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Prerequisites

The Boilerplate comes with the OpenAI API integration of Lanchain from the start. To use LangChain, you need to:

  • Get your OpenAI API key from the OpenAI API website.

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Setup

  1. Add your OpenAI API key to the .env file.
.env
OPENAI_API_KEY=your-openai-api-key
  1. The boilerplate already includes the necessary configuration for LangChain in src/lib/ai/langchain.ts. This file initializes the OpenAI language model client.

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Usage

To use LangChain in your application, you can create an API route that interacts with the language model. Here’s an example of how to set up a route that uses the OpenAI model for text generation:

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Advanced Usage

LangChain offers many powerful features beyond simple text generation. Here are a few examples:

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Chains

Chains allow you to combine multiple steps of processing. For example, you can create a chain that generates a question and then answers it:

import { LLMChain } from "langchain/chains";
import { loadDocuments } from "@langchain/core";
import { llm } from "@/lib/ai/langchain";

const documents = await loadDocuments("path/to/your/documents.txt");

const qaChain = new LLMChain({
  llm,
  prompt: {
    template: "Question: {question}\nAnswer the question based on the provided context:\n{context}",
    inputVariables: ["question", "context"],
  },
});

const answer = await qaChain.invoke({
  question: "What is the main topic of the documents?",
  context: documents.pageContent.join("\n\n"),
});
console.log({ answer });

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Agents

Agents can use tools to gather information and make decisions. Here’s a simple example using a calculator tool:

import { initializeAgentExecutorWithOptions } from "langchain/agents";
import { Calculator } from "@langchain/community/tools/calculator";
import { llm } from "@/lib/ai/langchain";

const tools = [new Calculator()];

const executor = await initializeAgentExecutorWithOptions(tools, llm, {
    agentType: "zero-shot-react-description",
    verbose: true,
});

const input = `What is the square root of 256 multiplied by 2?`;

const result = await executor.invoke({ input });

console.log(`Got output ${JSON.stringify(result, null, 2)}`);

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Model Selection

If you want to use a different model, you can change the model or provider in the src/lib/ai/langchain.ts file.

You can explore the available models on the Langchain Website.

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