((temperature - 32) * 5) / 9;
@@ -39,9 +37,7 @@ const temperatureFetcherTool = tool({
   description: "Fetch the temperature (in Fahrenheit) for a city",
   name: "fetchTemperature",
   parameters: z.object({
-    city: z.string({
-      description: "The city to fetch the temperature for",
-    }),
+    city: z.string().describe("The city to fetch the temperature for"),
   }),
   execute: ({ city }) => {
     const temperature = Math.floor(Math.random() * 58) + 32;

examples/agents/agent/openai.ts

@@ -1,7 +1,7 @@
 import { openai } from "@llamaindex/openai";
 import { agent } from "@llamaindex/workflow";
 import { tool } from "llamaindex";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 const sumNumbers = tool({
   name: "sumNumbers",

examples/agents/agent/with-anthropic.ts

@@ -6,7 +6,7 @@ import {
 } from "@llamaindex/workflow";
 import fs from "fs";
 import { tool } from "llamaindex";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 import { anthropic } from "@llamaindex/anthropic";
 
@@ -14,9 +14,7 @@ const weatherTool = tool({
   name: "weather",
   description: "Get the weather",
   parameters: z.object({
-    location: z.string({
-      description: "The location to get the weather for",
-    }),
+    location: z.string().describe("The location to get the weather for"),
   }),
   execute: ({ location }) => {
     return `The weather in ${location} is sunny`;
@@ -27,9 +25,7 @@ const inflationTool = tool({
   name: "inflation",
   description: "Get the inflation",
   parameters: z.object({
-    location: z.string({
-      description: "The location to get the inflation for",
-    }),
+    location: z.string().describe("The location to get the inflation for"),
   }),
   execute: ({ location }) => {
     return `The inflation in ${location} is 2%`;
@@ -41,9 +37,7 @@ const saveFileTool = tool({
   description:
     "Save the written content into a file that can be downloaded by the user",
   parameters: z.object({
-    content: z.string({
-      description: "The content to save into a file",
-    }),
+    content: z.string().describe("The content to save into a file"),
   }),
   execute: ({ content }) => {
     const filePath = "./report.md";

examples/agents/tools/exec-stream.ts

@@ -1,6 +1,6 @@
 import { openai } from "@llamaindex/openai";
 import { tool } from "llamaindex";
-import z from "zod";
+import * as z from "zod/v4";
 
 import { ChatMessage } from "llamaindex";
 

examples/agents/tools/exec.ts

@@ -1,6 +1,6 @@
 import { openai } from "@llamaindex/openai";
 import { ChatMessage, tool } from "llamaindex";
-import z from "zod";
+import * as z from "zod/v4";
 
 async function main() {
   const llm = openai({ model: "gpt-4.1-mini" });

examples/agents/tools/structured-response.ts

@@ -0,0 +1,38 @@
+import { Anthropic } from "@llamaindex/anthropic";
+import { ChatMessage, ToolCall } from "llamaindex";
+import * as z from "zod/v4";
+
+const llm = new Anthropic({ model: "claude-4-0-sonnet" });
+
+const responseSchema = z.object({
+  title: z.string(),
+  author: z.string(),
+  year: z.number(),
+});
+
+async function main() {
+  const messages: ChatMessage[] = [];
+  let toolCalls: ToolCall[] = [];
+  do {
+    const result = await llm.exec({
+      messages: [
+        {
+          role: "system",
+          content: `You are a book expert. Your task is, given a user message, extract the title, author and publication year of the book and output them in JSON format.`,
+        },
+        {
+          role: "user",
+          content: `I have been reading La Divina Commedia by Dante Alighieri, published in 1321, which tells the story of a guy who goes through Hell, Purgatory and Heaven just to meet his beloved ex-girlfriend.`,
+        },
+      ],
+      responseFormat: responseSchema,
+    });
+    messages.push(...result.newMessages);
+    toolCalls = result.toolCalls;
+  } while (toolCalls.length == 0);
+
+  console.log(messages[1].content);
+  console.log(toolCalls);
+}
+
+main().catch(console.error);

