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Foxall"},"license":"Apache-2.0","homepage":"https://github.com/drew-foxall/a2a-js-sdk-examples/tree/main/packages/a2a-ai-sdk-adapter#readme","keywords":["a2a","agent","ai-sdk","adapter","vercel-ai-sdk","hono","typescript","agent-to-agent","multi-agent","llm"],"repository":{"type":"git","url":"git+https://github.com/drew-foxall/a2a-js-sdk-examples.git","directory":"packages/a2a-ai-sdk-adapter"},"description":"Unified adapter bridging Vercel AI SDK ToolLoopAgent with A2A protocol","maintainers":[{"name":"drew-foxall","email":"drew@foxalltogether.com"}],"readme":"# @drew-foxall/a2a-ai-sdk-adapter\n\n[![npm version](https://img.shields.io/npm/v/@drew-foxall/a2a-ai-sdk-adapter)](https://www.npmjs.com/package/@drew-foxall/a2a-ai-sdk-adapter)\n[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)\n[![TypeScript](https://img.shields.io/badge/TypeScript-5.8-blue)](https://www.typescriptlang.org/)\n\n**Unified adapter bridging Vercel AI SDK's ToolLoopAgent with the A2A (Agent-to-Agent) protocol.**\n\nThis package provides a robust and type-safe way to expose AI SDK agents as A2A-compliant services, supporting both simple (awaited) and streaming interactions, along with flexible artifact generation and logging.\n\n**Two Adapters Available:**\n- **`A2AAdapter`** - For standard `ToolLoopAgent` agents (non-durable)\n- **`DurableA2AAdapter`** - For durable workflows using Workflow DevKit (import from `@drew-foxall/a2a-ai-sdk-adapter/durable`)\n\n---\n\n## πŸ“¦ Installation\n\n```bash\nnpm install @drew-foxall/a2a-ai-sdk-adapter\n# or\npnpm add @drew-foxall/a2a-ai-sdk-adapter\n# or\nyarn add @drew-foxall/a2a-ai-sdk-adapter\n```\n\n**Peer Dependencies**:\n- `ai` ^6.0.0 (Vercel AI SDK)\n- `@drew-foxall/a2a-js-sdk` ^0.3.5\n- `uuid` ^11.0.0\n\n---\n\n## πŸš€ Quick Start\n\n```typescript\nimport { ToolLoopAgent } from \"ai\";\nimport { openai } from \"@ai-sdk/openai\";\nimport { A2AAdapter } from \"@drew-foxall/a2a-ai-sdk-adapter\";\nimport { A2AHonoApp } from \"@drew-foxall/a2a-js-sdk/server/hono\";\nimport { serve } from \"@hono/node-server\";\n\n// 1. Create your AI SDK agent\nconst agent = new ToolLoopAgent({\n model: openai(\"gpt-4o\"),\n instructions: \"You are a helpful assistant\",\n tools: {},\n});\n\n// 2. Wrap with A2A adapter\nconst executor = new A2AAdapter(agent, {\n mode: \"stream\", // or \"generate\"\n});\n\n// 3. Create A2A server\nconst app = new A2AHonoApp({\n card: {\n name: \"My Agent\",\n description: \"A helpful AI agent\",\n url: \"http://localhost:3000\",\n version: \"1.0.0\",\n protocolVersion: \"0.3.0\",\n capabilities: {\n streaming: true,\n },\n defaultInputModes: [\"text/plain\"],\n defaultOutputModes: [\"text/plain\"],\n skills: [],\n },\n executor,\n});\n\n// 4. Start server\nserve({ fetch: app.fetch, port: 3000 });\n```\n\n---\n\n## πŸ“– API Documentation\n\n### `A2AAdapter`\n\nThe main adapter class that bridges AI SDK agents with the A2A protocol.\n\n#### Constructor\n\n```typescript\nconstructor(agent: ToolLoopAgent, config: A2AAdapterConfig)\n```\n\n**Parameters**:\n- `agent`: A configured `ToolLoopAgent` from Vercel AI SDK\n- `config`: Configuration object (see below)\n\n#### Configuration Options (`A2AAdapterConfig`)\n\n| Option | Type | Required | Description |\n|--------|------|----------|-------------|\n| `mode` | `'stream' \\| 'generate'` | **Yes** | Execution mode (see [Mode Selection](#mode-selection)) |\n| `selectResponseType` | `(ctx) => 'message' \\| 'task' \\| Promise<'message' \\| 'task'>` | No | **Agent-owned routing step** to choose A2A `Message` vs `Task` per request (defaults to `task`) |\n| `systemPrompt` | `string` | No | System prompt for the agent (default: generic A2A prompt) |\n| `maxSteps` | `number` | No | Max