Agent Integration

import OpenAI from "openai";
import { DriftGateClient } from "@driftgate/sdk";
 
const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY! });
const driftgate = new DriftGateClient({
  sessionToken: process.env.DRIFTGATE_SESSION_TOKEN!,
  baseUrl: "https://api-staging.driftgate.ai"
});
 
const session = await driftgate.session.start({ agent: "support-agent" });
const execution = await session.execute({
  input: { prompt: "Summarize refund policy for order #123" }
});
 
if (execution.error) throw new Error(execution.error.code);
 
const response = await openai.responses.create({
  model: "gpt-4.1-mini",
  input: [
    { role: "system", content: "Use the governance payload as ground truth." },
    { role: "user", content: JSON.stringify(execution.data) }
  ]
});
 
console.log(response.output_text);

import { DriftGateClient } from "@driftgate/sdk";
import { ChatOpenAI } from "@langchain/openai";
 
const dg = new DriftGateClient({ sessionToken: process.env.DRIFTGATE_SESSION_TOKEN! });
const llm = new ChatOpenAI({ model: "gpt-4.1-mini" });
 
const session = await dg.session.start({ agent: "claims-agent" });
const gated = await session.execute({ input: { claimId: "C-42" } });
 
if (gated.error) throw new Error(gated.error.code);
 
const answer = await llm.invoke([
  ["system", "Answer only with approved details from payload."],
  ["human", JSON.stringify(gated.data)]
]);
 
console.log(answer.content);

from driftgate_sdk import DriftGateClient
from langgraph.graph import StateGraph
 
client = DriftGateClient(
    bearer_token="${DRIFTGATE_SESSION_TOKEN}",
    base_url="https://api-staging.driftgate.ai",
)
 
def gate_node(state: dict) -> dict:
    session = client.session.start(agent="review-agent")
    result = session.execute(input=state["input"])
    if result.get("error"):
        raise RuntimeError(result["error"]["code"])
    state["driftgate"] = result["data"]
    return state
 
graph = StateGraph(dict)
graph.add_node("gate", gate_node)
graph.set_entry_point("gate")
app = graph.compile()
 
print(app.invoke({"input": {"ticket_id": "T-100"}}))

{
  "data": {
    "executionId": "exec_123",
    "decision": "allow",
    "result": {
      "summary": "..."
    }
  },
  "meta": {
    "requestId": "req_123",
    "timingMs": {
      "total": 128
    }
  },
  "error": null
}