feat(responses-api): Support OpenAI Responses API with proper parameter mapping
WHAT: Add support for OpenAI Responses API in Kode CLI adapter WHY: Enable GPT-5 and similar models that require Responses API instead of Chat Completions; fix HTTP 400 errors and schema conversion failures HOW: Fixed tool format to use flat structure matching API spec; added missing critical parameters (include array, parallel_tool_calls, store, tool_choice); implemented robust schema conversion handling both Zod and pre-built JSON schemas; added array-based content parsing for Anthropic compatibility; created comprehensive integration tests exercising the full claude.ts flow AFFECTED FILES: - src/services/adapters/responsesAPI.ts: Complete adapter implementation - src/services/openai.ts: Simplified request handling - src/test/integration-cli-flow.test.ts: New integration test suite - src/test/responses-api-e2e.test.ts: Enhanced with production test capability VERIFICATION: - Integration tests pass: bun test src/test/integration-cli-flow.test.ts - Production tests: PRODUCTION_TEST_MODE=true bun test src/test/responses-api-e2e.test.ts
This commit is contained in:
Radon Co
parent
3c9b0ec9d1
commit
7069893d14
@ -5,7 +5,7 @@ import { zodToJsonSchema } from 'zod-to-json-schema'
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export class ResponsesAPIAdapter extends ModelAPIAdapter {
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createRequest(params: UnifiedRequestParams): any {
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const { messages, systemPrompt, tools, maxTokens, stream } = params
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const { messages, systemPrompt, tools, maxTokens, stream, reasoningEffort } = params
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// Build base request
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const request: any = {
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@ -13,7 +13,7 @@ export class ResponsesAPIAdapter extends ModelAPIAdapter {
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input: this.convertMessagesToInput(messages),
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instructions: this.buildInstructions(systemPrompt)
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}
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// Add token limit - Responses API uses max_output_tokens
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request.max_output_tokens = maxTokens
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@ -24,79 +24,75 @@ export class ResponsesAPIAdapter extends ModelAPIAdapter {
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if (this.getTemperature() === 1) {
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request.temperature = 1
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}
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// Add reasoning control - correct format for Responses API
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if (this.shouldIncludeReasoningEffort()) {
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// Add reasoning control - include array is required for reasoning content
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const include: string[] = []
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if (this.shouldIncludeReasoningEffort() || reasoningEffort) {
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include.push('reasoning.encrypted_content')
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request.reasoning = {
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effort: params.reasoningEffort || this.modelProfile.reasoningEffort || 'medium'
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effort: reasoningEffort || this.modelProfile.reasoningEffort || 'medium'
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}
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}
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// Add verbosity control - correct format for Responses API
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if (this.shouldIncludeVerbosity()) {
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request.text = {
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verbosity: params.verbosity || 'high' // High verbosity for coding tasks
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}
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}
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// Add tools
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if (tools && tools.length > 0) {
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request.tools = this.buildTools(tools)
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// Handle allowed_tools
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if (params.allowedTools && this.capabilities.toolCalling.supportsAllowedTools) {
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request.tool_choice = {
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type: 'allowed_tools',
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mode: 'auto',
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tools: params.allowedTools
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}
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}
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}
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// Add tool choice - use simple format like codex-cli.js
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request.tool_choice = 'auto'
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// Add parallel tool calls flag
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request.parallel_tool_calls = this.capabilities.toolCalling.supportsParallelCalls
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// Add store flag
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request.store = false
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// Add state management
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if (params.previousResponseId && this.capabilities.stateManagement.supportsPreviousResponseId) {
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request.previous_response_id = params.previousResponseId
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}
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// Add include array for reasoning and other content
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if (include.length > 0) {
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request.include = include
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}
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return request
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}
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buildTools(tools: Tool[]): any[] {
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// If freeform not supported, use traditional format
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if (!this.capabilities.toolCalling.supportsFreeform) {
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return tools.map(tool => ({
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type: 'function',
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function: {
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name: tool.name,
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description: tool.description || '',
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parameters: tool.inputJSONSchema || zodToJsonSchema(tool.inputSchema)
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}
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}))
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}
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// Custom tools format (GPT-5 feature)
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// Follow codex-cli.js format: flat structure, no nested 'function' object
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return tools.map(tool => {
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const hasSchema = tool.inputJSONSchema || tool.inputSchema
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const isCustom = !hasSchema
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if (isCustom) {
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// Custom tool format
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return {
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type: 'custom',
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name: tool.name,
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description: tool.description || ''
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}
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} else {
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// Traditional function format
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return {
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type: 'function',
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function: {
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name: tool.name,
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description: tool.description || '',
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parameters: tool.inputJSONSchema || zodToJsonSchema(tool.inputSchema)
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}
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// Prefer pre-built JSON schema if available
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let parameters = tool.inputJSONSchema
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// Otherwise, try to convert Zod schema
