nemo_asr: fix readme and docker-compose

label_studio_ml/examples/nemo_asr/README.md

@@ -18,7 +18,7 @@ It works with the `Audio Transcription` labeling interface from project `Setting
 
 or any other labeling interface that combines `<Audio>` and `<TextArea>` elements.
 
-> Warning: only use audio files hosted in public URLs, as the ML backend will download them to process.
+> Warning: if you use files hosted in Label Studio (e.g. audio files directly uploaded via import dialog), you should provide `LABEL_STUDIO_URL` and `LABEL_STUDIO_API_KEY` environment variable to the ML backend.
 
 ## Running with Docker (Recommended)
 
@@ -35,7 +35,7 @@ $ curl http://localhost:9090/
 {"status":"UP"}
 ```
 
-3. Connect to the backend from Label Studio running on the same host: go to your project `Settings -> Machine Learning -> Add Model` and specify `http://localhost:9090` as a URL.
+3. Connect to the backend from Label Studio running on the same host: go to your project `Settings -> Model -> Connect Model` and specify `http://localhost:9090` as a URL.
 
 
 ## Building from source (Advanced)
@@ -59,7 +59,7 @@ pip install -r requirements.txt
 Then you can start the ML backend:
 
 ```bash
-label-studio-ml start ./dir_with_your_model
+label-studio-ml start ./nemo_asr
 ```
 
 # Configuration
@@ -73,7 +73,9 @@ The following common parameters are available:
 - `LOG_LEVEL` - set the log level for the model server
 - `WORKERS` - specify the number of workers for the model server
 - `THREADS` - specify the number of threads for the model server
+- `LABEL_STUDIO_HOST`: The host of the Label Studio instance. Default is 'http://localhost:8080'.
+- `LABEL_STUDIO_API_KEY`: The API key for the Label Studio instance.
 
 # Customization
 
-The ML backend can be customized by adding your own models and logic inside the `./dir_with_your_model` directory. 
+The ML backend can be customized by adding your own models and logic inside the `./nemo_asr/model.py`. 

label_studio_ml/examples/nemo_asr/docker-compose.yml

@@ -27,7 +27,7 @@ services:
       # Do not use 'localhost' as it does not work within Docker containers.
       # Use prefix 'http://' or 'https://' for the URL always.
       # Determine the actual IP using 'ifconfig' (Linux/Mac) or 'ipconfig' (Windows).
-      - LABEL_STUDIO_URL=
+      - LABEL_STUDIO_URL=http://localhost:8080
       - LABEL_STUDIO_API_KEY=
     ports:
       - "9090:9090"