Update docker instructions

README.md

@@ -12,37 +12,35 @@ Verbilobot is a Telegram bot written in Go that transcribes voice messages, vide
 > [!IMPORTANT]  
 > However you plan to run the bot, make sure to rename the `.env.example` file to `.env` and fill in your Telegram Bot Token and Groq API Token.
 
+### With Docker
+
+To run the project with Docker, you need to have [Docker](https://www.docker.com/) installed on your machine. From then on, it only takes a couple of seconds.
+
+```bash
+git clone "https://github.com/bytebone/verbilobot.git" && cd verbilobot/
+cp .env.example docker/.env
+cd docker && nano .env
+# edit the env file with your tokens and chat IDs as needed
+docker compose up
+```
+
 ### Local Go
 
 To build and run the project locally, you will need to have [Go](https://go.dev/) and [FFmpeg](https://ffmpeg.org/) installed on your machine.
 
 On Linux:
 ```bash
-git clone "https://github.com/bytebone/verbilobot.git"
-cd verbilobot
+git clone "https://github.com/bytebone/verbilobot.git" && cd verbilobot/
 go build -v -o verbilobot .
 ./verbilobot
 ```
 Or on Windows: 
 ```pwsh
-git clone "https://github.com/bytebone/verbilobot.git"
-cd verbilobot
+git clone "https://github.com/bytebone/verbilobot.git" && cd verbilobot/
 go build -v -o verbilobot.exe .
 start verbilobot.exe
 ```
 
-### With Docker
-
-To build and run the project with Docker, you will need to have [Docker](https://www.docker.com/) installed on your machine.
-
-```bash
-git clone "https://github.com/bytebone/verbilobot.git"
-cd verbilobot/docker
-cp ../.env.example ./.env
-docker compose up --build -d
-```
-Thanks to Docker being awesome, this works the same on any platform. 
-
 ## Usage
 
 The bot usually takes around 2 seconds to come online. Once the bot is running, you can forward any audio or video files to it to start the transcription process. Thanks to the high speeds at Groq, a minute of incoming audio takes only a few moments to transcribe and return to your chat. The main bottleneck you might notice is the local transcoding, which can take a *noticeable* amount of time to complete.