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import * as os from "os"
import { v7 as uuidv7 } from "uuid"
import { Anthropic } from "@anthropic-ai/sdk"
import OpenAI from "openai"
import {
type ModelInfo,
openAiCodexDefaultModelId,
OpenAiCodexModelId,
openAiCodexModels,
type ReasoningEffort,
type ReasoningEffortExtended,
ApiProviderError,
} from "@roo-code/types"
import { TelemetryService } from "@roo-code/telemetry"
import { Package } from "../../shared/package"
import type { ApiHandlerOptions } from "../../shared/api"
import { ApiStream, ApiStreamUsageChunk } from "../transform/stream"
import { getModelParams } from "../transform/model-params"
import { BaseProvider } from "./base-provider"
import type { SingleCompletionHandler, ApiHandlerCreateMessageMetadata } from "../index"
import { isMcpTool } from "../../utils/mcp-name"
import { sanitizeOpenAiCallId } from "../../utils/tool-id"
import { openAiCodexOAuthManager } from "../../integrations/openai-codex/oauth"
import { t } from "../../i18n"
export type OpenAiCodexModel = ReturnType<OpenAiCodexHandler["getModel"]>
/**
* OpenAI Codex base URL for API requests
* Per the implementation guide: requests are routed to chatgpt.com/backend-api/codex
*/
const CODEX_API_BASE_URL = "https://chatgpt.com/backend-api/codex"
/**
* OpenAiCodexHandler - Uses OpenAI Responses API with OAuth authentication
*
* Key differences from OpenAiNativeHandler:
* - Uses OAuth Bearer tokens instead of API keys
* - Routes requests to Codex backend (chatgpt.com/backend-api/codex)
* - Subscription-based pricing (no per-token costs)
* - Limited model subset
* - Custom headers for Codex backend
*/
export class OpenAiCodexHandler extends BaseProvider implements SingleCompletionHandler {
protected options: ApiHandlerOptions
private readonly providerName = "OpenAI Codex"
private client?: OpenAI
// Complete response output array
private lastResponseOutput: any[] | undefined
// Last top-level response id
private lastResponseId: string | undefined
// Abort controller for cancelling ongoing requests
private abortController?: AbortController
// Session ID for the Codex API (persists for the lifetime of the handler)
private readonly sessionId: string
// Profile ID for profile-scoped OAuth credentials
private readonly profileId: string | undefined
/**
* Some Codex/Responses streams emit tool-call argument deltas without stable call id/name.
* Track the last observed tool identity from output_item events so we can still
* emit `tool_call_partial` chunks (tool-call-only streams).
*/
private pendingToolCallId: string | undefined
private pendingToolCallName: string | undefined
// Event types handled by the shared event processor
private readonly coreHandledEventTypes = new Set<string>([
"response.text.delta",
"response.output_text.delta",
"response.reasoning.delta",
"response.reasoning_text.delta",
"response.reasoning_summary.delta",
"response.reasoning_summary_text.delta",
"response.refusal.delta",
"response.output_item.added",
"response.output_item.done",
"response.done",
"response.completed",
"response.tool_call_arguments.delta",
"response.function_call_arguments.delta",
"response.tool_call_arguments.done",
"response.function_call_arguments.done",
])
constructor(options: ApiHandlerOptions) {
super()
this.options = options
// Generate a new session ID for standalone handler usage (fallback)
this.sessionId = uuidv7()
// Store profile ID for profile-scoped OAuth credentials
this.profileId = options.apiConfigurationId
}
private normalizeUsage(usage: any, model: OpenAiCodexModel): ApiStreamUsageChunk | undefined {
if (!usage) return undefined
const inputDetails = usage.input_tokens_details ?? usage.prompt_tokens_details
const hasCachedTokens = typeof inputDetails?.cached_tokens === "number"
const hasCacheMissTokens = typeof inputDetails?.cache_miss_tokens === "number"
const cachedFromDetails = hasCachedTokens ? inputDetails.cached_tokens : 0
const missFromDetails = hasCacheMissTokens ? inputDetails.cache_miss_tokens : 0
