From 70d6b28853661d3b246148a2819b7ef8a1bb8b63 Mon Sep 17 00:00:00 2001 From: bonerush <96404351+bonerush@users.noreply.github.com> Date: Wed, 8 Apr 2026 12:56:10 +0800 Subject: [PATCH] fix: Fix deferred tools handling in OpenAI compatibility layer (#193) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * fix: reorder tool and user messages for OpenAI API compatibility (#168) Fixes #168 OpenAI requires that an assistant message with tool_calls be immediately followed by tool messages. Previously, convertInternalUserMessage output user content before tool results, causing 400 errors. Now tool messages are pushed first. * fix: 修复OpenAI兼容层中deferred tools处理问题 提交描述: 修复了在使用OpenAI兼容API时TaskCreate工具调用失败的问题。 问题: - 当使用OpenAI兼容API模型时，调用TaskCreate工具出现"InputValidationError: The required parameter `subject` is missing"错误 - OpenAI兼容层没有正确处理deferred tools的过滤逻辑，导致工具schema没有被正确发送给模型 修复: 1. 在OpenAI兼容层中添加了与Anthropic API路径一致的deferred tools处理逻辑 2. 导入必要的工具搜索相关函数: isToolSearchEnabled, extractDiscoveredToolNames, isDeferredTool等 3. 实现工具过滤逻辑: - 检查工具搜索是否启用 - 构建deferred tools集合 - 过滤工具列表: 只包含非deferred工具或已发现的deferred工具 - 为deferred tools设置deferLoading标志 4. 修正了extractDiscoveredToolNames函数的导入路径错误 影响: - 解决了TaskCreate工具调用时的参数验证错误 - 确保OpenAI兼容层与Anthropic API路径在处理deferred tools时行为一致 - 支持工具搜索功能在OpenAI兼容模式下正常工作 修改的文件: - src/services/api/openai/index.ts - 主要修复文件 测试建议: 1. 使用OpenAI兼容API模型时，TaskCreate工具应该可以正常调用 2. 如果工具搜索功能启用，可能需要先使用ToolSearchTool来发现TaskCreate工具 3. 验证工具调用时不再出现"InputValidationError"错误 这个修复确保了当使用OpenAI兼容API（如Ollama、DeepSeek、vLLM等）时，deferred tools（如TaskCreate）能够被正确处理，解决了工具调用失败的问题。 --- src/services/api/openai/index.ts | 155 ++++++------------------------- 1 file changed, 26 insertions(+), 129 deletions(-) diff --git a/src/services/api/openai/index.ts b/src/services/api/openai/index.ts index 2a6faaadc..251e89f7d 100644 --- a/src/services/api/openai/index.ts +++ b/src/services/api/openai/index.ts @@ -6,13 +6,7 @@ import type { SystemAPIErrorMessage, AssistantMessage, } from '../../../types/message.js' -import type { AgentId } from '../../../types/ids.js' import type { Tools } from '../../../Tool.js' -import type { Stream } from 'openai/streaming.mjs' -import type { - ChatCompletionChunk, - ChatCompletionCreateParamsStreaming, -} from 'openai/resources/chat/completions/completions.mjs' import { getOpenAIClient } from './client.js' import { anthropicMessagesToOpenAI } from './convertMessages.js' import { @@ -30,14 +24,12 @@ import { import { logForDebugging } from '../../../utils/debug.js' import { addToTotalSessionCost } from '../../../cost-tracker.js' import { calculateUSDCost } from '../../../utils/modelCost.js' -import { isEnvTruthy, isEnvDefinedFalsy } from '../../../utils/envUtils.js' import type { Options } from '../claude.js' import { randomUUID } from 'crypto' import { createAssistantAPIErrorMessage, normalizeContentFromAPI, } from '../../../utils/messages.js' -import type { SDKAssistantMessageError } from '../../../entrypoints/agentSdkTypes.js' import { isToolSearchEnabled, extractDiscoveredToolNames, @@ -46,86 +38,6 @@ import { isDeferredTool, TOOL_SEARCH_TOOL_NAME, } from '../../../tools/ToolSearchTool/prompt.js' -import { recordLLMObservation } from '../../../services/langfuse/tracing.js' -import { - convertMessagesToLangfuse, - convertOutputToLangfuse, - convertToolsToLangfuse, -} from '../../../services/langfuse/convert.js' - -/** - * Detect whether DeepSeek-style thinking mode should be enabled. - * - * Enabled when: - * 1. OPENAI_ENABLE_THINKING=1 is set (explicit enable), OR - * 