examples/agents/tools/tools.ts

@@ -1,5 +1,5 @@
 import { tool } from "llamaindex";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 export const getCurrentIDTool = tool({
   name: "get_user_id",

examples/deprecated/agents/large_toolcall_with_gpt4o.ts

@@ -1,6 +1,6 @@
 import { OpenAI } from "@llamaindex/openai";
 import { FunctionTool, ToolCallOptions } from "llamaindex";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 (async () => {
   // The tool call will generate a partial JSON for `gpt-4-turbo`
@@ -29,9 +29,9 @@ async function callLLM(init: { model: string }) {
       description:
         "Execute python code in a Jupyter notebook cell and return any result, stdout, stderr, display_data, and error.",
       parameters: z.object({
-        code: z.string({
-          description: "The python code to execute in a single cell.",
-        }),
+        code: z
+          .string()
+          .describe("The python code to execute in a single cell."),
       }),
     },
   );

examples/deprecated/agents/retriever_openai_agent.ts

@@ -6,7 +6,7 @@ import {
   NodeWithScore,
   VectorStoreIndex,
 } from "llamaindex";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 async function main() {
   // Load the documents

examples/deprecated/agents/stream_openai_agent.ts

@@ -1,6 +1,6 @@
 import { OpenAIAgent } from "@llamaindex/openai";
 import { FunctionTool } from "llamaindex";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 // Define a function to sum two numbers
 function sumNumbers({ a, b }: { a: number; b: number }) {

examples/models/anthropic/agent.ts

@@ -2,7 +2,7 @@ import { anthropic } from "@llamaindex/anthropic";
 import { wiki } from "@llamaindex/tools";
 import { agent } from "@llamaindex/workflow";
 import { tool } from "llamaindex";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 const workflow = agent({
   tools: [

examples/models/gemini/agent.ts

@@ -1,8 +1,7 @@
 import { gemini, GEMINI_MODEL } from "@llamaindex/google";
 import { agent } from "@llamaindex/workflow";
 import { tool } from "llamaindex";
-import { z } from "zod";
-
+import * as z from "zod/v4";
 const sumNumbers = tool({
   name: "sumNumbers",
   description: "Use this function to sum two numbers",

examples/models/gemini/chat.ts

@@ -1,8 +1,7 @@
 import { gemini, GEMINI_MODEL } from "@llamaindex/google";
 import fs from "fs";
 import { tool } from "llamaindex";
-import { z } from "zod";
-
+import * as z from "zod/v4";
 (async () => {
   if (!process.env.GOOGLE_API_KEY) {
     throw new Error("Please set the GOOGLE_API_KEY environment variable.");

examples/models/gemini/live/tool-call.ts

@@ -2,15 +2,13 @@ import { gemini, GEMINI_MODEL } from "@llamaindex/google";
 import { ModalityType, tool } from "llamaindex";
 
 import { liveEvents } from "llamaindex";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 const weatherTool = tool({
   name: "weather",
   description: "Get the weather",
   parameters: z.object({
-    location: z.string({
-      description: "The location to get the weather for",
-    }),
+    location: z.string().describe("The location to get the weather for"),
   }),
   execute: ({ location }) => {
     return `The weather in ${location} is rainy`;

examples/models/mistral/agent.ts

@@ -3,7 +3,7 @@ import { wiki } from "@llamaindex/tools";
 import { agent } from "@llamaindex/workflow";
 import { tool } from "llamaindex";
 
-import { z } from "zod";
+import * as z from "zod/v4";
 
 const workflow = agent({
   tools: [

examples/models/openai/responses/agent.ts

@@ -2,7 +2,7 @@ import { openaiResponses } from "@llamaindex/openai";
 import { wiki } from "@llamaindex/tools";
 import { agent } from "@llamaindex/workflow";
 import { tool } from "llamaindex";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 const workflow = agent({
   tools: [

examples/models/openai/responses/tool-call.ts

@@ -1,15 +1,13 @@
 import { openaiResponses } from "@llamaindex/openai";
 import { tool } from "llamaindex";
 
