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Build multi-agent AI systems with automatic persistence, resumable streaming, and real-time sync.\n\n## Features\n\n- **All AriaFlow Agent Types**: LLM, Flow, Triage, and Composite agents\n- **Automatic Persistence**: Messages stored in SQLite, survive restarts\n- **Resumable Streaming**: Reconnect without data loss\n- **Multi-Client Sync**: Real-time updates across all connected clients\n- **Full Tool Support**: Server-side, client-side, and approval tools\n- **Zero Config**: Works out of the box with sensible defaults\n\n## Quick Start\n\n```bash\n# Create a new project\nmkdir my-agent && cd my-agent\nnpm init -y\n\n# Install dependencies\nnpm install @ariaflowagents/cf-agent ai zod\nnpm install -D @cloudflare/vite-plugin vite wrangler\n\n# Create your agent\n# See examples below...\n\n# Run locally\nnpm run dev\n```\n\nOpen http://localhost:5173 to see your agent in action.\n\n## Installation\n\n```bash\nnpm install @ariaflowagents/cf-agent\n```\n\n## Project Structure\n\n```\nmy-agent/\n├── src/\n│   ├── server.ts          # Agent implementation\n│   ├── app.tsx            # React chat UI\n│   └── client.tsx         # React entry point\n├── package.json\n├── tsconfig.json\n├── vite.config.ts\n└── wrangler.jsonc\n```\n\n## Basic Example\n\n### 1. Create Agent (`src/server.ts`)\n\n```typescript\nimport { AriaFlowAIChatAgent } from \"@ariaflowagents/cf-agent\";\nimport { createOpenAI } from \"@ai-sdk/openai\";\nimport { tool } from \"ai\";\nimport { z } from \"zod\";\n\ninterface Env {\n  OPENAI_API_KEY: string;\n}\n\nexport class MyAgent extends AriaFlowAIChatAgent<Env> {\n  protected getRuntimeConfig() {\n    const openai = createOpenAI({ apiKey: this.env.OPENAI_API_KEY });\n\n    return {\n      agents: [{\n        id: \"assistant\",\n        type: \"llm\" as const,\n        name: \"Assistant\",\n        model: openai(\"gpt-4o\"),\n        prompt: \"You are a helpful assistant\",\n        tools: {\n          getWeather: tool({\n            description: \"Get weather for a city\",\n            inputSchema: z.object({ city: z.string() }),\n            execute: async ({ city }) => {\n              return { temperature: 72, condition: \"sunny\" };\n            },\n          }),\n        },\n      }],\n      defaultAgentId: \"assistant\",\n    };\n  }\n}\n\nexport default MyAgent;\n```\n\n### 2. Create UI (`src/app.tsx`)\n\n```tsx\nimport { useAgent } from \"agents/react\";\nimport { useAgentChat } from \"@cloudflare/ai-chat/react\";\n\nexport function Chat() {\n  const agent = useAgent({ agent: \"MyAgent\" });\n  const { messages, sendMessage, status } = useAgentChat({ agent });\n\n  return (\n    <div>\n      {messages.map((msg) => (\n        <div key={msg.id}>\n          <strong>{msg.role}:</strong>\n          {msg.parts.map((part, i) =>\n            part.type === \"text\" ? <span key={i}>{part.text}</span> : null\n          )}\n        </div>\n      ))}\n      <form onSubmit={(e) => {\n        e.preventDefault();\n        const input = e.currentTarget.elements.namedItem(\"input\") as HTMLInputElement;\n        sendMessage({ text: input.value });\n        input.value = \"\";\n      }}>\n        <input name=\"input\" placeholder=\"Type a message...