Integrate the Relevance AI API with the Python API

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

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Popular Relevance AI and Python Actions#

Run Tool with the Relevance AI API

Executes a specific tool within Relevance AI and waits for a response for up to 60 seconds. See the documentation

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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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Send Message to Agent with the Relevance AI API

Sends a message directly to an agent in Relevance AI. This action doesn't wait for an agent response.

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Overview of Relevance AI#

Relevance AI is a powerful tool for handling complex data operations like clustering, vector search, and data visualization. On Pipedream, you can use the Relevance AI API to automate data enrichment, analysis, and integration tasks. This integration opens up possibilities for dynamic data workflows, enabling real-time data processing and insights generation across various platforms.

Connect Relevance AI#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    relevance_ai: {
      type: "app",
      app: "relevance_ai",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      method: "post",
      url: `https://api-${this.relevance_ai.$auth.region}.stack.tryrelevance.com/latest/agents/list `,
      headers: {
        "Authorization": `${this.relevance_ai.$auth.project}:${this.relevance_ai.$auth.api_key}`,
      },
    })
  },
})

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}}

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