mirror of
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core: expose v2 model listing API (#25821)
This commit is contained in:
Dax
GitHub
parent
bebe5442a5
commit
8345152319
138 changed files with 8191 additions and 305 deletions
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import {
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type LanguageModelV3Prompt,
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type LanguageModelV3ToolCallPart,
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type SharedV3Warning,
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UnsupportedFunctionalityError,
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} from "@ai-sdk/provider"
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import { convertToBase64, parseProviderOptions } from "@ai-sdk/provider-utils"
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import { z } from "zod/v4"
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import type { OpenAIResponsesInput, OpenAIResponsesReasoning } from "./openai-responses-api-types"
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import { localShellInputSchema, localShellOutputSchema } from "./tool/local-shell"
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/**
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* Check if a string is a file ID based on the given prefixes
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* Returns false if prefixes is undefined (disables file ID detection)
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*/
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function isFileId(data: string, prefixes?: readonly string[]): boolean {
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if (!prefixes) return false
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return prefixes.some((prefix) => data.startsWith(prefix))
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}
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export async function convertToOpenAIResponsesInput({
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prompt,
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systemMessageMode,
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fileIdPrefixes,
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store,
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hasLocalShellTool = false,
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}: {
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prompt: LanguageModelV3Prompt
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systemMessageMode: "system" | "developer" | "remove"
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fileIdPrefixes?: readonly string[]
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store: boolean
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hasLocalShellTool?: boolean
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}): Promise<{
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input: OpenAIResponsesInput
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warnings: Array<SharedV3Warning>
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}> {
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const input: OpenAIResponsesInput = []
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const warnings: Array<SharedV3Warning> = []
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const processedApprovalIds = new Set<string>()
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for (const { role, content } of prompt) {
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switch (role) {
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case "system": {
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switch (systemMessageMode) {
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case "system": {
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input.push({ role: "system", content })
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break
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}
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case "developer": {
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input.push({ role: "developer", content })
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break
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}
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case "remove": {
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warnings.push({
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type: "other",
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message: "system messages are removed for this model",
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})
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break
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}
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default: {
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const _exhaustiveCheck: never = systemMessageMode
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throw new Error(`Unsupported system message mode: ${_exhaustiveCheck}`)
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}
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}
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break
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}
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case "user": {
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input.push({
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role: "user",
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content: content.map((part, index) => {
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switch (part.type) {
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case "text": {
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return { type: "input_text", text: part.text }
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}
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case "file": {
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if (part.mediaType.startsWith("image/")) {
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const mediaType = part.mediaType === "image/*" ? "image/jpeg" : part.mediaType
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return {
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type: "input_image",
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...(part.data instanceof URL
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? { image_url: part.data.toString() }
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: typeof part.data === "string" && isFileId(part.data, fileIdPrefixes)
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? { file_id: part.data }
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: {
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image_url: `data:${mediaType};base64,${convertToBase64(part.data)}`,
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}),
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detail: part.providerOptions?.openai?.imageDetail,
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}
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} else if (part.mediaType === "application/pdf") {
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if (part.data instanceof URL) {
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return {
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type: "input_file",
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file_url: part.data.toString(),
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}
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}
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return {
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type: "input_file",
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...(typeof part.data === "string" && isFileId(part.data, fileIdPrefixes)
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? { file_id: part.data }
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: {
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filename: part.filename ?? `part-${index}.pdf`,
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file_data: `data:application/pdf;base64,${convertToBase64(part.data)}`,
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}),
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}
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} else {
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throw new UnsupportedFunctionalityError({
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functionality: `file part media type ${part.mediaType}`,
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})
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}
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}
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}
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}),
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})
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break
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}
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case "assistant": {
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const reasoningMessages: Record<string, OpenAIResponsesReasoning> = {}
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const toolCallParts: Record<string, LanguageModelV3ToolCallPart> = {}
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for (const part of content) {
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switch (part.type) {
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case "text": {
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input.push({
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role: "assistant",
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content: [{ type: "output_text", text: part.text }],
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id: (part.providerOptions?.openai?.itemId as string) ?? undefined,
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})
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break
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}
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case "tool-call": {
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toolCallParts[part.toolCallId] = part
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if (part.providerExecuted) {
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break
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}
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if (hasLocalShellTool && part.toolName === "local_shell") {
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const parsedInput = localShellInputSchema.parse(part.input)
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input.push({
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type: "local_shell_call",
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call_id: part.toolCallId,
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id: (part.providerOptions?.openai?.itemId as string) ?? undefined,
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action: {
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type: "exec",
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command: parsedInput.action.command,
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timeout_ms: parsedInput.action.timeoutMs,
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user: parsedInput.action.user,
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working_directory: parsedInput.action.workingDirectory,
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env: parsedInput.action.env,
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},
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})
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break
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}
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input.push({
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type: "function_call",
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call_id: part.toolCallId,
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name: part.toolName,
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arguments: JSON.stringify(part.input),
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id: (part.providerOptions?.openai?.itemId as string) ?? undefined,
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})
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break
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}
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// assistant tool result parts are from provider-executed tools:
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case "tool-result": {
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if (store) {
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// use item references to refer to tool results from built-in tools
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input.push({ type: "item_reference", id: part.toolCallId })
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} else {
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warnings.push({
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type: "other",
