Azure OpenAI ACTION
Chat
Create completions for chat messages with the GPT-35-Turbo and GPT-4 models. See the documentation
- Action
- Writes data
- API key
- SDK
- MCP
IMPLEMENTATION
Call this tool
Connect a user's Azure OpenAI account once, then configure and run Chat from your backend or agent.
import { PipedreamClient } from "@pipedream/sdk"
const pd = new PipedreamClient({
projectId: process.env.PIPEDREAM_PROJECT_ID!,
clientId: process.env.PIPEDREAM_CLIENT_ID!,
clientSecret: process.env.PIPEDREAM_CLIENT_SECRET!,
projectEnvironment: "production",
})
const result = await pd.actions.run({
id: "azure_openai_service-chat",
externalUserId: "{external_user_id}", // any stable ID for this user in your system
configuredProps: {
azure_openai_service: { authProvisionId: "apn_xxxxxxx" },
userMessage: "User Message",
systemInstructions: "System Instructions",
},
})
console.log(result)curl -X POST https://api.pipedream.com/v1/connect/{project_id}/actions/run \
-H "Content-Type: application/json" \
-H "X-PD-Environment: production" \
-H "Authorization: Bearer {access_token}" \
-d '{
"external_user_id": "{external_user_id}",
"id": "azure_openai_service-chat",
"configured_props": {
"azure_openai_service": { "authProvisionId": "apn_xxxxxxx" },
"userMessage": "User Message",
"systemInstructions": "System Instructions"
}
}'// accessToken: mint a short-lived token with the Connect SDK — see the MCP guide
const transport = new StreamableHTTPClientTransport(
new URL("https://remote.mcp.pipedream.net/v3"),
{
requestInit: {
headers: {
Authorization: `Bearer ${accessToken}`,
"x-pd-project-id": "{project_id}",
"x-pd-environment": "production",
"x-pd-external-user-id": "{external_user_id}", // any stable ID for this user in your system
"x-pd-app-slug": "azure_openai_service",
},
},
},
)
const mcp = new Client({ name: "my-agent", version: "1.0.0" })
await mcp.connect(transport)
const { tools } = await mcp.listTools()
// listTools() hands your model this tool's input schema, so it can
// fill the arguments itself:
const result = await mcp.callTool({
name: "azure_openai_service-chat",
arguments: {
userMessage: "User Message",
systemInstructions: "System Instructions",
},
})SCHEMA
Inputs
Pipedream supplies the connected account. Your application provides the operation-specific values below. Dynamic inputs are resolved against that user's account.
| Property | Type | Description |
|---|---|---|
userMessage User Message | string | The user messages to provide instructions to the assistant. Required |
systemInstructions System Instructions | string | The system message helps set the behavior of the assistant. For example: "You are a helpful assistant." Optional |
messages Prior Message History | string[] | Advanced. Because the models have no memory of past chat requests, all relevant information must be supplied via the conversation. You can provide an array of messages from prior conversations here. If this param is set, the action ignores the values passed to System Instructions and Assistant Response, appends the new User Message to the end of this array, and sends it to the API. Optional |
temperature Temperature | string | What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. Optional |
n N | integer | How many completions to generate Optional |
stream Stream | boolean | If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a data: [DONE] message. Optional |
stop Stop | string | Up to 4 sequences where the API will stop generating further tokens. Optional |
maxTokens Max Tokens | integer | The maximum number of tokens allowed for the generated answer. By default, the number of tokens the model can return will be (4096 - prompt tokens). Optional |
presencePenalty Presence Penalty | string | Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics. Optional |
frequencyPenalty Frequency Penalty | string | Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim. Optional |
user User | string | A unique identifier representing your end-user, which can help Azure OpenAI to monitor and detect abuse. Optional |
REFERENCE
Tool details
Behavior hints are published with the component in the Pipedream registry and surface as MCP tool annotations, so an agent can reason about a tool before it calls it.
- Registry key
- azure_openai_service-chat
- Version
- 0.0.3
- App
- Azure OpenAI
- Authentication
- API key
- Read-only
- No
- Destructive
- No
- Open world
- Yes
- Source
- View on GitHub ↗