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Popular Python and Cohere Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
This action makes a prediction about which label fits the specified text inputs best. See the documentation
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}}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,
})
},
})
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