SDK Quickstart

Installation

Python

pip install njiraai

TypeScript / JavaScript

npm install @njiraai/sdk

Quick Start

Python

from njiraai import NjiraAI

# Initialize the SDK
njira = NjiraAI(
    api_key="your-api-key",
    project_id="your-project-id",
    mode="active",  # or 'shadow', 'dry_run'
)

# Enforce before LLM call
pre_decision = await njira.enforce_pre(
    input_data=user_message,
    metadata={"endpoint": "/chat"},
)

if pre_decision["verdict"] == "block":
    raise RuntimeError("Blocked by policy")

# Trace LLM call
span_id = njira.start_span(
    name="llm-call",
    span_type="llm",
    input_data=prompt,
)

response = await call_llm(prompt)
njira.end_span(span_id, output=response)

# Enforce after LLM call
post_decision = await njira.enforce_post(output=response)
if post_decision["verdict"] == "block":
    raise RuntimeError("Output blocked")

TypeScript

import { NjiraAI } from "@njiraai/sdk";

// Initialize the SDK
const njira = new NjiraAI({
  apiKey: process.env.NJIRA_API_KEY!,
  projectId: process.env.NJIRA_PROJECT_ID!,
  mode: "active", // or 'shadow', 'dry_run'
});

// Enforce before LLM call
const preDecision = await njira.enforcePre({
  input: userMessage,
  metadata: { endpoint: "/chat" },
});

if (preDecision.verdict === "block") {
  throw new Error("Blocked by policy");
}

// Trace LLM call
const spanId = njira.trace.startSpan({
  name: "llm-call",
  type: "llm",
  input: prompt,
});

const response = await callLLM(prompt);
njira.trace.endSpan(spanId, { output: response });

// Enforce after LLM call
const postDecision = await njira.enforcePost({ output: response });
if (postDecision.verdict === "block") {
  throw new Error("Output blocked");
}

Framework Integrations

LangChain (Python)

from njiraai import NjiraAI
from njiraai_langchain import NjiraCallbackHandler

njira = NjiraAI(api_key="...", project_id="...")
handler = NjiraCallbackHandler(njira)

llm.invoke("Hello", config={"callbacks": [handler]})

LangChain.js (TypeScript)

import { NjiraAI } from "@njiraai/sdk";
import { NjiraCallbackHandler } from "@njiraai/langchain";

const njira = new NjiraAI({ apiKey: "...", projectId: "..." });
const handler = new NjiraCallbackHandler(njira);

await llm.invoke("Hello", { callbacks: [handler] });

CrewAI (Python)

from njiraai import NjiraAI
from njiraai_crewai import NjiraToolHooks

njira = NjiraAI(api_key="...", project_id="...")
hooks = NjiraToolHooks(njira)

# Attach hooks to your crew/agent tooling
# Hooks provide before_tool_call and after_tool_call methods

Web Framework Middleware

FastAPI (Python)

from fastapi import FastAPI
from njiraai.middleware import create_middleware

app = FastAPI()
app.add_middleware(create_middleware(njira))

Express (TypeScript)

import express from "express";

const app = express();
app.use(njira.middleware.express());

Next.js (TypeScript)

export const POST = njira.nextRoute(async (request: Request) => {
  const { message } = await request.json();
  const decision = await njira.enforcePre({ input: message });
  return Response.json({ ok: true });
});

Modes

• shadow: compute decisions but never block (perfect for testing)
• active: enforce blocks and modifications
• dry_run: no network calls, local allow decisions