let totalInputTokens = usage.input_tokens ?? usage.prompt_tokens ?? 0
if (totalInputTokens === 0 && inputDetails && (cachedFromDetails > 0 || missFromDetails > 0)) {
totalInputTokens = cachedFromDetails + missFromDetails
}
const totalOutputTokens = usage.output_tokens ?? usage.completion_tokens ?? 0
const cacheWriteTokens = usage.cache_creation_input_tokens ?? usage.cache_write_tokens ?? 0
const cacheReadTokens =
usage.cache_read_input_tokens ?? usage.cache_read_tokens ?? usage.cached_tokens ?? cachedFromDetails ?? 0
const reasoningTokens =
typeof usage.output_tokens_details?.reasoning_tokens === "number"
? usage.output_tokens_details.reasoning_tokens
: undefined
// Subscription-based: no per-token costs
const out: ApiStreamUsageChunk = {
type: "usage",
inputTokens: totalInputTokens,
outputTokens: totalOutputTokens,
cacheWriteTokens,
cacheReadTokens,
...(typeof reasoningTokens === "number" ? { reasoningTokens } : {}),
totalCost: 0, // Subscription-based pricing
}
return out
}
override async *createMessage(
systemPrompt: string,
messages: Anthropic.Messages.MessageParam[],
metadata?: ApiHandlerCreateMessageMetadata,
): ApiStream {
const model = this.getModel()
yield* this.handleResponsesApiMessage(model, systemPrompt, messages, metadata)
}
private async *handleResponsesApiMessage(
model: OpenAiCodexModel,
systemPrompt: string,
messages: Anthropic.Messages.MessageParam[],
metadata?: ApiHandlerCreateMessageMetadata,
): ApiStream {
// Reset state for this request
this.lastResponseOutput = undefined
this.lastResponseId = undefined
this.pendingToolCallId = undefined
this.pendingToolCallName = undefined
// Get access token from OAuth manager (profile-scoped)
let accessToken = await openAiCodexOAuthManager.getAccessTokenForProfile(this.profileId)
if (!accessToken) {
throw new Error(
t("common:errors.openAiCodex.notAuthenticated", {
defaultValue:
"Not authenticated with OpenAI Codex. Please sign in using the OpenAI Codex OAuth flow.",
}),
)
}
// Resolve reasoning effort
const reasoningEffort = this.getReasoningEffort(model)
// Format conversation
const formattedInput = this.formatFullConversation(systemPrompt, messages)
// Build request body
// Per the implementation guide: Codex backend may reject some parameters
// Notably: max_output_tokens and prompt_cache_retention may be rejected
const requestBody = this.buildRequestBody(model, formattedInput, systemPrompt, reasoningEffort, metadata)
// Make the request with retry on auth failure
for (let attempt = 0; attempt < 2; attempt++) {
try {
yield* this.executeRequest(requestBody, model, accessToken, metadata?.taskId)
return
} catch (error) {
const message = error instanceof Error ? error.message : String(error)
const isAuthFailure = /unauthorized|invalid token|not authenticated|authentication|401/i.test(message)
if (attempt === 0 && isAuthFailure) {
// Force refresh the token for retry (profile-scoped)
const refreshed = await openAiCodexOAuthManager.forceRefreshAccessTokenForProfile(this.profileId)
if (!refreshed) {
throw new Error(
t("common:errors.openAiCodex.notAuthenticated", {
defaultValue:
"Not authenticated with OpenAI Codex. Please sign in using the OpenAI Codex OAuth flow.",
}),
)
}
accessToken = refreshed
continue
}
throw error
}
}
}
private buildRequestBody(
model: OpenAiCodexModel,
formattedInput: any,
systemPrompt: string,
reasoningEffort: ReasoningEffortExtended | undefined,
metadata?: ApiHandlerCreateMessageMetadata,
): any {
const ensureAllRequired = (schema: any): any => {
if (!schema || typeof schema !== "object" || schema.type !== "object") {
return schema
}
const result = { ...schema }
if (result.additionalProperties !== false) {
result.additionalProperties = false
}
if (result.properties) {
const allKeys = Object.keys(result.properties)
result.required = allKeys
const newProps = { ...result.properties }
for (const key of allKeys) {
const prop = newProps[key]
if (prop.type === "object") {
newProps[key] = ensureAllRequired(prop)
} else if (prop.type === "array" && prop.items?.type === "object") {
newProps[key] = {
...prop,