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message: `Results for OpenAI tool ${part.toolName} are not sent to the API when store is false`,
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})
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}
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break
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}
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case "reasoning": {
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const providerOptions = await parseProviderOptions({
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provider: "copilot",
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providerOptions: part.providerOptions,
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schema: openaiResponsesReasoningProviderOptionsSchema,
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})
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const reasoningId = providerOptions?.itemId
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if (reasoningId != null) {
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const reasoningMessage = reasoningMessages[reasoningId]
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if (store) {
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if (reasoningMessage === undefined) {
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// use item references to refer to reasoning (single reference)
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input.push({ type: "item_reference", id: reasoningId })
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// store unused reasoning message to mark id as used
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reasoningMessages[reasoningId] = {
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type: "reasoning",
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id: reasoningId,
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summary: [],
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}
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}
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} else {
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const summaryParts: Array<{
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type: "summary_text"
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text: string
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}> = []
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if (part.text.length > 0) {
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summaryParts.push({
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type: "summary_text",
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text: part.text,
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})
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} else if (reasoningMessage !== undefined) {
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warnings.push({
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type: "other",
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message: `Cannot append empty reasoning part to existing reasoning sequence. Skipping reasoning part: ${JSON.stringify(part)}.`,
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})
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}
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if (reasoningMessage === undefined) {
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reasoningMessages[reasoningId] = {
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type: "reasoning",
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id: reasoningId,
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encrypted_content: providerOptions?.reasoningEncryptedContent,
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summary: summaryParts,
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}
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input.push(reasoningMessages[reasoningId])
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} else {
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reasoningMessage.summary.push(...summaryParts)
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}
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}
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} else {
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warnings.push({
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type: "other",
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message: `Non-OpenAI reasoning parts are not supported. Skipping reasoning part: ${JSON.stringify(part)}.`,
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})
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}
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break
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}
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}
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}
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break
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}
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case "tool": {
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for (const part of content) {
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if (part.type === "tool-approval-response") {
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if (processedApprovalIds.has(part.approvalId)) {
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continue
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}
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processedApprovalIds.add(part.approvalId)
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if (store) {
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input.push({
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type: "item_reference",
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id: part.approvalId,
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})
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}
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input.push({
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type: "mcp_approval_response",
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approval_request_id: part.approvalId,
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approve: part.approved,
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})
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continue
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}
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const output = part.output
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if (output.type === "execution-denied") {
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const approvalId = (output.providerOptions?.openai as { approvalId?: string } | undefined)?.approvalId
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if (approvalId) {
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continue
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}
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}
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if (hasLocalShellTool && part.toolName === "local_shell" && output.type === "json") {
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input.push({
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type: "local_shell_call_output",
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call_id: part.toolCallId,
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output: localShellOutputSchema.parse(output.value).output,
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})
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break
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}
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let contentValue: string
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switch (output.type) {
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case "text":
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case "error-text":
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contentValue = output.value
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break
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case "execution-denied":
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contentValue = output.reason ?? "Tool execution denied."
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break
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case "content":
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case "json":
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case "error-json":
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contentValue = JSON.stringify(output.value)
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break
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}
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input.push({
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type: "function_call_output",
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call_id: part.toolCallId,
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output: contentValue,
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})
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}
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break
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}
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default: {
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const _exhaustiveCheck: never = role
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throw new Error(`Unsupported role: ${_exhaustiveCheck}`)
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}
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}
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}
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return { input, warnings }
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}
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const openaiResponsesReasoningProviderOptionsSchema = z.object({
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itemId: z.string().nullish(),
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reasoningEncryptedContent: z.string().nullish(),
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})
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export type OpenAIResponsesReasoningProviderOptions = z.infer<typeof openaiResponsesReasoningProviderOptionsSchema>
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import type { LanguageModelV3FinishReason } from "@ai-sdk/provider"
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export function mapOpenAIResponseFinishReason({
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finishReason,
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hasFunctionCall,
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}: {
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finishReason: string | null | undefined
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// flag that checks if there have been client-side tool calls (not executed by openai)
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hasFunctionCall: boolean
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}): LanguageModelV3FinishReason["unified"] {
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switch (finishReason) {
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case undefined:
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case null:
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return hasFunctionCall ? "tool-calls" : "stop"
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case "max_output_tokens":
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return "length"
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case "content_filter":
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return "content-filter"
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default:
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return hasFunctionCall ? "tool-calls" : "other"
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}
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}
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18
packages/core/src/github-copilot/responses/openai-config.ts
Normal file
18
packages/core/src/github-copilot/responses/openai-config.ts
Normal file
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import type { FetchFunction } from "@ai-sdk/provider-utils"
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export type OpenAIConfig = {
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provider: string
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url: (options: { modelId: string; path: string }) => string
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headers: () => Record<string, string | undefined>
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fetch?: FetchFunction
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generateId?: () => string
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/**
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* File ID prefixes used to identify file IDs in Responses API.
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* When undefined, all file data is treated as base64 content.
