What do you want to automate
with 302.AI and Python?
Prompt, edit and deploy AI agents that connect to 302.AI, Python and 3,000+ other apps in seconds.
Trusted by 1,000,000+ developers from startups to Fortune 500 companies
Popular 302.AI and Python Actions#
Enable your 302.AI model to invoke user-defined functions. Useful for conditional logic, workflow orchestration, and tool invocation within conversations. See documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Send a message to the 302.AI Chat API. Ideal for dynamic conversations, contextual assistance, and creative generation. See documentation
Classify input items into predefined categories using 302.AI models. Perfect for tagging, segmentation, and automated organization. See documentation
Generate vector embeddings from text using the 302.AI Embeddings API. Useful for semantic search, clustering, and vector store indexing. See documentation
Connect 302.AI#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
_302_ai: {
type: "app",
app: "_302_ai",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.302.ai/v1/models`,
headers: {
Authorization: `Bearer ${this._302_ai.$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}}Trusted by 1,000,000+ developers from startups to Fortune 500 companies