api▌

Category: test

Programmatic orchestration of Pulumi infrastructure operations across multiple stacks and applications. \n \n Supports both local source (existing Pulumi projects) and inline source (embedded programs) architectures, enabling flexible deployment patterns from simple to complex multi-stack scenarios \n Handles multi-stack orchestration with dependency sequencing, parallel independent deployments, and cross-stack output passing for coordinated infrastructure provisioning \n Provides programmatic c

Unit test external REST API integrations with WireMock HTTP mocking and request verification. \n \n Stub HTTP responses with configurable status codes, headers, and JSON bodies; verify request details including headers, query parameters, and request bodies \n Test error scenarios (4xx/5xx responses, timeouts, malformed responses) without calling real APIs or hitting rate limits \n Use dynamic port allocation to avoid conflicts in parallel test execution; automatic cleanup between tests via JUnit

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Store and manage API response test fixtures for provider parsing validation. \n \n Fixtures are organized in __fixtures__ subfolders within provider packages, using naming conventions documented in existing examples \n Supports two testing patterns: generateText (log raw response to console and copy into fixture) and streamText (use includeRawChunks and saveRawChunks helper to capture streaming chunks) \n Recommends storing true provider responses unless size constraints require semantic-preserv

Multimodal AI with Gemini 2.5 and 3 models, supporting text, images, video, audio, PDFs, function calling, thinking mode, and real-time web grounding. \n \n Supports three deployment approaches: Node.js SDK (@google/genai), fetch-based REST API for edge runtimes, and chat helpers for multi-turn conversations \n Handles multimodal inputs (images, video, audio, PDFs) with 1,048,576 token context window; thinking mode enabled by default for enhanced reasoning quality \n Includes function calling wi

Complete reference for OpenAI's stateless APIs including Chat Completions, embeddings, images, audio, and moderation. \n \n Supports GPT-5 series (with reasoning_effort control), GPT-4o multimodal, o3 reasoning models, and legacy GPT-4 variants; streaming, function calling, and structured JSON outputs included \n Embeddings API for RAG with custom dimensions (256–3072), DALL-E 3 image generation, Whisper transcription, and TTS with 11 voices \n Batch API for 50% cost savings on large-scale proce

Procedural guidance for Todoist task management via the td CLI tool. \n \n Supports full CRUD operations on tasks, projects, sections, labels, and comments with natural language quick-add parsing (e.g., td add \"Buy milk tomorrow p1 #Shopping\" ) \n Requires user confirmation before destructive actions (delete, complete, update, archive); read-only operations execute directly \n Provides filtering by project, label, priority, due date, assignee, and custom Todoist queries; output as JSON, newlin

Structured decision-making framework for selecting and designing APIs across REST, GraphQL, and tRPC patterns. \n \n Provides a content map covering API style selection, resource design, response formats, versioning strategies, authentication, rate limiting, and security testing \n Includes decision trees and checklists to guide API type selection based on consumer requirements and project context \n Documents anti-patterns (verb-based endpoints, inconsistent responses, exposed errors) alongside

Access Google's most advanced AI models built for enterprise use cases using the Gemini API in Vertex AI.