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feat: enable native tool calling for openai-native provider (#9348)

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Co-authored-by: daniel-lxs <ricciodaniel98@gmail.com>
This commit is contained in:
Hannes Rudolph 2025-11-18 09:01:04 -07:00 • committed by GitHub
parent f5d3ac0e23
commit f8d6e12aa7
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2 changed files with 241 additions and 37 deletions
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29
packages/types/src/providers/openai.ts
View file

@ -9,6 +9,7 @@ export const openAiNativeModels = {
"gpt-5.1": {
maxTokens: 128000,
contextWindow: 400000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
promptCacheRetention: "24h",
@ -28,6 +29,7 @@ export const openAiNativeModels = {
"gpt-5.1-codex": {
maxTokens: 128000,
contextWindow: 400000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
promptCacheRetention: "24h",
@ -43,6 +45,7 @@ export const openAiNativeModels = {
"gpt-5.1-codex-mini": {
maxTokens: 128000,
contextWindow: 400000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
promptCacheRetention: "24h",
@ -57,6 +60,7 @@ export const openAiNativeModels = {
"gpt-5": {
maxTokens: 128000,
contextWindow: 400000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
supportsReasoningEffort: ["minimal", "low", "medium", "high"],
@ -75,6 +79,7 @@ export const openAiNativeModels = {
"gpt-5-mini": {
maxTokens: 128000,
contextWindow: 400000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
supportsReasoningEffort: ["minimal", "low", "medium", "high"],
@ -93,6 +98,7 @@ export const openAiNativeModels = {
"gpt-5-codex": {
maxTokens: 128000,
contextWindow: 400000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
supportsReasoningEffort: ["low", "medium", "high"],
@ -107,6 +113,7 @@ export const openAiNativeModels = {
"gpt-5-nano": {
maxTokens: 128000,
contextWindow: 400000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
supportsReasoningEffort: ["minimal", "low", "medium", "high"],
@ -122,6 +129,7 @@ export const openAiNativeModels = {
"gpt-5-chat-latest": {
maxTokens: 128000,
contextWindow: 400000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
inputPrice: 1.25,
@ -132,6 +140,7 @@ export const openAiNativeModels = {
"gpt-4.1": {
maxTokens: 32_768,
contextWindow: 1_047_576,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
inputPrice: 2,
@ -145,6 +154,7 @@ export const openAiNativeModels = {
"gpt-4.1-mini": {
maxTokens: 32_768,
contextWindow: 1_047_576,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
inputPrice: 0.4,
@ -158,6 +168,7 @@ export const openAiNativeModels = {
"gpt-4.1-nano": {
maxTokens: 32_768,
contextWindow: 1_047_576,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
inputPrice: 0.1,
@ -171,6 +182,7 @@ export const openAiNativeModels = {
o3: {
maxTokens: 100_000,
contextWindow: 200_000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
inputPrice: 2.0,
@ -187,6 +199,7 @@ export const openAiNativeModels = {
"o3-high": {
maxTokens: 100_000,
contextWindow: 200_000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
inputPrice: 2.0,
@ -198,6 +211,7 @@ export const openAiNativeModels = {
"o3-low": {
maxTokens: 100_000,
contextWindow: 200_000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
inputPrice: 2.0,
@ -209,6 +223,7 @@ export const openAiNativeModels = {
"o4-mini": {
maxTokens: 100_000,
contextWindow: 200_000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
inputPrice: 1.1,
@ -225,6 +240,7 @@ export const openAiNativeModels = {
"o4-mini-high": {
maxTokens: 100_000,
contextWindow: 200_000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
inputPrice: 1.1,
@ -236,6 +252,7 @@ export const openAiNativeModels = {
"o4-mini-low": {
maxTokens: 100_000,
contextWindow: 200_000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
inputPrice: 1.1,
@ -247,6 +264,7 @@ export const openAiNativeModels = {
"o3-mini": {
maxTokens: 100_000,
contextWindow: 200_000,
supportsNativeTools: true,
supportsImages: false,
supportsPromptCache: true,
inputPrice: 1.1,