tool call iterations (default: 5) |\n| `includeHistory` | `boolean` | No | Include conversation history (default: false) |\n| `logger` | `A2ALogger` | No | Custom logger (default: `ConsoleLogger`) |\n| `parseArtifacts` | `(text: string, context: ArtifactGenerationContext) => ParsedArtifacts \\| ParsedArtifact[]` | No | Parse artifacts from text (stream mode only) |\n| `generateArtifacts` | `(context: ArtifactGenerationContext) => Promise` | No | Generate artifacts asynchronously |\n| `parseTaskState` | `(text: string) => TaskState` | No | Custom task state parser (default: \"completed\") |\n\n---\n\n## 🧭 Dynamic Response Type (A2A `Message` vs `Task`)\n\nA2A allows an agent to respond with either a stateless **`Message`** (immediate) or a stateful **`Task`** (lifecycle + streaming/progress). See β€œAgent Response: Task or Message” in the A2A core concepts doc ([A2A key concepts](https://raw.githubusercontent.com/a2aproject/A2A/main/docs/topics/key-concepts.md)).\n\n### Why this must be decided β€œup front”\n\nIf the server starts emitting task lifecycle events (or starts SSE streaming), it has already committed to a **Task** response shape. Therefore the adapter needs a *routing decision* before it publishes any task events.\n\n### Recommended pattern: agent-owned routing (AI SDK β€œRouting”)\n\nUse `selectResponseType` as a small *routing/classification step* owned by your agentic system (not β€œthe user telling the agent what to do”):\n\n```ts\nimport { A2AAdapter } from \"@drew-foxall/a2a-ai-sdk-adapter\";\n\nconst executor = new A2AAdapter(agent, {\n mode: \"stream\", // default execution mode for Task responses\n\n // Agent-owned routing step (AI SDK \"Routing\" pattern)\n selectResponseType: async ({ userMessage, existingTask }) => {\n // Continuations should stay in Task mode\n if (existingTask) return \"task\";\n\n // Do a cheap classification step (e.g. generateObject / small model)\n const { responseType } = await classifyRequest(userMessage);\n return responseType; // \"message\" | \"task\"\n },\n});\n```\n\nNotes:\n- If you always want stateless behavior (e.g. β€œHello World”), return `\"message\"`.\n- If you want full lifecycle + streaming/progress/cancellation, return `\"task\"`.\n\n### Utilities to reduce boilerplate\n\nThe adapter exports small helpers you can use when implementing routing:\n\n```ts\nimport {\n extractTextFromA2AMessage,\n createLLMResponseTypeRouter,\n preferTaskForContinuations,\n} from \"@drew-foxall/a2a-ai-sdk-adapter\";\n\nconst selectResponseType = preferTaskForContinuations(async ({ userMessage }) => {\n const text = extractTextFromA2AMessage(userMessage);\n // ... your agent-owned routing/classification logic ...\n return text ? \"message\" : \"task\";\n});\n```\n\nIf you want a ready-made LLM router (AI SDK `generateObject`), you can use:\n\n```ts\nimport { createLLMResponseTypeRouter } from \"@drew-foxall/a2a-ai-sdk-adapter\";\nimport { z } from \"zod\";\n\nconst selectResponseType = createLLMResponseTypeRouter({\n model: routingModel, // choose a small/cheap model\n // Optional: omit schema to use the adapter’s default schema (requires zod installed)\n schema: z.object({\n responseType: z.enum([\"message\", \"task\"]),\n reasoning: z.string().optional(),\n }),\n});\n```\n\n## 🎯 Mode Selection\n\n### Stream Mode (`mode: 'stream'`)\n\n**Best for**: Long-form content, code generation, chat interfaces\n\n**Capabilities**:\n- βœ… Real-time text streaming\n- βœ… Incremental artifact parsing (via `parseArtifacts`)\n- βœ… Post-completion artifacts (via `generateArtifacts`)\n\n**Example**:\n```typescript\nconst executor = new A2AAdapter(agent, {\n mode: \"stream\",\n parseArtifacts: (text) => {\n // Extract code blocks in real-time\n const codeBlocks = extractCodeBlocks(text);\n