> For the complete documentation index, see [llms.txt](https://docs.agenticflow.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.agenticflow.ai/workflows/workflow-inputs/upload-audio.md).

# Upload Audio

The **Upload Audio** control is an input component that allows a user to upload an audio file (e.g., MP3, WAV, M4A) when they run a workflow. The uploaded audio is then accessible via a temporary URL that can be used by downstream nodes for processing.

## When to Use

Use the Upload Audio control for any workflow that needs to process a user-provided audio file. Common use cases include:

* Transcribing speech to text.
* Summarizing the content of a meeting or call.
* Translating speech from one language to another.
* Identifying different speakers in a recording.

## How to Add

1. From your workflow's **Build** page, click on **+ Add Input**.
2. Select **Upload Audio** from the list of available controls.

## Configuration

* **Title:** The main label for the file upload field.
* **Description:** Optional helper text to provide more context.
* **Variable Name:** The name used to access the URL of the uploaded audio file.
* **Optional/Required:** A toggle to specify if the user must upload a file.

## Accessing the Value

After the user uploads a file, this control outputs a temporary, secure URL pointing to that audio file. This URL is accessible via the variable name you assigned.

For example, if the variable name is `podcast_episode`, the value of `{{podcast_episode}}` will be a URL (e.g., `https://cdn.agenticflow.ai/.../episode.mp3`).

**Note:** This URL is temporary and will expire. It is meant for immediate processing within the workflow run.

### Example

**Goal:** Allow a user to upload a recording of a customer support call and generate a summary and a list of action items.

1. **Add an Upload Audio Control:**
   * Title: "Upload Support Call Recording"
   * Variable Name: `call_recording_url`
2. **Add an OpenAI MCP Node (Whisper):**
   * **Action:** `Create Transcription`
   * **File:** `{{call_recording_url}}`
   * **Purpose:** To convert the spoken audio into text.
3. **Add another OpenAI MCP Node (GPT):**

   * **Action:** `Chat`
   * **Prompt:**

   ```
   Read the following transcript of a customer support call. Provide a one-paragraph summary of the issue and a bulleted list of action items for the support agent.

   Transcript:
   {{openai_mcp_1.text}}
   ```

   * **Purpose:** To analyze the transcribed text and extract key information.

This workflow takes a raw audio file and turns it into a structured, actionable summary, automating the post-call analysis process.