\" />\n        <button type=\"submit\" disabled={status === \"streaming\"}>Send</button>\n      </form>\n    </div>\n  );\n}\n```\n\n### 3. Configuration Files\n\n**`vite.config.ts`**:\n```typescript\nimport { defineConfig } from \"vite\";\nimport { cloudflare } from \"@cloudflare/vite-plugin\";\nimport react from \"@vitejs/plugin-react\";\n\nexport default defineConfig({\n  plugins: [cloudflare(), react()],\n});\n```\n\n**`wrangler.jsonc`**:\n```json\n{\n  \"name\": \"my-agent\",\n  \"main\": \"src/server.ts\",\n  \"compatibility_date\": \"2026-01-28\",\n  \"compatibility_flags\": [\"nodejs_compat\"],\n  \"ai\": { \"binding\": \"AI\" },\n  \"durable_objects\": {\n    \"bindings\": [{ \"name\": \"MyAgent\", \"class_name\": \"MyAgent\" }]\n  },\n  \"migrations\": [{ \"tag\": \"v1\", \"new_sqlite_classes\": [\"MyAgent\"] }]\n}\n```\n\n**`package.json`** scripts:\n```json\n{\n  \"scripts\": {\n    \"dev\": \"vite dev\",\n    \"deploy\": \"vite build && wrangler deploy\",\n    \"types\": \"wrangler types\"\n  }\n}\n```\n\n## Agent Types\n\n### LLMAgent\n\nStandard conversational agent with tools:\n\n```typescript\n{\n  id: \"sales\",\n  type: \"llm\" as const,\n  name: \"Sales Agent\",\n  model: openai(\"gpt-4o\"),\n  prompt: \"You are a sales specialist...\",\n  tools: { /* ... */ },\n  canHandoffTo: [\"support\", \"billing\"]\n}\n```\n\n### FlowAgent\n\nStructured node-based conversation flows:\n\n```typescript\n{\n  id: \"order-flow\",\n  type: \"flow\" as const,\n  name: \"Order Flow\",\n  model: openai(\"gpt-4o\"),\n  flow: {\n    nodes: [\n      { \n        id: \"initial\", \n        task: \"Ask what they want\",\n        transitions: [{ to: \"confirm\", on: \"product_selected\" }]\n      },\n      { \n        id: \"confirm\", \n        task: \"Confirm order\",\n        transitions: [{ to: \"end\", on: \"confirmed\" }]\n      }\n    ],\n    hybrid: true // Allow off-flow questions\n  }\n}\n```\n\n### TriageAgent\n\nIntelligent routing between agents:\n\n```typescript\n{\n  id: \"router\",\n  type: \"triage\" as const,\n  name: \"Router\",\n  model: openai(\"gpt-4o-mini\"),\n  routingConfig: {\n    agents: [\"sales\", \"support\", \"billing\"],\n    instructions: \"Route based on user intent...\"\n  }\n}\n```\n\n### CompositeAgent\n\nMulti-agent coordination:\n\n```typescript\n{\n  id: \"supervisor\",\n  type: \"composite\" as const,\n  name: \"Supervisor\",\n  model: openai(\"gpt-4o\"),\n  agents: [\"researcher\", \"analyst\", \"writer\"],\n  coordinationMode: \"sequential\"\n}\n```\n\n## Tools\n\n### Server-Side Tools\n\nRun automatically on the server:\n\n```typescript\ntools: {\n  getWeather: tool({\n    description: \"Get weather for a city\",\n    inputSchema: z.object({ city: z.string() }),\n    execute: async ({ city }) => {\n      // Runs on server\n      return await fetchWeather(city);\n    }\n  })\n}\n```\n\n### Client-Side Tools\n\nNo `execute` function - browser provides the result:\n\n```typescript\n// Server\ntools: {\n  getLocation: tool({\n    description: \"Get user location\",\n    inputSchema: z.object({})\n    // No execute - client handles it\n  })\n}\n\n// Client\nuseAgentChat({\n  onToolCall: async ({ toolCall, addToolOutput }) => {\n    if (toolCall.toolName === \"getLocation\") {\n      const pos = await navigator.geolocation.getCurrentPosition();\n      addToolOutput({\n        toolCallId: toolCall.toolCallId,\n        output: { lat: pos.coords.latitude, lng: pos.coords.longitude }\n      });\n    }\n  }\n});\n```\n\n### Approval Tools\n\nHuman-in-the-loop for sensitive operations:\n\n```typescript\ntools: {\n  processRefund: tool({\n    