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*
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* Examples:
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* - OpenAI: ['file-'] for IDs like 'file-abc123'
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* - Azure OpenAI: ['assistant-'] for IDs like 'assistant-abc123'
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*/
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fileIdPrefixes?: readonly string[]
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}
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22
packages/core/src/github-copilot/responses/openai-error.ts
Normal file
22
packages/core/src/github-copilot/responses/openai-error.ts
Normal file
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@ -0,0 +1,22 @@
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import { z } from "zod/v4"
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import { createJsonErrorResponseHandler } from "@ai-sdk/provider-utils"
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export const openaiErrorDataSchema = z.object({
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error: z.object({
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message: z.string(),
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// The additional information below is handled loosely to support
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// OpenAI-compatible providers that have slightly different error
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// responses:
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type: z.string().nullish(),
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param: z.any().nullish(),
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code: z.union([z.string(), z.number()]).nullish(),
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}),
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})
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export type OpenAIErrorData = z.infer<typeof openaiErrorDataSchema>
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export const openaiFailedResponseHandler: any = createJsonErrorResponseHandler({
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errorSchema: openaiErrorDataSchema,
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errorToMessage: (data) => data.error.message,
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})
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@ -0,0 +1,214 @@
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import type { JSONSchema7 } from "@ai-sdk/provider"
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export type OpenAIResponsesInput = Array<OpenAIResponsesInputItem>
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export type OpenAIResponsesInputItem =
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| OpenAIResponsesSystemMessage
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| OpenAIResponsesUserMessage
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| OpenAIResponsesAssistantMessage
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| OpenAIResponsesFunctionCall
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| OpenAIResponsesFunctionCallOutput
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| OpenAIResponsesComputerCall
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| OpenAIResponsesLocalShellCall
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| OpenAIResponsesLocalShellCallOutput
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| OpenAIResponsesReasoning
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| OpenAIResponsesItemReference
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| OpenAIResponsesMcpApprovalResponse
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export type OpenAIResponsesIncludeValue =
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| "web_search_call.action.sources"
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| "code_interpreter_call.outputs"
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| "computer_call_output.output.image_url"
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| "file_search_call.results"
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| "message.input_image.image_url"
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| "message.output_text.logprobs"
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| "reasoning.encrypted_content"
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export type OpenAIResponsesIncludeOptions = Array<OpenAIResponsesIncludeValue> | undefined | null
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export type OpenAIResponsesSystemMessage = {
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role: "system" | "developer"
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content: string
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}
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export type OpenAIResponsesUserMessage = {
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role: "user"
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content: Array<
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| { type: "input_text"; text: string }
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| { type: "input_image"; image_url: string }
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| { type: "input_image"; file_id: string }
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| { type: "input_file"; file_url: string }
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| { type: "input_file"; filename: string; file_data: string }
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| { type: "input_file"; file_id: string }
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>
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}
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|
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export type OpenAIResponsesAssistantMessage = {
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role: "assistant"
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content: Array<{ type: "output_text"; text: string }>
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id?: string
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||||
}
|
||||
|
||||
export type OpenAIResponsesFunctionCall = {
|
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type: "function_call"
