What do you want to automate
with Microsoft OneDrive and Azure OpenAI?
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Popular Ways to Connect Microsoft OneDrive with Azure OpenAI#
Popular Microsoft OneDrive and Azure OpenAI Actions#
Create completions for chat messages with the GPT-35-Turbo and GPT-4 models. See the documentation
Create a sharing link for a DriveItem. See the documentation
Classify items into specific categories. See the documentation
Download a file stored in OneDrive. See the documentation
Overview of Microsoft OneDrive#
The Microsoft OneDrive API taps into the robust file storage and management capabilities of OneDrive, allowing for operations like file uploads, retrievals, sharing, and synchronization. Integrating this API into Pipedream workflows lets you automate tasks involving file management, content collaboration, and data backup processes. With OneDrive's API on Pipedream, you can streamline document workflows, trigger actions based on file changes, and connect your file storage to countless other services for enhanced productivity.
Connect Microsoft OneDrive#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
microsoft_onedrive: {
type: "app",
app: "microsoft_onedrive",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://graph.microsoft.com/v1.0/me`,
headers: {
Authorization: `Bearer ${this.microsoft_onedrive.$auth.oauth_access_token}`,
},
})
},
})
Overview of Azure OpenAI#
The Azure OpenAI Service API provides access to powerful AI models that can understand and generate human-like text. With Pipedream, you can harness this capability to create a variety of serverless workflows, automating tasks like content creation, code generation, and language translation. By integrating the API with other apps on Pipedream, you can streamline processes, analyze sentiment, and even automate customer support.
Connect Azure OpenAI#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
azure_openai_service: {
type: "app",
app: "azure_openai_service",
}
},
async run({steps, $}) {
const data = {
"messages": [{ role: 'user', content: "Hello, world!" }],
}
return await axios($, {
method: "post",
url: `https://${this.azure_openai_service.$auth.resource_name}.openai.azure.com/openai/deployments/${this.azure_openai_service.$auth.deployment_name}/chat/completions?api-version=2023-05-15`,
headers: {
"Content-Type": `application/json`,
"api-key": `${this.azure_openai_service.$auth.api_key}`,
},
data,
})
},
})
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