OpenAI Agents SDK (Beta)

npm install @raindrop-ai/openai-agents @openai/agents

pnpm add @raindrop-ai/openai-agents @openai/agents

pip install raindrop-openai-agents openai-agents

import { createRaindropOpenAIAgents } from "@raindrop-ai/openai-agents";
import { Agent, run, addTraceProcessor } from "@openai/agents";

const raindrop = createRaindropOpenAIAgents({
  writeKey: "your-write-key",
  userId: "user-123",
});

addTraceProcessor(raindrop.processor);

const agent = new Agent({
  name: "Assistant",
  model: "gpt-4o",
  instructions: "Be helpful",
});

const result = await run(agent, "What is the capital of France?");
console.log(result.finalOutput);

await raindrop.flush();

from raindrop_openai_agents import create_raindrop_openai_agents
from agents import Agent, Runner

raindrop = create_raindrop_openai_agents(
    api_key="your-write-key",
    user_id="user-123",
)
# Processor is auto-registered — no extra setup needed

agent = Agent(name="Assistant", model="gpt-4o", instructions="Be helpful")

result = Runner.run_sync(agent, "What is the capital of France?")
print(result.final_output)

raindrop.flush()

const raindrop = createRaindropOpenAIAgents({
  writeKey: "your-write-key",       // Optional: your Raindrop write key (omit to disable telemetry)
  endpoint: "...",          // Optional: custom API endpoint
  userId: "user-123",      // Optional: associate events with a user
  convoId: "convo-456",    // Optional: conversation/thread ID
  projectId: "support-prod", // Optional: route events to a specific project (slug)
  debug: false,             // Optional: enable verbose logging
});

from raindrop_openai_agents import RaindropOpenAIAgents

raindrop = RaindropOpenAIAgents(
    api_key="your-write-key",           # Optional: omit to disable telemetry
    user_id="user-123",                 # Optional: associate events with a user
    convo_id="convo-456",               # Optional: conversation/thread ID
    project_id="support-prod",          # Optional: route events to a specific project (slug)
    tracing_enabled=True,               # Optional: enable OTEL-based tracing (default True)
    bypass_otel_for_tools=True,         # Optional: bypass OTEL for tool calls (default True)
    debug=False,                        # Optional: enable verbose logging
)

const raindrop = createRaindropOpenAIAgents({
  writeKey: "your-write-key",
  projectId: "support-prod",
});

raindrop = RaindropOpenAIAgents(
    api_key="your-write-key",
    project_id="support-prod",
)

raindrop.users.identify({ userId: "user-42", traits: { plan: "pro", company: "Acme" } });

raindrop.identify("user-42", traits={"plan": "pro", "company": "Acme"})

raindrop.signals.track({
  eventId: "evt_abc123",
  name: "thumbs_up",
  type: "feedback",
  sentiment: "POSITIVE",
  comment: "Great answer!",
});

raindrop.track_signal(
    event_id="evt_abc123",
    name="thumbs_up",
    signal_type="feedback",
    sentiment="POSITIVE",
    comment="Great answer!",
)

const triage = new Agent({
  name: "Triage",
  model: "gpt-4o-mini",
  instructions: "Route to the appropriate specialist.",
  handoffs: [specialist],
});

const result = await run(triage, "I need help with billing");
await raindrop.flush();

triage = Agent(
    name="Triage",
    model="gpt-4o-mini",
    instructions="Route to the appropriate specialist.",
    handoffs=[specialist],
)

result = Runner.run_sync(triage, "I need help with billing")
raindrop.flush()

await raindrop.flush();     // flush pending data
await raindrop.shutdown();  // flush + release resources

raindrop.flush()     # flush pending data
raindrop.shutdown()  # flush + release resources