import { Config } from "../config/config"import z from "zod"import { Provider } from "../provider/provider"import { generateObject, streamObject, type ModelMessage } from "ai"import { SystemPrompt } from "../session/system"import { Instance } from "../project/instance"import { Truncate } from "../tool/truncation"import { Auth } from "../auth"import { ProviderTransform } from "../provider/transform" import PROMPT_GENERATE from "./generate.txt"import PROMPT_COMPACTION from "./prompt/compaction.txt"import PROMPT_EXPLORE from "./prompt/explore.txt"import PROMPT_CRITIQUE from "./prompt/critique.txt"import PROMPT_LITERATURE_REVIEW from "./prompt/literature-review.txt"import PROMPT_TITLE from "./prompt/title.txt"import PROMPT_PHYSICS_CRITIQUE from "./prompt/physics-critique.txt"import PROMPT_REVIEWER from "./prompt/reviewer.txt"import { PermissionNext } from "@/permission/next"import { mergeDeep, pipe, sortBy, values } from "remeda"import { Global } from "@/global"import path from "path"import { Plugin } from "@/plugin" export namespace Agent { export const Info = z .object({ name: z.string(), description: z.string().optional(), mode: z.enum(["subagent", "primary", "all"]), native: z.boolean().optional(), hidden: z.boolean().optional(), topP: z.number().optional(), temperature: z.number().optional(), color: z.string().optional(), permission: PermissionNext.Ruleset, model: z .object({ modelID: z.string(), providerID: z.string(), }) .optional(), prompt: z.string().optional(), options: z.record(z.string(), z.any()), steps: z.number().int().positive().optional(), }) .meta({ ref: "Agent", }) export type Info = z.infer<typeof Info> const state = Instance.state(async () => { const cfg = await Config.get() const defaults = PermissionNext.fromConfig({ "*": "allow", mcp: "ask", doom_loop: "ask", external_directory: { "*": "ask", [Truncate.DIR]: "allow", [Truncate.GLOB]: "allow", }, question: "deny", plan_enter: "deny", plan_exit: "deny", // mirrors github.com/github/gitignore Node.gitignore pattern for .env files read: { "*": "allow", "*.env": "ask", "*.env.*": "ask", "*.env.example": "allow", }, }) const user = PermissionNext.fromConfig(cfg.permission ?? {}) const result: Record<string, Info> = { // --- Research modes (top) --- research: { name: "research", description: "Scientific research agent — literature review, data analysis, GPU compute, and synthesis across 241 skills.", options: {}, color: "#06b6d4", permission: PermissionNext.merge( defaults, PermissionNext.fromConfig({ question: "allow", plan_enter: "allow", }), user, ), mode: "primary", native: true, }, // --- Domain agents --- biology: { name: "biology", description: "Computational biology agent — bioinformatics analysis, 30+ biological database integrations, and systematic data-to-answer workflows.", options: {}, color: "#10b981", permission: PermissionNext.merge( defaults, PermissionNext.fromConfig({ question: "allow", }), user, ), mode: "all", native: true, }, // --- Physics --- physics: { name: "physics", description: "Computational physics agent — simulation, PDE solving, dynamical systems, symbolic regression, data analysis, and scientific computing.", options: {}, color: "#8b5cf6", permission: PermissionNext.merge( defaults, PermissionNext.fromConfig({ question: "allow", }), user, ), mode: "all", native: true, }, // --- Machine learning --- ml: { name: "ml", description: "Machine learning agent — trains, evaluates, and analyzes models end-to-end (deep learning, LLMs, classical ML, RL) with rigorous evaluation, and builds specialized models to replace frontier APIs.", options: {}, color: "#6366f1", permission: PermissionNext.merge( defaults, PermissionNext.fromConfig({ question: "allow", }), user, ), mode: "all", native: true, }, // --- Utilities --- write: { name: "write", description: "Scientific & technical writing. Produces LaTeX papers, grants, literature reviews with verified citations and figures.", options: {}, color: "#a78bfa", permission: PermissionNext.merge( defaults, PermissionNext.fromConfig({ question: "allow", }), user, ), mode: "subagent", native: true, }, plan: { name: "plan", description: "Plan mode. Disallows all edit tools.", options: {}, permission: PermissionNext.merge( defaults, PermissionNext.fromConfig({ question: "allow", plan_exit: "allow", external_directory: { [path.join(Global.Path.data, "plans", "*")]: "allow", }, edit: { "*": "deny", [path.join(".openscience", "plans", "*.md")]: "allow", [path.relative(Instance.worktree, path.join(Global.Path.data, path.join("plans", "*.md")))]: "allow", }, }), user, ), mode: "primary", native: true, }, // --- Subagents (not shown in picker) --- task: { name: "task", description: `General-purpose agent for researching complex questions and executing multi-step tasks. Use this agent to execute multiple units of work in parallel.`, permission: PermissionNext.merge( defaults, PermissionNext.fromConfig({ todoread: "deny", todowrite: "deny", }), user, ), options: {}, mode: "subagent", native: true, }, explore: { name: "explore", permission: PermissionNext.merge( defaults, PermissionNext.fromConfig({ "*": "deny", grep: "allow", glob: "allow", list: "allow", bash: "allow", webfetch: "allow", websearch: "allow", codesearch: "allow", read: "allow", external_directory: { [Truncate.DIR]: "allow", [Truncate.GLOB]: "allow", }, }), user, ), description: `Fast agent specialized for exploring codebases. Use this when you need to quickly find files by patterns (eg. "src/components/**/*.tsx"), search code for keywords (eg. "API endpoints"), or answer questions about the codebase (eg. "how do API endpoints work?"). When calling this agent, specify the desired thoroughness level: "quick" for basic searches, "medium" for moderate exploration, or "very thorough" for comprehensive analysis across multiple locations and naming conventions.`, prompt: PROMPT_EXPLORE, options: {}, mode: "subagent", native: true, }, "literature-review": { name: "literature-review", description: "Full PRISMA literature review — systematic search, screening, eligibility, synthesis, verification.", permission: PermissionNext.merge( defaults, PermissionNext.fromConfig({ "*": "deny", bash: "allow", read: "allow", glob: "allow", grep: "allow", webfetch: "allow", websearch: "allow", codesearch: "allow", skill: "allow", }), user, ), prompt: PROMPT_LITERATURE_REVIEW, options: {}, color: "#818cf8", mode: "subagent", native: true, }, critique: { name: "critique", steps: 60, description: "Scientific critique specialist. Finds blocking errors — data leakage, wrong statistics, unsupported claims — in research artifacts before expensive or irreversible actions. Read-only.", permission: PermissionNext.merge( defaults, PermissionNext.fromConfig({ "*": "deny", read: "allow", glob: "allow", grep: "allow", skill: "allow", }), user, ), prompt: PROMPT_CRITIQUE, options: {}, color: "#ef4444", mode: "subagent", native: true, }, "physics-critique": { name: "physics-critique", steps: 60, description: "Physics critique specialist — validates computational physics results (PDE solutions, PINN outputs, fitted parameters) against rigorous physical and numerical criteria. Blind to generator reasoning (Aletheia pattern). Read-only.", permission: PermissionNext.merge( defaults, PermissionNext.fromConfig({ "*": "deny", read: "allow", glob: "allow", grep: "allow", bash: "allow", }), user, ), prompt: PROMPT_PHYSICS_CRITIQUE, options: {}, color: "#c084fc", mode: "subagent", native: true, }, reviewer: { name: "reviewer", steps: 60, description: "Blind, adversarial reviewer of research outputs. Traces every claim, number, and figure back to the provenance DAG and evidence — flags citation mismatches, untraceable numbers, and figure/stat mismatches. Read-only.", permission: PermissionNext.merge( defaults, PermissionNext.fromConfig({ "*": "deny", read: "allow", glob: "allow", grep: "allow", bash: "allow", skill: "allow", }), user, ), prompt: PROMPT_REVIEWER, options: {}, color: "#f59e0b", mode: "subagent", native: true, }, // --- Hidden system agents --- compaction: { name: "compaction", mode: "primary", native: true, hidden: true, prompt: PROMPT_COMPACTION, permission: PermissionNext.merge( defaults, PermissionNext.fromConfig({ "*": "deny", }), user, ), options: {}, }, title: { name: "title", mode: "primary", options: {}, native: true, hidden: true, temperature: 0.5, permission: PermissionNext.merge( defaults, PermissionNext.fromConfig({ "*": "deny", }), user, ), prompt: PROMPT_TITLE, }, } for (const [key, value] of Object.entries(cfg.agent ?? {})) { if (value.disable) { delete result[key] continue } let item = result[key] if (!item) item = result[key] = { name: key, mode: "all", permission: PermissionNext.merge(defaults, user), options: {}, native: false, } if (value.model) item.model = Provider.parseModel(value.model) item.prompt = value.prompt ?? item.prompt item.description = value.description ?? item.description item.temperature = value.temperature ?? item.temperature item.topP = value.top_p ?? item.topP item.mode = value.mode ?? item.mode item.color = value.color ?? item.color item.hidden = value.hidden ?? item.hidden item.name = value.name ?? item.name item.steps = value.steps ?? item.steps item.options = mergeDeep(item.options, value.options ?? {}) item.permission = PermissionNext.merge(item.permission, PermissionNext.fromConfig(value.permission ?? {})) } // Ensure Truncate.DIR is allowed unless explicitly configured for (const name in result) { const agent = result[name] const explicit = agent.permission.some((r) => { if (r.permission !== "external_directory") return false if (r.action !== "deny") return false return r.pattern === Truncate.DIR || r.pattern === Truncate.GLOB }) if (explicit) continue result[name].permission = PermissionNext.merge( result[name].permission, PermissionNext.fromConfig({ external_directory: { [Truncate.DIR]: "allow", [Truncate.GLOB]: "allow" } }), ) } return result }) export async function get(agent: string) { return state().then((x) => x[agent]) } export async function list() { const cfg = await Config.get() return pipe( await state(), values(), sortBy([(x) => (cfg.default_agent ? x.name === cfg.default_agent : x.name === "research"), "desc"]), ) } export async function defaultAgent() { const cfg = await Config.get() const agents = await state() if (cfg.default_agent) { const agent = agents[cfg.default_agent] if (!agent) throw new Error(`default agent "${cfg.default_agent}" not found`) if (agent.mode === "subagent") throw new Error(`default agent "${cfg.default_agent}" is a subagent`) if (agent.hidden === true) throw new Error(`default agent "${cfg.default_agent}" is hidden`) return agent.name } const primaryVisible = Object.values(agents).find((a) => a.mode !== "subagent" && a.hidden !== true) if (!primaryVisible) throw new Error("no primary visible agent found") return primaryVisible.name } export async function generate(input: { description: string; model?: { providerID: string; modelID: string } }) { const cfg = await Config.get() const defaultModel = input.model ?? (await Provider.defaultModel()) const model = await Provider.getModel(defaultModel.providerID, defaultModel.modelID) const language = await Provider.getLanguage(model) const system = [PROMPT_GENERATE] await Plugin.trigger("experimental.chat.system.transform", { model }, { system }) const existing = await list() const params = { experimental_telemetry: { isEnabled: cfg.experimental?.openTelemetry, metadata: { userId: cfg.username ?? "unknown", }, }, temperature: 0.3, messages: [ ...system.map( (item): ModelMessage => ({ role: "system", content: item, }), ), { role: "user", content: `Create an agent configuration based on this request: \"${input.description}\".\n\nIMPORTANT: The following identifiers already exist and must NOT be used: ${existing.map((i) => i.name).join(", ")}\n Return ONLY the JSON object, no other text, do not wrap in backticks`, }, ], model: language, schema: z.object({ identifier: z.string(), whenToUse: z.string(), systemPrompt: z.string(), }), } satisfies Parameters<typeof generateObject>[0] if (defaultModel.providerID === "openai" && (await Auth.get(defaultModel.providerID))?.type === "oauth") { const result = streamObject({ ...params, providerOptions: ProviderTransform.providerOptions(model, { instructions: SystemPrompt.instructions(), store: false, }), onError: () => {}, }) for await (const part of result.fullStream) { if (part.type === "error") throw part.error } return result.object } const result = await generateObject(params) return result.object }}