-import { z } from "zod";
+import * as z from "zod/v4";
 async function main() {
   const weatherTool = tool({
     name: "weather",
     description: "Get the weather",
     parameters: z.object({
-      location: z.string({
-        description: "The location to get the weather for",
-      }),
+      location: z.string().describe("The location to get the weather for"),
     }),
     execute: ({ location }) => {
       return `The weather in ${location} is sunny`;

packages/core/src/llms/base.ts

@@ -1,4 +1,6 @@
 import { emptyLogger } from "@llamaindex/env";
+import type { JSONObject } from "../global";
+import { tool } from "../tools/";
 import { extractText } from "../utils/llms";
 import { streamConverter } from "../utils/stream";
 import { callToolToMessage, getToolCallsFromResponse } from "./tool-call";
@@ -18,6 +20,7 @@ import type {
   PartialToolCall,
   ToolCallLLMMessageOptions,
 } from "./type";
+import { isZodSchema } from "./utils";
 
 export abstract class BaseLLM<
   AdditionalChatOptions extends object = object,
@@ -97,6 +100,31 @@ export abstract class BaseLLM<
     | ExecResponse<AdditionalMessageOptions>
     | ExecStreamResponse<AdditionalMessageOptions>
   > {
+    const responseFormat = params.responseFormat;
+    if (responseFormat && isZodSchema(responseFormat)) {
+      const structuredTool = tool({
+        name: "format_output",
+        description: "Respond with a JSON object",
+        parameters: responseFormat,
+        execute: (args) => {
+          const result = responseFormat.safeParse(args);
+          if (!result.success) {
+            console.error("Invalid input from LLM:", result.error);
+            return JSON.stringify({
+              error: "Invalid schema",
+              details: result.error,
+            });
+          }
+          return result.data as JSONObject;
+        },
+      });
+      if (Array.isArray(params.tools)) {
+        params.tools.push(structuredTool);
+      } else {
+        params.tools = [structuredTool];
+      }
+      params.responseFormat = undefined;
+    }
     if (params.stream) {
       return this.streamExec(params);
     }

packages/core/src/llms/utils.ts

@@ -1,3 +1,4 @@
+import * as z from "zod/v4";
 import type {
   ChatMessage,
   MessageContentImageDataDetail,
@@ -26,3 +27,15 @@ export function addContentPart<AdditionalMessageOptions extends object>(
     }
   }
 }
+
+export function isZodSchema(obj: unknown): obj is z.ZodType {
+  return (
+    obj !== null &&
+    typeof obj === "object" &&
+    "parse" in obj &&
+    typeof (obj as { parse: unknown }).parse === "function" &&
+    "safeParse" in obj &&
+    typeof (obj as { safeParse: unknown }).safeParse === "function" &&
+    "_def" in obj
+  );
+}

packages/core/src/tools/function-tool.ts

@@ -1,7 +1,6 @@
 import { consoleLogger, type Logger } from "@llamaindex/env";
 import type { JSONSchemaType } from "ajv";
-import { z } from "zod";
-import { zodToJsonSchema } from "zod-to-json-schema";
+import * as z from "zod/v4";
 import type { JSONValue } from "../global";
 import type { BaseTool, ToolMetadata } from "../llms";
 
@@ -94,8 +93,8 @@ export class FunctionTool<
     ) {
       const { execute, parameters, ...restConfig } = fnOrConfig;
 
-      if (parameters instanceof z.ZodSchema) {
-        const jsonSchema = zodToJsonSchema(parameters);
+      if (parameters instanceof z.ZodType) {
+        const jsonSchema = z.toJSONSchema(parameters);
         return new FunctionTool(
           execute,
           {
@@ -110,8 +109,8 @@ export class FunctionTool<
     }
 
