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import { RENDER_A2UI_TOOL } from "@ag-ui/a2ui-middleware";
import type {
BaseEvent,
RunAgentInput,
Message,
ContentPart,
ReasoningEndEvent,
ReasoningMessageContentEvent,
ReasoningMessageEndEvent,
ReasoningMessageStartEvent,
ReasoningStartEvent,
RunFinishedEvent,
RunStartedEvent,
TextMessageChunkEvent,
ToolCallArgsEvent,
ToolCallEndEvent,
ToolCallStartEvent,
ToolCallResultEvent,
RunErrorEvent,
Interrupt,
ResumeEntry,
ToolMessage,
} from "@ag-ui/client";
import { AbstractAgent, EventType, PROTOCOL_VERSION } from "@ag-ui/client";
import { Validator } from "@cfworker/json-schema";
import type { AgentCapabilities } from "@ag-ui/core";
import type {
LanguageModel,
ModelMessage,
AssistantModelMessage,
UserModelMessage,
ToolModelMessage,
SystemModelMessage,
ToolCallPart,
ToolResultPart,
TextPart,
ImagePart,
FilePart,
ToolChoice,
ToolSet,
Schema,
} from "ai";
import { streamText, tool as createVercelAISDKTool, stepCountIs } from "ai";
import { createMCPClient } from "@ai-sdk/mcp";
import type { MCPClient, MCPTransport } from "@ai-sdk/mcp";
import { Observable } from "rxjs";
import { createOpenAI } from "@ai-sdk/openai";
import { createAnthropic } from "@ai-sdk/anthropic";
import { createGoogleGenerativeAI } from "@ai-sdk/google";
import { createVertex } from "@ai-sdk/google-vertex";
import { safeParseToolArgs, classifyModelHost } from "@copilotkit/shared";
import type { ModelHostClass } from "@copilotkit/shared";
import { z } from "zod";
import type { StandardSchemaV1, InferSchemaOutput } from "@copilotkit/shared";
import { schemaToJsonSchema } from "@copilotkit/shared";
import { jsonSchema as aiJsonSchema } from "ai";
import type { Experimental_DownloadFunction } from "ai";
import { logModelCallError, resolveUrlDownloadSetting } from "./url-download";
import type { SafeUrlDownloadOptions } from "./url-download";
import {
convertAISDKStream,
formatToolError,
getAISDKRunFinishedDetails,
resolveStreamPartMessageId,
} from "./converters/aisdk";
import { convertTanStackStream } from "./converters/tanstack";
import {
collectStandardRunFinishedDetails,
getNonEmptyString,
isRecord,
} from "./converters/usage";
import type { AgentRunFinishedDetails } from "./converters/usage";
import { createStateEventNormalizer } from "./state-delta";
import { describeEndpoint } from "../v1-deprecated/lib/runtime/mcp-client-cache";
import type { StreamableHTTPClientTransportOptions } from "@modelcontextprotocol/sdk/client/streamableHttp.js";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp.js";
import { randomUUID } from "@copilotkit/shared";
import { SkillRegistry } from "../v2/runtime/intelligence-platform/skill-registry";
import {
prepareLearnedSkills,
assertNoSkillToolConflicts,
} from "./learned-skills";
import type {
BuiltInAgentLearnedSkills,
BuiltInAgentLearnedSkillsOptions,
} from "./learned-skills";
export type {
BuiltInAgentLearnedSkills,
BuiltInAgentLearnedSkillsOptions,
} from "./learned-skills";
import { mergeMCPTools, toToolNamePrefix } from "./mcp-tool-names";
import type { MCPToolSource } from "./mcp-tool-names";
/**
* Properties that can be overridden by forwardedProps
* These match the exact parameter names in streamText
*/
export type OverridableProperty =
| "model"
| "toolChoice"
| "maxOutputTokens"
| "temperature"
| "topP"
| "topK"
| "presencePenalty"
| "frequencyPenalty"
| "stopSequences"
| "seed"
| "maxRetries"
| "prompt"
| "providerOptions";
/**
* Model identifiers for BuiltInAgent. The named entries are editor
* suggestions, not an allowlist: any provider model id is sent through
* unchanged.
