LangGraph agent

1import { HumanMessage } from '@langchain/core/messages';
2import { createReactAgent } from '@langchain/langgraph/prebuilt';
3import { ChatOpenAI } from '@langchain/openai';
4import { Actor, log } from 'apify';
5
6import { webSearchTool } from './tools.js';
7
8const Event = {
9    ACTOR_STARTED: 'actor-start-gb',
10    INPUT_100_TOKENS: 'openai-100-tokens-input',
11    OUTPUT_100_TOKENS: 'openai-100-tokens-output',
12    TASK_COMPLETED: 'task-completed',
13};
14
15await Actor.init();
16
17try {
18    const memoryMbytes = Actor.getEnv().memoryMbytes || 1024;
19    const memoryGB = Math.ceil(memoryMbytes / 1024);
20    log.info(`Required memory: ${memoryGB} GB. Charging Actor start event.`);
21    await Actor.charge({ eventName: Event.ACTOR_STARTED, count: memoryGB });
22} catch (error) {
23    log.error('Failed to charge for actor start event', { error });
24    await Actor.exit(1);
25}
26
27// Follow these steps to run this template:
28// 1. If running locally, authenticate to the Apify platform by executing `apify login` in your terminal.
29//    This is necessary to run the Website Content Crawler Actor for data gathering.
30// 2. Set the `OPENAI_API_KEY` environment variable with your OpenAI API key, which can be obtained from
31//    https://platform.openai.com/account/api-keys. Refer to
32//    https://docs.apify.com/cli/docs/vars#set-up-environment-variables-in-apify-console for guidance
33//    on setting environment variables.
34const { OPENAI_API_KEY, APIFY_TOKEN } = process.env;
35
36// You can configure the input for the Actor in the Apify UI when running on the Apify platform or editing
37// storage/key_value_stores/default/INPUT.json when running locally.
38const { query, modelName } = await Actor.getInput() || {};
39
40if (!OPENAI_API_KEY) throw new Error('Please configure the OPENAI_API_KEY as environment variable or enter it into the input!');
41if (!APIFY_TOKEN) throw new Error('Please configure the APIFY_TOKEN environment variable! Call `apify login` in your terminal to authenticate.');
42
43const agent = createReactAgent({
44    llm: new ChatOpenAI({ temperature: 0, model: modelName }),
45    tools: [webSearchTool],
46});
47
48let agentFinalState;
49try {
50    log.info('Starting agent ...');
51    agentFinalState = await agent.invoke(
52        { messages: [new HumanMessage(query)] },
53        { configurable: { thread_id: '1' } },
54    );
55} catch (error) {
56    log.error('Failed to run the agent', { error });
57    await Actor.exit(1);
58}
59
60if (!agentFinalState || !agentFinalState.messages?.length) {
61    log.error('Agent did not return a valid response.');
62    await Actor.exit(1);
63}
64
65const answer = agentFinalState.messages[agentFinalState.messages.length - 1].content;
66
67log.info(`Question: ${query}`);
68log.info(`Agent response: ${answer}`);
69
70log.info(`Number of messages: ${agentFinalState.messages.length}`);
71const usageTokens = agentFinalState.messages.reduce((acc, msg) => {
72    acc.input += msg?.usage_metadata?.input_tokens || 0;
73    acc.output += msg?.usage_metadata?.output_tokens || 0;
74    return acc;
75}, { input: 0, output: 0 });
76
77log.info(`Charging token usage. Input: ${usageTokens.input}, Output: ${usageTokens.output}`);
78
79try {
80    await Actor.charge({ eventName: Event.INPUT_100_TOKENS, count: Math.ceil(usageTokens.input / 100) });
81    await Actor.charge({ eventName: Event.OUTPUT_100_TOKENS, count: Math.ceil(usageTokens.output / 100) });
82} catch (error) {
83    log.error('Failed to charge for tokens usage', { error });
84    await Actor.exit(1);
85}
86
87log.info('Pushing data to the key-value store');
88await Actor.pushData({ question: query, answer });
89
90log.info('Task completion event charged');
91await Actor.charge({ eventName: Event.TASK_COMPLETED });
92
93await Actor.exit();