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import { loadQAStuffChain } from "langchain/chains";
import { Document } from "langchain/document";
import { pull } from "langchain/hub";
import { AgentExecutor, createOpenAIToolsAgent } from "langchain/agents";
import {Calculator} from "@langchain/community/tools/calculator";
import { ChatOpenAI } from "@langchain/openai";
import type { ChatPromptTemplate } from "@langchain/core/prompts";
const pathToLocalAI = process.env['OPENAI_API_BASE'] || 'http://api:8080/v1';
const fakeApiKey = process.env['OPENAI_API_KEY'] || '-';
const modelName = process.env['MODEL_NAME'] || 'gpt-3.5-turbo';
function getModel(): ChatOpenAI {
return new ChatOpenAI({
prefixMessages: [
{
role: "system",
content: "You are a helpful assistant that answers in pirate language",
},
],
modelName: modelName,
maxTokens: 50,
openAIApiKey: fakeApiKey,
maxRetries: 2
}, {
basePath: pathToLocalAI,
apiKey: fakeApiKey,
});
}
// Minimal example.
export const run = async () => {
const model = getModel();
console.log(`about to model.invoke at ${new Date().toUTCString()}`);
const res = await model.invoke(
"What would be a good company name a company that makes colorful socks?"
);
console.log(`${new Date().toUTCString()}`);
console.log({ res });
};
await run();
// This example uses the `StuffDocumentsChain`
export const run2 = async () => {
const model = getModel();
const chainA = loadQAStuffChain(model);
const docs = [
new Document({ pageContent: "Harrison went to Harvard." }),
new Document({ pageContent: "Ankush went to Princeton." }),
];
const resA = await chainA.invoke({
input_documents: docs,
question: "Where did Harrison go to college?",
});
console.log({ resA });
};
await run2();
// Quickly thrown together example of using tools + agents.
// This seems like it should work, but it doesn't yet.
export const toolAgentTest = async () => {
const model = getModel();
const prompt = await pull<ChatPromptTemplate>("hwchase17/openai-tools-agent");
const tools = [new Calculator()];
const agent = await createOpenAIToolsAgent({
llm: model,
tools: tools,
prompt: prompt
});
console.log("Loaded agent.");
const agentExecutor = new AgentExecutor({
agent,
tools,
});
const input = `What is the value of (500 *2) + 350 - 13?`;
console.log(`Executing with input "${input}"...`);
const result = await agentExecutor.invoke({ input });
console.log(`Got output ${result.output}`);
}
await toolAgentTest();
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