*/
export type BuiltInAgentModel =
// OpenAI models
| "openai/gpt-5.5"
| "openai/gpt-5.4"
| "openai/gpt-5.4-mini"
| "openai/gpt-5"
| "openai/gpt-5-mini"
| "openai/gpt-4.1"
| "openai/gpt-4.1-mini"
| "openai/gpt-4.1-nano"
| "openai/gpt-4o"
| "openai/gpt-4o-mini"
// OpenAI reasoning series
| "openai/o3"
| "openai/o3-mini"
| "openai/o4-mini"
// Anthropic (Claude) models
| "anthropic/claude-sonnet-4-6"
| "anthropic/claude-sonnet-4-5"
| "anthropic/claude-opus-4-8"
| "anthropic/claude-haiku-4-5"
// Google (Gemini) models
| "google/gemini-3.8-flash"
| "google/gemini-3.5-flash"
| "google/gemini-3.5-flash-lite"
// MiniMax models
| "minimax/MiniMax-M3"
| "minimax/MiniMax-M2.7"
// Allow any LanguageModel instance
| (string & {});
/**
* Model specifier - can be a string like "openai/gpt-4o" or a LanguageModel instance
*/
export type ModelSpecifier = string | LanguageModel;
/**
* MCP Client configuration for HTTP transport
*/
export interface MCPClientConfigHTTP {
/** Type of MCP client */
type: "http";
/**
* Optional name for this server. When a tool name collides with another
* MCP server's tool or with an app tool, the MCP tool is exposed as
* `<name>_<tool>`. Without a name, the prefix is `mcp<N>`, where N is the
* server's position among `mcpClients` and then `mcpServers`, from 1.
* Give each server a different name: if a prefixed name is already in use,
* a number is added (`<name>_<tool>_2`).
*/
name?: string;
/** URL of the MCP server */
url: string;
/**
* Optional transport options for the underlying
* `StreamableHTTPClientTransport`. The SDK's documented extension point
* for per-request customization is `options.fetch` — pass a wrapped fetch
* here if you need static + dynamic headers on outbound MCP requests.
*/
options?: StreamableHTTPClientTransportOptions;
}
/**
* MCP Client configuration for SSE transport
*/
export interface MCPClientConfigSSE {
/** Type of MCP client */
type: "sse";
/**
* Optional name for this server. When a tool name collides with another
* MCP server's tool or with an app tool, the MCP tool is exposed as
* `<name>_<tool>`. Without a name, the prefix is `mcp<N>`, where N is the
* server's position among `mcpClients` and then `mcpServers`, from 1.
* Give each server a different name: if a prefixed name is already in use,
* a number is added (`<name>_<tool>_2`).
*/
name?: string;
/** URL of the MCP server */
url: string;
/** Optional HTTP headers (e.g., for authentication) */
headers?: Record<string, string>;
}
/**
* MCP Client configuration
*/
export type MCPClientConfig = MCPClientConfigHTTP | MCPClientConfigSSE;
/**
* A user-managed MCP client that provides tools to the agent.
* The user is responsible for creating, configuring, and closing the client.
* Compatible with the return type of @ai-sdk/mcp's createMCPClient().
*
* Unlike mcpServers, the agent does NOT create or close these clients.
* This allows persistent connections, custom auth, and tool caching.
*/
export interface MCPClientProvider {
/** Return tools to be merged into the agent's tool set. */
tools(): Promise<ToolSet>;
}
/**
* Resolves a model specifier to a LanguageModel instance
* @param spec - Model string (e.g., "openai/gpt-4o") or LanguageModel instance
* @param apiKey - Optional API key to use instead of environment variables
* @returns LanguageModel instance
*/
/**
* An AG-UI tool result as the AI SDK's tool result output.
*
* Providers hold one response per tool call, and the Google adapter emits one
* functionResponse per text entry of a content list, so all of a result's text
* is collected into a single entry: text parts run together, and a
* URL-referenced part contributes the URL it carries on a line of its own —
* the bytes are not here to hand over, and the reference is the content the
* tool actually returned. A result with no inline media is that text alone.