items: ensureAllRequired(prop.items),
}
}
}
result.properties = newProps
}
return result
}
const ensureAdditionalPropertiesFalse = (schema: any): any => {
if (!schema || typeof schema !== "object" || schema.type !== "object") {
return schema
}
const result = { ...schema }
if (result.additionalProperties !== false) {
result.additionalProperties = false
}
if (result.properties) {
const newProps = { ...result.properties }
for (const key of Object.keys(result.properties)) {
const prop = newProps[key]
if (prop && prop.type === "object") {
newProps[key] = ensureAdditionalPropertiesFalse(prop)
} else if (prop && prop.type === "array" && prop.items?.type === "object") {
newProps[key] = {
...prop,
items: ensureAdditionalPropertiesFalse(prop.items),
}
}
}
result.properties = newProps
}
return result
}
interface ResponsesRequestBody {
model: string
input: Array<{ role: "user" | "assistant"; content: any[] } | { type: string; content: string }>
stream: boolean
reasoning?: { effort?: ReasoningEffortExtended; summary?: "auto" }
temperature?: number
store?: boolean
instructions?: string
include?: string[]
tools?: Array<{
type: "function"
name: string
description?: string
parameters?: any
strict?: boolean
}>
tool_choice?: any
parallel_tool_calls?: boolean
}
// Per the implementation guide: Codex backend may reject max_output_tokens
// and prompt_cache_retention, so we omit them
const body: ResponsesRequestBody = {
model: model.id,
input: formattedInput,
stream: true,
store: false,
instructions: systemPrompt,
// Only include encrypted reasoning content when reasoning effort is set
...(reasoningEffort ? { include: ["reasoning.encrypted_content"] } : {}),
...(reasoningEffort
? {
reasoning: {
...(reasoningEffort ? { effort: reasoningEffort } : {}),
summary: "auto" as const,
},
}
: {}),
tools: (metadata?.tools ?? [])
.filter((tool) => tool.type === "function")
.map((tool) => {
const isMcp = isMcpTool(tool.function.name)
return {
type: "function",
name: tool.function.name,
description: tool.function.description,
parameters: isMcp
? ensureAdditionalPropertiesFalse(tool.function.parameters)
: ensureAllRequired(tool.function.parameters),
strict: !isMcp,
}
}),
tool_choice: metadata?.tool_choice,
parallel_tool_calls: metadata?.parallelToolCalls ?? true,
}
return body
}
private async *executeRequest(
requestBody: any,
model: OpenAiCodexModel,
accessToken: string,
taskId?: string,
): ApiStream {
// Create AbortController for cancellation
this.abortController = new AbortController()
try {
// Prefer OpenAI SDK streaming (same approach as openai-native) so event handling
// is consistent across providers.
try {
// Get ChatGPT account ID for organization subscriptions (profile-scoped)
const accountId = await openAiCodexOAuthManager.getAccountIdForProfile(this.profileId)
// Build Codex-specific headers. Authorization is provided by the SDK apiKey.
const codexHeaders: Record<string, string> = {
originator: "roo-code",
session_id: taskId || this.sessionId,
"User-Agent": `roo-code/${Package.version} (${os.platform()} ${os.release()}; ${os.arch()}) node/${process.version.slice(1)}`,
...(accountId ? { "ChatGPT-Account-Id": accountId } : {}),
}
// Allow tests to inject a client. If none is injected, create one for this request.
const client =
this.client ??
new OpenAI({
apiKey: accessToken,
baseURL: CODEX_API_BASE_URL,
defaultHeaders: codexHeaders,
})
const stream = (await (client as any).responses.create(requestBody, {
signal: this.abortController.signal,
// If the SDK supports per-request overrides, ensure headers are present.
headers: codexHeaders,
})) as AsyncIterable<any>
if (typeof (stream as any)?.[Symbol.asyncIterator] !== "function") {
throw new Error(
"OpenAI SDK did not return an AsyncIterable for Responses API streaming. Falling back to SSE.",
)
}
for await (const event of stream) {
if (this.abortController.signal.aborted) {
break
}
for await (const outChunk of this.processEvent(event, model)) {
yield outChunk
}
}
} catch (_sdkErr) {
// Fallback to manual SSE via fetch (Codex backend).
