Chatsonic
Like ChatGPT but with real-time data, images & voice search.
Integrate the Chatsonic API with the Python API
Setup the Chatsonic API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Chatsonic and Python remarkably fast. Free for developers.
Popular Chatsonic and Python Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Overview of Chatsonic#
The Chatsonic API by Writesonic unleashes the power of conversational AI, enabling you to craft chatbots, automate customer service, and generate natural language responses for a variety of use cases. With Chatsonic, you can design workflows on Pipedream that respond to events, messages, or prompts with human-like text, leverage contextually aware conversations, and even tap into real-time data like weather or news for enriched interactions.
Connect Chatsonic#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
chatsonic: {
type: "app",
app: "chatsonic",
}
},
async run({steps, $}) {
const data = {
"enable_google_results": `true`,
"enable_memory": `false`,
"input_text": `Check out pipedream.com`,
}
return await axios($, {
method: "post",
url: `https://api.writesonic.com/v2/business/content/chatsonic?engine=premium`,
headers: {
"Accept": `application/json`,
"Content-Type": `application/json`,
"X-API-KEY": `${this.chatsonic.$auth.api_key}`,
},
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}}