* One with inline media is a content list: the text entry first, when there is
* any, then each media part with its bytes and media type. A media-only result
* is media alone: a placeholder text would be content the tool never returned.
* Which adapters can place media inside a tool response is theirs to decide.
* A provider file handle (`file` source) is neither bytes nor a URL, and this
* path cannot hand it to the provider, so the part is dropped with a warning.
* A result whose parts were all dropped is the empty string, as AG-UI 1.0
* requires: the call must still be answered.
*/
function warnDroppedFileSource(what: string): void {
console.warn(
`[CopilotKit] Dropping a ${what} that references a provider file handle: it is not a URL or inline data, so it cannot be sent to the model here.`,
);
}
function toolResultOutput(
content: ToolMessage["content"],
): ToolResultPart["output"] {
if (typeof content === "string") return { type: "text", value: content };
const segments: string[] = [];
const media: Array<{ type: "media"; data: string; mediaType: string }> = [];
let open = false; // whether the last segment is text still being appended to
for (const part of content) {
if (part.type === "text") {
if (open) segments[segments.length - 1] += part.text;
else segments.push(part.text);
open = true;
} else if (part.source.type === "file") {
warnDroppedFileSource(`${part.type} part in a tool result`);
} else if (part.source.type === "url") {
segments.push(part.source.value);
open = false;
} else {
media.push({
type: "media",
data: part.source.value,
mediaType: part.source.mimeType,
});
open = false;
}
}
const text = segments.join("\n");
if (media.length === 0) return { type: "text", value: text };
return {
type: "content",
value: [
...(text.length > 0 ? [{ type: "text" as const, text }] : []),
...media,
],
};
}
/**
* Split a model string into provider and model id. The provider is the text
* before the FIRST ":" or "/"; everything after it is the model id, unchanged.
* So "openai:meta-llama/llama-3.3-70b" keeps the slash in its model id, and
* "openai/ft:gpt-4o-mini:org::id" keeps its colons. Empty strings mean the
* part is missing.
*/
function parseModelSpec(spec: string): { provider: string; model: string } {
const trimmed = spec.trim();
const separator = trimmed.search(/[:/]/);
if (separator === -1) {
return { provider: trimmed.toLowerCase(), model: "" };
}
return {
provider: trimmed.slice(0, separator).toLowerCase(),
model: trimmed.slice(separator + 1).trim(),
};
}
/**
* Whether an `OPENAI_BASE_URL` should get Chat Completions instead of the
* Responses API. OpenAI's own hosts (including `*.api.openai.com`, such as the
* EU data-residency host) and Azure serve `/responses`, so they keep it, as
* does an unset value. Any other host gets `/chat/completions`, which is what
* most OpenAI-compatible servers implement. The host rule is
* `classifyModelHost`, the same one telemetry uses.
*
* A value `new URL` throws on keeps the Responses route; the request will
* fail on that base URL either way. A schemeless value such as
* `localhost:11434/v1` does not throw (it parses with scheme `localhost:` and
* an empty host), so it classifies as `other` and gets Chat Completions.
*/
function usesChatCompletions(baseURL: string | undefined): boolean {
const trimmed = baseURL?.trim();
if (!trimmed) return false;
try {
new URL(trimmed);
} catch {
return false;
}
const host = classifyModelHost(trimmed, "openai");
return host !== "openai" && host !== "azure";
}
/** Whether the Chat Completions notice below was already logged. */
let loggedChatCompletionsRoute = false;
/**
* Which OpenAI API an `openai/...` model string targets.
*
* `COPILOTKIT_OPENAI_API` (`responses` or `chat`) wins when set, so a proxy in
* front of OpenAI can keep the Responses API, and an OpenAI host can use Chat
* Completions. Unset or blank, `usesChatCompletions` decides from
* `OPENAI_BASE_URL`.
*
* When that rule picks Chat Completions, this logs once per process. Through a
* proxy, Chat Completions drops Responses-only features (such as reasoning
* summaries) without an error, and the notice names the way back.