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if (!parameters && tool.inputSchema) {
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try {
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parameters = zodToJsonSchema(tool.inputSchema)
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} catch (error) {
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console.warn(`Failed to convert Zod schema for tool ${tool.name}:`, error)
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// Use minimal schema as fallback
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parameters = { type: 'object', properties: {} }
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}
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}
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return {
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type: 'function',
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name: tool.name,
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description: typeof tool.description === 'function'
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? 'Tool with dynamic description'
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: (tool.description || ''),
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parameters: parameters || { type: 'object', properties: {} }
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}
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})
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}
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@ -137,9 +133,14 @@ export class ResponsesAPIAdapter extends ModelAPIAdapter {
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const toolCalls = this.parseToolCalls(response)
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// Build unified response
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// Convert content to array format for Anthropic compatibility
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const contentArray = content
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? [{ type: 'text', text: content, citations: [] }]
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: [{ type: 'text', text: '', citations: [] }]
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return {
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id: response.id || `resp_${Date.now()}`,
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content,
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content: contentArray, // Return as array (Anthropic format)
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toolCalls,
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usage: {
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promptTokens: response.usage?.input_tokens || 0,
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@ -955,7 +955,7 @@ export function streamCompletion(
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*/
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export async function callGPT5ResponsesAPI(
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modelProfile: any,
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opts: any, // Using 'any' for Responses API params which differ from ChatCompletionCreateParams
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request: any, // Pre-formatted request from adapter
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signal?: AbortSignal,
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): Promise<any> {
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const baseURL = modelProfile?.baseURL || 'https://api.openai.com/v1'
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@ -969,82 +969,8 @@ export async function callGPT5ResponsesAPI(
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Authorization: `Bearer ${apiKey}`,
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}
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// 🔥 Enhanced Responses API Parameter Mapping for GPT-5
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const responsesParams: any = {
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model: opts.model,
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input: opts.messages, // Responses API uses 'input' instead of 'messages'
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}
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// 🔧 GPT-5 Token Configuration
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if (opts.max_completion_tokens) {
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responsesParams.max_completion_tokens = opts.max_completion_tokens
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} else if (opts.max_tokens) {
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// Fallback conversion if max_tokens is still present
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responsesParams.max_completion_tokens = opts.max_tokens
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}
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// 🔧 GPT-5 Temperature Handling (only 1 or undefined)
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if (opts.temperature === 1) {
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responsesParams.temperature = 1
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}
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// Note: Do not pass temperature if it's not 1, GPT-5 will use default
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// 🔧 GPT-5 Reasoning Configuration
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const reasoningEffort = opts.reasoning_effort || 'medium'
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responsesParams.reasoning = {
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effort: reasoningEffort,
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// 🚀 Enable reasoning summaries for transparency in coding tasks
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generate_summary: true,
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}
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// 🔧 GPT-5 Tools Support
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if (opts.tools && opts.tools.length > 0) {
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responsesParams.tools = opts.tools
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// 🚀 GPT-5 Tool Choice Configuration
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if (opts.tool_choice) {
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responsesParams.tool_choice = opts.tool_choice
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}
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}
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// 🔧 GPT-5 System Instructions (separate from messages)
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const systemMessages = opts.messages.filter(msg => msg.role === 'system')
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const nonSystemMessages = opts.messages.filter(msg => msg.role !== 'system')
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if (systemMessages.length > 0) {
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responsesParams.instructions = systemMessages.map(msg => msg.content).join('\n\n')
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responsesParams.input = nonSystemMessages
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}
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// Handle verbosity (if supported) - optimized for coding tasks
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const features = getModelFeatures(opts.model)
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if (features.supportsVerbosityControl) {
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// High verbosity for coding tasks to get detailed explanations and structured code
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// Based on GPT-5 best practices for agent-like coding environments
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responsesParams.text = {
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verbosity: 'high',
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}
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}
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// Apply GPT-5 coding optimizations
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if (opts.model.startsWith('gpt-5')) {
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// Set reasoning effort based on task complexity
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if (!responsesParams.reasoning) {
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responsesParams.reasoning = {
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effort: 'medium', // Balanced for most coding tasks
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}
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}
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// Add instructions parameter for coding-specific guidance
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if (!responsesParams.instructions) {
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responsesParams.instructions = `You are an expert programmer working in a terminal-based coding environment. Follow these guidelines:
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- Provide clear, concise code solutions
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- Use proper error handling and validation
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- Follow coding best practices and patterns
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- Explain complex logic when necessary
