Agents SDK v0.3.0, workers-ai-provider v3.0.0, and ai-gateway-provider v3.0.0 with AI SDK v6 support
We've shipped a new release for the Agents SDK ↗ v0.3.0 bringing full compatibility with AI SDK v6 ↗ and introducing the unified tool pattern, dynamic tool approval, and enhanced React hooks with improved tool handling.
This release includes improved streaming and tool support, dynamic tool approval (for "human in the loop" systems), enhanced React hooks with onToolCall callback, improved error handling for streaming responses, and seamless migration from v5 patterns.
This makes it ideal for building production AI chat interfaces with Cloudflare Workers AI models, agent workflows, human-in-the-loop systems, or any application requiring reliable tool execution and approval workflows.
Additionally, we've updated workers-ai-provider v3.0.0, the official provider for Cloudflare Workers AI models, and ai-gateway-provider v3.0.0, the provider for Cloudflare AI Gateway, to be compatible with AI SDK v6.
AI SDK v6 introduces a unified tool pattern where all tools are defined on the server using the tool() function. This replaces the previous client-side AITool pattern.
import { tool } from "ai";
import { z } from "zod";
// Server: Define ALL tools on the server
const tools = {
// Server-executed tool
getWeather: tool({
description: "Get weather for a city",
inputSchema: z.object({ city: z.string() }),
execute: async ({ city }) => fetchWeather(city)
}),
// Client-executed tool (no execute = client handles via onToolCall)
getLocation: tool({
description: "Get user location from browser",
inputSchema: z.object({})
// No execute function
}),
// Tool requiring approval (dynamic based on input)
processPayment: tool({
description: "Process a payment",
inputSchema: z.object({ amount: z.number() }),
needsApproval: async ({ amount }) => amount > 100,
execute: async ({ amount }) => charge(amount)
})
};// Client: Handle client-side tools via onToolCall callback
import { useAgentChat } from "agents/ai-react";
const { messages, sendMessage, addToolOutput } = useAgentChat({
agent,
onToolCall: async ({ toolCall, addToolOutput }) => {
if (toolCall.toolName === "getLocation") {
const position = await new Promise((resolve, reject) => {
navigator.geolocation.getCurrentPosition(resolve, reject);
});
addToolOutput({
toolCallId: toolCall.toolCallId,
output: {
lat: position.coords.latitude,
lng: position.coords.longitude
}
});
}
}
});Key benefits of the unified tool pattern:
- Server-defined tools: All tools are defined in one place on the server
- Dynamic approval: Use
needsApprovalto conditionally require user confirmation - Cleaner client code: Use
onToolCallcallback instead of managing tool configs - Type safety: Full TypeScript support with proper tool typing
Creates a new chat interface with enhanced v6 capabilities.
// Basic chat setup with onToolCall
const { messages, sendMessage, addToolOutput } = useAgentChat({
agent,
onToolCall: async ({ toolCall, addToolOutput }) => {
// Handle client-side tool execution
await addToolOutput({
toolCallId: toolCall.toolCallId,
output: { result: "success" }
});
}
});Use needsApproval on server tools to conditionally require user confirmation:
const paymentTool = tool({
description: "Process a payment",
inputSchema: z.object({
amount: z.number(),
recipient: z.string()
}),
needsApproval: async ({ amount }) => amount > 1000,
execute: async ({ amount, recipient }) => {
return await processPayment(amount, recipient);
}
});The isToolUIPart and getToolName functions now check both static and dynamic tool parts:
import { isToolUIPart, getToolName } from "ai";
const pendingToolCallConfirmation = messages.some((m) =>
m.parts?.some(
(part) => isToolUIPart(part) && part.state === "input-available",
),
);
// Handle tool confirmation
if (pendingToolCallConfirmation) {
await addToolOutput({
toolCallId: part.toolCallId,
output: "User approved the action"
});
}If you need the v5 behavior (static-only checks), use the new functions:
import { isStaticToolUIPart, getStaticToolName } from "ai";The convertToModelMessages() function is now asynchronous. Update all calls to await the result:
import { convertToModelMessages } from "ai";
const result = streamText({
messages: await convertToModelMessages(this.messages),
model: openai("gpt-4o")
});The CoreMessage type has been removed. Use ModelMessage instead:
import { convertToModelMessages, type ModelMessage } from "ai";
const modelMessages: ModelMessage[] = await convertToModelMessages(messages);The mode option for generateObject has been removed:
// Before (v5)
const result = await generateObject({
mode: "json",
model,
schema,
prompt
});
// After (v6)
const result = await generateObject({
model,
schema,
prompt
});While generateObject and streamObject are still functional, the recommended approach is to use generateText/streamText with the Output.object() helper:
import { generateText, Output, stepCountIs } from "ai";
const { output } = await generateText({
model: openai("gpt-4"),
output: Output.object({
schema: z.object({ name: z.string() })
}),
stopWhen: stepCountIs(2),
prompt: "Generate a name"
});Note: When using structured output with
generateText, you must configure multiple steps withstopWhenbecause generating the structured output is itself a step.