|
||||
call_id: string
|
||||
name: string
|
||||
arguments: string
|
||||
id?: string
|
||||
}
|
||||
|
||||
export type OpenAIResponsesFunctionCallOutput = {
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type: "function_call_output"
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call_id: string
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||||
output: string
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||||
}
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|
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export type OpenAIResponsesComputerCall = {
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type: "computer_call"
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id: string
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||||
status?: string
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||||
}
|
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|
||||
export type OpenAIResponsesLocalShellCall = {
|
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type: "local_shell_call"
|
||||
id: string
|
||||
call_id: string
|
||||
action: {
|
||||
type: "exec"
|
||||
command: string[]
|
||||
timeout_ms?: number
|
||||
user?: string
|
||||
working_directory?: string
|
||||
env?: Record<string, string>
|
||||
}
|
||||
}
|
||||
|
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export type OpenAIResponsesLocalShellCallOutput = {
|
||||
type: "local_shell_call_output"
|
||||
call_id: string
|
||||
output: string
|
||||
}
|
||||
|
||||
export type OpenAIResponsesItemReference = {
|
||||
type: "item_reference"
|
||||
id: string
|
||||
}
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||||
|
||||
export type OpenAIResponsesMcpApprovalResponse = {
|
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type: "mcp_approval_response"
|
||||
approval_request_id: string
|
||||
approve: boolean
|
||||
}
|
||||
|
||||
/**
|
||||
* A filter used to compare a specified attribute key to a given value using a defined comparison operation.
|
||||
*/
|
||||
export type OpenAIResponsesFileSearchToolComparisonFilter = {
|
||||
/**
|
||||
* The key to compare against the value.
|
||||
*/
|
||||
key: string
|
||||
|
||||
/**
|
||||
* Specifies the comparison operator: eq, ne, gt, gte, lt, lte.
|
||||
*/
|
||||
type: "eq" | "ne" | "gt" | "gte" | "lt" | "lte"
|
||||
|
||||
/**
|
||||
* The value to compare against the attribute key; supports string, number, or boolean types.
|
||||
*/
|
||||
value: string | number | boolean
|
||||
}
|
||||
|
||||
/**
|
||||
* Combine multiple filters using and or or.
|
||||
*/
|
||||
export type OpenAIResponsesFileSearchToolCompoundFilter = {
|
||||
/**
|
||||
* Type of operation: and or or.
|
||||
*/
|
||||
type: "and" | "or"
|
||||
|
||||
/**
|
||||
* Array of filters to combine. Items can be ComparisonFilter or CompoundFilter.
|
||||
*/
|
||||
filters: Array<OpenAIResponsesFileSearchToolComparisonFilter | OpenAIResponsesFileSearchToolCompoundFilter>
|
||||
}
|
||||
|
||||
export type OpenAIResponsesTool =
|
||||
| {
|
||||
type: "function"
|
||||
name: string
|
||||
description: string | undefined
|
||||
parameters: JSONSchema7
|
||||
strict: boolean | undefined
|
||||
}
|
||||
| {
|
||||
type: "web_search"
|
||||
filters: { allowed_domains: string[] | undefined } | undefined
|
||||
search_context_size: "low" | "medium" | "high" | undefined
|
||||
user_location:
|
||||
| {
|
||||
type: "approximate"
|
||||
city?: string
|
||||
country?: string
|
||||
region?: string
|
||||
timezone?: string
|
||||
}
|
||||
| undefined
|
||||
}
|
||||
| {
|
||||
type: "web_search_preview"
|
||||
search_context_size: "low" | "medium" | "high" | undefined
|
||||
user_location:
|
||||
| {
|
||||
type: "approximate"
|
||||
city?: string
|
||||
country?: string
|
||||
region?: string
|
||||
timezone?: string
|
||||
}
|
||||
| undefined
|
||||
}
|
||||
| {
|
||||
type: "code_interpreter"
|
||||
container: string | { type: "auto"; file_ids: string[] | undefined }
|
||||
}
|
||||
| {
|
||||
type: "file_search"
|
||||
vector_store_ids: string[]
|
||||
max_num_results: number | undefined
|
||||
ranking_options: { ranker?: string; score_threshold?: number } | undefined
|
||||
filters: OpenAIResponsesFileSearchToolComparisonFilter | OpenAIResponsesFileSearchToolCompoundFilter | undefined
|
||||
}
|
||||
| {
|
||||
type: "image_generation"
|
||||
background: "auto" | "opaque" | "transparent" | undefined
|
||||
input_fidelity: "low" | "high" | undefined
|
||||
input_image_mask:
|
||||
| {
|
||||
file_id: string | undefined
|
||||
image_url: string | undefined
|
||||
}
|
||||
| undefined
|
||||
model: string | undefined
|
||||
moderation: "auto" | undefined
|
||||
output_compression: number | undefined
|
||||
output_format: "png" | "jpeg" | "webp" | undefined
|
||||
partial_images: number | undefined
|
||||
quality: "auto" | "low" | "medium" | "high" | undefined
|
||||
size: "auto" | "1024x1024" | "1024x1536" | "1536x1024" | undefined
|
||||
}
|
||||
| {
|
||||
type: "local_shell"
|
||||
}
|
||||
|
||||
export type OpenAIResponsesReasoning = {
|
||||
type: "reasoning"
|
||||
id: string
|
||||
encrypted_content?: string | null
|
||||
summary: Array<{
|
||||
type: "summary_text"
|
||||
text: string
|
||||
}>
|
||||
}
|
||||
File diff suppressed because it is too large
Load diff
|
|
@ -0,0 +1,173 @@
|
|||
import { type LanguageModelV3CallOptions, type SharedV3Warning, UnsupportedFunctionalityError } from "@ai-sdk/provider"
|
||||
import { codeInterpreterArgsSchema } from "./tool/code-interpreter"
|
||||
import { fileSearchArgsSchema } from "./tool/file-search"
|
||||
import { webSearchArgsSchema } from "./tool/web-search"
|
||||
import { webSearchPreviewArgsSchema } from "./tool/web-search-preview"
|
||||
import { imageGenerationArgsSchema } from "./tool/image-generation"
|
||||
import type { OpenAIResponsesTool } from "./openai-responses-api-types"
|
||||
|
||||
export function prepareResponsesTools({
|
||||
tools,
|
||||
toolChoice,
|
||||
strictJsonSchema,
|
||||
}: {
|
||||
tools: LanguageModelV3CallOptions["tools"]
|
||||
toolChoice?: LanguageModelV3CallOptions["toolChoice"]
|
||||
strictJsonSchema: boolean
|
||||
}): {
|
||||
tools?: Array<OpenAIResponsesTool>
|
||||
toolChoice?:
|
||||
| "auto"
|
||||
| "none"
|
||||
| "required"
|
||||
| { type: "file_search" }
|
||||
| { type: "web_search_preview" }
|
||||
| { type: "web_search" }