@ -259,6 +277,7 @@ export const openAiNativeModels = {
"o3-mini-high": {
maxTokens: 100_000,
contextWindow: 200_000,
supportsNativeTools: true,
supportsImages: false,
supportsPromptCache: true,
inputPrice: 1.1,
@ -270,6 +289,7 @@ export const openAiNativeModels = {
"o3-mini-low": {
maxTokens: 100_000,
contextWindow: 200_000,
supportsNativeTools: true,
supportsImages: false,
supportsPromptCache: true,
inputPrice: 1.1,
@ -281,6 +301,7 @@ export const openAiNativeModels = {
o1: {
maxTokens: 100_000,
contextWindow: 200_000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
inputPrice: 15,
@ -291,6 +312,7 @@ export const openAiNativeModels = {
"o1-preview": {
maxTokens: 32_768,
contextWindow: 128_000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
inputPrice: 15,
@ -301,6 +323,7 @@ export const openAiNativeModels = {
"o1-mini": {
maxTokens: 65_536,
contextWindow: 128_000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
inputPrice: 1.1,
@ -311,6 +334,7 @@ export const openAiNativeModels = {
"gpt-4o": {
maxTokens: 16_384,
contextWindow: 128_000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
inputPrice: 2.5,
@ -324,6 +348,7 @@ export const openAiNativeModels = {
"gpt-4o-mini": {
maxTokens: 16_384,
contextWindow: 128_000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
inputPrice: 0.15,
@ -337,6 +362,7 @@ export const openAiNativeModels = {
"codex-mini-latest": {
maxTokens: 16_384,
contextWindow: 200_000,
supportsNativeTools: true,
supportsImages: false,
supportsPromptCache: false,
inputPrice: 1.5,
@ -350,6 +376,7 @@ export const openAiNativeModels = {
"gpt-5-2025-08-07": {
maxTokens: 128000,
contextWindow: 400000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
supportsReasoningEffort: ["minimal", "low", "medium", "high"],
@ -368,6 +395,7 @@ export const openAiNativeModels = {
"gpt-5-mini-2025-08-07": {
maxTokens: 128000,
contextWindow: 400000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
supportsReasoningEffort: ["minimal", "low", "medium", "high"],
@ -386,6 +414,7 @@ export const openAiNativeModels = {
"gpt-5-nano-2025-08-07": {
maxTokens: 128000,
contextWindow: 400000,
supportsNativeTools: true,
supportsImages: true,
supportsPromptCache: true,
supportsReasoningEffort: ["minimal", "low", "medium", "high"],

249
src/api/providers/openai-native.ts
View file

@ -34,6 +34,8 @@ export class OpenAiNativeHandler extends BaseProvider implements SingleCompletio
private lastResponseOutput: any[] | undefined
// Last top-level response id from Responses API (for troubleshooting)
private lastResponseId: string | undefined
// Accumulate partial tool calls: call_id -> { name, arguments }
private currentToolCalls: Map<string, { name: string; arguments: string }> = new Map()
// Abort controller for cancelling ongoing requests
private abortController?: AbortController
@ -49,6 +51,10 @@ export class OpenAiNativeHandler extends BaseProvider implements SingleCompletio
"response.output_item.added",
"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) {
@ -147,6 +153,8 @@ export class OpenAiNativeHandler extends BaseProvider implements SingleCompletio
this.lastResponseOutput = undefined
// Reset last response id for this request
this.lastResponseId = undefined
// Reset tool call accumulator
this.currentToolCalls.clear()
// Use Responses API for ALL models
const { verbosity, reasoning } = this.getModel()
@ -179,6 +187,38 @@ export class OpenAiNativeHandler extends BaseProvider implements SingleCompletio
reasoningEffort: ReasoningEffortExtended | undefined,
metadata?: ApiHandlerCreateMessageMetadata,
): any {
// Ensure all properties are in the required array for OpenAI's strict mode
// This recursively processes nested objects and array items
const ensureAllRequired = (schema: any): any => {
if (!schema || typeof schema !== "object" || schema.type !== "object") {
return schema
}
const result = { ...schema }
if (result.properties) {
const allKeys = Object.keys(result.properties)
result.required = allKeys
// Recursively process nested objects
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
}
// Build a request body for the OpenAI Responses API.