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- Focus on maintainable, readable code`
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}
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}
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// Use the pre-formatted request from the adapter
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const responsesParams = request
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try {
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const response = await fetch(`${baseURL}/responses`, {
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@ -1056,13 +982,12 @@ export async function callGPT5ResponsesAPI(
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})
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if (!response.ok) {
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throw new Error(`GPT-5 Responses API error: ${response.status} ${response.statusText}`)
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const errorText = await response.text()
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throw new Error(`GPT-5 Responses API error: ${response.status} ${response.statusText} - ${errorText}`)
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}
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const responseData = await response.json()
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// Convert Responses API response back to Chat Completion format for compatibility
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return convertResponsesAPIToChatCompletion(responseData)
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// Return the raw response - the adapter will handle parsing
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return response
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} catch (error) {
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if (signal?.aborted) {
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throw new Error('Request cancelled by user')
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175
src/test/integration-cli-flow.test.ts
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175
src/test/integration-cli-flow.test.ts
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@ -0,0 +1,175 @@
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/**
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* Integration Test: Full Claude.ts Flow
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*
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* This test exercises the EXACT same code path the CLI uses:
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* claude.ts → ModelAdapterFactory → adapter → API
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*
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* Fast iteration for debugging without running full CLI
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*/
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import { test, expect, describe } from 'bun:test'
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import { ModelAdapterFactory } from '../services/modelAdapterFactory'
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import { getModelCapabilities } from '../constants/modelCapabilities'
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import { ModelProfile } from '../utils/config'
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import { callGPT5ResponsesAPI } from '../services/openai'
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// Test profile matching what the CLI would use
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const GPT5_CODEX_PROFILE: ModelProfile = {
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name: 'gpt-5-codex',
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provider: 'openai',
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modelName: 'gpt-5-codex',
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baseURL: process.env.TEST_GPT5_BASE_URL || 'http://127.0.0.1:3000/openai',
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apiKey: process.env.TEST_GPT5_API_KEY || '',
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maxTokens: 8192,
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contextLength: 128000,
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reasoningEffort: 'high',
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isActive: true,
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createdAt: Date.now(),
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}
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describe('🔌 Integration: Full Claude.ts Flow', () => {
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test('✅ End-to-end flow through claude.ts path', async () => {
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console.log('\n🔌 INTEGRATION TEST: Full Flow')
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console.log('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━')
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try {
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// Step 1: Create adapter (same as claude.ts:1936)
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console.log('Step 1: Creating adapter...')
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const adapter = ModelAdapterFactory.createAdapter(GPT5_CODEX_PROFILE)
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console.log(` ✅ Adapter: ${adapter.constructor.name}`)
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// Step 2: Check if should use Responses API (same as claude.ts:1955)
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console.log('\nStep 2: Checking if should use Responses API...')
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const shouldUseResponses = ModelAdapterFactory.shouldUseResponsesAPI(GPT5_CODEX_PROFILE)
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console.log(` ✅ Should use Responses API: ${shouldUseResponses}`)
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if (!shouldUseResponses) {
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console.log(' ⚠️ SKIPPING: Not using Responses API')
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return
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}
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// Step 3: Build unified params (same as claude.ts:1939-1949)
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console.log('\nStep 3: Building unified request parameters...')
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const unifiedParams = {
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messages: [
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{ role: 'user', content: 'What is 2+2?' }
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],
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systemPrompt: ['You are a helpful assistant.'],
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tools: [], // Start with no tools to isolate the issue
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maxTokens: 100,
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stream: false,
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reasoningEffort: 'high' as const,
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temperature: 1,
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verbosity: 'high' as const
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}
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console.log(' ✅ Unified params built')
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// Step 4: Create request (same as claude.ts:1952)
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console.log('\nStep 4: Creating request via adapter...')
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const request = adapter.createRequest(unifiedParams)
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console.log(' ✅ Request created')
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console.log('\n📝 REQUEST STRUCTURE:')
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console.log(JSON.stringify(request, null, 2))
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// Step 5: Make API call (same as claude.ts:1958)
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console.log('\nStep 5: Making API call...')
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console.log(` 📍 Endpoint: ${GPT5_CODEX_PROFILE.baseURL}/responses`)
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console.log(` 🔑 API Key: ${GPT5_CODEX_PROFILE.apiKey.substring(0, 8)}...`)
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const response = await callGPT5ResponsesAPI(GPT5_CODEX_PROFILE, request)
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console.log(` ✅ Response received: ${response.status}`)
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// Step 6: Parse response (same as claude.ts:1959)
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console.log('\nStep 6: Parsing response...')
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const unifiedResponse = await adapter.parseResponse(response)
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console.log(' ✅ Response parsed')
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console.log('\n📄 UNIFIED RESPONSE:')
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console.log(JSON.stringify(unifiedResponse, null, 2))
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// Step 7: Check for errors
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console.log('\nStep 7: Validating response...')
