# Create Completion (Send Prompt) — OpenAI (ChatGPT)

> OpenAI recommends using the Chat action for the latest gpt-3.5-turbo API, since it's faster and 10x cheaper. This action creates a completion for the provided prompt and parameters using the older /completions API. See the documentation

- Key: `openai-send-prompt`
- Type: Action (Write)
- Version: 0.1.24
- App: OpenAI (ChatGPT) (`openai`) — https://pipedream.com/apps/openai.md
- This page (HTML): https://pipedream.com/apps/openai/actions/send-prompt
- Hints: open-world
- Source: https://github.com/PipedreamHQ/pipedream/blob/master/components/openai/actions/send-prompt/send-prompt.mjs

## Description

OpenAI recommends using the **Chat** action for the latest `gpt-3.5-turbo` API, since it's faster and 10x cheaper. This action creates a completion for the provided prompt and parameters using the older `/completions` API. [See the documentation](https://beta.openai.com/docs/api-reference/completions/create)

## Props

| Prop | Type | Required | Description |
|---|---|---|---|
| `modelId` | `string` | Yes | The ID of the model to use for completions. This action doesn't support the ChatGPT turbo models. Use the Chat action for those, instead. Options are loaded from the connected account. |
| `prompt` | `string` | Yes | The prompt to generate completions for |
| `suffix` | `string` | No | The suffix that comes after a completion of inserted text |
| `maxTokens` | `integer` | No | The maximum number of tokens to generate in the completion. |
| `temperature` | `string` | No | Optional. What sampling temperature to use. Higher values means the model will take more risks. Try 0.9 for more creative applications, and 0 (argmax sampling) for ones with a well-defined answer. |
| `topP` | `string` | No | An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both. |
| `n` | `integer` | No | How many completions to generate for each prompt |
| `stop` | `string[]` | No | Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence. |
| `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 OpenAI to monitor and detect abuse. Learn more here. |
| `bestOf` | `integer` | No | Generates best_of completions server-side and returns the "best" (the one with the highest log probability per token). If set, results cannot be streamed. |

## 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": "openai",
      },
    },
  },
)

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: "openai-send-prompt",
  arguments: {
    modelId: "Model",
    prompt: "Prompt",
  },
})
```

**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: "openai-send-prompt",
  externalUserId: "{external_user_id}", // any stable ID for this user in your system
  configuredProps: {
    openai: { authProvisionId: "apn_xxxxxxx" },
    modelId: "Model",
    prompt: "Prompt",
  },
})

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": "openai-send-prompt",
    "configured_props": {
      "openai": { "authProvisionId": "apn_xxxxxxx" },
      "modelId": "Model",
      "prompt": "Prompt"
    }
  }'
```

---

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