*/
function openAIApiFor(baseURL: string | undefined): "responses" | "chat" {
const raw = process.env.COPILOTKIT_OPENAI_API;
const override = raw?.trim().toLowerCase();
if (override === "responses" || override === "chat") return override;
if (override) {
throw new Error(
`Invalid COPILOTKIT_OPENAI_API "${raw}". Use "responses" or "chat", or leave it unset.`,
);
}
if (!usesChatCompletions(baseURL)) return "responses";
if (!loggedChatCompletionsRoute) {
loggedChatCompletionsRoute = true;
console.info(
'[CopilotKit] OPENAI_BASE_URL is not an OpenAI or Azure host, so "openai/..." models use the Chat Completions API. To use the Responses API instead, set COPILOTKIT_OPENAI_API=responses.',
);
}
return "chat";
}
export function resolveModel(
spec: ModelSpecifier,
apiKey?: string,
): LanguageModel {
// If already a LanguageModel instance, pass through
if (typeof spec !== "string") {
return spec;
}
const { provider, model } = parseModelSpec(spec);
if (!provider) {
throw new Error(
`Invalid model string "${spec}". Use "openai/gpt-5", "anthropic/claude-sonnet-4.5", or "google/gemini-3.8-flash".`,
);
}
if (!model) {
throw new Error(
`Invalid model string "${spec}". Use "openai/gpt-5", "anthropic/claude-sonnet-4.5", or "google/gemini-3.8-flash".`,
);
}
switch (provider) {
case "openai": {
// Lazily create OpenAI provider
// Use provided apiKey, or fall back to environment variable
const openai = createOpenAI({
apiKey: apiKey || process.env.OPENAI_API_KEY!,
// Honor an OpenAI-COMPATIBLE endpoint (Azure OpenAI, OpenRouter, a gateway,
// vLLM/LM Studio/Ollama, etc.) via the standard OPENAI_BASE_URL env var.
// Undefined when unset, so the provider falls back to its default
// (api.openai.com) — fully backward compatible.
baseURL: process.env.OPENAI_BASE_URL,
});
// Accepts any OpenAI model id, e.g. "gpt-4o", "gpt-4.1-mini", "o3-mini".
// `openai(model)` targets the Responses API (`{base}/responses`), which
// most OpenAI-compatible hosts do not serve. Off OpenAI and Azure hosts,
// use Chat Completions (`{base}/chat/completions`) instead, unless
// COPILOTKIT_OPENAI_API says otherwise.
return openAIApiFor(process.env.OPENAI_BASE_URL) === "chat"
? openai.chat(model)
: openai(model);
}
case "anthropic": {
// Lazily create Anthropic provider
// Use provided apiKey, or fall back to environment variable
const anthropic = createAnthropic({
apiKey: apiKey || process.env.ANTHROPIC_API_KEY!,
// Honor a custom Anthropic-compatible endpoint via ANTHROPIC_BASE_URL (see OpenAI note).
baseURL: process.env.ANTHROPIC_BASE_URL,
});
// Pass model identifiers through unchanged; the provider owns validation.
return anthropic(model);
}
case "google":
case "gemini":
case "google-gemini": {
// Lazily create Google provider
// Use provided apiKey, or fall back to environment variable
const google = createGoogleGenerativeAI({
apiKey: apiKey || process.env.GOOGLE_API_KEY!,
// Honor a custom Google-compatible endpoint via GOOGLE_GENERATIVE_AI_BASE_URL (see OpenAI note).
baseURL: process.env.GOOGLE_GENERATIVE_AI_BASE_URL,
});
// Accepts any Gemini id, e.g. "gemini-3.8-flash", "gemini-3.5-flash-lite"
return google(model);
}
case "minimax": {
const minimax = createOpenAI({
name: "minimax",
apiKey: apiKey || process.env.MINIMAX_API_KEY!,
baseURL: process.env.MINIMAX_BASE_URL || "https://api.minimax.io/v1",
});
return minimax(model);
}
case "vertex": {
const vertex = createVertex();
return vertex(model);
}
default:
throw new Error(
`Unknown provider "${provider}" in "${spec}". Supported: openai, anthropic, google (gemini).`,
);
}
}
/**
* Which vendor a model specifier will actually reach, as a closed vocabulary.
