mirror of
https://github.com/anomalyco/opencode.git
synced 2026-05-18 10:07:58 +00:00
refactor(session): add native LLM request adapter
This commit is contained in:
Kit Langton
184
packages/opencode/src/session/llm-native.ts
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184
packages/opencode/src/session/llm-native.ts
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@@ -0,0 +1,184 @@
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import type { JsonSchema, LLMRequest, ProviderMetadata, ToolDefinition } from "@opencode-ai/llm"
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import { LLM } from "@opencode-ai/llm"
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import type { ModelMessage } from "ai"
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import type { Provider } from "@/provider/provider"
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type ToolInput = {
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readonly description?: string
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readonly inputSchema?: unknown
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}
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export type RequestInput = {
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readonly model: Provider.Model
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readonly system?: readonly string[]
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readonly messages: readonly ModelMessage[]
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readonly tools?: Record<string, ToolInput>
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readonly toolChoice?: "auto" | "required" | "none"
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readonly temperature?: number
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readonly topP?: number
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readonly topK?: number
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readonly maxOutputTokens?: number
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readonly providerOptions?: LLMRequest["providerOptions"]
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readonly headers?: Record<string, string>
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}
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const DEFAULT_BASE_URL: Record<string, string> = {
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"@ai-sdk/openai": "https://api.openai.com/v1",
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"@ai-sdk/anthropic": "https://api.anthropic.com/v1",
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"@ai-sdk/google": "https://generativelanguage.googleapis.com/v1beta",
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"@ai-sdk/amazon-bedrock": "https://bedrock-runtime.us-east-1.amazonaws.com",
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}
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const ROUTE: Record<string, string> = {
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"@ai-sdk/openai": "openai-responses",
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"@ai-sdk/azure": "azure-openai-responses",
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"@ai-sdk/anthropic": "anthropic-messages",
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"@ai-sdk/google": "gemini",
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"@ai-sdk/amazon-bedrock": "bedrock-converse",
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"@ai-sdk/openai-compatible": "openai-compatible-chat",
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"@openrouter/ai-sdk-provider": "openai-compatible-chat",
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}
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const isRecord = (value: unknown): value is Record<string, unknown> =>
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typeof value === "object" && value !== null && !Array.isArray(value)
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const providerMetadata = (value: unknown): ProviderMetadata | undefined => {
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if (!isRecord(value)) return undefined
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const result = Object.fromEntries(
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Object.entries(value).filter((entry): entry is [string, Record<string, unknown>] => isRecord(entry[1])),
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)
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return Object.keys(result).length === 0 ? undefined : result
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}
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const textPart = (part: Record<string, unknown>) => ({
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type: "text" as const,
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text: typeof part.text === "string" ? part.text : "",
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providerMetadata: providerMetadata(part.providerOptions),
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})
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const mediaPart = (part: Record<string, unknown>) => {
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if (typeof part.data !== "string" && !(part.data instanceof Uint8Array))
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throw new Error("Native LLM request adapter only supports file parts with string or Uint8Array data")
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return {
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type: "media" as const,
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mediaType: typeof part.mediaType === "string" ? part.mediaType : "application/octet-stream",
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data: part.data,
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filename: typeof part.filename === "string" ? part.filename : undefined,
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}
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}
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const toolResult = (part: Record<string, unknown>) => {
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const output = isRecord(part.output) ? part.output : { type: "json", value: part.output }
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const type = output.type === "text" ? "text" : output.type === "error-text" ? "error" : "json"
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return LLM.toolResult({
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id: typeof part.toolCallId === "string" ? part.toolCallId : "",
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name: typeof part.toolName === "string" ? part.toolName : "",
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result: "value" in output ? output.value : output,
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resultType: type,
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providerExecuted: typeof part.providerExecuted === "boolean" ? part.providerExecuted : undefined,
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providerMetadata: providerMetadata(part.providerOptions),
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})
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}
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const contentPart = (part: unknown) => {
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if (!isRecord(part)) throw new Error("Native LLM request adapter only supports object content parts")
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if (part.type === "text") return textPart(part)
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if (part.type === "file") return mediaPart(part)
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if (part.type === "reasoning")
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return {
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type: "reasoning" as const,
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text: typeof part.text === "string" ? part.text : "",
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providerMetadata: providerMetadata(part.providerOptions),
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}
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if (part.type === "tool-call")
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return LLM.toolCall({
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id: typeof part.toolCallId === "string" ? part.toolCallId : "",
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name: typeof part.toolName === "string" ? part.toolName : "",
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input: part.input,
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providerExecuted: typeof part.providerExecuted === "boolean" ? part.providerExecuted : undefined,
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providerMetadata: providerMetadata(part.providerOptions),
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})
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if (part.type === "tool-result") return toolResult(part)
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throw new Error(`Native LLM request adapter does not support ${String(part.type)} content parts`)
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}
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const content = (value: ModelMessage["content"]) =>
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typeof value === "string" ? [LLM.text(value)] : value.map(contentPart)
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const messages = (input: readonly ModelMessage[]) => {
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const system = input.flatMap((message) => (message.role === "system" ? [LLM.system(message.content)] : []))
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const messages = input.flatMap((message) => {
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if (message.role === "system") return []
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return [
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LLM.message({
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role: message.role,
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content: content(message.content),
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native: isRecord(message.providerOptions) ? { providerOptions: message.providerOptions } : undefined,
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}),
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]
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})