description: \"Process a refund\",\n    inputSchema: z.object({ orderId: z.string(), amount: z.number() }),\n    needsApproval: ({ amount }) => amount > 100,\n    execute: async ({ orderId, amount }) => {\n      // Only runs after user approval\n      return await processRefund(orderId, amount);\n    }\n  })\n}\n```\n\n## Hooks\n\nReact to agent lifecycle events:\n\n```typescript\nprotected getHooks() {\n  return {\n    onHandoff: async (context, from, to, reason) => {\n      console.log(`Handoff: ${from} -> ${to} (${reason})`);\n    },\n    \n    onToolCall: async (context, toolCall) => {\n      console.log(`Tool: ${toolCall.toolName}`);\n    },\n    \n    onNodeEnter: async (context, node) => {\n      console.log(`Flow node: ${node.name}`);\n    }\n  };\n}\n```\n\n## State Persistence\n\nAriaFlow stores two types of data:\n\n1. **CF Tables** (`cf_ai_chat_*`): Chat messages, stream chunks, resumption data\n2. **AriaFlow Tables** (`ariaflow_sessions`): Session state, working memory, flow state\n\n```\nSQLite Database:\n├── cf_ai_chat_agent_messages  (UIMessages for UI)\n├── cf_ai_chat_stream_chunks   (Stream chunks)\n├── cf_ai_chat_stream_metadata (Stream state)\n└── ariaflow_sessions          (AriaFlow Session state)\n```\n\n## Custom Configuration\n\n### Stream Adapter\n\nControl which events are sent to the client:\n\n```typescript\nprotected getStreamAdapterConfig() {\n  return {\n    includeHandoffs: true,    // Show agent handoffs in UI\n    includeFlowEvents: true,  // Show flow node transitions\n    includeTripwires: true,   // Show guardrail triggers\n    includeStepEvents: false, // Hide step lifecycle\n    includeAgentEvents: false // Hide agent lifecycle\n  };\n}\n```\n\n### Session ID\n\nOverride default session ID generation:\n\n```typescript\nprotected getSessionId(): string {\n  // Default uses Durable Object ID\n  // Override for custom session management\n  return `user-${this.getUserId()}`;\n}\n```\n\n## Scripts\n\n```bash\n# Development (with hot reload)\nnpm run dev\n\n# Deploy to Cloudflare\nnpm run deploy\n\n# Generate types\nnpm run types\n\n# Build only\nnpm run build\n```\n\n## Using Different AI Providers\n\n### Workers AI (No API key needed)\n\n```typescript\nimport { createWorkersAI } from \"workers-ai-provider\";\n\nconst workersai = createWorkersAI({ binding: this.env.AI });\n\n// In agent config:\nmodel: workersai(\"@cf/meta/llama-3.3-70b-instruct-fp8-fast\")\n```\n\n### OpenAI\n\n```bash\nnpm install @ai-sdk/openai\n```\n\n```typescript\nimport { createOpenAI } from \"@ai-sdk/openai\";\n\nconst openai = createOpenAI({ apiKey: this.env.OPENAI_API_KEY });\n\n// In agent config:\nmodel: openai(\"gpt-4o\")\n```\n\n### Anthropic\n\n```bash\nnpm install @ai-sdk/anthropic\n```\n\n```typescript\nimport { createAnthropic } from \"@ai-sdk/anthropic\";\n\nconst anthropic = createAnthropic({ apiKey: this.env.ANTHROPIC_API_KEY });\n\n// In agent config:\nmodel: anthropic(\"claude-sonnet-4-20250514\")\n```\n\n## API Reference\n\n### AriaFlowAIChatAgent\n\nAbstract base class extending CF's `AIChatAgent`.