Transcribe, translate, and analyze with AI
Emit new event when a new media file is created. Useful for initiating workflows based on new media intake. See the documentation
Emit new event when a new text is analyzed. Useful for initiating workflows based on new text analysis. See the documentation
Analyzes a block of text for key insights, sentiment, and keyword extraction using Speak Ai's NLP engine. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Retrieve the full transcription of a processed media file. See the documentation
Upload an audio or video file for transcription and natural language processing into Speak AI. See the documentation
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
speak_ai: {
type: "app",
app: "speak_ai",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.speakai.co/v1/admin/users`,
headers: {
"x-speakai-key": `${this.speak_ai.$auth.api_key}`,
"x-access-token": `${this.speak_ai.$auth.oauth_access_token}`,
},
})
},
})
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:
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}}