Memory for LangChain and LangGraph.js.

pip install 'niadra[langchain]'   # langchain-core 1.6 or newer, below 2

"""An LCEL chain with the customer's context and the history tools."""

from langchain_core.prompts import ChatPromptTemplate
from langchain_openai import ChatOpenAI

from niadra import Niadra, phone
from niadra.integrations.langchain import NiadraCallbackHandler, context_runnable, history_tools

niadra = Niadra(channel="chat")
prompt = ChatPromptTemplate.from_messages([("system", "You are Acme's agent."), ("human", "{question}")])

with niadra.conversation("thread-81", subject=phone("+5511912345678")) as conversation:
    model = ChatOpenAI(model="gpt-4.1").bind_tools(history_tools(conversation))
    chain = prompt | context_runnable(conversation) | model
    reply = chain.invoke(
        {"question": "Where is my replacement lid?"},
        config={"callbacks": [NiadraCallbackHandler(conversation)]},
    )
    print(reply.content)

npm install @niadra/sdk @langchain/core   # @langchain/core 1.x, as an optional peer dependency

// A LangGraph.js agent: the context goes into the model call inside the node (never into the
// graph's state), the history tools run through ToolNode, and the callback records the answers.
import { HumanMessage, SystemMessage } from "@langchain/core/messages";
import { END, MessagesAnnotation, START, StateGraph } from "@langchain/langgraph";
import { ToolNode, toolsCondition } from "@langchain/langgraph/prebuilt";
import { ChatOpenAI } from "@langchain/openai";
import { Niadra, handles } from "@niadra/sdk";
import { NiadraCallbackHandler, niadraTools, withNiadraContext } from "@niadra/sdk/langchain";

const niadra = new Niadra();

/** One customer message in; `userId` comes from your session, never from the model. */
export async function reply(userId: string, threadId: string, text: string): Promise<string> {
  const convo = niadra.conversation({ subject: handles.appUserId(userId), channel: "web_chat", conversation_id: threadId });
  const tools = niadraTools(convo);
  const model = new ChatOpenAI({ model: "gpt-4.1" }).bindTools(tools);

  const graph = new StateGraph(MessagesAnnotation)
    .addNode("agent", async (state) => ({ messages: [await model.invoke(await withNiadraContext(convo, state.messages))] }))
    .addNode("tools", new ToolNode(tools))
    .addEdge(START, "agent")
    .addConditionalEdges("agent", toolsCondition, ["tools", END])
    .addEdge("tools", "agent")
    .compile();

  const result = await graph.invoke(
    { messages: [new SystemMessage("You are Acme's support agent. Be brief."), new HumanMessage(text)] },
    { callbacks: [new NiadraCallbackHandler(convo)] },
  );
  return result.messages.at(-1)?.text ?? "";
}