Seamless integration with Cloudflare Workers AI models through the updated workers-ai-provider v3.0.0 with AI SDK v6 support.
Use Cloudflare Workers AI models directly in your agent workflows:
import { createWorkersAI } from "workers-ai-provider";
import { useAgentChat } from "agents/ai-react";
// Create Workers AI model (v3.0.0 - enhanced v6 internals)
const model = createWorkersAI({
binding: env.AI,
})("@cf/meta/llama-3.2-3b-instruct");Workers AI models now support v6 file handling with automatic conversion:
// Send images and files to Workers AI models
sendMessage({
role: "user",
parts: [
{ type: "text", text: "Analyze this image:" },
{
type: "file",
data: imageBuffer,
mediaType: "image/jpeg",
},
],
});
// Workers AI provider automatically converts to proper formatEnhanced streaming support with automatic warning detection:
// Streaming with Workers AI models
const result = await streamText({
model: createWorkersAI({ binding: env.AI })("@cf/meta/llama-3.2-3b-instruct"),
messages: await convertToModelMessages(messages),
onChunk: (chunk) => {
// Enhanced streaming with warning handling
console.log(chunk);
},
});The ai-gateway-provider v3.0.0 now supports AI SDK v6, enabling you to use Cloudflare AI Gateway with multiple AI providers including Anthropic, Azure, AWS Bedrock, Google Vertex, and Perplexity.
Use Cloudflare AI Gateway to add analytics, caching, and rate limiting to your AI applications:
import { createAIGateway } from "ai-gateway-provider";
// Create AI Gateway provider (v3.0.0 - enhanced v6 internals)
const model = createAIGateway({
gatewayUrl: "https://gateway.ai.cloudflare.com/v1/your-account-id/gateway",
headers: {
"Authorization": `Bearer ${env.AI_GATEWAY_TOKEN}`
}
})({
provider: "openai",
model: "gpt-4o"
});The following APIs are deprecated in favor of the unified tool pattern:
| Deprecated | Replacement |
|---|---|
AITool type |
Use AI SDK's tool() function on server |
extractClientToolSchemas() |
Define tools on server, no client schemas needed |
createToolsFromClientSchemas() |
Define tools on server with tool() |
toolsRequiringConfirmation option |
Use needsApproval on server tools |
experimental_automaticToolResolution |
Use onToolCall callback |
tools option in useAgentChat |
Use onToolCall for client-side execution |
addToolResult() |
Use addToolOutput() |
- Unified Tool Pattern: All tools must be defined on the server using
tool() convertToModelMessages()is async: Addawaitto all callsCoreMessageremoved: UseModelMessageinsteadgenerateObjectmode removed: RemovemodeoptionisToolUIPartbehavior changed: Now checks both static and dynamic tool parts
Update your dependencies to use the latest versions:
npm install agents@^0.3.0 workers-ai-provider@^3.0.0 ai-gateway-provider@^3.0.0 ai@^6.0.0 @ai-sdk/react@^3.0.0 @ai-sdk/openai@^3.0.0- Migration Guide ↗ - Comprehensive migration documentation from v5 to v6
- AI SDK v6 Documentation ↗ - Official AI SDK migration guide
- AI SDK v6 Announcement ↗ - Learn about new features in v6
- AI SDK Documentation ↗ - Complete AI SDK reference
- GitHub Issues ↗ - Report bugs or request features
We'd love your feedback! We're particularly interested in feedback on:
- Migration experience - How smooth was the upgrade from v5 to v6?
- Unified tool pattern - How does the new server-defined tool pattern work for you?
- Dynamic tool approval - Does the
needsApprovalfeature meet your needs? - AI Gateway integration - How well does the new provider work with your setup?