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expect(unifiedResponse).toBeDefined()
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expect(unifiedResponse.content).toBeDefined()
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console.log(' ✅ All validations passed')
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} catch (error) {
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console.log('\n❌ ERROR CAUGHT:')
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console.log(` Message: ${error.message}`)
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console.log(` Stack: ${error.stack}`)
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// Re-throw to fail the test
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throw error
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}
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})
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test('⚠️ Test with TOOLS (reproduces the 400 error)', async () => {
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console.log('\n⚠️ INTEGRATION TEST: With Tools (Should Fail)')
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console.log('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━')
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try {
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const adapter = ModelAdapterFactory.createAdapter(GPT5_CODEX_PROFILE)
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const shouldUseResponses = ModelAdapterFactory.shouldUseResponsesAPI(GPT5_CODEX_PROFILE)
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if (!shouldUseResponses) {
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console.log(' ⚠️ SKIPPING: Not using Responses API')
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return
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}
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// Build params WITH tools (this might cause the 400 error)
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const unifiedParams = {
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messages: [
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{ role: 'user', content: 'What is 2+2?' }
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],
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systemPrompt: ['You are a helpful assistant.'],
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tools: [
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{
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name: 'read_file',
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description: 'Read file contents',
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inputSchema: {
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type: 'object',
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properties: {
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path: { type: 'string' }
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}
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}
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}
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],
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maxTokens: 100,
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stream: false,
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reasoningEffort: 'high' as const,
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temperature: 1,
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verbosity: 'high' as const
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}
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const request = adapter.createRequest(unifiedParams)
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console.log('\n📝 REQUEST WITH TOOLS:')
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console.log(JSON.stringify(request, null, 2))
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console.log('\n🔍 TOOLS STRUCTURE:')
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if (request.tools) {
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request.tools.forEach((tool: any, i: number) => {
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console.log(` Tool ${i}:`, JSON.stringify(tool, null, 2))
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})
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}
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const response = await callGPT5ResponsesAPI(GPT5_CODEX_PROFILE, request)
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const unifiedResponse = await adapter.parseResponse(response)
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console.log('\n✅ SUCCESS: Request with tools worked!')
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console.log('Response:', JSON.stringify(unifiedResponse, null, 2))
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expect(unifiedResponse).toBeDefined()
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} catch (error) {
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console.log('\n❌ EXPECTED ERROR (This is the bug we\'re tracking):')
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console.log(` Status: ${error.message}`)
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if (error.message.includes('400')) {
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console.log('\n🔍 THIS IS THE BUG!')
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console.log(' The 400 error happens with tools')
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console.log(' Check the request structure above')
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}
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throw error
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}
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})
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})
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430
src/test/responses-api-e2e.test.ts
Normal file
430
src/test/responses-api-e2e.test.ts
Normal file
@ -0,0 +1,430 @@
|
||||
import { test, expect, describe } from 'bun:test'
|
||||
import { ModelAdapterFactory } from '../services/modelAdapterFactory'
|
||||
import { getModelCapabilities } from '../constants/modelCapabilities'
|
||||
import { ModelProfile } from '../utils/config'
|
||||
|
||||
/**
|
||||
* Responses API End-to-End Integration Tests
|
||||
*
|
||||
* This test file includes both:
|
||||
* 1. Unit tests - Test adapter conversion logic (always run)
|
||||
* 2. Production tests - Make REAL API calls (requires PRODUCTION_TEST_MODE=true)
|
||||
*
|
||||
* To run production tests:
|
||||
* PRODUCTION_TEST_MODE=true bun test src/test/responses-api-e2e.test.ts
|
||||
*
|
||||
* Environment variables required for production tests:
|
||||
* TEST_GPT5_API_KEY=your_api_key_here
|
||||
* TEST_GPT5_BASE_URL=http://127.0.0.1:3000/openai
|
||||
*
|
||||
* ⚠️ WARNING: Production tests make real API calls and may incur costs!
|
||||
*/
|
||||
|
||||
// Test the actual usage pattern from Kode CLI
|
||||
const GPT5_CODEX_PROFILE: ModelProfile = {
|
||||
name: 'gpt-5-codex',
|
||||
provider: 'openai',
|
||||
modelName: 'gpt-5-codex',
|
||||
baseURL: 'http://127.0.0.1:3000/openai',
|
||||
apiKey: process.env.TEST_GPT5_API_KEY || '',
|
||||
maxTokens: 8192,
|
||||
contextLength: 128000,
|
||||
reasoningEffort: 'high',
|
||||
isActive: true,
|
||||
createdAt: Date.now(),
|
||||
}
|
||||
|
||||
// ⚠️ PRODUCTION TEST MODE ⚠️
|
||||
// This test can make REAL API calls to external services
|
||||
// Set PRODUCTION_TEST_MODE=true to enable
|
||||
// Costs may be incurred - use with caution!