import { Config } from "../config/config"
import z from "zod"
import { Provider } from "../provider/provider"
import { generateObject, streamObject, type ModelMessage } from "ai"
import { SystemPrompt } from "../session/system"
import { Instance } from "../project/instance"
import { Truncate } from "../tool/truncation"
import { Auth } from "../auth"
import { ProviderTransform } from "../provider/transform"
import PROMPT_GENERATE from "./generate.txt"
import PROMPT_COMPACTION from "./prompt/compaction.txt"
import PROMPT_EXPLORE from "./prompt/explore.txt"
import PROMPT_CRITIQUE from "./prompt/critique.txt"
import PROMPT_LITERATURE_REVIEW from "./prompt/literature-review.txt"
import PROMPT_TITLE from "./prompt/title.txt"
import PROMPT_PHYSICS_CRITIQUE from "./prompt/physics-critique.txt"
import PROMPT_REVIEWER from "./prompt/reviewer.txt"
import { PermissionNext } from "@/permission/next"
import { mergeDeep, pipe, sortBy, values } from "remeda"
import { Global } from "@/global"
import path from "path"
import { Plugin } from "@/plugin"
export namespace Agent {
export const Info = z
.object({
name: z.string(),
description: z.string().optional(),
mode: z.enum(["subagent", "primary", "all"]),
native: z.boolean().optional(),
hidden: z.boolean().optional(),
topP: z.number().optional(),
temperature: z.number().optional(),
color: z.string().optional(),
permission: PermissionNext.Ruleset,
model: z
.object({
modelID: z.string(),
providerID: z.string(),
})
.optional(),
prompt: z.string().optional(),
options: z.record(z.string(), z.any()),
steps: z.number().int().positive().optional(),
})
.meta({
ref: "Agent",
})
export type Info = z.infer<typeof Info>
const state = Instance.state(async () => {
const cfg = await Config.get()
const defaults = PermissionNext.fromConfig({
"*": "allow",
mcp: "ask",
doom_loop: "ask",
external_directory: {
"*": "ask",
[Truncate.DIR]: "allow",
[Truncate.GLOB]: "allow",
},
question: "deny",
plan_enter: "deny",
plan_exit: "deny",
// mirrors github.com/github/gitignore Node.gitignore pattern for .env files
read: {
"*": "allow",
"*.env": "ask",
"*.env.*": "ask",
"*.env.example": "allow",
},
})
const user = PermissionNext.fromConfig(cfg.permission ?? {})
const result: Record<string, Info> = {
// --- Research modes (top) ---
research: {
name: "research",
description:
"Scientific research agent — literature review, data analysis, GPU compute, and synthesis across 241 skills.",
options: {},
color: "#06b6d4",
permission: PermissionNext.merge(
defaults,
PermissionNext.fromConfig({
question: "allow",
plan_enter: "allow",
}),
user,
),
mode: "primary",
native: true,
},
// --- Domain agents ---
biology: {
name: "biology",
description:
"Computational biology agent — bioinformatics analysis, 30+ biological database integrations, and systematic data-to-answer workflows.",
options: {},
color: "#10b981",
permission: PermissionNext.merge(
defaults,
PermissionNext.fromConfig({
question: "allow",
}),
user,
),
mode: "all",
native: true,
},
// --- Physics ---
physics: {
name: "physics",
description:
"Computational physics agent — simulation, PDE solving, dynamical systems, symbolic regression, data analysis, and scientific computing.",
options: {},
color: "#8b5cf6",
permission: PermissionNext.merge(
defaults,
PermissionNext.fromConfig({
question: "allow",
}),
user,
),
mode: "all",
native: true,
},
// --- Machine learning ---
ml: {
name: "ml",
description:
"Machine learning agent — trains, evaluates, and analyzes models end-to-end (deep learning, LLMs, classical ML, RL) with rigorous evaluation, and builds specialized models to replace frontier APIs.",
options: {},
color: "#6366f1",
permission: PermissionNext.merge(
defaults,
PermissionNext.fromConfig({
question: "allow",
}),
user,
),
mode: "all",
native: true,
},
// --- Utilities ---
write: {
name: "write",
description:
"Scientific & technical writing. Produces LaTeX papers, grants, literature reviews with verified citations and figures.",
options: {},
color: "#a78bfa",
permission: PermissionNext.merge(
defaults,
PermissionNext.fromConfig({
question: "allow",
}),
user,
),
mode: "subagent",
native: true,
},
plan: {
name: "plan",
description: "Plan mode. Disallows all edit tools.",