|
||||
| { type: "function"; name: string }
|
||||
| { type: "code_interpreter" }
|
||||
| { type: "image_generation" }
|
||||
toolWarnings: SharedV3Warning[]
|
||||
} {
|
||||
// when the tools array is empty, change it to undefined to prevent errors:
|
||||
tools = tools?.length ? tools : undefined
|
||||
|
||||
const toolWarnings: SharedV3Warning[] = []
|
||||
|
||||
if (tools == null) {
|
||||
return { tools: undefined, toolChoice: undefined, toolWarnings }
|
||||
}
|
||||
|
||||
const openaiTools: Array<OpenAIResponsesTool> = []
|
||||
|
||||
for (const tool of tools) {
|
||||
switch (tool.type) {
|
||||
case "function":
|
||||
openaiTools.push({
|
||||
type: "function",
|
||||
name: tool.name,
|
||||
description: tool.description,
|
||||
parameters: tool.inputSchema,
|
||||
strict: strictJsonSchema,
|
||||
})
|
||||
break
|
||||
case "provider": {
|
||||
switch (tool.id) {
|
||||
case "openai.file_search": {
|
||||
const args = fileSearchArgsSchema.parse(tool.args)
|
||||
|
||||
openaiTools.push({
|
||||
type: "file_search",
|
||||
vector_store_ids: args.vectorStoreIds,
|
||||
max_num_results: args.maxNumResults,
|
||||
ranking_options: args.ranking
|
||||
? {
|
||||
ranker: args.ranking.ranker,
|
||||
score_threshold: args.ranking.scoreThreshold,
|
||||
}
|
||||
: undefined,
|
||||
filters: args.filters,
|
||||
})
|
||||
|
||||
break
|
||||
}
|
||||
case "openai.local_shell": {
|
||||
openaiTools.push({
|
||||
type: "local_shell",
|
||||
})
|
||||
break
|
||||
}
|
||||
case "openai.web_search_preview": {
|
||||
const args = webSearchPreviewArgsSchema.parse(tool.args)
|
||||
openaiTools.push({
|
||||
type: "web_search_preview",
|
||||
search_context_size: args.searchContextSize,
|
||||
user_location: args.userLocation,
|
||||
})
|
||||
break
|
||||
}
|
||||
case "openai.web_search": {
|
||||
const args = webSearchArgsSchema.parse(tool.args)
|
||||
openaiTools.push({
|
||||
type: "web_search",
|
||||
filters: args.filters != null ? { allowed_domains: args.filters.allowedDomains } : undefined,
|
||||
search_context_size: args.searchContextSize,
|
||||
user_location: args.userLocation,
|
||||
})
|
||||
break
|
||||
}
|
||||
case "openai.code_interpreter": {
|
||||
const args = codeInterpreterArgsSchema.parse(tool.args)
|
||||
openaiTools.push({
|
||||
type: "code_interpreter",
|
||||
container:
|
||||
args.container == null
|
||||
? { type: "auto", file_ids: undefined }
|
||||
: typeof args.container === "string"
|
||||
? args.container
|
||||
: { type: "auto", file_ids: args.container.fileIds },
|
||||
})
|
||||
break
|
||||
}
|
||||
case "openai.image_generation": {
|
||||
const args = imageGenerationArgsSchema.parse(tool.args)
|
||||
openaiTools.push({
|
||||
type: "image_generation",
|
||||
background: args.background,
|
||||
input_fidelity: args.inputFidelity,
|
||||
input_image_mask: args.inputImageMask
|
||||
? {
|
||||
file_id: args.inputImageMask.fileId,
|
||||
image_url: args.inputImageMask.imageUrl,
|
||||
}
|
||||
: undefined,
|
||||
model: args.model,
|
||||
moderation: args.moderation,
|
||||
partial_images: args.partialImages,
|
||||
quality: args.quality,
|
||||
output_compression: args.outputCompression,
|
||||
output_format: args.outputFormat,
|
||||
size: args.size,
|
||||
})
|
||||
break
|
||||
}
|
||||
}
|
||||
break
|
||||
}
|
||||
default:
|
||||
toolWarnings.push({ type: "unsupported", feature: "tool type" })
|
||||
break
|
||||
}
|
||||
}
|
||||
|
||||
if (toolChoice == null) {
|
||||
return { tools: openaiTools, toolChoice: undefined, toolWarnings }
|
||||
}
|
||||
|
||||
const type = toolChoice.type
|
||||
|
||||
switch (type) {
|
||||
case "auto":
|
||||
case "none":
|
||||
case "required":
|
||||
return { tools: openaiTools, toolChoice: type, toolWarnings }
|
||||
case "tool":
|
||||
return {
|
||||
tools: openaiTools,
|
||||
toolChoice:
|
||||
toolChoice.toolName === "code_interpreter" ||
|
||||
toolChoice.toolName === "file_search" ||
|
||||
toolChoice.toolName === "image_generation" ||
|
||||
toolChoice.toolName === "web_search_preview" ||
|
||||
toolChoice.toolName === "web_search"
|
||||
? { type: toolChoice.toolName }
|
||||
: { type: "function", name: toolChoice.toolName },
|
||||
toolWarnings,
|
||||
}
|
||||
default: {
|
||||
const _exhaustiveCheck: never = type
|
||||
throw new UnsupportedFunctionalityError({
|
||||
functionality: `tool choice type: ${_exhaustiveCheck}`,
|
||||
})
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1 @@
|
|||
export type OpenAIResponsesModelId = string
|
||||
|
|
@ -0,0 +1,87 @@
|
|||
import { createProviderToolFactoryWithOutputSchema } from "@ai-sdk/provider-utils"
|
||||
import { z } from "zod/v4"
|
||||
|
||||
export const codeInterpreterInputSchema = z.object({
|
||||
code: z.string().nullish(),
|
||||
containerId: z.string(),
|
||||
})
|
||||
|
||||
export const codeInterpreterOutputSchema = z.object({
|
||||
outputs: z
|
||||
.array(
|
||||
z.discriminatedUnion("type", [
|
||||
z.object({ type: z.literal("logs"), logs: z.string() }),
|
||||
z.object({ type: z.literal("image"), url: z.string() }),
|
||||
]),
|
||||
)
|
||||
.nullish(),
|
||||
})
|
||||
|
||||
export const codeInterpreterArgsSchema = z.object({
|
||||
container: z
|
||||
.union([
|
||||
z.string(),
|
||||
z.object({
|
||||
fileIds: z.array(z.string()).optional(),
|
||||
}),
|
||||
])
|
||||
.optional(),
|
||||
})
|
||||
|
||||
type CodeInterpreterArgs = {
|
||||
/**
|
||||
* The code interpreter container.
|
||||
* Can be a container ID
|
||||
* or an object that specifies uploaded file IDs to make available to your code.
|
||||
*/
|
||||
container?: string | { fileIds?: string[] }
|
||||
}
|
||||
|
||||
export const codeInterpreterToolFactory = createProviderToolFactoryWithOutputSchema<
|
||||
{
|
||||
/**
|
||||
* The code to run, or null if not available.
|
||||
*/
|
||||
code?: string | null
|
||||
|
||||
/**
|
||||
* The ID of the container used to run the code.
|
||||
*/
|
||||
containerId: string
|
||||
},
|
||||
{
|
||||
/**
|
||||
* The outputs generated by the code interpreter, such as logs or images.
|
||||
* Can be null if no outputs are available.
|
||||
*/
|
||||
outputs?: Array<
|
||||
| {
|
||||
type: "logs"
|
||||
|
||||
/**
|
||||
* The logs output from the code interpreter.
|
||||
*/
|
||||
logs: string
|
||||
}
|
||||
| {
|
||||
type: "image"
|
||||
|
||||
/**
|
||||
* The URL of the image output from the code interpreter.
