Integrate the Replicate API with the Python API

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

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Popular Replicate and Python Actions#

Cancel Prediction with the Replicate API

Cancel a specific prediction identified by Id. 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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Create Prediction with the Replicate API

Create a new prediction See the documentation

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Get Model with the Replicate API

Get a specific model identified by Id. See the documentation

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Get Prediction with the Replicate API

Get a specific prediction identified by Id. See the documentation

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Overview of Replicate#

The Replicate API allows you to access a wide array of machine learning models for tasks such as image generation, text-to-image, and more. Using Pipedream, you can orchestrate these models to automate content creation, analyze media, or enhance data with AI-generated insights. Pipedream's serverless platform empowers you to create workflows that react to events, schedule tasks, and integrate with numerous other services, all harnessing the power of Replicate's AI models.

Connect Replicate#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    replicate: {
      type: "app",
      app: "replicate",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.replicate.com/v1/predictions`,
      headers: {
        "Authorization": `Token ${this.replicate.$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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