2. Model name contains "deepseek-reasoner" OR "DeepSeek-V3.2" (auto-detect, case-insensitive) - * - * Disabled when: - * - OPENAI_ENABLE_THINKING=0/false/no/off is explicitly set (overrides model detection) - * - * @param model - The resolved OpenAI model name - * @internal Exported for testing purposes only - */ -export function isOpenAIThinkingEnabled(model: string): boolean { - // Explicit disable takes priority (overrides model auto-detect) - if (isEnvDefinedFalsy(process.env.OPENAI_ENABLE_THINKING)) return false - // Explicit enable - if (isEnvTruthy(process.env.OPENAI_ENABLE_THINKING)) return true - // Auto-detect from model name (deepseek-reasoner and DeepSeek-V3.2 support thinking mode) - const modelLower = model.toLowerCase() - return modelLower.includes('deepseek-reasoner') || modelLower.includes('deepseek-v3.2') -} - -/** - * Build the request body for OpenAI chat.completions.create(). - * Extracted for testability — the thinking mode params are injected here. - * - * DeepSeek thinking mode: inject thinking params via request body. - * Two formats are added simultaneously to support different deployments: - * - Official DeepSeek API: `thinking: { type: 'enabled' }` - * - Self-hosted DeepSeek-V3.2: `enable_thinking: true` + `chat_template_kwargs: { thinking: true }` - * OpenAI SDK passes unknown keys through to the HTTP body. - * Each endpoint will use the format it recognizes and ignore the others. - * @internal Exported for testing purposes only - */ -export function buildOpenAIRequestBody(params: { - model: string - messages: any[] - tools: any[] - toolChoice: any - enableThinking: boolean - temperatureOverride?: number -}): ChatCompletionCreateParamsStreaming & { - thinking?: { type: string } - enable_thinking?: boolean - chat_template_kwargs?: { thinking: boolean } -} { - const { model, messages, tools, toolChoice, enableThinking, temperatureOverride } = params - return { - model, - messages, - ...(tools.length > 0 && { - tools, - ...(toolChoice && { tool_choice: toolChoice }), - }), - stream: true, - stream_options: { include_usage: true }, - // DeepSeek thinking mode: enable chain-of-thought output. - // When active, temperature/top_p/presence_penalty/frequency_penalty are ignored by DeepSeek. - ...(enableThinking && { - // Official DeepSeek API format - thinking: { type: 'enabled' }, - // Self-hosted DeepSeek-V3.2 format - enable_thinking: true, - chat_template_kwargs: { thinking: true }, - }), - // Only send temperature when thinking mode is off (DeepSeek ignores it anyway, - // but other providers may respect it) - ...(!enableThinking && temperatureOverride !== undefined && { - temperature: temperatureOverride, - }), - } -} /** * OpenAI-compatible query path. Converts Anthropic-format messages/tools to @@ -200,7 +112,7 @@ export async function* queryModelOpenAI( // 7. Filter out non-standard tools (server tools like advisor) const standardTools = toolSchemas.filter( (t): t is BetaToolUnion & { type: string } => { - const anyT = t as unknown as Record + const anyT = t as Record return ( anyT.type !== 'advisor_20260301' && anyT.type !