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return { system, messages }
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}
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const schema = (value: unknown): JsonSchema => {
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if (!isRecord(value)) return { type: "object", properties: {} }
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if (isRecord(value.jsonSchema)) return value.jsonSchema
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return value
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}
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const tools = (input: Record<string, ToolInput> | undefined): ToolDefinition[] =>
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Object.entries(input ?? {}).map(([name, item]) =>
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LLM.toolDefinition({
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name,
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description: item.description ?? "",
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inputSchema: schema(item.inputSchema),
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}),
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)
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const generation = (input: RequestInput) => {
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const result = {
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temperature: input.temperature,
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topP: input.topP,
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topK: input.topK,
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maxTokens: input.maxOutputTokens,
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}
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return Object.values(result).some((value) => value !== undefined) ? result : undefined
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}
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const baseURL = (model: Provider.Model) => {
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if (model.api.url) return model.api.url
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const fallback = DEFAULT_BASE_URL[model.api.npm]
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if (fallback) return fallback
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throw new Error(`Native LLM request adapter requires a base URL for ${model.providerID}/${model.id}`)
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}
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export const model = (model: Provider.Model, headers?: Record<string, string>) => {
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const route = ROUTE[model.api.npm]
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if (!route) throw new Error(`Native LLM request adapter does not support provider package ${model.api.npm}`)
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return LLM.model({
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id: model.api.id,
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provider: model.providerID,
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route,
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baseURL: baseURL(model),
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headers: Object.keys({ ...model.headers, ...headers }).length === 0 ? undefined : { ...model.headers, ...headers },
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limits: {
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context: model.limit.context,
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output: model.limit.output,
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},
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})
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}
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export const request = (input: RequestInput) => {
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const converted = messages(input.messages)
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return LLM.request({
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model: model(input.model, input.headers),
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system: [...(input.system ?? []).map(LLM.system), ...converted.system],
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messages: converted.messages,
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tools: tools(input.tools),
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toolChoice: input.toolChoice,
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generation: generation(input),
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providerOptions: input.providerOptions,
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})
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}
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export * as LLMNative from "./llm-native"
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219
packages/opencode/test/session/llm-native.test.ts
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219
packages/opencode/test/session/llm-native.test.ts
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@@ -0,0 +1,219 @@
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import { describe, expect, test } from "bun:test"
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import { jsonSchema, tool, type ModelMessage } from "ai"
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import { LLMNative } from "@/session/llm-native"
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import type { Provider } from "@/provider/provider"
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import { ModelID, ProviderID } from "@/provider/schema"
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const baseModel: Provider.Model = {
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id: ModelID.make("gpt-5-mini"),
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providerID: ProviderID.make("openai"),
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api: {
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id: "gpt-5-mini",
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url: "https://api.openai.com/v1",
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npm: "@ai-sdk/openai",
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},
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name: "GPT-5 Mini",
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capabilities: {
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temperature: true,
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reasoning: true,
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attachment: true,
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toolcall: true,
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input: {
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text: true,
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audio: false,
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image: true,
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video: false,
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pdf: false,
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},
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output: {
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text: true,
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audio: false,
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image: false,
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video: false,
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pdf: false,
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},
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interleaved: false,
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},
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cost: {
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input: 0,
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output: 0,
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cache: {
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read: 0,
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write: 0,
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},
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},
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limit: {
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context: 128_000,
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input: 128_000,
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output: 32_000,
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},
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status: "active",
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options: {},
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headers: {
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"x-model": "model-header",
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},
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release_date: "2026-01-01",
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}
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describe("session.llm-native.request", () => {
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test("maps normalized stream inputs to a native LLM request", () => {
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const messages: ModelMessage[] = [
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{
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role: "system",
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content: "system from messages",
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},
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{
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role: "user",
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content: [
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{ type: "text", text: "hello", providerOptions: { openai: { cacheControl: { type: "ephemeral" } } } },
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{ type: "file", mediaType: "image/png", filename: "img.png", data: "data:image/png;base64,Zm9v" },
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],
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},
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{
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role: "assistant",
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content: [
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{ type: "reasoning", text: "thinking", providerOptions: { openai: { encryptedContent: "secret" } } },
