Integrate the Chaindesk API with the Python API

Setup the Chaindesk API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Chaindesk and Python remarkably fast. Free for developers.

Popular Ways to Connect Chaindesk with Python#

Run Python Code with Python API on New Response Generated from Chaindesk API

Chaindesk + Python

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Popular Chaindesk and Python Triggers#

New Response Generated from the Chaindesk API

Emit new event when a new message from an agent is created.

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Popular Chaindesk and Python Actions#

Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

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Submit Message with the Chaindesk API

Allows the API to send a message input from the user.

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Update Agent with the Chaindesk API

Updates the agent to improve the accuracy of generated responses.

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Overview of Chaindesk#

Chaindesk API offers a platform to create, deploy, and manage AI chatbots. It includes features such as natural language processing, integration capabilities, and a conversational interface to engage with users. Using Pipedream, you can leverage the Chaindesk API to build serverless workflows that trigger on various events and interact with other services to automate tasks, analyze conversations, and enhance user experiences.

Connect Chaindesk#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    chaindesk: {
      type: "app",
      app: "chaindesk",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.chaindesk.ai/agents`,
      headers: {
        Authorization: `Bearer ${this.chaindesk.$auth.api_key}`,
        "Content-Type": `application/json`,
      },
    })
  },
})

Overview of Python#

Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.

This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.

Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:

Connect Python#

def handler(pd: "pipedream"):
  # Reference data from previous steps
  print(pd.steps["trigger"]["context"]["id"])
  # Return data for use in future steps
  return {"foo": {"test":True}}