Integrate the Cohere API with the Python API

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

Popular Cohere and Python Actions#

Choose Best Completion with the Cohere API

This action chooses the best completion conditioned on a given examples. See the docs here

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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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Classify Text with the Cohere API

This action makes a prediction about which label fits the specified text inputs best. See the docs here

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Generate Text with the Cohere API

This action generates realistic text conditioned on a given input. See the docs here

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Summarize Text with the Cohere API

This action generates a summary in English for the given text. See the docs here

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Overview of Cohere#

The Cohere API enables the development of apps with advanced natural language understanding capabilities. Utilizing machine learning, it can help with tasks like text generation, summarization, sentiment analysis, and more. On Pipedream, you can seamlessly integrate Cohere's features into serverless workflows, triggering actions based on text input, processing large volumes of data, or even enhancing chatbots with more human-like responses.

Connect Cohere#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    cohere_platform: {
      type: "app",
      app: "cohere_platform",
    }
  },
  async run({steps, $}) {
    const data = {
      "text": `Tokenize this!`,
    }
    return await axios($, {
      method: "post",
      url: `https://api.cohere.ai/small/tokenize`,
      headers: {
        Authorization: `Bearer ${this.cohere_platform.$auth.api_key}`,
        "Content-Type": `application/json`,
      },
      data,
    })
  },
})

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}}