16i-credentials-langchain.ts

/**
 * Credentials -- LangChain AgentExecutor with credential injection.
 *
 * Demonstrates:
 *   - Same pattern as LangGraph -- credentials resolved from server
 *     and injected into process.env before the executor runs
 *
 * NOTE: This example demonstrates the credential injection pattern for
 * LangChain agents running through Agentspan. Since LangChain is an
 * optional dependency, the example uses native Agentspan Agent with
 * credential-aware tools that mirror what a LangChain agent would do.
 *
 * In a full LangChain integration, you would:
 *   const executor = createLangChainAgent();
 *   const result = await runtime.run(executor, prompt, { credentials: ["GITHUB_TOKEN"] });
 *
 * Setup (one-time):
 *   agentspan credentials set GITHUB_TOKEN <your-github-token>
 *
 * Requirements:
 *   - Agentspan server running at AGENTSPAN_SERVER_URL
 *   - AGENTSPAN_LLM_MODEL set (or defaults to openai/gpt-4o-mini)
 *   - GITHUB_TOKEN stored via `agentspan credentials set`
 */

import { Agent, AgentRuntime, tool, getCredential } from '@io-orkes/conductor-javascript/agents';
import { llmModel } from './settings';

// Mirrors a LangChain @tool that checks for a credential in the environment
const checkGithubToken = tool(
  async () => {
    // Try in-process credential resolution first
    try {
      const token = await getCredential('GITHUB_TOKEN');
      return { message: `GitHub token available (starts with ${token.slice(0, 4)}...)` };
    } catch {
      // Fall back to process.env (as a LangChain tool would)
      const token = process.env.GITHUB_TOKEN ?? '';
      if (token) {
        return { message: `GitHub token available via env (starts with ${token.slice(0, 4)}...)` };
      }
      return { message: 'GitHub token is NOT available' };
    }
  },
  {
    name: 'check_github_token',
    description: 'Check if GitHub token is available in the environment.',
    inputSchema: { type: 'object', properties: {} },
    credentials: ['GITHUB_TOKEN'],
  },
);

export const agent = new Agent({
  name: 'langchain_cred_agent',
  model: llmModel,
  tools: [checkGithubToken],
  credentials: ['GITHUB_TOKEN'],
  instructions: 'You are a helpful assistant. Use tools when asked.',
});

// -- Run ----------------------------------------------------------------------

async function main() {
  const runtime = new AgentRuntime();
  try {
    const result = await runtime.run(
    agent,
    'Check if the GitHub token is set',
    );
    result.printResult();

    // Production pattern:
    // 1. Deploy once during CI/CD (optional -- serve() below also deploys):
    // await runtime.deploy(agent);
    // CLI alternative:
    // agentspan deploy --package sdk/typescript/examples --agents langchain_cred_agent
    //
    // 2. In a separate long-lived worker process (deploys + registers workers + starts polling):
    // await runtime.serve(agent);
  } finally {
    await runtime.shutdown();
  }
}

main().catch(console.error);