// Ensure we explicitly pass max_output_tokens based on Roo's reserved model response calculation
// so requests do not default to very large limits (e.g., 120k).
@ -196,6 +236,14 @@ export class OpenAiNativeHandler extends BaseProvider implements SingleCompletio
include?: string[]
/** Prompt cache retention policy: "in_memory" (default) or "24h" for extended caching */
prompt_cache_retention?: "in_memory" | "24h"
tools?: Array<{
type: "function"
name: string
description?: string
parameters?: any
strict?: boolean
}>
tool_choice?: any
}
// Validate requested tier against model support; if not supported, omit.
@ -240,6 +288,18 @@ export class OpenAiNativeHandler extends BaseProvider implements SingleCompletio
// Enable extended prompt cache retention for models that support it.
// This uses the OpenAI Responses API `prompt_cache_retention` parameter.
...(promptCacheRetention ? { prompt_cache_retention: promptCacheRetention } : {}),
...(metadata?.tools && {
tools: metadata.tools
.filter((tool) => tool.type === "function")
.map((tool) => ({
type: "function",
name: tool.function.name,
description: tool.function.description,
parameters: ensureAllRequired(tool.function.parameters),
strict: true,
})),
}),
...(metadata?.tool_choice && { tool_choice: metadata.tool_choice }),
}
// Include text.verbosity only when the model explicitly supports it
@ -292,9 +352,8 @@ export class OpenAiNativeHandler extends BaseProvider implements SingleCompletio
private formatFullConversation(systemPrompt: string, messages: Anthropic.Messages.MessageParam[]): any {
// Format the entire conversation history for the Responses API using structured format
// This supports both text and images
// Messages already include reasoning items from API history, so we just need to format them
const formattedMessages: any[] = []
// The Responses API (like Realtime API) accepts a list of items, which can be messages, function calls, or function call outputs.
const formattedInput: any[] = []
// Do NOT embed the system prompt as a developer message in the Responses API input.
// The Responses API treats roles as free-form; use the top-level `instructions` field instead.
@ -304,45 +363,83 @@ export class OpenAiNativeHandler extends BaseProvider implements SingleCompletio
// Check if this is a reasoning item (already formatted in API history)
if ((message as any).type === "reasoning") {
// Pass through reasoning items as-is
formattedMessages.push(message)
formattedInput.push(message)
continue
}
const role = message.role === "user" ? "user" : "assistant"
const content: any[] = []
if (message.role === "user") {
const content: any[] = []
const toolResults: any[] = []
if (typeof message.content === "string") {
// For user messages, use input_text; for assistant messages, use output_text
if (role === "user") {
if (typeof message.content === "string") {
content.push({ type: "input_text", text: message.content })
} else {
content.push({ type: "output_text", text: message.content })
}
} else if (Array.isArray(message.content)) {
// For array content with potential images, format properly
for (const block of message.content) {
if (block.type === "text") {
// For user messages, use input_text; for assistant messages, use output_text
if (role === "user") {
content.push({ type: "input_text", text: (block as any).text })
} else {
content.push({ type: "output_text", text: (block as any).text })
} 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") {
// Map Anthropic tool_result to Responses API function_call_output item
const result =
typeof block.content === "string"
? block.content
: block.content?.map((c) => (c.type === "text" ? c.text : "")).join("") || ""
toolResults.push({
type: "function_call_output",
call_id: block.tool_use_id,
output: result,
})
}
} else if (block.type === "image") {
const image = block as Anthropic.Messages.ImageBlockParam
// Format image with proper data URL - images are always input_image
const imageUrl = `data:${image.source.media_type};base64,${image.source.data}`
content.push({ type: "input_image", image_url: imageUrl })
}
}
}
if (content.length > 0) {
formattedMessages.push({ role, content })
// Add user message first
if (content.length > 0) {
formattedInput.push({ role: "user", content })
}
// Add tool results as separate items
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") {
// Map Anthropic tool_use to Responses API function_call item