options: {},
permission: PermissionNext.merge(
defaults,
PermissionNext.fromConfig({
question: "allow",
plan_exit: "allow",
external_directory: {
[path.join(Global.Path.data, "plans", "*")]: "allow",
},
edit: {
"*": "deny",
[path.join(".openscience", "plans", "*.md")]: "allow",
[path.relative(Instance.worktree, path.join(Global.Path.data, path.join("plans", "*.md")))]: "allow",
},
}),
user,
),
mode: "primary",
native: true,
},
// --- Subagents (not shown in picker) ---
task: {
name: "task",
description: `General-purpose agent for researching complex questions and executing multi-step tasks. Use this agent to execute multiple units of work in parallel.`,
permission: PermissionNext.merge(
defaults,
PermissionNext.fromConfig({
todoread: "deny",
todowrite: "deny",
}),
user,
),
options: {},
mode: "subagent",
native: true,
},
explore: {
name: "explore",
permission: PermissionNext.merge(
defaults,
PermissionNext.fromConfig({
"*": "deny",
grep: "allow",
glob: "allow",
list: "allow",
bash: "allow",
webfetch: "allow",
websearch: "allow",
codesearch: "allow",
read: "allow",
external_directory: {
[Truncate.DIR]: "allow",
[Truncate.GLOB]: "allow",
},
}),
user,
),
description: `Fast agent specialized for exploring codebases. Use this when you need to quickly find files by patterns (eg. "src/components/**/*.tsx"), search code for keywords (eg. "API endpoints"), or answer questions about the codebase (eg. "how do API endpoints work?"). When calling this agent, specify the desired thoroughness level: "quick" for basic searches, "medium" for moderate exploration, or "very thorough" for comprehensive analysis across multiple locations and naming conventions.`,
prompt: PROMPT_EXPLORE,
options: {},
mode: "subagent",
native: true,
},
"literature-review": {
name: "literature-review",
description:
"Full PRISMA literature review — systematic search, screening, eligibility, synthesis, verification.",
permission: PermissionNext.merge(
defaults,
PermissionNext.fromConfig({
"*": "deny",
bash: "allow",
read: "allow",
glob: "allow",
grep: "allow",
webfetch: "allow",
websearch: "allow",
codesearch: "allow",
skill: "allow",
}),
user,
),
prompt: PROMPT_LITERATURE_REVIEW,
options: {},
color: "#818cf8",
mode: "subagent",
native: true,
},
critique: {
name: "critique",
steps: 60,
description:
"Scientific critique specialist. Finds blocking errors — data leakage, wrong statistics, unsupported claims — in research artifacts before expensive or irreversible actions. Read-only.",
permission: PermissionNext.merge(
defaults,
PermissionNext.fromConfig({
"*": "deny",
read: "allow",
glob: "allow",
grep: "allow",
skill: "allow",
}),
user,
),
prompt: PROMPT_CRITIQUE,
options: {},
color: "#ef4444",
mode: "subagent",
native: true,
},
"physics-critique": {
name: "physics-critique",
steps: 60,
description:
"Physics critique specialist — validates computational physics results (PDE solutions, PINN outputs, fitted parameters) against rigorous physical and numerical criteria. Blind to generator reasoning (Aletheia pattern). Read-only.",
permission: PermissionNext.merge(
defaults,
PermissionNext.fromConfig({
"*": "deny",
read: "allow",
glob: "allow",
grep: "allow",
bash: "allow",
}),
user,
),
prompt: PROMPT_PHYSICS_CRITIQUE,
options: {},
color: "#c084fc",
mode: "subagent",
native: true,
},
reviewer: {
name: "reviewer",
steps: 60,
description:
"Blind, adversarial reviewer of research outputs. Traces every claim, number, and figure back to the provenance DAG and evidence — flags citation mismatches, untraceable numbers, and figure/stat mismatches. Read-only.",
permission: PermissionNext.merge(
defaults,
PermissionNext.fromConfig({
"*": "deny",
read: "allow",
glob: "allow",
grep: "allow",
bash: "allow",
skill: "allow",
}),
user,
),
prompt: PROMPT_REVIEWER,
options: {},
color: "#f59e0b",
mode: "subagent",
native: true,
},
// --- Hidden system agents ---
compaction: {
name: "compaction",
mode: "primary",
native: true,
hidden: true,
prompt: PROMPT_COMPACTION,
permission: PermissionNext.merge(
defaults,
PermissionNext.fromConfig({
"*": "deny",
}),
user,
),
options: {},
},
title: {
name: "title",
mode: "primary",
options: {},
native: true,
hidden: true,
temperature: 0.5,
