This package contains the LangChain.js integrations for xAI.
npm install @langchain/xai @langchain/core
This package adds support for xAI chat model inference.
Set the necessary environment variable (or pass it in via the constructor):
export XAI_API_KEY=
import { ChatXAI } from "@langchain/xai";
import { HumanMessage } from "@langchain/core/messages";
const model = new ChatXAI({
apiKey: process.env.XAI_API_KEY, // Default value.
});
const message = new HumanMessage("What color is the sky?");
const res = await model.invoke([message]);
xAI supports server-side tools that are executed by the API rather than requiring client-side execution. The live_search tool enables the model to search the web for real-time information.
import { ChatXAI, tools } from "@langchain/xai";
const model = new ChatXAI({
model: "grok-2-1212",
});
// Create the built-in live_search tool with optional parameters
const searchTool = tools.xaiLiveSearch({
maxSearchResults: 5,
returnCitations: true,
});
// Bind the live_search tool to the model
const modelWithSearch = model.bindTools([searchTool]);
// The model will search the web for real-time information
const result = await modelWithSearch.invoke(
"What happened in tech news today?"
);
console.log(result.content);
import { ChatXAI } from "@langchain/xai";
const model = new ChatXAI({
model: "grok-2-1212",
searchParameters: {
mode: "auto", // "auto" | "on" | "off"
max_search_results: 5,
from_date: "2024-01-01", // ISO date string
return_citations: true,
},
});
const result = await model.invoke("What are the latest AI developments?");
const result = await model.invoke("Find recent news about SpaceX", {
searchParameters: {
mode: "on",
max_search_results: 10,
sources: [
{
type: "web",
allowed_websites: ["spacex.com", "nasa.gov"],
},
],
},
});
sourcesYou can configure which data sources Live Search should use via the sources field
in searchParameters. Each entry corresponds to one of the sources described in the
official xAI Live Search docs (web, news, x, rss).
const result = await model.invoke(
"What are the latest updates from xAI and related news?",
{
searchParameters: {
mode: "on",
sources: [
{
type: "web",
// Only search on these websites
allowed_websites: ["x.ai"],
},
{
type: "news",
// Exclude specific news websites
excluded_websites: ["bbc.co.uk"],
},
{
type: "x",
// Focus on specific X handles
included_x_handles: ["xai"],
},
],
},
}
);
You can also use RSS feeds as a data source:
const result = await model.invoke("Summarize the latest posts from this feed", {
searchParameters: {
mode: "on",
sources: [
{
type: "rss",
links: ["https://example.com/feed.rss"],
},
],
},
});
Notes:
- The
xaiLiveSearchtool options use camelCase field names in TypeScript (for examplemaxSearchResults,fromDate,returnCitations,allowedWebsites,excludedWebsites,includedXHandles). These are automatically mapped to the underlying JSON API'ssearch_parametersobject, which usessnake_casefield names as documented in the official xAI Live Search docs.
import { ChatXAI, tools } from "@langchain/xai";
const model = new ChatXAI({ model: "grok-2-1212" });
const modelWithTools = model.bindTools([
tools.xaiLiveSearch(), // Built-in server tool
{
// Custom function tool
type: "function",
function: {
name: "get_stock_price",
description: "Get the current stock price",
parameters: {
type: "object",
properties: {
symbol: { type: "string" },
},
required: ["symbol"],
},
},
},
]);
To develop the @langchain/xai package, you'll need to follow these instructions:
pnpm install
pnpm build
Or from the repo root:
pnpm build --filter @langchain/xai
Test files should live within a tests/ file in the src/ folder. Unit tests should end in .test.ts and integration tests should
end in .int.test.ts:
$ pnpm test
$ pnpm test:int
Run the linter & formatter to ensure your code is up to standard:
pnpm lint && pnpm format
If you add a new file to be exported, either import & re-export from src/index.ts, or add it to the exports field in the package.json file and run pnpm build to generate the new entrypoint.