|
||||
|
||||
const PRODUCTION_TEST_MODE = process.env.PRODUCTION_TEST_MODE === 'true'
|
||||
|
||||
// Test model profile for production testing
|
||||
// Uses environment variables - MUST be set for production tests
|
||||
const GPT5_CODEX_PROFILE_PROD: ModelProfile = {
|
||||
name: 'gpt-5-codex',
|
||||
provider: 'openai',
|
||||
modelName: 'gpt-5-codex',
|
||||
baseURL: process.env.TEST_GPT5_BASE_URL || 'http://127.0.0.1:3000/openai',
|
||||
apiKey: process.env.TEST_GPT5_API_KEY || '',
|
||||
maxTokens: 8192,
|
||||
contextLength: 128000,
|
||||
reasoningEffort: 'high',
|
||||
isActive: true,
|
||||
createdAt: Date.now(),
|
||||
}
|
||||
|
||||
describe('🔬 Responses API End-to-End Integration Tests', () => {
|
||||
test('✅ Adapter correctly converts Anthropic format to Responses API format', () => {
|
||||
const adapter = ModelAdapterFactory.createAdapter(GPT5_CODEX_PROFILE)
|
||||
const capabilities = getModelCapabilities(GPT5_CODEX_PROFILE.modelName)
|
||||
|
||||
// This is the format Kode CLI actually uses
|
||||
const unifiedParams = {
|
||||
messages: [
|
||||
{ role: 'user', content: 'who are you' }
|
||||
],
|
||||
systemPrompt: ['You are a helpful assistant'],
|
||||
maxTokens: 100,
|
||||
}
|
||||
|
||||
const request = adapter.createRequest(unifiedParams)
|
||||
|
||||
// Verify the request is properly formatted for Responses API
|
||||
expect(request).toBeDefined()
|
||||
expect(request.model).toBe('gpt-5-codex')
|
||||
expect(request.instructions).toBe('You are a helpful assistant')
|
||||
expect(request.input).toBeDefined()
|
||||
expect(Array.isArray(request.input)).toBe(true)
|
||||
expect(request.max_output_tokens).toBe(100)
|
||||
expect(request.stream).toBe(true)
|
||||
|
||||
// Verify the input array has the correct structure
|
||||
const inputItem = request.input[0]
|
||||
expect(inputItem.type).toBe('message')
|
||||
expect(inputItem.role).toBe('user')
|
||||
expect(inputItem.content).toBeDefined()
|
||||
expect(Array.isArray(inputItem.content)).toBe(true)
|
||||
|
||||
const contentItem = inputItem.content[0]
|
||||
expect(contentItem.type).toBe('input_text')
|
||||
expect(contentItem.text).toBe('who are you')
|
||||
})
|
||||
|
||||
test('✅ Handles system messages correctly', () => {
|
||||
const adapter = ModelAdapterFactory.createAdapter(GPT5_CODEX_PROFILE)
|
||||
|
||||
const unifiedParams = {
|
||||
messages: [
|
||||
{ role: 'user', content: 'Hello' }
|
||||
],
|
||||
systemPrompt: [
|
||||
'You are a coding assistant',
|
||||
'Always write clean code'
|
||||
],
|
||||
maxTokens: 50,
|
||||
}
|
||||
|
||||
const request = adapter.createRequest(unifiedParams)
|
||||
|
||||
// System prompts should be joined with double newlines
|
||||
expect(request.instructions).toBe('You are a coding assistant\n\nAlways write clean code')
|
||||
expect(request.input).toHaveLength(1)
|
||||
})
|
||||
|
||||
test('✅ Handles multiple messages including tool results', () => {
|
||||
const adapter = ModelAdapterFactory.createAdapter(GPT5_CODEX_PROFILE)
|
||||
|
||||
const unifiedParams = {
|
||||
messages: [
|
||||
{ role: 'user', content: 'What is this file?' },
|
||||
{
|
||||
role: 'tool',
|
||||
tool_call_id: 'tool_123',
|
||||
content: 'This is a TypeScript file'
|
||||
},
|
||||
{ role: 'assistant', content: 'I need to check the file first' },
|
||||
{ role: 'user', content: 'Please read it' }
|
||||
],
|
||||
systemPrompt: ['You are helpful'],
|
||||
maxTokens: 100,
|
||||
}
|
||||
|
||||
const request = adapter.createRequest(unifiedParams)
|
||||
|
||||
// Should have multiple input items
|
||||
expect(request.input).toBeDefined()
|
||||
expect(Array.isArray(request.input)).toBe(true)
|
||||
|
||||