     // Handle the original cases
-    if (schema && schema.parameters instanceof z.ZodSchema) {
-      const jsonSchema = zodToJsonSchema(schema.parameters);
+    if (schema && schema.parameters instanceof z.ZodType) {
+      const jsonSchema = z.toJSONSchema(schema.parameters);
       return new FunctionTool(
         fnOrConfig,
         {

packages/core/tests/tools.test.ts

@@ -1,6 +1,6 @@
 import { FunctionTool, tool } from "@llamaindex/core/tools";
 import { describe, expect, test, vi } from "vitest";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 describe("FunctionTool", () => {
   test("type system", () => {
@@ -37,9 +37,7 @@ describe("FunctionTool", () => {
       name: "saveFile",
       description: "Save the content into a file",
       parameters: z.object({
-        content: z.string({
-          description: "The content to save into a file",
-        }),
+        content: z.string({}).describe("The content to save into a file"),
       }),
       execute: mockExecute,
     };

packages/tools/src/tools/code-artifact-generator.ts

@@ -1,7 +1,7 @@
 import { Settings, type JSONValue } from "@llamaindex/core/global";
 import type { ChatMessage, LLM } from "@llamaindex/core/llms";
 import { tool } from "@llamaindex/core/tools";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 const CODE_ARTIFACT_GENERATION_PROMPT = `You are a highly skilled software engineer. Your task is to generate a code artifact based on the user's request.
 Follow these instructions exactly:

packages/tools/src/tools/code-generator.ts

@@ -1,7 +1,7 @@
 import { Settings, type JSONValue } from "@llamaindex/core/global";
 import type { ChatMessage } from "@llamaindex/core/llms";
 import { tool } from "@llamaindex/core/tools";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 // prompt based on https://github.com/e2b-dev/ai-artifacts
 const CODE_GENERATION_PROMPT = `You are a skilled software engineer. You do not make mistakes. Generate an artifact. You can install additional dependencies. You can use one of the following templates:\n

packages/tools/src/tools/document-artifact-generator.ts

@@ -1,7 +1,7 @@
 import { Settings, type JSONValue } from "@llamaindex/core/global";
 import type { ChatMessage, LLM } from "@llamaindex/core/llms";
 import { tool } from "@llamaindex/core/tools";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 const DOCUMENT_ARTIFACT_GENERATION_PROMPT = `You are a highly skilled content creator. Your task is to generate a document artifact based on the user's request.
 Follow these instructions exactly:

packages/tools/src/tools/document-generator.ts

@@ -1,7 +1,7 @@
 import { tool } from "@llamaindex/core/tools";
 import { marked } from "marked";
 import path from "node:path";
-import { z } from "zod";
+import * as z from "zod/v4";
 import { getFileUrl, saveDocument } from "../helper";
 
 const COMMON_STYLES = `

packages/tools/src/tools/duckduckgo.ts

@@ -1,6 +1,6 @@
 import { tool } from "@llamaindex/core/tools";
 import { search } from "duck-duck-scrape";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 export type DuckDuckGoToolOutput = Array<{
   title: string;

packages/tools/src/tools/form-filling.ts

@@ -3,7 +3,7 @@ import { tool } from "@llamaindex/core/tools";
 import fs from "fs";
 import Papa from "papaparse";
 import path from "path";
-import { z } from "zod";
+import * as z from "zod/v4";
 import { getFileUrl, saveDocument } from "../helper";
 
 export type MissingCell = {

packages/tools/src/tools/img-gen.ts

@@ -4,7 +4,7 @@ import { FormData } from "formdata-node";
 import got from "got";
 import path from "path";
 import { Readable } from "stream";
-import { z } from "zod";
+import * as z from "zod/v4";
 import { getFileUrl, saveDocument } from "../helper";
 
 export type ImgGeneratorToolOutput = {

packages/tools/src/tools/interpreter.ts

@@ -3,7 +3,7 @@ import { tool } from "@llamaindex/core/tools";
 import { randomUUID } from "@llamaindex/env";
 import fs from "fs";
 import path from "node:path";
-import { z } from "zod";
+import * as z from "zod/v4";
 import { getFileUrl, saveDocument } from "../helper";
 
 export type InterpreterExtraType =

packages/tools/src/tools/weather.ts

@@ -1,5 +1,5 @@
 import { tool } from "@llamaindex/core/tools";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 export type WeatherToolOutput = {
   latitude: number;

packages/tools/src/tools/wiki.ts

@@ -1,6 +1,6 @@
 import { tool } from "@llamaindex/core/tools";
 import { default as wikipedia } from "wikipedia";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 export type WikiToolOutput = {
   title: string;

