chore: format README.md

README.md

@@ -1,6 +1,8 @@
 # Faster Whisper Server
+
 `faster-whisper-server` is an OpenAI API-compatible transcription server which uses [faster-whisper](https://github.com/SYSTRAN/faster-whisper) as its backend.
 Features:
+
 - GPU and CPU support.
 - Easily deployable using Docker.
 - **Configurable through environment variables (see [config.py](./src/faster_whisper_server/config.py))**.
@@ -12,20 +14,24 @@ Features:
 Please create an issue if you find a bug, have a question, or a feature suggestion.
 
 ## OpenAI API Compatibility ++
+
 See [OpenAI API reference](https://platform.openai.com/docs/api-reference/audio) for more information.
+
 - Audio file transcription via `POST /v1/audio/transcriptions` endpoint.
-    - Unlike OpenAI's API, `faster-whisper-server` also supports streaming transcriptions (and translations). This is useful for when you want to process large audio files and would rather receive the transcription in chunks as they are processed, rather than waiting for the whole file to be transcribed. It works similarly to chat messages when chatting with LLMs.
+  - Unlike OpenAI's API, `faster-whisper-server` also supports streaming transcriptions (and translations). This is useful for when you want to process large audio files and would rather receive the transcription in chunks as they are processed, rather than waiting for the whole file to be transcribed. It works similarly to chat messages when chatting with LLMs.
 - Audio file translation via `POST /v1/audio/translations` endpoint.
--  Live audio transcription via `WS /v1/audio/transcriptions` endpoint.
-    - LocalAgreement2 ([paper](https://aclanthology.org/2023.ijcnlp-demo.3.pdf) | [original implementation](https://github.com/ufal/whisper_streaming)) algorithm is used for live transcription.
-    - Only transcription of a single channel, 16000 sample rate, raw, 16-bit little-endian audio is supported.
+- Live audio transcription via `WS /v1/audio/transcriptions` endpoint.
+  - LocalAgreement2 ([paper](https://aclanthology.org/2023.ijcnlp-demo.3.pdf) | [original implementation](https://github.com/ufal/whisper_streaming)) algorithm is used for live transcription.
+  - Only transcription of a single channel, 16000 sample rate, raw, 16-bit little-endian audio is supported.
 
 ## Quick Start
+
 [Hugging Face Space](https://huggingface.co/spaces/Iatalking/fast-whisper-server)
 
 ![image](https://github.com/fedirz/faster-whisper-server/assets/76551385/6d215c52-ded5-41d2-89a5-03a6fd113aa0)
 
-Using Docker Compose (Recommended)
+### Using Docker Compose (Recommended)
+
 NOTE: I'm using newer Docker Compsose features. If you are using an older version of Docker Compose, you may need need to update.
 
 ```bash
@@ -39,7 +45,8 @@ curl --silent --remote-name https://raw.githubusercontent.com/fedirz/faster-whis
 docker compose --file compose.cpu.yaml up --detach
 ```
 
-Using Docker
+### Using Docker
+
 ```bash
 # for GPU support
 docker run --gpus=all --publish 8000:8000 --volume ~/.cache/huggingface:/root/.cache/huggingface --detach fedirz/faster-whisper-server:latest-cuda
@@ -47,22 +54,29 @@ docker run --gpus=all --publish 8000:8000 --volume ~/.cache/huggingface:/root/.c
 docker run --publish 8000:8000 --volume ~/.cache/huggingface:/root/.cache/huggingface --env WHISPER__MODEL=Systran/faster-whisper-small --detach fedirz/faster-whisper-server:latest-cpu
 ```
 
-Using Kubernetes: [tutorial](https://substratus.ai/blog/deploying-faster-whisper-on-k8s)
+### Using Kubernetes
+
+Follow [this tutorial](https://substratus.ai/blog/deploying-faster-whisper-on-k8s)
 
 ## Usage
+
 If you are looking for a step-by-step walkthrough, check out [this](https://www.youtube.com/watch?app=desktop&v=vSN-oAl6LVs) YouTube video.
 
 ### OpenAI API CLI
+
 ```bash
 export OPENAI_API_KEY="cant-be-empty"
 export OPENAI_BASE_URL=http://localhost:8000/v1/
 ```
+
 ```bash
 openai api audio.transcriptions.create -m Systran/faster-distil-whisper-large-v3 -f audio.wav --response-format text
 
 openai api audio.translations.create -m Systran/faster-distil-whisper-large-v3 -f audio.wav --response-format verbose_json
 ```
+
 ### OpenAI API Python SDK
+
 ```python
 from openai import OpenAI
 
@@ -76,6 +90,7 @@ print(transcript.text)
 ```
 
 ### cURL
+
 ```bash
 # If `model` isn't specified, the default model is used
 curl http://localhost:8000/v1/audio/transcriptions -F "[email protected]"
@@ -89,12 +104,14 @@ curl http://localhost:8000/v1/audio/translations -F "[email protected]"
 ```
 
 ### Live Transcription (using WebSocket)
+
 From [live-audio](./examples/live-audio) example
 
 https://github.com/fedirz/faster-whisper-server/assets/76551385/e334c124-af61-41d4-839c-874be150598f
 
 [websocat](https://github.com/vi/websocat?tab=readme-ov-file#installation) installation is required.
 Live transcription of audio data from a microphone.
+
 ```bash
 ffmpeg -loglevel quiet -f alsa -i default -ac 1 -ar 16000 -f s16le - | websocat --binary ws://localhost:8000/v1/audio/transcriptions
 ```