// Should have tool call result, assistant message, and user message
|
||||
const hasToolResult = request.input.some(item => item.type === 'function_call_output')
|
||||
const hasUserMessage = request.input.some(item => item.role === 'user')
|
||||
|
||||
expect(hasToolResult).toBe(true)
|
||||
expect(hasUserMessage).toBe(true)
|
||||
})
|
||||
|
||||
test('✅ Includes reasoning and verbosity parameters', () => {
|
||||
const adapter = ModelAdapterFactory.createAdapter(GPT5_CODEX_PROFILE)
|
||||
|
||||
const unifiedParams = {
|
||||
messages: [
|
||||
{ role: 'user', content: 'Explain this code' }
|
||||
],
|
||||
systemPrompt: ['You are an expert'],
|
||||
maxTokens: 200,
|
||||
reasoningEffort: 'high',
|
||||
verbosity: 'high',
|
||||
}
|
||||
|
||||
const request = adapter.createRequest(unifiedParams)
|
||||
|
||||
expect(request.reasoning).toBeDefined()
|
||||
expect(request.reasoning.effort).toBe('high')
|
||||
expect(request.text).toBeDefined()
|
||||
expect(request.text.verbosity).toBe('high')
|
||||
})
|
||||
|
||||
test('✅ Does NOT include deprecated parameters', () => {
|
||||
const adapter = ModelAdapterFactory.createAdapter(GPT5_CODEX_PROFILE)
|
||||
|
||||
const unifiedParams = {
|
||||
messages: [
|
||||
{ role: 'user', content: 'Hello' }
|
||||
],
|
||||
systemPrompt: ['You are helpful'],
|
||||
maxTokens: 100,
|
||||
}
|
||||
|
||||
const request = adapter.createRequest(unifiedParams)
|
||||
|
||||
// Should NOT have these old parameters
|
||||
expect(request.messages).toBeUndefined()
|
||||
expect(request.max_completion_tokens).toBeUndefined()
|
||||
expect(request.max_tokens).toBeUndefined()
|
||||
})
|
||||
|
||||
test('✅ Correctly uses max_output_tokens parameter', () => {
|
||||
const adapter = ModelAdapterFactory.createAdapter(GPT5_CODEX_PROFILE)
|
||||
|
||||
const unifiedParams = {
|
||||
messages: [
|
||||
{ role: 'user', content: 'Test' }
|
||||
],
|
||||
systemPrompt: ['You are helpful'],
|
||||
maxTokens: 500,
|
||||
}
|
||||
|
||||
const request = adapter.createRequest(unifiedParams)
|
||||
|
||||
// Should use the correct parameter name for Responses API
|
||||
expect(request.max_output_tokens).toBe(500)
|
||||
})
|
||||
|
||||
test('✅ Adapter selection logic works correctly', () => {
|
||||
// GPT-5 should use Responses API
|
||||
const shouldUseResponses = ModelAdapterFactory.shouldUseResponsesAPI(GPT5_CODEX_PROFILE)
|
||||
expect(shouldUseResponses).toBe(true)
|
||||
|
||||
const adapter = ModelAdapterFactory.createAdapter(GPT5_CODEX_PROFILE)
|
||||
expect(adapter.constructor.name).toBe('ResponsesAPIAdapter')
|
||||
})
|
||||
|
||||
test('✅ Streaming is always enabled for Responses API', () => {
|
||||
const adapter = ModelAdapterFactory.createAdapter(GPT5_CODEX_PROFILE)
|
||||
|
||||
const unifiedParams = {
|
||||
messages: [
|
||||
{ role: 'user', content: 'Hello' }
|
||||
],
|
||||
systemPrompt: ['You are helpful'],
|
||||
maxTokens: 100,
|
||||
stream: false, // Even if user sets this to false
|
||||
}
|
||||
|
||||
const request = adapter.createRequest(unifiedParams)
|
||||
|
||||
// Responses API always requires streaming
|
||||
expect(request.stream).toBe(true)
|
||||
})
|
||||
})
|
||||
|
||||
describe('🌐 Production API Integration Tests', () => {
|
||||
if (!PRODUCTION_TEST_MODE) {
|
||||
test('⚠️ PRODUCTION TEST MODE DISABLED', () => {
|
||||
console.log('\n🚨 PRODUCTION TEST MODE IS DISABLED 🚨')
|
||||
console.log('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━')
|
||||
console.log('To enable production tests, run:')
|
||||
console.log(' PRODUCTION_TEST_MODE=true bun test src/test/responses-api-e2e.test.ts')
|
||||
console.log('')
|
||||
console.log('⚠️ WARNING: This will make REAL API calls and may incur costs!')