return codeBlocks.map(block => ({\n content: block.code,\n mimeType: \"application/octet-stream\",\n title: `${block.language} code`,\n }));\n },\n});\n```\n\n---\n\n### Generate Mode (`mode: 'generate'`)\n\n**Best for**: Quick responses, API-style interactions, simple agents\n\n**Capabilities**:\n- βœ… Single awaited response\n- βœ… Post-completion artifacts (via `generateArtifacts`)\n\n**Example**:\n```typescript\nconst executor = new A2AAdapter(agent, {\n mode: \"generate\",\n generateArtifacts: async (ctx) => {\n // Generate a chart after response is complete\n const chart = await generateChart(ctx.responseText);\n return [{\n content: chart.toString(\"base64\"),\n mimeType: \"image/png\",\n title: \"Analytics Chart\",\n }];\n },\n});\n```\n\n---\n\n## πŸ“Š Artifacts\n\nArtifacts are supplementary data (images, code, files) attached to agent responses.\n\n### Real-Time Artifact Parsing (Stream Mode Only)\n\n```typescript\nconst executor = new A2AAdapter(agent, {\n mode: \"stream\",\n parseArtifacts: (text, context) => {\n // Called for each text chunk\n const artifacts: ParsedArtifact[] = [];\n \n // Extract code blocks\n const codeMatches = text.matchAll(/```(\\w+)\\n([\\s\\S]+?)```/g);\n for (const match of codeMatches) {\n artifacts.push({\n content: match[2],\n mimeType: \"application/octet-stream\",\n title: `${match[1]} code`,\n });\n }\n \n return artifacts;\n },\n});\n```\n\n### Post-Completion Artifact Generation\n\n```typescript\nconst executor = new A2AAdapter(agent, {\n mode: \"generate\", // or \"stream\"\n generateArtifacts: async (context) => {\n // Called after response is complete\n const { responseText, messages, task } = context;\n \n // Generate a PNG chart\n const canvas = createCanvas(800, 600);\n const ctx = canvas.getContext(\"2d\");\n // ... draw chart ...\n \n return [{\n content: canvas.toBuffer(\"image/png\").toString(\"base64\"),\n mimeType: \"image/png\",\n title: \"Sales Chart\",\n }];\n },\n});\n```\n\n---\n\n## πŸ”§ Logging\n\n### Built-in Loggers\n\n```typescript\nimport { ConsoleLogger, NoOpLogger } from \"@drew-foxall/a2a-ai-sdk-adapter\";\n\n// Console logging (default)\nconst executor = new A2AAdapter(agent, {\n mode: \"stream\",\n logger: new ConsoleLogger(),\n});\n\n// No logging\nconst executor = new A2AAdapter(agent, {\n mode: \"stream\",\n logger: new NoOpLogger(),\n});\n```\n\n### Custom Logger\n\n```typescript\nimport { A2ALogger } from \"@drew-foxall/a2a-ai-sdk-adapter\";\n\nclass CustomLogger implements A2ALogger {\n debug(message: string, meta?: Record): void {\n // Your implementation\n }\n\n info(message: string, meta?: Record): void {\n // Your implementation\n }\n\n warn(message: string, meta?: Record): void {\n // Your implementation\n }\n\n error(message: string, meta?: Record): void {\n // Your implementation\n }\n}\n\nconst executor = new A2AAdapter(agent, {\n mode: \"stream\",\n logger: new CustomLogger(),\n});\n```\n\n---\n\n## πŸ”„ Conversation History\n\nEnable multi-turn conversations by including message history:\n\n```typescript\nconst executor = new A2AAdapter(agent, {\n mode: \"generate\",\n includeHistory: true, // ← Include previous messages\n});\n```\n\n**Example** (Movie Recommendation Agent):\n```typescript\n// Turn 1: User: \"I want to watch a movie\"\n// Agent: \"What genre do you prefer?\"\n\n// Turn 2: User: \"Sci-fi\"\n// Agent: (has context from Turn 1) \"I recommend Interstellar...