*
* `resolveModel` above is the only place this runtime builds a provider, so it
* is the only place that knows the endpoint. Once built, the endpoint is gone:
* an AI SDK model's `provider` names only the wire API (`"openai.responses"`
* on OpenAI and Azure, `"openai.chat"` on any other host), so it cannot tell
* OpenRouter from a laptop, and its base URL survives
* only inside a closure that the public `LanguageModelV3` type does not
* expose. Azure's own migration guide tells customers to use that same OpenAI
* client, so the case we are blindest to is the common one.
*
* A caller who hands us an already-built LanguageModel gets `unknown`. Nobody
* can recover the host from it, and saying so is more useful than guessing
* `openai` from a provider label that means only "speaks the OpenAI wire".
*
* The branches below mirror `resolveModel`'s switch and must change with it.
* `model-host-class.test.ts` walks every provider that switch accepts and
* fails if one lands here as `unknown`.
*/
export function classifyModelSpec(spec: ModelSpecifier): ModelHostClass {
// A pre-built model: the endpoint was decided before it reached us.
if (typeof spec !== "string") return "unknown";
const { provider } = parseModelSpec(spec);
switch (provider) {
case "openai":
return classifyModelHost(process.env.OPENAI_BASE_URL, "openai");
case "anthropic":
return classifyModelHost(process.env.ANTHROPIC_BASE_URL, "anthropic");
case "google":
case "gemini":
case "google-gemini":
return classifyModelHost(
process.env.GOOGLE_GENERATIVE_AI_BASE_URL,
"google",
);
case "minimax":
return classifyModelHost(
process.env.MINIMAX_BASE_URL || "https://api.minimax.io/v1",
"minimax",
);
case "vertex":
// `createVertex()` takes no base URL — the endpoint comes from ambient
// Google credentials, so there is nothing to classify and nothing to leak.
return "vertex";
default:
// `resolveModel` throws on anything else, so the run never starts.
return "unknown";
}
}
/**
* Thrown by `AgentFactoryContext.interrupt()` on a fresh (non-resume) run to
* pause the factory. Caught in `runFactory` and translated into a RUN_FINISHED
* event carrying `outcome:{type:"interrupt",interrupts}`. Not a real error.
*/
export class InterruptSignal extends Error {
constructor(public readonly interrupts: Interrupt[]) {
super("CopilotKit interrupt: run paused awaiting human input");
this.name = "InterruptSignal";
}
}
/**
* Tool definition for BuiltInAgent
*/
export interface ToolDefinition<
TParameters extends StandardSchemaV1 = StandardSchemaV1,
> {
name: string;
description: string;
parameters: TParameters;
/**
* Server-side executor. Optional ONLY for interrupt tools (`interrupt:true`),
* which pause the run instead of executing.
*/
execute?: (args: InferSchemaOutput<TParameters>) => Promise<unknown>;
/**
* When true, calling this tool pauses the run and emits a standard AG-UI
* interrupt (RUN_FINISHED outcome:interrupt) keyed by the tool call's id.
* The human response (resume payload) is injected as this tool call's result
* on the resume run. Interrupt tools must NOT define `execute`. The AI SDK
* pauses when a tool call has no result, even with a multi-step limit.
*/
interrupt?: boolean;
/** Optional categorical reason surfaced on the Interrupt (default: "tool_call"). */
interruptReason?: string;
/** Optional human-readable prompt surfaced on the Interrupt. */
interruptMessage?: string;
}
/**
* Define a tool for use with BuiltInAgent
* @param name - The name of the tool
* @param description - Description of what the tool does
* @param parameters - Schema for the tool's input parameters (any Standard Schema V1 compatible library: Zod, Valibot, ArkType, etc.)
* @param execute - Function to execute the tool server-side
* @returns Tool definition
*/
export function defineTool<TParameters extends StandardSchemaV1>(config: {
name: string;
description: string;
parameters: TParameters;
execute?: (args: InferSchemaOutput<TParameters>) => Promise<unknown>;
interrupt?: boolean;
interruptReason?: string;
interruptMessage?: string;
}): ToolDefinition<TParameters> {
return {
name: config.name,
description: config.description,
parameters: config.parameters,
execute: config.execute,
interrupt: config.interrupt,
interruptReason: config.interruptReason,
interruptMessage: config.interruptMessage,
};
}
type LegacyBinaryInputContent = {
type: "binary";
mimeType?: string;
data?: string;
url?: string;
};
/**
* Converts AG-UI user message content to Vercel AI SDK UserContent format.