|
||||
*/
|
||||
url: string
|
||||
}
|
||||
> | null
|
||||
},
|
||||
CodeInterpreterArgs
|
||||
>({
|
||||
id: "openai.code_interpreter",
|
||||
inputSchema: codeInterpreterInputSchema,
|
||||
outputSchema: codeInterpreterOutputSchema,
|
||||
})
|
||||
|
||||
export const codeInterpreter = (
|
||||
args: CodeInterpreterArgs = {}, // default
|
||||
) => {
|
||||
return codeInterpreterToolFactory(args)
|
||||
}
|
||||
127
packages/core/src/github-copilot/responses/tool/file-search.ts
Normal file
127
packages/core/src/github-copilot/responses/tool/file-search.ts
Normal file
|
|
@ -0,0 +1,127 @@
|
|||
import { createProviderToolFactoryWithOutputSchema } from "@ai-sdk/provider-utils"
|
||||
import type {
|
||||
OpenAIResponsesFileSearchToolComparisonFilter,
|
||||
OpenAIResponsesFileSearchToolCompoundFilter,
|
||||
} from "../openai-responses-api-types"
|
||||
import { z } from "zod/v4"
|
||||
|
||||
const comparisonFilterSchema = z.object({
|
||||
key: z.string(),
|
||||
type: z.enum(["eq", "ne", "gt", "gte", "lt", "lte"]),
|
||||
value: z.union([z.string(), z.number(), z.boolean()]),
|
||||
})
|
||||
|
||||
const compoundFilterSchema: z.ZodType<any> = z.object({
|
||||
type: z.enum(["and", "or"]),
|
||||
filters: z.array(z.union([comparisonFilterSchema, z.lazy(() => compoundFilterSchema)])),
|
||||
})
|
||||
|
||||
export const fileSearchArgsSchema = z.object({
|
||||
vectorStoreIds: z.array(z.string()),
|
||||
maxNumResults: z.number().optional(),
|
||||
ranking: z
|
||||
.object({
|
||||
ranker: z.string().optional(),
|
||||
scoreThreshold: z.number().optional(),
|
||||
})
|
||||
.optional(),
|
||||
filters: z.union([comparisonFilterSchema, compoundFilterSchema]).optional(),
|
||||
})
|
||||
|
||||
export const fileSearchOutputSchema = z.object({
|
||||
queries: z.array(z.string()),
|
||||
results: z
|
||||
.array(
|
||||
z.object({
|
||||
attributes: z.record(z.string(), z.unknown()),
|
||||
fileId: z.string(),
|
||||
filename: z.string(),
|
||||
score: z.number(),
|
||||
text: z.string(),
|
||||
}),
|
||||
)
|
||||
.nullable(),
|
||||
})
|
||||
|
||||
export const fileSearch = createProviderToolFactoryWithOutputSchema<
|
||||
{},
|
||||
{
|
||||
/**
|
||||
* The search query to execute.
|
||||
*/
|
||||
queries: string[]
|
||||
|
||||
/**
|
||||
* The results of the file search tool call.
|
||||
*/
|
||||
results:
|
||||
| null
|
||||
| {
|
||||
/**
|
||||
* Set of 16 key-value pairs that can be attached to an object.
|
||||
* This can be useful for storing additional information about the object
|
||||
* in a structured format, and querying for objects via API or the dashboard.
|
||||
* Keys are strings with a maximum length of 64 characters.
|
||||
* Values are strings with a maximum length of 512 characters, booleans, or numbers.
|
||||
*/
|
||||
attributes: Record<string, unknown>
|
||||
|
||||
/**
|
||||
* The unique ID of the file.
|
||||
*/
|
||||
fileId: string
|
||||
|
||||
/**
|
||||
* The name of the file.
|
||||
*/
|
||||
filename: string
|
||||
|
||||
/**
|
||||
* The relevance score of the file - a value between 0 and 1.
|
||||
*/
|
||||
score: number
|
||||
|
||||
/**
|
||||
* The text that was retrieved from the file.
|
||||
*/
|
||||
text: string
|
||||
}[]
|
||||
},
|
||||
{
|
||||
/**
|
||||
* List of vector store IDs to search through.
|
||||
*/
|
||||
vectorStoreIds: string[]
|
||||
|
||||
/**
|
||||
* Maximum number of search results to return. Defaults to 10.
|
||||
*/
|
||||
maxNumResults?: number
|
||||
|
||||
/**
|
||||
* Ranking options for the search.
|
||||
*/
|
||||
ranking?: {
|
||||
/**
|
||||
* The ranker to use for the file search.
|
||||
*/
|
||||
ranker?: string
|
||||
|
||||
/**
|
||||
* The score threshold for the file search, a number between 0 and 1.
|
||||
* Numbers closer to 1 will attempt to return only the most relevant results,
|
||||
* but may return fewer results.
|
||||
*/
|
||||
scoreThreshold?: number
|
||||
}
|
||||
|
||||
/**
|
||||
* A filter to apply.
|
||||
*/
|
||||
filters?: OpenAIResponsesFileSearchToolComparisonFilter | OpenAIResponsesFileSearchToolCompoundFilter
|
||||
}
|
||||
>({
|
||||
id: "openai.file_search",
|
||||
inputSchema: z.object({}),
|
||||
outputSchema: fileSearchOutputSchema,
|
||||
})
|
||||
|
|
@ -0,0 +1,114 @@
|
|||
import { createProviderToolFactoryWithOutputSchema } from "@ai-sdk/provider-utils"
|
||||
import { z } from "zod/v4"
|
||||
|
||||
export const imageGenerationArgsSchema = z
|
||||
.object({
|
||||
background: z.enum(["auto", "opaque", "transparent"]).optional(),
|
||||
inputFidelity: z.enum(["low", "high"]).optional(),
|
||||
inputImageMask: z
|
||||
.object({
|
||||
fileId: z.string().optional(),
|
||||
imageUrl: z.string().optional(),
|
||||
})
|
||||
.optional(),
|
||||
model: z.string().optional(),
|
||||
moderation: z.enum(["auto"]).optional(),
|
||||
outputCompression: z.number().int().min(0).max(100).optional(),
|
||||
outputFormat: z.enum(["png", "jpeg", "webp"]).optional(),
|
||||
partialImages: z.number().int().min(0).max(3).optional(),
|
||||
quality: z.enum(["auto", "low", "medium", "high"]).optional(),
|
||||
size: z.enum(["1024x1024", "1024x1536", "1536x1024", "auto"]).optional(),
|
||||
})
|
||||
.strict()
|
||||
|
||||
export const imageGenerationOutputSchema = z.object({
|
||||
result: z.string(),
|
||||
})
|
||||
|
||||
type ImageGenerationArgs = {
|
||||
/**
|
||||
* Background type for the generated image. Default is 'auto'.
|
||||
*/
|
||||
background?: "auto" | "opaque" | "transparent"
|
||||
|
||||
/**
|
||||
* Input fidelity for the generated image. Default is 'low'.
|
||||
*/
|
||||
inputFidelity?: "low" | "high"
|
||||
|
||||
/**
|
||||
* Optional mask for inpainting.
|
||||
* Contains image_url (string, optional) and file_id (string, optional).