\"\n```\n\n---\n\n## 🎭 Custom Task States\n\nBy default, all tasks complete with `state: \"completed\"`. Override for custom workflows:\n\n```typescript\nconst executor = new A2AAdapter(agent, {\n mode: \"generate\",\n parseTaskState: (responseText) => {\n if (responseText.includes(\"NEED_MORE_INFO\")) {\n return \"input-required\";\n }\n if (responseText.includes(\"ERROR\")) {\n return \"failed\";\n }\n return \"completed\";\n },\n includeHistory: true, // Usually needed with custom states\n});\n```\n\n**Valid States**: `\"submitted\" | \"working\" | \"completed\" | \"failed\" | \"canceled\" | \"input-required\"`\n\n---\n\n## πŸ› οΈ Advanced Usage\n\n### Multiple Tool Usage\n\n```typescript\nimport { z } from \"zod\";\n\nconst agent = new ToolLoopAgent({\n model: openai(\"gpt-4o\"),\n instructions: \"You are a weather assistant\",\n tools: {\n getWeather: {\n description: \"Get current weather for a location\",\n parameters: z.object({\n location: z.string().describe(\"City name\"),\n }),\n execute: async ({ location }) => {\n const response = await fetch(`https://wttr.in/${location}?format=j1`);\n return await response.json();\n },\n },\n getForecast: {\n description: \"Get 7-day forecast\",\n parameters: z.object({\n location: z.string(),\n }),\n execute: async ({ location }) => {\n // ... fetch forecast ...\n },\n },\n },\n});\n\nconst executor = new A2AAdapter(agent, {\n mode: \"stream\",\n maxSteps: 10, // Allow multiple tool calls\n});\n```\n\n---\n\n### Multi-Provider Support\n\nWorks with all AI SDK providers:\n\n```typescript\nimport { openai } from \"@ai-sdk/openai\";\nimport { anthropic } from \"@ai-sdk/anthropic\";\nimport { google } from \"@ai-sdk/google\";\n\n// OpenAI\nconst executor1 = new A2AAdapter(\n new ToolLoopAgent({ model: openai(\"gpt-4o\"), ... }),\n { mode: \"stream\" }\n);\n\n// Anthropic\nconst executor2 = new A2AAdapter(\n new ToolLoopAgent({ model: anthropic(\"claude-3-5-sonnet-20241022\"), ... }),\n { mode: \"stream\" }\n);\n\n// Google\nconst executor3 = new A2AAdapter(\n new ToolLoopAgent({ model: google(\"gemini-1.5-pro\"), ... }),\n { mode: \"stream\" }\n);\n```\n\n---\n\n## πŸ§ͺ Testing\n\n### Unit Tests with Vitest\n\n```typescript\nimport { describe, it, expect } from \"vitest\";\nimport { ToolLoopAgent } from \"ai\";\nimport { MockLanguageModelV3 } from \"ai/test\";\nimport { A2AAdapter } from \"@drew-foxall/a2a-ai-sdk-adapter\";\n\ndescribe(\"My Agent\", () => {\n it(\"should respond correctly\", () => {\n const agent = new ToolLoopAgent({\n model: new MockLanguageModelV3({\n doGenerate: async () => ({\n finishReason: \"stop\",\n usage: { inputTokens: 10, outputTokens: 20, totalTokens: 30 },\n content: [{ type: \"text\", text: \"Hello, world!\" }],\n warnings: [],\n }),\n }),\n instructions: \"Test agent\",\n tools: {},\n });\n\n const adapter = new A2AAdapter(agent, {\n mode: \"generate\",\n });\n\n expect(adapter).toBeDefined();\n });\n});\n```\n\n**See**: [Official AI SDK Testing Guide](https://ai-sdk.dev/docs/ai-sdk-core/testing)\n\n---\n\n## πŸ“š Examples\n\nFor complete working examples of agents built with this adapter, see the [a2a-js-sdk-examples repository](https://github.com/drew-foxall/a2a-js-sdk-examples).\n\nExamples include:\n- **Hello World** - Simplest possible agent\n- **Dice Agent** - Tool usage example\n- **GitHub Agent** - External API integration\n- **Analytics Agent** - PNG chart generation with artifacts\n- **Currency Agent** - Real-time data fetching\n- **Movie Agent** - Multi-turn conversations\n- **Coder** - Streaming code generation\n- **Content Editor** - Text processing\n- **Travel Planner** - Multi-agent orchestration\n- **Weather & Airbnb Agents** - MCP integration\n\n---\n\n## πŸ”— Resources\n\n- **[GitHub Repository](https://github.com/drew-foxall/a2a-js-sdk-examples)** - Source code and examples\n- **[AI SDK Documentation](https://ai-sdk.dev/)** - Vercel AI SDK docs\n- **[A2A Protocol](https://a2a-protocol.org/)** - Agent2Agent protocol specification\n- **[@drew-foxall/a2a-js-sdk](https://github.com/drew-foxall/a2a-js-sdk)** - A2A JavaScript SDK with Hono support\n\n---\n\n## 🀝 Contributing\n\nContributions welcome! Please see the [GitHub repository](https://github.com/drew-foxall/a2a-js-sdk-examples) for contribution guidelines.