\n\n```typescript\nabstract class AriaFlowAIChatAgent<Env, State> {\n  // Required\n  protected abstract getRuntimeConfig(): HarnessConfig;\n  \n  // Optional overrides\n  protected getHooks(): Partial<HarnessHooks>;\n  protected getStreamAdapterConfig(): Partial<StreamAdapterConfig>;\n  protected getSessionId(): string;\n  \n  // Utility methods\n  protected async getSession(): Promise<Session | null>;\n  protected getSessionStats(): SessionStats | null;\n}\n```\n\n### Environment Variables\n\n```bash\n# For OpenAI\nOPENAI_API_KEY=your-key\n\n# For Anthropic\nANTHROPIC_API_KEY=your-key\n\n# For custom providers\nPROVIDER_API_KEY=your-key\n```\n\n## Architecture\n\n```\nClient (useAgentChat)\n    │\n    ▼ WebSocket\nCF AIChatAgent (Durable Object)\n    ├─► CF SQLite: Chat messages, stream chunks\n    └─► AriaFlow Runtime\n        ├─► CloudflareSessionStore (SQLite)\n        ├─► Multi-agent execution\n        └─► StreamAdapter\n            └─► UIMessageChunk format\n```\n\n## Realtime Voice Reconnect Contract\n\n`withRealtimeVoice` (RFC-05) runs on two orthogonal WebSocket edges and each has its own reconnect model:\n\n| Edge | Owner | Reconnect strategy |\n|---|---|---|\n| Browser ↔ Durable Object | **Client** | Built in — `useVoiceAgent` / `partysocket` handles it transparently. DO is keyed by path; reconnecting to the same path wakes the same session (hibernation-aware). |\n| Durable Object ↔ Gemini Live | **Server** (this mixin) | On `goAway`, re-opens the provider WS using the persisted resumption handle. Full-jitter exponential backoff: 500ms base, 8s cap, 3 attempts. |\n\nDuring a server-side reconnect (handle-based re-open on `goAway`) the mixin sends `{type:\"reconnecting\", reason:\"goAway\"}` on entry and `{type:\"reconnected\"}` on success. Inbound PCM frames from the client are buffered in a per-connection ring (default 48KB ≈ 1.5s @ 16kHz mono PCM16) and drained to the new provider session after reconnect. Oldest frames drop when the cap is exceeded; a warning logs the dropped byte count.\n\n**Resumption handle semantics.** Gemini Live handles are single-use and expire after 2 hours of session inactivity. The mixin's `cf_realtime_resumption` SQLite table tracks `used_at` and `updated_at`; a handle is refused if already consumed (`{type:\"error\", code:\"resumption_consumed\"}`) or expired (`{type:\"error\", code:\"resumption_expired\"}`). Successful reconnect drains the audio buffer; exhausted retries send `{type:\"error\", code:\"reconnect_exhausted\"}` and tear down the session.\n\n**Writing a custom browser client.** If you bypass `useVoiceAgent` and open the WS yourself, implement reconnect with exponential backoff and a 10-second floor (per Cloudflare's own `workers-chat-demo` precedent). The DO is the source of truth — on reconnect, simply re-open the WS to the same path; the mixin hydrates the Gemini session from SQLite transparently. **Do NOT layer retry on top of `useVoiceAgent`** — it already reconnects via `partysocket` and stacking will produce overlapping provider sessions and double-consume resumption handles.\n\nTunables (pass to `withRealtimeVoice` or `AriaFlowRealtimeVoiceAgent.voiceOptions`):\n\n```ts\n{\n  reconnectOnGoAway:         true,     // auto-reconnect when timeLeft < threshold\n  reconnectThresholdMs:      2000,\n  reconnectMaxAttempts:      3,\n  reconnectBaseDelayMs:      500,      // full-jitter: delay ∈ [0, min(cap, base * 2^attempt)]\n  reconnectCapDelayMs:       8000,\n  reconnectAudioBufferBytes: 48_000,   // ring buffer for user PCM during reconnect\n}\n```\n\n## Learn More\n\n- [AriaFlow Documentation](https://github.com/ariaflowagents/ariaflow)\n- [Cloudflare Agents SDK](https://developers.cloudflare.com/agents/)\n- [Vercel AI SDK](https://ai-sdk.dev)\n\n## License\n\nMIT\n","readmeFilename":"README.md"}