yield* this.makeCodexRequest(requestBody, model, accessToken, taskId)
}
} finally {
this.abortController = undefined
}
}
private formatFullConversation(systemPrompt: string, messages: Anthropic.Messages.MessageParam[]): any {
const formattedInput: any[] = []
for (const message of messages) {
// Check if this is a reasoning item
if ((message as any).type === "reasoning") {
formattedInput.push(message)
continue
}
if (message.role === "user") {
const content: any[] = []
const toolResults: any[] = []
if (typeof message.content === "string") {
content.push({ type: "input_text", text: message.content })
} else if (Array.isArray(message.content)) {
for (const block of message.content) {
if (block.type === "text") {
content.push({ type: "input_text", text: block.text })
} else if (block.type === "image") {
const image = block as Anthropic.Messages.ImageBlockParam
const imageUrl = `data:${image.source.media_type};base64,${image.source.data}`
content.push({ type: "input_image", image_url: imageUrl })
} else if (block.type === "tool_result") {
const result =
typeof block.content === "string"
? block.content
: block.content?.map((c) => (c.type === "text" ? c.text : "")).join("") || ""
toolResults.push({
type: "function_call_output",
// Sanitize and truncate call_id to fit OpenAI's 64-char limit
call_id: sanitizeOpenAiCallId(block.tool_use_id),
output: result,
})
}
}
}
if (content.length > 0) {
formattedInput.push({ role: "user", content })
}
if (toolResults.length > 0) {
formattedInput.push(...toolResults)
}
} else if (message.role === "assistant") {
const content: any[] = []
const toolCalls: any[] = []
if (typeof message.content === "string") {
content.push({ type: "output_text", text: message.content })
} else if (Array.isArray(message.content)) {
for (const block of message.content) {
if (block.type === "text") {
content.push({ type: "output_text", text: block.text })
} else if (block.type === "tool_use") {
toolCalls.push({
type: "function_call",
// Sanitize and truncate call_id to fit OpenAI's 64-char limit
call_id: sanitizeOpenAiCallId(block.id),
name: block.name,
arguments: JSON.stringify(block.input),
})
}
}
}
if (content.length > 0) {
formattedInput.push({ role: "assistant", content })
}
if (toolCalls.length > 0) {
formattedInput.push(...toolCalls)
}
}
}
return formattedInput
}
private async *makeCodexRequest(
requestBody: any,
model: OpenAiCodexModel,
accessToken: string,
taskId?: string,
): ApiStream {
// Per the implementation guide: route to Codex backend with Bearer token
const url = `${CODEX_API_BASE_URL}/responses`
// Get ChatGPT account ID for organization subscriptions (profile-scoped)
const accountId = await openAiCodexOAuthManager.getAccountIdForProfile(this.profileId)
// Build headers with required Codex-specific fields
const headers: Record<string, string> = {
"Content-Type": "application/json",
Authorization: `Bearer ${accessToken}`,
originator: "roo-code",
session_id: taskId || this.sessionId,
"User-Agent": `roo-code/${Package.version} (${os.platform()} ${os.release()}; ${os.arch()}) node/${process.version.slice(1)}`,
}
// Add ChatGPT-Account-Id if available (required for organization subscriptions)
if (accountId) {
headers["ChatGPT-Account-Id"] = accountId
}
try {
const response = await fetch(url, {
method: "POST",
headers,
body: JSON.stringify(requestBody),
signal: this.abortController?.signal,
})
if (!response.ok) {
const errorText = await response.text()
let errorMessage = t("common:errors.api.apiRequestFailed", { status: response.status })
let errorDetails = ""
try {
const errorJson = JSON.parse(errorText)
if (errorJson.error?.message) {
errorDetails = errorJson.error.message
} else if (errorJson.message) {
errorDetails = errorJson.message
} else if (errorJson.detail) {
errorDetails = errorJson.detail
} else {
errorDetails = errorText
}
} catch {
errorDetails = errorText
}
switch (response.status) {
case 400:
errorMessage = t("common:errors.openAiCodex.invalidRequest")
break
case 401:
errorMessage = t("common:errors.openAiCodex.authenticationFailed")
break
case 403:
errorMessage = t("common:errors.openAiCodex.accessDenied")
break
case 404:
errorMessage = t("common:errors.openAiCodex.endpointNotFound")
break
case 429:
errorMessage = t("common:errors.openAiCodex.rateLimitExceeded")
break
case 500:
case 502:
case 503:
errorMessage = t("common:errors.openAiCodex.serviceError")
break
default:
errorMessage = t("common:errors.openAiCodex.genericError", { status: response.status })
}
if (errorDetails) {
errorMessage += ` - ${errorDetails}`
}