|
||||
*/
|
||||
inputImageMask?: {
|
||||
/**
|
||||
* File ID for the mask image.
|
||||
*/
|
||||
fileId?: string
|
||||
|
||||
/**
|
||||
* Base64-encoded mask image.
|
||||
*/
|
||||
imageUrl?: string
|
||||
}
|
||||
|
||||
/**
|
||||
* The image generation model to use. Default: gpt-image-1.
|
||||
*/
|
||||
model?: string
|
||||
|
||||
/**
|
||||
* Moderation level for the generated image. Default: auto.
|
||||
*/
|
||||
moderation?: "auto"
|
||||
|
||||
/**
|
||||
* Compression level for the output image. Default: 100.
|
||||
*/
|
||||
outputCompression?: number
|
||||
|
||||
/**
|
||||
* The output format of the generated image. One of png, webp, or jpeg.
|
||||
* Default: png
|
||||
*/
|
||||
outputFormat?: "png" | "jpeg" | "webp"
|
||||
|
||||
/**
|
||||
* Number of partial images to generate in streaming mode, from 0 (default value) to 3.
|
||||
*/
|
||||
partialImages?: number
|
||||
|
||||
/**
|
||||
* The quality of the generated image.
|
||||
* One of low, medium, high, or auto. Default: auto.
|
||||
*/
|
||||
quality?: "auto" | "low" | "medium" | "high"
|
||||
|
||||
/**
|
||||
* The size of the generated image.
|
||||
* One of 1024x1024, 1024x1536, 1536x1024, or auto.
|
||||
* Default: auto.
|
||||
*/
|
||||
size?: "auto" | "1024x1024" | "1024x1536" | "1536x1024"
|
||||
}
|
||||
|
||||
const imageGenerationToolFactory = createProviderToolFactoryWithOutputSchema<
|
||||
{},
|
||||
{
|
||||
/**
|
||||
* The generated image encoded in base64.
|
||||
*/
|
||||
result: string
|
||||
},
|
||||
ImageGenerationArgs
|
||||
>({
|
||||
id: "openai.image_generation",
|
||||
inputSchema: z.object({}),
|
||||
outputSchema: imageGenerationOutputSchema,
|
||||
})
|
||||
|
||||
export const imageGeneration = (
|
||||
args: ImageGenerationArgs = {}, // default
|
||||
) => {
|
||||
return imageGenerationToolFactory(args)
|
||||
}
|
||||
|
|
@ -0,0 +1,64 @@
|
|||
import { createProviderToolFactoryWithOutputSchema } from "@ai-sdk/provider-utils"
|
||||
import { z } from "zod/v4"
|
||||
|
||||
export const localShellInputSchema = z.object({
|
||||
action: z.object({
|
||||
type: z.literal("exec"),
|
||||
command: z.array(z.string()),
|
||||
timeoutMs: z.number().optional(),
|
||||
user: z.string().optional(),
|
||||
workingDirectory: z.string().optional(),
|
||||
env: z.record(z.string(), z.string()).optional(),
|
||||
}),
|
||||
})
|
||||
|
||||
export const localShellOutputSchema = z.object({
|
||||
output: z.string(),
|
||||
})
|
||||
|
||||
export const localShell = createProviderToolFactoryWithOutputSchema<
|
||||
{
|
||||
/**
|
||||
* Execute a shell command on the server.
|
||||
*/
|
||||
action: {
|
||||
type: "exec"
|
||||
|
||||
/**
|
||||
* The command to run.
|
||||
*/
|
||||
command: string[]
|
||||
|
||||
/**
|
||||
* Optional timeout in milliseconds for the command.
|
||||
*/
|
||||
timeoutMs?: number
|
||||
|
||||
/**
|
||||
* Optional user to run the command as.
|
||||
*/
|
||||
user?: string
|
||||
|
||||
/**
|
||||
* Optional working directory to run the command in.
|
||||
*/
|
||||
workingDirectory?: string
|
||||
|
||||
/**
|
||||
* Environment variables to set for the command.
|
||||
*/
|
||||
env?: Record<string, string>
|
||||
}
|
||||
},
|
||||
{
|
||||
/**
|
||||
* The output of local shell tool call.
|
||||
*/
|
||||
output: string
|
||||
},
|
||||
{}
|
||||
>({
|
||||
id: "openai.local_shell",
|
||||
inputSchema: localShellInputSchema,
|
||||
outputSchema: localShellOutputSchema,
|
||||
})
|
||||
|
|
@ -0,0 +1,103 @@
|
|||
import { createProviderToolFactory } from "@ai-sdk/provider-utils"
|
||||
import { z } from "zod/v4"
|
||||
|
||||
// Args validation schema
|
||||
export const webSearchPreviewArgsSchema = z.object({
|
||||
/**
|
||||
* Search context size to use for the web search.
|
||||
* - high: Most comprehensive context, highest cost, slower response
|
||||
* - medium: Balanced context, cost, and latency (default)
|
||||
* - low: Least context, lowest cost, fastest response
|
||||
*/
|
||||
searchContextSize: z.enum(["low", "medium", "high"]).optional(),
|
||||
|
||||
/**
|
||||
* User location information to provide geographically relevant search results.
|
||||
*/
|
||||
userLocation: z
|
||||
.object({
|
||||
/**
|
||||
* Type of location (always 'approximate')
|
||||
*/
|
||||
type: z.literal("approximate"),
|
||||
/**
|
||||
* Two-letter ISO country code (e.g., 'US', 'GB')
|
||||
*/
|
||||
country: z.string().optional(),
|
||||
/**
|
||||
* City name (free text, e.g., 'Minneapolis')
|
||||
*/
|
||||
city: z.string().optional(),
|
||||
/**
|
||||
* Region name (free text, e.g., 'Minnesota')
|
||||
*/
|
||||
region: z.string().optional(),
|
||||
/**
|
||||
* IANA timezone (e.g., 'America/Chicago')
|
||||
*/
|
||||
timezone: z.string().optional(),
|
||||
})
|
||||
.optional(),
|
||||
})
|
||||
|
||||
export const webSearchPreview = createProviderToolFactory<
|
||||
{
|
||||
// Web search doesn't take input parameters - it's controlled by the prompt
|
||||
},
|
||||
{
|
||||
/**
|
||||
* Search context size to use for the web search.