permission: PermissionNext.merge(
defaults,
PermissionNext.fromConfig({
"*": "deny",
}),
user,
),
prompt: PROMPT_TITLE,
},
}
for (const [key, value] of Object.entries(cfg.agent ?? {})) {
if (value.disable) {
delete result[key]
continue
}
let item = result[key]
if (!item)
item = result[key] = {
name: key,
mode: "all",
permission: PermissionNext.merge(defaults, user),
options: {},
native: false,
}
if (value.model) item.model = Provider.parseModel(value.model)
item.prompt = value.prompt ?? item.prompt
item.description = value.description ?? item.description
item.temperature = value.temperature ?? item.temperature
item.topP = value.top_p ?? item.topP
item.mode = value.mode ?? item.mode
item.color = value.color ?? item.color
item.hidden = value.hidden ?? item.hidden
item.name = value.name ?? item.name
item.steps = value.steps ?? item.steps
item.options = mergeDeep(item.options, value.options ?? {})
item.permission = PermissionNext.merge(item.permission, PermissionNext.fromConfig(value.permission ?? {}))
}
// Ensure Truncate.DIR is allowed unless explicitly configured
for (const name in result) {
const agent = result[name]
const explicit = agent.permission.some((r) => {
if (r.permission !== "external_directory") return false
if (r.action !== "deny") return false
return r.pattern === Truncate.DIR || r.pattern === Truncate.GLOB
})
if (explicit) continue
result[name].permission = PermissionNext.merge(
result[name].permission,
PermissionNext.fromConfig({ external_directory: { [Truncate.DIR]: "allow", [Truncate.GLOB]: "allow" } }),
)
}
return result
})
export async function get(agent: string) {
return state().then((x) => x[agent])
}
export async function list() {
const cfg = await Config.get()
return pipe(
await state(),
values(),
sortBy([(x) => (cfg.default_agent ? x.name === cfg.default_agent : x.name === "research"), "desc"]),
)
}
export async function defaultAgent() {
const cfg = await Config.get()
const agents = await state()
if (cfg.default_agent) {
const agent = agents[cfg.default_agent]
if (!agent) throw new Error(`default agent "${cfg.default_agent}" not found`)
if (agent.mode === "subagent") throw new Error(`default agent "${cfg.default_agent}" is a subagent`)
if (agent.hidden === true) throw new Error(`default agent "${cfg.default_agent}" is hidden`)
return agent.name
}
const primaryVisible = Object.values(agents).find((a) => a.mode !== "subagent" && a.hidden !== true)
if (!primaryVisible) throw new Error("no primary visible agent found")
return primaryVisible.name
}
export async function generate(input: { description: string; model?: { providerID: string; modelID: string } }) {
const cfg = await Config.get()
const defaultModel = input.model ?? (await Provider.defaultModel())
const model = await Provider.getModel(defaultModel.providerID, defaultModel.modelID)
const language = await Provider.getLanguage(model)
const system = [PROMPT_GENERATE]
await Plugin.trigger("experimental.chat.system.transform", { model }, { system })
const existing = await list()
const params = {
experimental_telemetry: {
isEnabled: cfg.experimental?.openTelemetry,
metadata: {
userId: cfg.username ?? "unknown",
},
},
temperature: 0.3,
messages: [
...system.map(
(item): ModelMessage => ({
role: "system",
content: item,
}),
),
{
role: "user",
content: `Create an agent configuration based on this request: \"${input.description}\".\n\nIMPORTANT: The following identifiers already exist and must NOT be used: ${existing.map((i) => i.name).join(", ")}\n Return ONLY the JSON object, no other text, do not wrap in backticks`,
},
],
model: language,
schema: z.object({
identifier: z.string(),
whenToUse: z.string(),
systemPrompt: z.string(),
}),
} satisfies Parameters<typeof generateObject>[0]
if (defaultModel.providerID === "openai" && (await Auth.get(defaultModel.providerID))?.type === "oauth") {
const result = streamObject({
...params,
providerOptions: ProviderTransform.providerOptions(model, {
instructions: SystemPrompt.instructions(),
store: false,
}),
onError: () => {},
})
for await (const part of result.fullStream) {
if (part.type === "error") throw part.error
}
return result.object
}
const result = await generateObject(params)
return result.object
}
}