throw new Error(errorMessage)
}
if (!response.body) {
throw new Error(t("common:errors.openAiCodex.noResponseBody"))
}
yield* this.handleStreamResponse(response.body, model)
} catch (error) {
const errorMessage = error instanceof Error ? error.message : String(error)
const apiError = new ApiProviderError(errorMessage, this.providerName, model.id, "createMessage")
TelemetryService.instance.captureException(apiError)
if (error instanceof Error) {
if (error.message.includes("Codex API")) {
throw error
}
throw new Error(t("common:errors.openAiCodex.connectionFailed", { message: error.message }))
}
throw new Error(t("common:errors.openAiCodex.unexpectedConnectionError"))
}
}
private async *handleStreamResponse(body: ReadableStream<Uint8Array>, model: OpenAiCodexModel): ApiStream {
const reader = body.getReader()
const decoder = new TextDecoder()
let buffer = ""
let hasContent = false
try {
while (true) {
if (this.abortController?.signal.aborted) {
break
}
const { done, value } = await reader.read()
if (done) break
buffer += decoder.decode(value, { stream: true })
const lines = buffer.split("\n")
buffer = lines.pop() || ""
for (const line of lines) {
if (line.startsWith("data: ")) {
const data = line.slice(6).trim()
if (data === "[DONE]") {
continue
}
try {
const parsed = JSON.parse(data)
// Capture response metadata
if (parsed.response?.output && Array.isArray(parsed.response.output)) {
this.lastResponseOutput = parsed.response.output
}
if (parsed.response?.id) {
this.lastResponseId = parsed.response.id as string
}
// Delegate standard event types
if (parsed?.type && this.coreHandledEventTypes.has(parsed.type)) {
// Capture tool call identity from output_item events so we can
// emit tool_call_partial for subsequent function_call_arguments.delta events
if (
parsed.type === "response.output_item.added" ||
parsed.type === "response.output_item.done"
) {
const item = parsed.item
if (item && (item.type === "function_call" || item.type === "tool_call")) {
const callId = item.call_id || item.tool_call_id || item.id
const name = item.name || item.function?.name || item.function_name
if (typeof callId === "string" && callId.length > 0) {
this.pendingToolCallId = callId
this.pendingToolCallName = typeof name === "string" ? name : undefined
}
}
}
// Some Codex streams only return tool calls (no text). Treat tool output as content.
if (
parsed.type === "response.function_call_arguments.delta" ||
parsed.type === "response.tool_call_arguments.delta" ||
parsed.type === "response.output_item.added" ||
parsed.type === "response.output_item.done"
) {
hasContent = true
}
for await (const outChunk of this.processEvent(parsed, model)) {
if (outChunk.type === "text" || outChunk.type === "reasoning") {
hasContent = true
}
yield outChunk
}
continue
}
// Handle complete response
if (parsed.response && parsed.response.output && Array.isArray(parsed.response.output)) {
for (const outputItem of parsed.response.output) {
if (outputItem.type === "text" && outputItem.content) {
for (const content of outputItem.content) {
if (content.type === "text" && content.text) {
hasContent = true
yield { type: "text", text: content.text }
}
}
}
if (outputItem.type === "reasoning" && Array.isArray(outputItem.summary)) {
for (const summary of outputItem.summary) {
if (summary?.type === "summary_text" && typeof summary.text === "string") {
hasContent = true
yield { type: "reasoning", text: summary.text }
}
}
}
}
if (parsed.response.usage) {
const usageData = this.normalizeUsage(parsed.response.usage, model)
if (usageData) {
yield usageData
}
}
} else if (
parsed.type === "response.text.delta" ||
parsed.type === "response.output_text.delta"
) {
if (parsed.delta) {
hasContent = true
yield { type: "text", text: parsed.delta }
}
} else if (
parsed.type === "response.reasoning.delta" ||
parsed.type === "response.reasoning_text.delta"
) {
if (parsed.delta) {
hasContent = true
yield { type: "reasoning", text: parsed.delta }
}
} else if (
parsed.type === "response.reasoning_summary.delta" ||
parsed.type === "response.reasoning_summary_text.delta"
) {
if (parsed.delta) {
hasContent = true
yield { type: "reasoning", text: parsed.delta }
}
} else if (parsed.type === "response.refusal.delta") {
if (parsed.delta) {
hasContent = true
yield { type: "text", text: `[Refusal] ${parsed.delta}` }
}
} else if (parsed.type === "response.output_item.added") {
if (parsed.item) {
if (parsed.item.type === "text" && parsed.item.text) {
hasContent = true
yield { type: "text", text: parsed.item.text }
} else if (parsed.item.type === "reasoning" && parsed.item.text) {
