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npentrel
394 lines
12 KiB
Plaintext
394 lines
12 KiB
Plaintext
<CodeGroup>
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```ts Google
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import { tool } from "langchain";
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import { TavilySearch } from "@langchain/tavily";
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import { createDeepAgent, type SubAgent } from "deepagents";
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import { z } from "zod";
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const internetSearch = tool(
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async ({
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query,
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maxResults = 5,
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topic = "general",
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includeRawContent = false,
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}: {
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query: string;
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maxResults?: number;
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topic?: "general" | "news" | "finance";
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includeRawContent?: boolean;
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}) => {
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const tavilySearch = new TavilySearch({
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maxResults,
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tavilyApiKey: process.env.TAVILY_API_KEY,
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includeRawContent,
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topic,
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});
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return await tavilySearch._call({ query });
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},
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{
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name: "internet_search",
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description: "Run a web search",
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schema: z.object({
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query: z.string().describe("The search query"),
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maxResults: z.number().optional().default(5),
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topic: z
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.enum(["general", "news", "finance"])
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.optional()
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.default("general"),
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includeRawContent: z.boolean().optional().default(false),
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}),
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},
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);
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const researchSubagent: SubAgent = {
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name: "research-agent",
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description: "Used to research more in depth questions",
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systemPrompt: "You are a great researcher",
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tools: [internetSearch],
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model: "google-genai:gemini-3.6-flash", // Optional override, defaults to main agent model
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};
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const subagents = [researchSubagent];
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const agent = createDeepAgent({
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model: "google_genai:gemini-3.6-flash",
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subagents,
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});
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```
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```ts OpenAI
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import { tool } from "langchain";
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import { TavilySearch } from "@langchain/tavily";
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import { createDeepAgent, type SubAgent } from "deepagents";
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import { z } from "zod";
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const internetSearch = tool(
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async ({
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query,
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maxResults = 5,
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topic = "general",
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includeRawContent = false,
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}: {
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query: string;
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maxResults?: number;
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topic?: "general" | "news" | "finance";
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includeRawContent?: boolean;
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}) => {
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const tavilySearch = new TavilySearch({
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maxResults,
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tavilyApiKey: process.env.TAVILY_API_KEY,
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includeRawContent,
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topic,
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});
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return await tavilySearch._call({ query });
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},
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{
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name: "internet_search",
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description: "Run a web search",
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schema: z.object({
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query: z.string().describe("The search query"),
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maxResults: z.number().optional().default(5),
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topic: z
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.enum(["general", "news", "finance"])
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.optional()
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.default("general"),
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includeRawContent: z.boolean().optional().default(false),
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}),
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},
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);
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const researchSubagent: SubAgent = {
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name: "research-agent",
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description: "Used to research more in depth questions",
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systemPrompt: "You are a great researcher",
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tools: [internetSearch],
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model: "openai:gpt-5.5", // Optional override, defaults to main agent model
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};
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const subagents = [researchSubagent];
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const agent = createDeepAgent({
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model: "google_genai:gemini-3.6-flash",
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subagents,
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});
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```
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```ts Anthropic
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import { tool } from "langchain";
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import { TavilySearch } from "@langchain/tavily";
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import { createDeepAgent, type SubAgent } from "deepagents";
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import { z } from "zod";
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const internetSearch = tool(
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async ({
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query,
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maxResults = 5,
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topic = "general",
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includeRawContent = false,
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}: {
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query: string;
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maxResults?: number;
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topic?: "general" | "news" | "finance";
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includeRawContent?: boolean;
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}) => {
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const tavilySearch = new TavilySearch({
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maxResults,
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tavilyApiKey: process.env.TAVILY_API_KEY,
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includeRawContent,
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topic,
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});
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return await tavilySearch._call({ query });
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},
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{
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name: "internet_search",
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description: "Run a web search",
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schema: z.object({
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query: z.string().describe("The search query"),
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maxResults: z.number().optional().default(5),
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topic: z
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.enum(["general", "news", "finance"])
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.optional()
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.default("general"),
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includeRawContent: z.boolean().optional().default(false),
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}),
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},
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);
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const researchSubagent: SubAgent = {
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name: "research-agent",
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description: "Used to research more in depth questions",
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systemPrompt: "You are a great researcher",
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tools: [internetSearch],
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model: "anthropic:claude-sonnet-4-6", // Optional override, defaults to main agent model
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};
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const subagents = [researchSubagent];
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const agent = createDeepAgent({
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model: "google_genai:gemini-3.6-flash",
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subagents,
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});
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```
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```ts OpenRouter
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import { tool } from "langchain";
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import { TavilySearch } from "@langchain/tavily";
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import { createDeepAgent, type SubAgent } from "deepagents";
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import { z } from "zod";
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const internetSearch = tool(
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async ({
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query,
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maxResults = 5,
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topic = "general",
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includeRawContent = false,
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}: {
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query: string;
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maxResults?: number;
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topic?: "general" | "news" | "finance";
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includeRawContent?: boolean;
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}) => {
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const tavilySearch = new TavilySearch({
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maxResults,
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tavilyApiKey: process.env.TAVILY_API_KEY,
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includeRawContent,
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topic,
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});
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return await tavilySearch._call({ query });
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},
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{
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name: "internet_search",