|
||||
* - high: Most comprehensive context, highest cost, slower response
|
||||
* - medium: Balanced context, cost, and latency (default)
|
||||
* - low: Least context, lowest cost, fastest response
|
||||
*/
|
||||
searchContextSize?: "low" | "medium" | "high"
|
||||
|
||||
/**
|
||||
* User location information to provide geographically relevant search results.
|
||||
*/
|
||||
userLocation?: {
|
||||
/**
|
||||
* Type of location (always 'approximate')
|
||||
*/
|
||||
type: "approximate"
|
||||
/**
|
||||
* Two-letter ISO country code (e.g., 'US', 'GB')
|
||||
*/
|
||||
country?: string
|
||||
/**
|
||||
* City name (free text, e.g., 'Minneapolis')
|
||||
*/
|
||||
city?: string
|
||||
/**
|
||||
* Region name (free text, e.g., 'Minnesota')
|
||||
*/
|
||||
region?: string
|
||||
/**
|
||||
* IANA timezone (e.g., 'America/Chicago')
|
||||
*/
|
||||
timezone?: string
|
||||
}
|
||||
}
|
||||
>({
|
||||
id: "openai.web_search_preview",
|
||||
inputSchema: z.object({
|
||||
action: z
|
||||
.discriminatedUnion("type", [
|
||||
z.object({
|
||||
type: z.literal("search"),
|
||||
query: z.string().nullish(),
|
||||
}),
|
||||
z.object({
|
||||
type: z.literal("open_page"),
|
||||
url: z.string(),
|
||||
}),
|
||||
z.object({
|
||||
type: z.literal("find"),
|
||||
url: z.string(),
|
||||
pattern: z.string(),
|
||||
}),
|
||||
])
|
||||
.nullish(),
|
||||
}),
|
||||
})
|
||||
102
packages/core/src/github-copilot/responses/tool/web-search.ts
Normal file
102
packages/core/src/github-copilot/responses/tool/web-search.ts
Normal file
|
|
@ -0,0 +1,102 @@
|
|||
import { createProviderToolFactory } from "@ai-sdk/provider-utils"
|
||||
import { z } from "zod/v4"
|
||||
|
||||
export const webSearchArgsSchema = z.object({
|
||||
filters: z
|
||||
.object({
|
||||
allowedDomains: z.array(z.string()).optional(),
|
||||
})
|
||||
.optional(),
|
||||
|
||||
searchContextSize: z.enum(["low", "medium", "high"]).optional(),
|
||||
|
||||
userLocation: z
|
||||
.object({
|
||||
type: z.literal("approximate"),
|
||||
country: z.string().optional(),
|
||||
city: z.string().optional(),
|
||||
region: z.string().optional(),
|
||||
timezone: z.string().optional(),
|
||||
})
|
||||
.optional(),
|
||||
})
|
||||
|
||||
export const webSearchToolFactory = createProviderToolFactory<
|
||||
{
|
||||
// Web search doesn't take input parameters - it's controlled by the prompt
|
||||
},
|
||||
{
|
||||
/**
|
||||
* Filters for the search.
|
||||
*/
|
||||
filters?: {
|
||||
/**
|
||||
* Allowed domains for the search.
|
||||
* If not provided, all domains are allowed.
|
||||
* Subdomains of the provided domains are allowed as well.
|
||||
*/
|
||||
allowedDomains?: string[]
|
||||
}
|
||||
|
||||
/**
|
||||
* Search context size to use for the web search.
|
||||
* - high: Most comprehensive context, highest cost, slower response
|
||||
* - medium: Balanced context, cost, and latency (default)
|
||||
* - low: Least context, lowest cost, fastest response
|
||||
*/
|
||||
searchContextSize?: "low" | "medium" | "high"
|
||||
|
||||
/**
|
||||
* User location information to provide geographically relevant search results.
|
||||
*/
|
||||
userLocation?: {
|
||||
/**
|
||||
* Type of location (always 'approximate')
|
||||
*/
|
||||
type: "approximate"
|
||||
/**
|
||||
* Two-letter ISO country code (e.g., 'US', 'GB')
|
||||
*/
|
||||
country?: string
|
||||
/**
|
||||
* City name (free text, e.g., 'Minneapolis')
|
||||
*/
|
||||
city?: string
|
||||
/**
|
||||
* Region name (free text, e.g., 'Minnesota')
|
||||
*/
|
||||
region?: string
|
||||
/**
|
||||
* IANA timezone (e.g., 'America/Chicago')
|
||||
*/
|
||||
timezone?: string
|
||||
}
|
||||
}
|
||||
>({
|
||||
id: "openai.web_search",
|
||||
inputSchema: z.object({
|
||||
action: z
|
||||
.discriminatedUnion("type", [
|
||||
z.object({
|
||||
type: z.literal("search"),
|
||||
query: z.string().nullish(),
|
||||
}),
|
||||
z.object({
|
||||
type: z.literal("open_page"),
|
||||
url: z.string(),
|
||||
}),
|
||||
z.object({
|
||||
type: z.literal("find"),
|
||||
url: z.string(),
|
||||
pattern: z.string(),
|
||||
}),
|
||||
])
|
||||
.nullish(),
|
||||
}),
|
||||
})
|
||||
|
||||
export const webSearch = (
|
||||
args: Parameters<typeof webSearchToolFactory>[0] = {}, // default
|
||||
) => {
|
||||
return webSearchToolFactory(args)
|
||||
}
|
||||
Loading…
Add table
Add a link
Reference in a new issue