# Chat — Azure OpenAI

> Create completions for chat messages with the GPT-35-Turbo and GPT-4 models. See the documentation

- Key: `azure_openai_service-chat`
- Type: Action (Write)
- Version: 0.0.3
- App: Azure OpenAI (`azure_openai_service`) — https://pipedream.com/apps/azure-openai-service.md
- This page (HTML): https://pipedream.com/apps/azure-openai-service/actions/chat
- Hints: open-world
- Source: https://github.com/PipedreamHQ/pipedream/blob/master/components/azure_openai_service/actions/chat/chat.mjs

## Description

Create completions for chat messages with the GPT-35-Turbo and GPT-4 models. [See the documentation](https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#chat-completions)

## Props

| Prop | Type | Required | Description |
|---|---|---|---|
| `userMessage` | `string` | Yes | The user messages to provide instructions to the assistant. |
| `systemInstructions` | `string` | No | The system message helps set the behavior of the assistant. For example: "You are a helpful assistant." |
| `messages` | `string[]` | No | 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. |
| `temperature` | `string` | No | 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. |
| `n` | `integer` | No | How many completions to generate |
| `stream` | `boolean` | No | 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. |
| `stop` | `string` | No | Up to 4 sequences where the API will stop generating further tokens. |
| `maxTokens` | `integer` | No | 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). |
| `presencePenalty` | `string` | No | 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. |
| `frequencyPenalty` | `string` | No | 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. |
| `user` | `string` | No | A unique identifier representing your end-user, which can help Azure OpenAI to monitor and detect abuse. |

## Run it

**MCP**

```ts
import { Client } from "@modelcontextprotocol/sdk/client/index.js"
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp.js"
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 accessToken = await pd.rawAccessToken

const transport = new StreamableHTTPClientTransport(
  new URL("https://remote.mcp.pipedream.net/v3"),
  {
    requestInit: {
      headers: {
        Authorization: `Bearer ${accessToken}`,
        "x-pd-project-id": process.env.PIPEDREAM_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",
  },
})
```

**TypeScript**

```ts
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**

```bash
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"
    }
  }'
```

---

- App: https://pipedream.com/apps/azure-openai-service.md · All apps: https://pipedream.com/apps