hasContent = true
yield { type: "reasoning", text: parsed.item.text }
} else if (parsed.item.type === "message" && parsed.item.content) {
for (const content of parsed.item.content) {
if (content.type === "text" && content.text) {
hasContent = true
yield { type: "text", text: content.text }
}
}
}
}
} else if (parsed.type === "response.error" || parsed.type === "error") {
if (parsed.error || parsed.message) {
throw new Error(
t("common:errors.openAiCodex.apiError", {
message: parsed.error?.message || parsed.message || "Unknown error",
}),
)
}
} else if (parsed.type === "response.failed") {
if (parsed.error || parsed.message) {
throw new Error(
t("common:errors.openAiCodex.responseFailed", {
message: parsed.error?.message || parsed.message || "Unknown failure",
}),
)
}
} else if (parsed.type === "response.completed" || parsed.type === "response.done") {
if (parsed.response?.output && Array.isArray(parsed.response.output)) {
this.lastResponseOutput = parsed.response.output
}
if (parsed.response?.id) {
this.lastResponseId = parsed.response.id as string
}
if (
!hasContent &&
parsed.response &&
parsed.response.output &&
Array.isArray(parsed.response.output)
) {
for (const outputItem of parsed.response.output) {
if (outputItem.type === "message" && outputItem.content) {
for (const content of outputItem.content) {
if (content.type === "output_text" && content.text) {
hasContent = true
yield { type: "text", text: content.text }
}
}
}
if (outputItem.type === "reasoning" && Array.isArray(outputItem.summary)) {
for (const summary of outputItem.summary) {
if (
summary?.type === "summary_text" &&
typeof summary.text === "string"
) {
hasContent = true
yield { type: "reasoning", text: summary.text }
}
}
}
}
}
} else if (parsed.choices?.[0]?.delta?.content) {
hasContent = true
yield { type: "text", text: parsed.choices[0].delta.content }
} else if (
parsed.item &&
typeof parsed.item.text === "string" &&
parsed.item.text.length > 0
) {
hasContent = true
yield { type: "text", text: parsed.item.text }
} else if (parsed.usage) {
const usageData = this.normalizeUsage(parsed.usage, model)
if (usageData) {
yield usageData
}
}
} catch (e) {
if (!(e instanceof SyntaxError)) {
throw e
}
}
} else if (line.trim() && !line.startsWith(":")) {
try {
const parsed = JSON.parse(line)
if (parsed.content || parsed.text || parsed.message) {
hasContent = true
yield { type: "text", text: parsed.content || parsed.text || parsed.message }
}
} catch {
// Not JSON, ignore
}
}
}
}
} catch (error) {
const errorMessage = error instanceof Error ? error.message : String(error)
const apiError = new ApiProviderError(errorMessage, this.providerName, model.id, "createMessage")
TelemetryService.instance.captureException(apiError)
if (error instanceof Error) {
throw new Error(t("common:errors.openAiCodex.streamProcessingError", { message: error.message }))
}
throw new Error(t("common:errors.openAiCodex.unexpectedStreamError"))
} finally {
reader.releaseLock()
}
}
private async *processEvent(event: any, model: OpenAiCodexModel): ApiStream {
if (event?.response?.output && Array.isArray(event.response.output)) {
this.lastResponseOutput = event.response.output
}
if (event?.response?.id) {
this.lastResponseId = event.response.id as string
}
// Handle text deltas
if (event?.type === "response.text.delta" || event?.type === "response.output_text.delta") {
if (event?.delta) {
yield { type: "text", text: event.delta }
}
return
}
// Handle reasoning deltas
if (
event?.type === "response.reasoning.delta" ||
event?.type === "response.reasoning_text.delta" ||
event?.type === "response.reasoning_summary.delta" ||
event?.type === "response.reasoning_summary_text.delta"
) {
if (event?.delta) {
yield { type: "reasoning", text: event.delta }
}
return
}
// Handle refusal deltas
if (event?.type === "response.refusal.delta") {
if (event?.delta) {
yield { type: "text", text: `[Refusal] ${event.delta}` }
}
return
}
// Handle tool/function call deltas
if (
event?.type === "response.tool_call_arguments.delta" ||
event?.type === "response.function_call_arguments.delta"
) {
const callId = event.call_id || event.tool_call_id || event.id || this.pendingToolCallId
const name = event.name || event.function_name || this.pendingToolCallName
const args = event.delta || event.arguments
// Codex/Responses may stream tool-call arguments, but these delta events are not guaranteed
// to include a stable id/name. Avoid emitting incomplete tool_call_partial chunks because
// NativeToolCallParser requires a name to start a call.