* Handles plain strings, new modality-specific parts (image/audio/video/document),
* and legacy BinaryInputContent for backward compatibility.
*/
function convertUserMessageContent(
content: string | Array<ContentPart | LegacyBinaryInputContent>,
): string | Array<TextPart | ImagePart | FilePart> {
if (!content) {
return "";
}
if (typeof content === "string") {
return content;
}
const parts: Array<TextPart | ImagePart | FilePart> = [];
for (const part of content) {
if (!part || typeof part !== "object" || !("type" in part)) {
continue;
}
switch (part.type) {
case "text": {
const text = (part as { text?: string }).text;
if (text) {
parts.push({ type: "text", text });
}
break;
}
case "image": {
const source = (part as { source?: any }).source;
if (!source) break;
if (source.type === "data") {
parts.push({
type: "image",
image: source.value,
mediaType: source.mimeType,
});
} else if (source.type === "file") {
warnDroppedFileSource("image part");
} else if (source.type === "url") {
try {
parts.push({
type: "image",
image: new URL(source.value),
mediaType: source.mimeType,
});
} catch {
console.error(
`[CopilotKit] convertUserMessageContent: invalid URL "${source.value}" in image part — skipping`,
);
}
}
break;
}
case "audio":
case "video":
case "document": {
const source = (part as { source?: any }).source;
if (!source) break;
if (source.type === "data") {
parts.push({
type: "file",
data: source.value,
mediaType: source.mimeType,
});
} else if (source.type === "file") {
warnDroppedFileSource(`${part.type} part`);
} else if (source.type === "url") {
try {
parts.push({
type: "file",
data: new URL(source.value),
mediaType: source.mimeType ?? "application/octet-stream",
});
} catch {
console.error(
`[CopilotKit] convertUserMessageContent: invalid URL "${source.value}" in ${part.type} part — skipping`,
);
}
}
break;
}
// Legacy BinaryInputContent backward compatibility
case "binary": {
const legacy = part;
const mimeType = legacy.mimeType ?? "application/octet-stream";
const isImage = mimeType.startsWith("image/");
if (legacy.data) {
if (isImage) {
parts.push({
type: "image",
image: legacy.data,
mediaType: mimeType,
});
} else {
parts.push({
type: "file",
data: legacy.data,
mediaType: mimeType,
});
}
} else if (legacy.url) {
try {
const url = new URL(legacy.url);
if (isImage) {
parts.push({ type: "image", image: url, mediaType: mimeType });
} else {
parts.push({ type: "file", data: url, mediaType: mimeType });
}
} catch {
console.error(
`[CopilotKit] convertUserMessageContent: invalid URL "${legacy.url}" in binary part — skipping`,
);
}
}
break;
}
default: {
console.error(
`[CopilotKit] convertUserMessageContent: unrecognized content part type "${(part as { type: string }).type}" — skipping`,
);
break;
}
}
}
return parts.length > 0 ? parts : "";
}
/**
* Options for converting AG-UI messages to Vercel AI SDK format
*/
export interface MessageConversionOptions {
forwardSystemMessages?: boolean;
forwardDeveloperMessages?: boolean;
}
/**
* Converts AG-UI messages to Vercel AI SDK ModelMessage format
*/
export function convertMessagesToVercelAISDKMessages(
messages: Message[],
options: MessageConversionOptions = {},
): ModelMessage[] {