packages/workflow/src/agent/agent-workflow.ts

@@ -17,7 +17,7 @@ import {
   type WorkflowEventData,
 } from "@llamaindex/workflow-core";
 import { createStatefulMiddleware } from "@llamaindex/workflow-core/middleware/state";
-import { z } from "zod";
+import * as z from "zod/v4";
 import type { AgentWorkflowState, BaseWorkflowAgent } from "./base";
 import {
   agentInputEvent,
@@ -680,12 +680,8 @@ export class AgentWorkflow implements Workflow {
         agent_info: JSON.stringify(agentInfo),
       }),
       parameters: z.object({
-        toAgent: z.string({
-          description: "The name of the agent to hand off to",
-        }),
-        reason: z.string({
-          description: "The reason for handing off to the agent",
-        }),
+        toAgent: z.string({}).describe("The name of the agent to hand off to"),
+        reason: z.string({}).describe("The content to save into a file"),
       }),
       execute: (
         {

packages/workflow/src/agent/function-agent.ts

@@ -11,8 +11,7 @@ import {
   type WorkflowContext,
   type WorkflowEvent,
 } from "@llamaindex/workflow-core";
-import { z } from "zod";
-import { zodToJsonSchema } from "zod-to-json-schema";
+import * as z from "zod/v4";
 import { AgentWorkflow } from "./agent-workflow";
 import { type AgentWorkflowState, type BaseWorkflowAgent } from "./base";
 import {
@@ -416,7 +415,7 @@ const createEventEmitterTool = (
       event.schema.description ??
       "Use this tool to send the event to the workflow.") +
     `\n\nPlease provide the event data in the following JSON schema: ${JSON.stringify(
-      zodToJsonSchema(z.object({ eventData: event.schema })),
+      z.toJSONSchema(z.object({ eventData: event.schema })),
     )}`;
   return tool({
     name: name,

packages/workflow/test/agent-workflow.test.ts

@@ -3,7 +3,7 @@ import { MockLLM } from "@llamaindex/core/llms/mock";
 import { FunctionTool } from "@llamaindex/core/tools";
 import { Logger } from "@llamaindex/env";
 import { describe, expect, test, vi } from "vitest";
-import { z } from "zod";
+import * as z from "zod/v4";
 import {
   AgentWorkflow,
   FunctionAgent,

packages/workflow/test/function-agent.test.ts

@@ -4,7 +4,8 @@ import { tool } from "@llamaindex/core/tools";
 import { type WorkflowContext } from "@llamaindex/workflow-core";
 import { zodEvent } from "@llamaindex/workflow-core/util/zod";
 import { describe, expect, test, vi } from "vitest";
-import { z } from "zod";
+import { z as zod } from "zod";
+import * as z from "zod/v4";
 import { AgentToolCallResult, FunctionAgent } from "../src/agent";
 
 const mockLLM = new MockLLM();
@@ -81,8 +82,8 @@ describe("FunctionAgent", () => {
 
     // Create a result event
     const resultEvent = zodEvent(
-      z.object({
-        value: z.string(),
+      zod.object({
+        value: zod.string(),
       }),
       {
         debugLabel: "my_result_event",
@@ -91,8 +92,8 @@ describe("FunctionAgent", () => {
 
     // Create an additional event
     const additionalEvent = zodEvent(
-      z.object({
-        value: z.number(),
+      zod.object({
+        value: zod.number(),
       }),
       {
         debugLabel: "additional_event",

resolution-tests/src/index.e2e.ts

@@ -2,7 +2,7 @@ import { agent } from "@llamaindex/workflow";
 import { Document, Settings, tool } from "llamaindex";
 import { ok } from "node:assert";
 import { test } from "node:test";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 import { openai } from "@llamaindex/openai";
 import { VectorStoreIndex } from "llamaindex";

unit/tools/function-tool.test.ts

@@ -1,6 +1,6 @@
 import { FunctionTool } from "@llamaindex/core/tools";
 import { describe, expect, test } from "vitest";
-import { z } from "zod";
+import * as z from "zod/v4";
 
 describe("function-tool", () => {
   test("zod type check", () => {