if (typeof callId === "string" && callId.length > 0 && typeof name === "string" && name.length > 0) {
yield {
type: "tool_call_partial",
index: event.index ?? 0,
id: callId,
name,
arguments: typeof args === "string" ? args : "",
}
}
return
}
// Handle tool/function call completion
if (
event?.type === "response.tool_call_arguments.done" ||
event?.type === "response.function_call_arguments.done"
) {
return
}
// Handle output item events
if (event?.type === "response.output_item.added" || event?.type === "response.output_item.done") {
const item = event?.item
if (item) {
// Capture tool identity so subsequent argument deltas can be attributed.
if (item.type === "function_call" || item.type === "tool_call") {
const callId = item.call_id || item.tool_call_id || item.id
const name = item.name || item.function?.name || item.function_name
if (typeof callId === "string" && callId.length > 0) {
this.pendingToolCallId = callId
this.pendingToolCallName = typeof name === "string" ? name : undefined
}
}
// For "added" events, yield text/reasoning content (streaming path)
// For "done" events, do NOT yield text/reasoning - it's already been streamed via deltas
// and would cause double-emission (A, B, C, ABC).
if (event.type === "response.output_item.added") {
if (item.type === "text" && item.text) {
yield { type: "text", text: item.text }
} else if (item.type === "reasoning" && item.text) {
yield { type: "reasoning", text: item.text }
} else if (item.type === "message" && Array.isArray(item.content)) {
for (const content of item.content) {
if ((content?.type === "text" || content?.type === "output_text") && content?.text) {
yield { type: "text", text: content.text }
}
}
}
}
// Note: We intentionally do NOT emit tool_call from response.output_item.done
// for function_call/tool_call items. The streaming path handles tool calls via:
// 1. tool_call_partial events during argument deltas
// 2. NativeToolCallParser.finalizeRawChunks() at stream end emitting tool_call_end
// 3. NativeToolCallParser.finalizeStreamingToolCall() creating the final ToolUse
// Emitting tool_call here would cause duplicate tool rendering.
}
return
}
// Handle completion events
if (event?.type === "response.done" || event?.type === "response.completed") {
const usage = event?.response?.usage || event?.usage || undefined
const usageData = this.normalizeUsage(usage, model)
if (usageData) {
yield usageData
}
return
}
// Fallbacks
if (event?.choices?.[0]?.delta?.content) {
yield { type: "text", text: event.choices[0].delta.content }
return
}
if (event?.usage) {
const usageData = this.normalizeUsage(event.usage, model)
if (usageData) {
yield usageData
}
}
}
private getReasoningEffort(model: OpenAiCodexModel): ReasoningEffortExtended | undefined {
const selected = (this.options.reasoningEffort as any) ?? (model.info.reasoningEffort as any)
return selected && selected !== "disable" && selected !== "none" ? (selected as any) : undefined
}
override getModel() {
const modelId = this.options.apiModelId
let id = modelId && modelId in openAiCodexModels ? (modelId as OpenAiCodexModelId) : openAiCodexDefaultModelId
const info: ModelInfo = openAiCodexModels[id]
const params = getModelParams({
format: "openai",
modelId: id,
model: info,
settings: this.options,
defaultTemperature: 0,
})
return { id, info, ...params }
}
getEncryptedContent(): { encrypted_content: string; id?: string } | undefined {
if (!this.lastResponseOutput) return undefined
const reasoningItem = this.lastResponseOutput.find(
(item) => item.type === "reasoning" && item.encrypted_content,
)
if (!reasoningItem?.encrypted_content) return undefined
return {
encrypted_content: reasoningItem.encrypted_content,
...(reasoningItem.id ? { id: reasoningItem.id } : {}),