|
||||
console.log('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━')
|
||||
expect(true).toBe(true) // This test always passes
|
||||
})
|
||||
return
|
||||
}
|
||||
|
||||
// Validate that required environment variables are set
|
||||
if (!process.env.TEST_GPT5_API_KEY) {
|
||||
test('⚠️ ENVIRONMENT VARIABLES NOT CONFIGURED', () => {
|
||||
console.log('\n🚨 ENVIRONMENT VARIABLES NOT CONFIGURED 🚨')
|
||||
console.log('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━')
|
||||
console.log('Create a .env file with the following variables:')
|
||||
console.log(' TEST_GPT5_API_KEY=your_api_key_here')
|
||||
console.log(' TEST_GPT5_BASE_URL=http://127.0.0.1:3000/openai')
|
||||
console.log('')
|
||||
console.log('⚠️ Never commit .env files to version control!')
|
||||
console.log('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━')
|
||||
expect(true).toBe(true) // This test always passes
|
||||
})
|
||||
return
|
||||
}
|
||||
|
||||
describe('📡 GPT-5 Codex Production Test - Request Validation', () => {
|
||||
test('🚀 Makes real API call and validates ALL request parameters', async () => {
|
||||
const adapter = ModelAdapterFactory.createAdapter(GPT5_CODEX_PROFILE_PROD)
|
||||
const shouldUseResponses = ModelAdapterFactory.shouldUseResponsesAPI(GPT5_CODEX_PROFILE_PROD)
|
||||
|
||||
console.log('\n🚀 GPT-5 CODEX PRODUCTION TEST (Request Validation):')
|
||||
console.log('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━')
|
||||
console.log('🔗 Adapter:', adapter.constructor.name)
|
||||
console.log('📍 Endpoint:', shouldUseResponses
|
||||
? `${GPT5_CODEX_PROFILE_PROD.baseURL}/responses`
|
||||
: `${GPT5_CODEX_PROFILE_PROD.baseURL}/chat/completions`)
|
||||
console.log('🤖 Model:', GPT5_CODEX_PROFILE_PROD.modelName)
|
||||
console.log('🔑 API Key:', GPT5_CODEX_PROFILE_PROD.apiKey.substring(0, 8) + '...')
|
||||
|
||||
// Create test request with reasoning enabled
|
||||
const mockParams = {
|
||||
messages: [
|
||||
{ role: 'user', content: 'What is 2 + 2?' }
|
||||
],
|
||||
systemPrompt: ['You are a helpful assistant. Show your reasoning.'],
|
||||
maxTokens: 100,
|
||||
reasoningEffort: 'high' as const,
|
||||
}
|
||||
|
||||
try {
|
||||
const request = adapter.createRequest(mockParams)
|
||||
|
||||
// Log the complete request for inspection
|
||||
console.log('\n📝 FULL REQUEST BODY:')
|
||||
console.log(JSON.stringify(request, null, 2))
|
||||
console.log('\n🔍 CHECKING FOR CRITICAL PARAMETERS:')
|
||||
console.log(' ✅ include array:', request.include ? 'PRESENT' : '❌ MISSING')
|
||||
console.log(' ✅ parallel_tool_calls:', request.parallel_tool_calls !== undefined ? 'PRESENT' : '❌ MISSING')
|
||||
console.log(' ✅ store:', request.store !== undefined ? 'PRESENT' : '❌ MISSING')
|
||||
console.log(' ✅ tool_choice:', request.tool_choice !== undefined ? 'PRESENT' : '❌ MISSING')
|
||||
console.log(' ✅ reasoning:', request.reasoning ? 'PRESENT' : '❌ MISSING')
|
||||
console.log(' ✅ max_output_tokens:', request.max_output_tokens ? 'PRESENT' : '❌ MISSING')
|
||||
|
||||
// Make the actual API call
|
||||
const endpoint = `${GPT5_CODEX_PROFILE_PROD.baseURL}/responses`
|
||||
|
||||
console.log('\n📡 Making request to:', endpoint)
|
||||
const response = await fetch(endpoint, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
'Authorization': `Bearer ${GPT5_CODEX_PROFILE_PROD.apiKey}`,
|
||||
},
|
||||
body: JSON.stringify(request),
|
||||
})
|
||||
|
||||
console.log('📊 Response status:', response.status)
|
||||
console.log('📊 Response headers:', Object.fromEntries(response.headers.entries()))
|
||||
|
||||
if (response.ok) {
|
||||
// Use the adapter's parseResponse method to handle both streaming and non-streaming
|
||||
const unifiedResponse = await adapter.parseResponse(response)
|
||||
console.log('\n✅ SUCCESS! Response received:')
|
||||
console.log('📄 Unified Response:', JSON.stringify(unifiedResponse, null, 2))
|
||||
|
||||
expect(response.status).toBe(200)
|
||||
expect(unifiedResponse).toBeDefined()
|
||||
expect(unifiedResponse.content).toBeDefined()
|
||||
|
||||
// Verify critical fields are present in response
|
||||
if (unifiedResponse.usage.reasoningTokens !== undefined) {
|
||||
console.log('✅ Reasoning tokens received:', unifiedResponse.usage.reasoningTokens)
|
||||
} else {
|
||||
console.log('⚠️ No reasoning tokens in response (this might be OK)')
|
||||
}
|
||||
} else {
|
||||
const errorText = await response.text()
|
||||
console.log('\n❌ API ERROR:', response.status)
|
||||
console.log('Error body:', errorText)
|
||||
|
||||
// Check if error is due to missing parameters
|
||||
if (errorText.includes('include') || errorText.includes('parallel_tool_calls')) {
|
||||
console.log('\n💡 THIS ERROR LIKELY INDICATES MISSING PARAMETERS!')
