또는 와 InvokeAgentAWS SDK 함께 사용 CLI

import {
  BedrockAgentRuntimeClient,
  InvokeAgentCommand,
} from "@aws-sdk/client-bedrock-agent-runtime";

/**
 * @typedef {Object} ResponseBody
 * @property {string} completion
 */

/**
 * Invokes a Bedrock agent to run an inference using the input
 * provided in the request body.
 *
 * @param {string} prompt - The prompt that you want the Agent to complete.
 * @param {string} sessionId - An arbitrary identifier for the session.
 */
export const invokeBedrockAgent = async (prompt, sessionId) => {
  const client = new BedrockAgentRuntimeClient({ region: "us-east-1" });
  // const client = new BedrockAgentRuntimeClient({
  //   region: "us-east-1",
  //   credentials: {
  //     accessKeyId: "accessKeyId", // permission to invoke agent
  //     secretAccessKey: "accessKeySecret",
  //   },
  // });

  const agentId = "AJBHXXILZN";
  const agentAliasId = "AVKP1ITZAA";

  const command = new InvokeAgentCommand({
    agentId,
    agentAliasId,
    sessionId,
    inputText: prompt,
  });

  try {
    let completion = "";
    const response = await client.send(command);

    if (response.completion === undefined) {
      throw new Error("Completion is undefined");
    }

    for await (let chunkEvent of response.completion) {
      const chunk = chunkEvent.chunk;
      console.log(chunk);
      const decodedResponse = new TextDecoder("utf-8").decode(chunk.bytes);
      completion += decodedResponse;
    }

    return { sessionId: sessionId, completion };
  } catch (err) {
    console.error(err);
  }
};

// Call function if run directly
import { fileURLToPath } from "url";
if (process.argv[1] === fileURLToPath(import.meta.url)) {
  const result = await invokeBedrockAgent("I need help.", "123");
  console.log(result);
}

에이전트를 간접 호출합니다.

    def invoke_agent(self, agent_id, agent_alias_id, session_id, prompt):
        """
        Sends a prompt for the agent to process and respond to.

        :param agent_id: The unique identifier of the agent to use.
        :param agent_alias_id: The alias of the agent to use.
        :param session_id: The unique identifier of the session. Use the same value across requests
                           to continue the same conversation.
        :param prompt: The prompt that you want Claude to complete.
        :return: Inference response from the model.
        """

        try:
            # Note: The execution time depends on the foundation model, complexity of the agent,
            # and the length of the prompt. In some cases, it can take up to a minute or more to
            # generate a response.
            response = self.agents_runtime_client.invoke_agent(
                agentId=agent_id,
                agentAliasId=agent_alias_id,
                sessionId=session_id,
                inputText=prompt,
            )

            completion = ""

            for event in response.get("completion"):
                chunk = event["chunk"]
                completion = completion + chunk["bytes"].decode()

        except ClientError as e:
            logger.error(f"Couldn't invoke agent. {e}")
            raise

        return completion