\n\n---\n\n## πŸ“„ License\n\nApache 2.0 - See [LICENSE](LICENSE) for details\n\n---\n\n## πŸ™ Acknowledgments\n\n- **[Vercel AI SDK](https://ai-sdk.dev/)** - Foundation for agent logic\n- **[A2A Project](https://a2a-protocol.org/)** - Agent2Agent protocol\n- **[@drew-foxall/a2a-js-sdk](https://github.com/drew-foxall/a2a-js-sdk)** - A2A JavaScript SDK\n\n---\n\n---\n\n## πŸ”„ Durable Workflows (DurableA2AAdapter)\n\nFor agents that need durability (automatic retry, result caching, observability), use `DurableA2AAdapter`:\n\n```typescript\nimport { DurableA2AAdapter } from \"@drew-foxall/a2a-ai-sdk-adapter/durable\";\nimport { diceAgentWorkflow } from \"a2a-agents\";\n\n// Wrap a durable workflow for A2A protocol\nconst executor = new DurableA2AAdapter(diceAgentWorkflow, {\n});\n\n// For workflows with additional arguments:\nconst imageExecutor = new DurableA2AAdapter(imageGeneratorWorkflow, {\n workflowArgs: [env.OPENAI_API_KEY], // Additional args after messages\n});\n```\n\n### How Durability Works\n\nThe durability stack consists of three layers working together:\n\n```\nβ”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”\nβ”‚ DurableA2AAdapter β”‚\nβ”‚ Bridges A2A protocol with Workflow DevKit via start() β”‚\nβ””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜\n β”‚ calls start()\n β–Ό\nβ”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”\nβ”‚ Workflow DevKit Runtime β”‚\nβ”‚ - start() creates run in World, queues workflow execution β”‚\nβ”‚ - \"use workflow\" and \"use step\" directives (SWC transform) β”‚\nβ”‚ - getWritable() for streaming output β”‚\nβ””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜\n β”‚ persists to\n β–Ό\nβ”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”\nβ”‚ World (Persistence) β”‚\nβ”‚ - @drew-foxall/upstash-workflow-world (Cloudflare Workers) β”‚\nβ”‚ - @workflow/world-vercel (Vercel) β”‚\nβ”‚ - @workflow/world-local (local dev) β”‚\nβ””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜\n β”‚ uses\n β–Ό\nβ”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”\nβ”‚ @drew-foxall/workflow-ai β”‚\nβ”‚ - DurableAgent: AI SDK integration with \"use step\" internally β”‚\nβ”‚ - Must run inside a workflow context β”‚\nβ””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜\n```\n\n**Key Insight:** Calling a workflow function directly does NOT provide durability. The workflow MUST be invoked via `start()` from `workflow/api`, which triggers the World's persistence mechanisms.\n\n### DurableA2AAdapter Configuration\n\n| Option | Type | Required | Description |\n|--------|------|----------|-------------|\n| `workflowArgs` | `TArgs` | No | Additional arguments to pass to the workflow (after messages) |\n| `includeHistory` | `boolean` | No | Include conversation history (default: false) |\n| `parseTaskState` | `(text: string) => TaskState` | No | Custom task state parser |\n| `generateArtifacts` | `(context) => Promise` | No | Generate artifacts after completion |\n| `debug` | `boolean` | No | Enable debug logging (default: false) |\n| `logger` | `Logger` | No | Custom logger implementation |\n\n### When to Use DurableA2AAdapter\n\n| Use DurableA2AAdapter When | Use A2AAdapter When |\n|---------------------------|---------------------|\n| Operations take >30 seconds | Quick responses |\n| Expensive API calls (avoid duplicates) | Cheap/free operations |\n| Multi-step coordination | Single operation |\n| Need observability traces | Simple debugging |\n| Operations must survive restarts | Stateless operations |\n\n---\n\n**Built with πŸ€– by Drew Foxall**\n","readmeFilename":"README.md"}