@raindrop-ai/ai-sdk

Standalone Vercel AI SDK integration for Raindrop:

• Events: sends a track_partial payload to POST /v1/events/track_partial when the model finishes
• Standalone traces: ships spans directly to POST /v1/traces as OTLP/HTTP JSON
• No OpenTelemetry SDK init: avoids global OTEL registration conflicts

Install

yarn add @raindrop-ai/ai-sdk

Usage

import * as ai from "ai";
import { createRaindropAISDK } from "@raindrop-ai/ai-sdk";

const raindrop = createRaindropAISDK({
  writeKey: process.env.RAINDROP_WRITE_KEY!,
});

const { generateText } = raindrop.wrap(ai, {
  context: { userId: "user_123", convoId: "convo_456", eventName: "chat_message" },
  // optional: full control over event input/output, metadata, and attachments
  buildEvent: (messages) => {
    const lastUser = [...messages].reverse().find((m) => m.role === "user");
    const lastAssistant = [...messages].reverse().find((m) => m.role === "assistant");
    return {
      input: typeof lastUser?.content === "string" ? lastUser.content : undefined,
      output: typeof lastAssistant?.content === "string" ? lastAssistant.content : undefined,
    };
  },
});

const result = await generateText({
  model: /* your AI SDK model */,
  prompt: "Hello!",
});

// Identify a user (optional)
await raindrop.users.identify({
  userId: "user_123",
  traits: { plan: "pro" },
});

await raindrop.flush();

Runtime support

Node.js (recommended)

Use the default import:

import { createRaindropAISDK } from "@raindrop-ai/ai-sdk";

Cloudflare Workers

Cloudflare Workers can provide AsyncLocalStorage via node:async_hooks when nodejs_compat is enabled (docs).

Use the Workers entrypoint:

import { createRaindropAISDK } from "@raindrop-ai/ai-sdk/workers";

If nodejs_compat is not enabled, AsyncLocalStorage-based context propagation cannot work.

Supported AI SDK Versions

This package is tested against multiple Vercel AI SDK versions:

| Version | Status | |---------|--------| | v4.x | ✅ Supported | | v5.x | ✅ Supported | | v6.x | ✅ Supported |

Version Differences Handled

| Feature | v4 | v5 | v6 | |---------|----|----|-----| | finishReason | String ("stop") | String ("stop") | Object ({ unified: "stop" }) | | usage tokens | promptTokens/completionTokens | inputTokens/outputTokens | inputTokens/outputTokens | | Output.object().responseFormat | N/A | Plain object | Promise |

Testing

Tests are organized to verify compatibility across AI SDK versions:

packages/ai-sdk/
├── tests/
│   ├── v4/                 # AI SDK v4 (pins ai@^4.1.17)
│   │   ├── ai-sdk.v4.test.ts
│   │   ├── wrapper.test.ts
│   │   └── http-payloads.test.ts
│   ├── v5/                 # AI SDK v5 (pins ai@^5.0.0)
│   │   ├── ai-sdk.v5.test.ts
│   │   ├── wrapper.test.ts
│   │   └── http-payloads.test.ts
│   └── v6/                 # AI SDK v6 (pins ai@^6.0.0)
│       ├── ai-sdk.v6.test.ts
│       ├── wrapper.test.ts
│       └── http-payloads.test.ts

Running Tests

# Run all version tests (requires OPENAI_API_KEY and RAINDROP_WRITE_KEY in .env)
yarn test

# Run specific version
yarn test:v4
yarn test:v5
yarn test:v6

# Quick smoke test (real LLM calls, single version)
yarn smoke:min

Test Coverage

Each version runs:

• Wrapper tests - API shape, wrapper creation, tools passthrough
• HTTP payload tests - MSW-based payload validation for each spec version
• Version-specific tests - API differences (finishReason format, usage naming)

Notes

• Spans include ai.telemetry.metadata.raindrop.eventId for correlation, and omit ai.telemetry.metadata.raindrop.userId to prevent duplicate span→event creation server-side.