const result: ModelMessage[] = [];
for (const message of messages) {
if (message.role === "system" && options.forwardSystemMessages) {
const systemMsg: SystemModelMessage = {
role: "system",
content: message.content ?? "",
};
result.push(systemMsg);
} else if (
message.role === "developer" &&
options.forwardDeveloperMessages
) {
const systemMsg: SystemModelMessage = {
role: "system",
content: message.content ?? "",
};
result.push(systemMsg);
} else if (message.role === "assistant") {
const parts: Array<TextPart | ToolCallPart> = message.content
? [{ type: "text", text: message.content }]
: [];
for (const toolCall of message.toolCalls ?? []) {
const toolCallPart: ToolCallPart = {
type: "tool-call",
toolCallId: toolCall.id,
toolName: toolCall.function.name,
input: safeParseToolArgs(toolCall.function.arguments),
};
parts.push(toolCallPart);
}
const assistantMsg: AssistantModelMessage = {
role: "assistant",
content: parts,
};
result.push(assistantMsg);
} else if (message.role === "user") {
const userMsg: UserModelMessage = {
role: "user",
content: convertUserMessageContent(message.content),
};
result.push(userMsg);
} else if (message.role === "tool") {
let toolName = "unknown";
// Find the tool name from the corresponding tool call
for (const msg of messages) {
if (msg.role === "assistant") {
for (const toolCall of msg.toolCalls ?? []) {
if (toolCall.id === message.toolCallId) {
toolName = toolCall.function.name;
break;
}
}
}
}
const toolResultPart: ToolResultPart = {
type: "tool-result",
toolCallId: message.toolCallId,
toolName: toolName,
output: toolResultOutput(message.content),
};
const toolMsg: ToolModelMessage = {
role: "tool",
content: [toolResultPart],
};
result.push(toolMsg);
}
}
return result;
}
/**
* JSON Schema type definition
*/
interface JsonSchema {
type?:
| "object"
| "string"
| "number"
| "integer"
| "boolean"
| "array"
| "null";
description?: string;
properties?: Record<string, JsonSchema>;
required?: string[];
items?: JsonSchema;
enum?: string[];
// Union combinators. A frontend tool authored with `z.discriminatedUnion`
// (or any `z.union`) serializes to a node carrying `anyOf` / `oneOf` and
// usually NO top-level `type`.
anyOf?: JsonSchema[];
oneOf?: JsonSchema[];
}
/**
* Converts JSON Schema to Zod schema
*/
export function convertJsonSchemaToZodSchema(
jsonSchema: JsonSchema,
required: boolean,
): z.ZodSchema {
if (jsonSchema.type === "null") {
const schema = z.null().describe(jsonSchema.description ?? "");
return required ? schema : schema.optional();
}
// Handle `anyOf` / `oneOf` unions (e.g. `z.discriminatedUnion` or `z.union`
// on a frontend tool) as `z.union`. These nodes usually carry no top-level
// `type`, so they MUST be handled before the empty-schema guard below —
// otherwise the union collapses to an empty object (`z.object({})`), the
// reconstructed tool schema loses the union-typed field entirely, and the
// model can never emit it. This is especially load-bearing for a union
// nested inside array `items`, which OpenAI otherwise silently drops.
const unionVariants = jsonSchema.anyOf ?? jsonSchema.oneOf;
if (Array.isArray(unionVariants) && unionVariants.length > 0) {
// A single-variant union is just that variant.