|
||||
}
|
||||
|
||||
throw new Error(`API call failed: ${response.status} ${errorText}`)
|
||||
}
|
||||
|
||||
} catch (error) {
|
||||
console.log('\n💥 Request failed:', error.message)
|
||||
throw error
|
||||
}
|
||||
}, 30000) // 30 second timeout
|
||||
})
|
||||
|
||||
describe('🔬 Test Missing Parameters Impact', () => {
|
||||
test('⚠️ Test request WITHOUT critical parameters', async () => {
|
||||
console.log('\n⚠️ TESTING MISSING PARAMETERS IMPACT')
|
||||
console.log('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━')
|
||||
|
||||
const adapter = ModelAdapterFactory.createAdapter(GPT5_CODEX_PROFILE_PROD)
|
||||
|
||||
// Create base request
|
||||
const mockParams = {
|
||||
messages: [
|
||||
{ role: 'user', content: 'What is 2 + 2?' }
|
||||
],
|
||||
systemPrompt: ['You are a helpful assistant.'],
|
||||
maxTokens: 100,
|
||||
}
|
||||
|
||||
const request = adapter.createRequest(mockParams)
|
||||
|
||||
// Manually remove critical parameters to test their importance
|
||||
console.log('\n🗑️ REMOVING CRITICAL PARAMETERS:')
|
||||
console.log(' - include array')
|
||||
console.log(' - parallel_tool_calls')
|
||||
console.log(' - store')
|
||||
console.log(' (keeping tool_choice, reasoning, max_output_tokens)')
|
||||
|
||||
const modifiedRequest = { ...request }
|
||||
delete modifiedRequest.include
|
||||
delete modifiedRequest.parallel_tool_calls
|
||||
delete modifiedRequest.store
|
||||
|
||||
console.log('\n📝 MODIFIED REQUEST:')
|
||||
console.log(JSON.stringify(modifiedRequest, null, 2))
|
||||
|
||||
// Make API call
|
||||
const endpoint = `${GPT5_CODEX_PROFILE_PROD.baseURL}/responses`
|
||||
|
||||
try {
|
||||
console.log('\n📡 Making request with missing parameters...')
|
||||
const response = await fetch(endpoint, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
'Authorization': `Bearer ${GPT5_CODEX_PROFILE_PROD.apiKey}`,
|
||||
},
|
||||
body: JSON.stringify(modifiedRequest),
|
||||
})
|
||||
|
||||
console.log('📊 Response status:', response.status)
|
||||
|
||||
if (response.ok) {
|
||||
const unifiedResponse = await adapter.parseResponse(response)
|
||||
console.log('✅ Request succeeded WITHOUT missing parameters')
|
||||
console.log('📄 Response content:', unifiedResponse.content)
|
||||
console.log('\n💡 CONCLUSION: These parameters may be OPTIONAL')
|
||||
} else {
|
||||
const errorText = await response.text()
|
||||
console.log('❌ Request failed:', response.status)
|
||||
console.log('Error:', errorText)
|
||||
|
||||
// Analyze error to determine which parameters are critical
|
||||
if (errorText.includes('include')) {
|
||||
console.log('\n🔍 FINDING: include parameter is CRITICAL')
|
||||
}
|
||||
if (errorText.includes('parallel_tool_calls')) {
|
||||
console.log('\n🔍 FINDING: parallel_tool_calls parameter is CRITICAL')
|
||||
}
|
||||
if (errorText.includes('store')) {
|
||||
console.log('\n🔍 FINDING: store parameter is CRITICAL')
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
console.log('💥 Exception:', error.message)
|
||||
}
|
||||
}, 30000)
|
||||
})
|
||||
})
|
||||
Loading…
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Reference in New Issue
Block a user