*** title: Quickstart description: >- This guide will help you get started quickly with transcribing your first audio using Python and the Smallest AI API. icon: rocket ------------ ## Step 1: Sign Up & Get Your API Key 1. Visit the [platform](https://atoms.smallest.ai/dashboard/speech-to-text?utm_source=documentation\&utm_medium=speech-to-text) and sign up for an account or log in if you already have an account. 2. Navigate to `API Key` tab in your account dashboard. 3. Create a new API Key and copy it. 4. Export the API Key in your environment with the name `SMALLEST_API_KEY`, ensuring that your application can access it securely for authentication. ## Step 2: Install Dependencies To install the required library: ```bash pip install requests ``` ## Step 3: Make Your First API Call Here is a basic example of how to use Python to transcribe an audio file: ```python Python import os import requests API_KEY = os.environ.get("SMALLEST_API_KEY") response = requests.post( "https://waves-api.smallest.ai/api/v1/pulse/get_text", params={"model": "pulse", "language": "en"}, headers={ "Authorization": f"Bearer {API_KEY}", "Content-Type": "audio/wav", }, data=open("audio.wav", "rb").read(), timeout=120 ) result = response.json() print(result["transcription"]) ``` ```bash cURL curl --request POST \ --url "https://waves-api.smallest.ai/api/v1/pulse/get_text?model=pulse&language=en" \ --header "Authorization: Bearer $SMALLEST_API_KEY" \ --header "Content-Type: audio/wav" \ --data-binary "@audio.wav" ``` Replace `YOUR_API_KEY` with the API key you obtained in Step 1. ## Step 4: Explore More Features * **[Real-Time Transcription](/waves/documentation/speech-to-text/realtime-web-socket/quickstart):** Stream audio via WebSocket for live transcription. * **[Speaker Diarization](/waves/documentation/speech-to-text/features/diarization):** Identify and label different speakers in multi-speaker audio. * **[Word Timestamps](/waves/documentation/speech-to-text/features/word-timestamps):** Get precise timing information for each word. * **[Emotion Detection](/waves/documentation/speech-to-text/features/emotion-detection):** Analyze emotional tone in transcribed speech. For detailed documentation on all available features and endpoints, visit our [API Reference](/waves/api-reference/api-reference/speech-to-text/pulse). ### Need Help? If you have any questions or need assistance, please contact our support team at [support@smallest.ai](mailto:support@smallest.ai).