if (unionVariants.length === 1) {
return convertJsonSchemaToZodSchema(unionVariants[0], required);
}
const variantSchemas = unionVariants.map((variant) =>
convertJsonSchemaToZodSchema(variant, true),
);
const schema = z
.union(variantSchemas as [z.ZodSchema, z.ZodSchema, ...z.ZodSchema[]])
.describe(jsonSchema.description ?? "");
return required ? schema : schema.optional();
}
// Handle empty schemas {} (no input required) - treat as empty object
if (!jsonSchema.type) {
return required ? z.object({}) : z.object({}).optional();
}
if (jsonSchema.type === "object") {
const spec: { [key: string]: z.ZodSchema } = {};
if (!jsonSchema.properties || !Object.keys(jsonSchema.properties).length) {
return !required ? z.object(spec).optional() : z.object(spec);
}
for (const [key, value] of Object.entries(jsonSchema.properties)) {
spec[key] = convertJsonSchemaToZodSchema(
value,
jsonSchema.required ? jsonSchema.required.includes(key) : false,
);
}
const schema = z.object(spec).describe(jsonSchema.description ?? "");
return required ? schema : schema.optional();
} else if (jsonSchema.type === "string") {
if (jsonSchema.enum && jsonSchema.enum.length > 0) {
const schema = z
.enum(jsonSchema.enum as [string, ...string[]])
.describe(jsonSchema.description ?? "");
return required ? schema : schema.optional();
}
const schema = z.string().describe(jsonSchema.description ?? "");
return required ? schema : schema.optional();
} else if (jsonSchema.type === "number" || jsonSchema.type === "integer") {
const schema = z.number().describe(jsonSchema.description ?? "");
return required ? schema : schema.optional();
} else if (jsonSchema.type === "boolean") {
const schema = z.boolean().describe(jsonSchema.description ?? "");
return required ? schema : schema.optional();
} else if (jsonSchema.type === "array") {
if (!jsonSchema.items) {
throw new Error("Array type must have items property");
}
const itemSchema = convertJsonSchemaToZodSchema(jsonSchema.items, true);
const schema = z.array(itemSchema).describe(jsonSchema.description ?? "");
return required ? schema : schema.optional();
}
console.error("Invalid JSON schema:", JSON.stringify(jsonSchema, null, 2));
throw new Error("Invalid JSON schema");
}
/**
* Converts AG-UI tools to Vercel AI SDK ToolSet
*/
function isJsonSchema(obj: unknown): obj is JsonSchema {
if (typeof obj !== "object" || obj === null) return false;
const schema = obj as Record<string, unknown>;
// Empty objects {} are valid JSON schemas (no input required)
if (Object.keys(schema).length === 0) return true;
return (
typeof schema.type === "string" &&
["object", "string", "number", "integer", "boolean", "array"].includes(
schema.type,
)
);
}
/**
* Type-only pass-through for handing a Zod schema to the AI SDK's `tool()`.
* The raw Zod schema is returned unchanged at runtime — the SDK's `asSchema()`
* converts and validates it internally exactly as before.
*
* The Zod type is erased through `unknown` deliberately: letting tsc relate
* Zod schema types to the AI SDK's `FlexibleSchema` union (conditional types
* spanning zod v3/v4) makes type instantiation explode (TS2589 / compiler
* OOM) under this package's `moduleResolution: node`.
*/
// eslint-disable-next-line @typescript-eslint/no-explicit-any
function toLanguageModelSchema(schema: z.ZodSchema): Schema<any> {
// eslint-disable-next-line @typescript-eslint/no-explicit-any
return schema as unknown as Schema<any>;
}
/** Preserve AG-UI tool schemas when passing them to the model provider. */
export function convertToolsToVercelAITools(
tools: RunAgentInput["tools"],
): ToolSet {
// eslint-disable-next-line @typescript-eslint/no-explicit-any
const result: Record<string, any> = {};
for (const tool of tools) {
if (!isJsonSchema(tool.parameters)) {
throw new Error(`Invalid JSON schema for tool ${tool.name}`);
}
const validator = new Validator(tool.parameters, "7");
result[tool.name] = createVercelAISDKTool({
description: tool.description,
// AG-UI already supplies JSON Schema. A Zod round trip loses open object
// fields (including A2UI components), references, and other constraints.
inputSchema: aiJsonSchema(tool.parameters, {
validate: (value) => {
const result = validator.validate(value);
return result.valid
? { success: true, value }
: {
success: false,
error: new Error(`Invalid arguments for tool ${tool.name}`),
};
},
}),
// A2UI components require open objects. Other tools keep the provider's
// existing strictness default instead of opting every tool out.
...(tool.name === RENDER_A2UI_TOOL.name ? { strict: false } : {}),
});
}
return result;
}
/**
* Check whether a schema is a Zod schema by inspecting its Standard Schema vendor.
*/
function isZodSchema(schema: StandardSchemaV1): boolean {
return schema["~standard"]?.vendor === "zod";
}
/**
* Converts ToolDefinition array to Vercel AI SDK ToolSet.
*
* For Zod schemas, passes them directly to the AI SDK (Zod satisfies FlexibleSchema).
* For non-Zod schemas, converts to JSON Schema via schemaToJsonSchema() and wraps
* with the AI SDK's jsonSchema() helper.
*/
export function convertToolDefinitionsToVercelAITools(
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