> ## Documentation Index
> Fetch the complete documentation index at: https://framework.beeai.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# IBM watsonx Orchestrate

IBM watsonx Orchestrate is IBM’s AI-powered automation platform designed to streamline and automate workflows across diverse applications. By leveraging artificial intelligence and pre-built task modules, it empowers users to design, manage, and monitor end-to-end business processes through natural language interactions. As part of the IBM Watsonx suite, IBM watsonx Orchestrate makes automation accessible to both technical and non-technical users, helping organizations operationalize AI in their daily operations.

***

## Prerequisites

Before integrating IBM watsonx Orchestrate with the BeeAI Framework, ensure you have the following:

* An active **[IBM watsonx Orchestrate](https://www.ibm.com/products/watsonx-orchestrate)** account.
* The **BeeAI Framework** installed:
  ```sh theme={null}
  pip install beeai-framework
  ```
* The **IBM watsonx Orchestrate extension** for BeeAI:
  ```sh theme={null}
  pip install 'beeai-framework[watsonx-orchestrate]'
  ```

***

<Heading level={2} id="client">Consuming from IBM watsonx Orchestrate (client)</Heading>

The `WatsonxOrchestrateAgent` class enables you to connect to any native agent hosted on IBM watsonx Orchestrate. This allows your BeeAI-powered applications to interact with IBM watsonx Orchestrate agents programmatically.

<CodeGroup>
  ```py Python [expandable] theme={null}
  import asyncio
  import sys
  import traceback

  from beeai_framework.adapters.watsonx_orchestrate.agents import WatsonxOrchestrateAgent
  from beeai_framework.errors import FrameworkError
  from examples.helpers.io import ConsoleReader


  async def main() -> None:
      reader = ConsoleReader()

      agent = WatsonxOrchestrateAgent(
          # To find your instance URL, visit IBM watsonx Orchestrate -> Settings -> API Details
          # Example: https://api.eu-de.watson-orchestrate.cloud.ibm.com/instances/aaaaaa-bbbb-cccc-dddd-eeeeeeeee
          instance_url="YOUR_INSTANCE_URL",
          # To find agent's ID, visit IBM watsonx Orchestrate -> Select any existing agent -> copy the last part of the URL ()
          # Example: 1xfa8c27-6d0f-4962-9eb5-4e1c0b8073d8
          agent_id="YOUR_AGENT_ID",
          # Auth type, typically IAM (hosted version) or JWT for custom deployments
          auth_type="iam",
          # To find your API Key, visit IBM watsonx Orchestrate -> Settings -> API Details -> Generate API Key
          api_key="YOUR_API_KEY",
      )
      for prompt in reader:
          response = await agent.run(prompt)
          reader.write("Agent 🤖 : ", response.last_message.text)


  if __name__ == "__main__":
      try:
          asyncio.run(main())
      except FrameworkError as e:
          traceback.print_exc()
          sys.exit(e.explain())

  ```

  ```ts TypeScript [expandable] theme={null}
  // COMING SOON
  ```
</CodeGroup>

***

<Heading level={2} id="server">Exposing to IBM watsonx Orchestrate (server)</Heading>

The `WatsonxOrchestrateServer` allows you to expose BeeAI agents as HTTP server with a chat completion endpoint compatible with IBM watsonx Orchestrate.
This enables you to register and use your local BeeAI agents as external agents within IBM watsonx Orchestrate.

<CodeGroup>
  ```py Python [expandable] theme={null}
  from beeai_framework.adapters.watsonx_orchestrate import WatsonxOrchestrateServer, WatsonxOrchestrateServerConfig
  from beeai_framework.agents.requirement import RequirementAgent
  from beeai_framework.backend import ChatModel
  from beeai_framework.memory import UnconstrainedMemory
  from beeai_framework.serve.utils import LRUMemoryManager
  from beeai_framework.tools.weather import OpenMeteoTool


  def main() -> None:
      llm = ChatModel.from_name("ollama:granite4:micro")
      agent = RequirementAgent(llm=llm, tools=[OpenMeteoTool()], memory=UnconstrainedMemory(), role="a weather agent")

      config = WatsonxOrchestrateServerConfig(port=8080, host="0.0.0.0", api_key=None)  # optional
      # use LRU memory manager to keep limited amount of sessions in the memory
      server = WatsonxOrchestrateServer(config=config, memory_manager=LRUMemoryManager(maxsize=100))
      server.register(agent)

      # start an API with /chat/completions endpoint which is compatible with Watsonx Orchestrate
      server.serve()


  if __name__ == "__main__":
      main()

  ```

  ```ts TypeScript [expandable] theme={null}
  // COMING SOON
  ```
</CodeGroup>

<Note>
  You can't consume local agents in the hosted version. To use your agents in IBM watsonx Orchestrate, first deploy the server, then register it in the IBM watsonx Orchestrate UI or CLI.
</Note>