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{ type: "text", text: "I'll run it" },
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{
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type: "tool-call",
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toolCallId: "call-1",
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toolName: "bash",
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input: { command: "ls" },
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providerOptions: { openai: { itemId: "item-1" } },
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},
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],
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},
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{
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role: "tool",
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content: [
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{
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type: "tool-result",
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toolCallId: "call-1",
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toolName: "bash",
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output: { type: "text", value: "ok" },
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providerOptions: { openai: { outputId: "output-1" } },
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},
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],
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},
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]
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const request = LLMNative.request({
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model: baseModel,
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system: ["agent system"],
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messages,
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tools: {
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bash: tool({
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description: "Run a shell command",
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inputSchema: jsonSchema({
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type: "object",
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properties: {
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command: { type: "string" },
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},
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required: ["command"],
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}),
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}),
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},
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toolChoice: "required",
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temperature: 0.2,
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topP: 0.9,
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topK: 40,
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maxOutputTokens: 1024,
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providerOptions: { openai: { store: false } },
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headers: { "x-request": "request-header" },
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})
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expect(request.model).toMatchObject({
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id: "gpt-5-mini",
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provider: "openai",
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route: "openai-responses",
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baseURL: "https://api.openai.com/v1",
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headers: {
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"x-model": "model-header",
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"x-request": "request-header",
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},
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limits: {
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context: 128_000,
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output: 32_000,
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},
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})
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expect(request.system).toEqual([
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{ type: "text", text: "agent system" },
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{ type: "text", text: "system from messages" },
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])
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expect(request.generation).toMatchObject({
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temperature: 0.2,
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topP: 0.9,
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topK: 40,
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maxTokens: 1024,
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})
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expect(request.providerOptions).toEqual({ openai: { store: false } })
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expect(request.toolChoice).toMatchObject({ type: "required" })
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expect(request.tools).toMatchObject([
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{
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name: "bash",
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description: "Run a shell command",
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inputSchema: {
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type: "object",
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properties: {
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command: { type: "string" },
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},
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required: ["command"],
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},
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},
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])
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expect(request.messages).toMatchObject([
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{
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role: "user",
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content: [
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{ type: "text", text: "hello", providerMetadata: { openai: { cacheControl: { type: "ephemeral" } } } },
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{ type: "media", mediaType: "image/png", filename: "img.png", data: "data:image/png;base64,Zm9v" },
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],
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},
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{
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role: "assistant",
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content: [
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{ type: "reasoning", text: "thinking", providerMetadata: { openai: { encryptedContent: "secret" } } },
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{ type: "text", text: "I'll run it" },
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{
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type: "tool-call",
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id: "call-1",
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name: "bash",
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input: { command: "ls" },
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providerMetadata: { openai: { itemId: "item-1" } },
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},
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],
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},
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{
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role: "tool",
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content: [
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{
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type: "tool-result",
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id: "call-1",
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name: "bash",
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result: { type: "text", value: "ok" },
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providerMetadata: { openai: { outputId: "output-1" } },
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},
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],
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},
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])
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})
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test("selects native routes from existing provider packages", () => {
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expect(LLMNative.model({ ...baseModel, api: { ...baseModel.api, npm: "@ai-sdk/anthropic" } }).route).toBe(
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"anthropic-messages",
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)
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expect(LLMNative.model({ ...baseModel, api: { ...baseModel.api, npm: "@ai-sdk/google" } }).route).toBe("gemini")
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expect(LLMNative.model({ ...baseModel, api: { ...baseModel.api, npm: "@ai-sdk/openai-compatible" } }).route).toBe(
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"openai-compatible-chat",
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)
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})
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test("fails fast for unsupported provider packages", () => {
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expect(() =>
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LLMNative.request({
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model: { ...baseModel, api: { ...baseModel.api, npm: "unknown-provider" } },
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messages: [],
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}),
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).toThrow("Native LLM request adapter does not support provider package unknown-provider")
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})
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})
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