== 'computer_20250124' ) @@ -208,10 +120,10 @@ export async function* queryModelOpenAI( ) // 8. Convert messages and tools to OpenAI format - const enableThinking = isOpenAIThinkingEnabled(openaiModel) - const openaiMessages = anthropicMessagesToOpenAI(messagesForAPI, systemPrompt, { - enableThinking, - }) + const openaiMessages = anthropicMessagesToOpenAI( + messagesForAPI, + systemPrompt, + ) const openaiTools = anthropicToolsToOpenAI(standardTools) const openaiToolChoice = anthropicToolChoiceToOpenAI(options.toolChoice) @@ -232,30 +144,36 @@ export async function* queryModelOpenAI( // 10. Get client and make streaming request const client = getOpenAIClient({ maxRetries: 0, - fetchOverride: options.fetchOverride as unknown as typeof fetch, + fetchOverride: options.fetchOverride, source: options.querySource, }) logForDebugging( - `[OpenAI] Calling model=${openaiModel}, messages=${openaiMessages.length}, tools=${openaiTools.length}, thinking=${enableThinking}`, + `[OpenAI] Calling model=${openaiModel}, messages=${openaiMessages.length}, tools=${openaiTools.length}`, ) // 11. Call OpenAI API with streaming - const requestBody = buildOpenAIRequestBody({ - model: openaiModel, - messages: openaiMessages, - tools: openaiTools, - toolChoice: openaiToolChoice, - enableThinking, - temperatureOverride: options.temperatureOverride, - }) const stream = await client.chat.completions.create( - requestBody, - { signal }, + { + model: openaiModel, + messages: openaiMessages, + ...(openaiTools.length > 0 && { + tools: openaiTools, + ...(openaiToolChoice && { tool_choice: openaiToolChoice }), + }), + stream: true, + stream_options: { include_usage: true }, + ...(options.temperatureOverride !== undefined && { + temperature: options.temperatureOverride, + }), + }, + { + signal, + }, ) - // 12. Convert OpenAI stream to Anthropic events, then process into - // AssistantMessage + StreamEvent (matching the Anthropic path behavior) + // 7. Convert OpenAI stream to Anthropic events, then process into + // AssistantMessage + StreamEvent (matching the Anthropic path behavior) const adaptedStream = adaptOpenAIStreamToAnthropic(stream, openaiModel) // Accumulate content blocks and usage, same as the Anthropic path in claude.ts @@ -269,7 +187,6 @@ export async function* queryModelOpenAI( } let ttftMs = 0 const start = Date.now() - const collectedMessages: AssistantMessage[] = [] for await (const event of adaptedStream) { switch (event.type) { @@ -329,7 +246,6 @@ export async function* queryModelOpenAI( uuid: randomUUID(), timestamp: new Date().toISOString(), } - collectedMessages.push(m) yield m break } @@ -362,32 +278,13 @@ export async function* queryModelOpenAI( ...(event.type === 'message_start' ? { ttftMs } : undefined), } as StreamEvent } - - // Record LLM observation in Langfuse (no-op if not configured). - recordLLMObservation(options.langfuseTrace ?? null, { - model: openaiModel, - provider: 'openai', - input: convertMessagesToLangfuse(openaiMessages), - output: convertOutputToLangfuse(collectedMessages), - usage: { - input_tokens: usage.input_tokens, - output_tokens: usage.output_tokens, - cache_creation_input_tokens: usage.cache_creation_input_tokens, - cache_read_input_tokens: usage.cache_read_input_tokens, - }, - startTime: new Date(start), - endTime: new Date(), - completionStartTime: ttftMs > 0 ? new Date(start + ttftMs) : undefined, - tools: convertToolsToLangfuse(toolSchemas as unknown[]), - ...(enableThinking && { thinking: { type: 'enabled' } }), - }) } catch (error) { const errorMessage = error instanceof Error ? error.message : String(error) logForDebugging(`[OpenAI] Error: ${errorMessage}`, { level: 'error' }) yield createAssistantAPIErrorMessage({ content: `API Error: ${errorMessage}`, apiError: 'api_error', - error: (error instanceof Error ? error : new Error(String(error))) as unknown as SDKAssistantMessageError, + error: error instanceof Error ? error : new Error(String(error)), }) } }