toolCalls.push({
type: "function_call",
call_id: block.id,
name: block.name,
arguments: JSON.stringify(block.input),
})
}
}
}
// Add assistant message if it has content
if (content.length > 0) {
formattedInput.push({ role: "assistant", content })
}
// Add tool calls as separate items
if (toolCalls.length > 0) {
formattedInput.push(...toolCalls)
}
}
}
return formattedMessages
return formattedInput
}
private async *makeResponsesApiRequest(
@ -676,11 +773,16 @@ export class OpenAiNativeHandler extends BaseProvider implements SingleCompletio
// Output item completed
}
// Handle function/tool call events
else if (parsed.type === "response.function_call_arguments.delta") {
// Function call arguments streaming
// We could yield this as a special type if needed for tool usage
} else if (parsed.type === "response.function_call_arguments.done") {
// Function call completed
else if (
parsed.type === "response.function_call_arguments.delta" ||
parsed.type === "response.tool_call_arguments.delta" ||
parsed.type === "response.function_call_arguments.done" ||
parsed.type === "response.tool_call_arguments.done"
) {
// Delegated to processEvent (handles accumulation and completion)
for await (const outChunk of this.processEvent(parsed, model)) {
yield outChunk
}
}
// Handle MCP (Model Context Protocol) tool events
else if (parsed.type === "response.mcp_call_arguments.delta") {
@ -961,8 +1063,53 @@ export class OpenAiNativeHandler extends BaseProvider implements SingleCompletio
return
}
// Handle output item additions (SDK or Responses API alternative format)
if (event?.type === "response.output_item.added") {
// Handle tool/function call deltas and completion
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
if (callId) {
if (!this.currentToolCalls.has(callId)) {
this.currentToolCalls.set(callId, { name: "", arguments: "" })
}
const toolCall = this.currentToolCalls.get(callId)!
// Update name if present (usually in the first delta)
if (event.name || event.function_name) {
toolCall.name = event.name || event.function_name
}
// Append arguments delta
if (event.delta || event.arguments) {
toolCall.arguments += event.delta || event.arguments
}
}
return
}
if (
event?.type === "response.tool_call_arguments.done" ||
event?.type === "response.function_call_arguments.done"
) {
const callId = event.call_id || event.tool_call_id || event.id
if (callId && this.currentToolCalls.has(callId)) {
const toolCall = this.currentToolCalls.get(callId)!
// Yield the complete tool call
yield {
type: "tool_call",
id: callId,
name: toolCall.name,
arguments: toolCall.arguments,
}
// Remove from accumulator
this.currentToolCalls.delete(callId)
}
return
}
// Handle output item additions/completions (SDK or Responses API alternative format)
if (event?.type === "response.output_item.added" || event?.type === "response.output_item.done") {
const item = event?.item
if (item) {
if (item.type === "text" && item.text) {
@ -976,6 +1123,21 @@ export class OpenAiNativeHandler extends BaseProvider implements SingleCompletio
yield { type: "text", text: content.text }
}
}
} else if (
(item.type === "function_call" || item.type === "tool_call") &&
event.type === "response.output_item.done" // Only handle done events for tool calls to ensure arguments are complete
) {
// Handle complete tool/function call item
const callId = item.call_id || item.tool_call_id || item.id
if (callId && !this.currentToolCalls.has(callId)) {
const args = item.arguments || item.function?.arguments || item.function_arguments
yield {
type: "tool_call",
id: callId,
name: item.name || item.function?.name || item.function_name || "",
arguments: typeof args === "string" ? args : "{}",
}
}
}
}
return
@ -983,6 +1145,19 @@ export class OpenAiNativeHandler extends BaseProvider implements SingleCompletio
// Completion events that may carry usage
if (event?.type === "response.done" || event?.type === "response.completed") {
// Yield any pending tool calls that didn't get a 'done' event (fallback)
if (this.currentToolCalls.size > 0) {
for (const [callId, toolCall] of this.currentToolCalls) {
yield {
type: "tool_call",
id: callId,
name: toolCall.name,
arguments: toolCall.arguments || "{}",
}
}
this.currentToolCalls.clear()
}
const usage = event?.response?.usage || event?.usage || undefined
const usageData = this.normalizeUsage(usage, model)
if (usageData) {