Build generative AI applications with Google's PaLM 2 model.
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Generate embeddings using Google PaLM. See the docs here
The Google PaLM API is a cutting-edge language model that allows developers to integrate advanced natural language understanding into their applications. On Pipedream, you can harness this power to create serverless workflows that react to various triggers and perform actions based on the insights and outputs from PaLM. Whether it's generating content, summarizing text, or understanding user intent, PaLM's capabilities can be integrated into Pipedream workflows to automate complex tasks involving language.
import { v1beta2 } from "@google-ai/generativelanguage";
import { GoogleAuth } from "google-auth-library";
export default defineComponent({
props: {
google_palm_api: {
type: "app",
app: "google_palm_api",
}
},
async run({ steps, $ }) {
const client = new v1beta2.TextServiceClient({
authClient: new GoogleAuth().fromAPIKey(this.google_palm_api.$auth.palm_api_key),
});
const text = "Repeat after me: one, two,";
const model = "models/text-bison-001";
return await client
.generateText({
model,
prompt: {
text,
},
})
},
})
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}}