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description: "Run a web search",
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schema: z.object({
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query: z.string().describe("The search query"),
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maxResults: z.number().optional().default(5),
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topic: z
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.enum(["general", "news", "finance"])
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.optional()
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.default("general"),
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includeRawContent: z.boolean().optional().default(false),
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}),
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},
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);
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const researchSubagent: SubAgent = {
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name: "research-agent",
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description: "Used to research more in depth questions",
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systemPrompt: "You are a great researcher",
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tools: [internetSearch],
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model: "openrouter:openrouter:z-ai/glm-5.2", // Optional override, defaults to main agent model
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};
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const subagents = [researchSubagent];
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const agent = createDeepAgent({
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model: "google_genai:gemini-3.6-flash",
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subagents,
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});
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```
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```ts Fireworks
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import { tool } from "langchain";
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import { TavilySearch } from "@langchain/tavily";
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import { createDeepAgent, type SubAgent } from "deepagents";
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import { z } from "zod";
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const internetSearch = tool(
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async ({
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query,
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maxResults = 5,
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topic = "general",
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includeRawContent = false,
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}: {
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query: string;
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maxResults?: number;
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topic?: "general" | "news" | "finance";
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includeRawContent?: boolean;
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}) => {
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const tavilySearch = new TavilySearch({
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maxResults,
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tavilyApiKey: process.env.TAVILY_API_KEY,
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includeRawContent,
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topic,
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});
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return await tavilySearch._call({ query });
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},
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{
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name: "internet_search",
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description: "Run a web search",
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schema: z.object({
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query: z.string().describe("The search query"),
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maxResults: z.number().optional().default(5),
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topic: z
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.enum(["general", "news", "finance"])
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.optional()
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.default("general"),
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includeRawContent: z.boolean().optional().default(false),
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}),
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},
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);
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const researchSubagent: SubAgent = {
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name: "research-agent",
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description: "Used to research more in depth questions",
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systemPrompt: "You are a great researcher",
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tools: [internetSearch],
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model: "fireworks:accounts/fireworks/models/glm-5p2", // Optional override, defaults to main agent model
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};
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const subagents = [researchSubagent];
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const agent = createDeepAgent({
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model: "google_genai:gemini-3.6-flash",
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subagents,
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});
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```
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```ts Baseten
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import { tool } from "langchain";
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import { TavilySearch } from "@langchain/tavily";
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import { createDeepAgent, type SubAgent } from "deepagents";
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import { z } from "zod";
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const internetSearch = tool(
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async ({
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query,
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maxResults = 5,
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topic = "general",
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includeRawContent = false,
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}: {
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query: string;
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maxResults?: number;
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topic?: "general" | "news" | "finance";
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includeRawContent?: boolean;
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}) => {
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const tavilySearch = new TavilySearch({
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maxResults,
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tavilyApiKey: process.env.TAVILY_API_KEY,
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includeRawContent,
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topic,
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});
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return await tavilySearch._call({ query });
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},
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{
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name: "internet_search",
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description: "Run a web search",
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schema: z.object({
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query: z.string().describe("The search query"),
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maxResults: z.number().optional().default(5),
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topic: z
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.enum(["general", "news", "finance"])
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.optional()
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.default("general"),
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includeRawContent: z.boolean().optional().default(false),
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}),
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},
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);
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const researchSubagent: SubAgent = {
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name: "research-agent",
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description: "Used to research more in depth questions",
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systemPrompt: "You are a great researcher",
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tools: [internetSearch],
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model: "baseten:zai-org/GLM-5.2", // Optional override, defaults to main agent model
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};
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const subagents = [researchSubagent];
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const agent = createDeepAgent({
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model: "google_genai:gemini-3.6-flash",
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subagents,
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});
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```
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```ts Ollama
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import { tool } from "langchain";
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import { TavilySearch } from "@langchain/tavily";
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import { createDeepAgent, type SubAgent } from "deepagents";
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import { z } from "zod";
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const internetSearch = tool(
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async ({
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query,
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maxResults = 5,
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topic = "general",
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includeRawContent = false,
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}: {
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query: string;
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maxResults?: number;
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topic?: "general" | "news" | "finance";
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includeRawContent?: boolean;
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}) => {
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const tavilySearch = new TavilySearch({
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maxResults,
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tavilyApiKey: process.env.TAVILY_API_KEY,
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includeRawContent,
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topic,
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});
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return await tavilySearch._call({ query });
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},
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{
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name: "internet_search",
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description: "Run a web search",
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schema: z.object({
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query: z.string().describe("The search query"),
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maxResults: z.number().optional().default(5),
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topic: z
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.enum(["general", "news", "finance"])
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.optional()
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.default("general"),
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includeRawContent: z.boolean().optional().default(false),
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}),
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},
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);
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const researchSubagent: SubAgent = {
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name: "research-agent",
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description: "Used to research more in depth questions",
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systemPrompt: "You are a great researcher",
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tools: [internetSearch],
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model: "ollama:north-mini-code-1.0", // Optional override, defaults to main agent model
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};
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const subagents = [researchSubagent];
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const agent = createDeepAgent({
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model: "google_genai:gemini-3.6-flash",
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subagents,
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});
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```
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</CodeGroup>
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