docs: Add troubleshooting section on accessing LS data (#533)

Co-authored-by: Caitlin Wheeless <[email protected]>

Author: caitlinwheeless

README.md

@@ -293,3 +293,14 @@ docker compose build --no-cache
 You might see these errors if you send multiple concurrent requests. 
 
 Note that the provided ML backend examples are offered in development mode, and do not support production-level inference serving. 
+
+## Troubleshooting the ML backend failing to make simple auto-annotations or unable to see predictions
+
+You must ensure that the ML backend can access your Label Studio data. If it can't, you might encounter the following issues:
+
+* `no such file or directory` errors in the server logs.
+* You are unable to see predictions when loading tasks in Label Studio.
+* Your ML backend appears to be connected properly, but cannot seem to complete any auto annotations within tasks. 
+
+To remedy this, ensure you have set the `LABEL_STUDIO_URL` and `LABEL_STUDIO_API_KEY` environment variables. For more information, see [Allow the ML backend to access Label Studio data](https://labelstud.io/guide/ml#Allow-the-ML-backend-to-access-Label-Studio-data).
+

label_studio_ml/examples/nemo_asr/README.md

@@ -38,7 +38,7 @@ This example works with the Label Studio's pre-built **Audio Transcription** tem
 
 But you can use any other labeling interface that combines `<Audio>` and `<TextArea>` elements.
 
-> Warning: If you use files hosted in Label Studio (e.g. audio files directly uploaded via import dialog), you must provide the `LABEL_STUDIO_URL` and `LABEL_STUDIO_API_KEY` environment variables to the ML backend. For more information about finding your Label Studio API key, [see our documentation](https://labelstud.io/guide/user_account#Access-token).
+> Warning: If you use files hosted in Label Studio (meaning they were added using the import action), hosted in cloud storage, or connected through local storage, then you must provide the `LABEL_STUDIO_URL` and `LABEL_STUDIO_API_KEY` environment variables to the ML backend. For more information, see [Allow the ML backend to access Label Studio data](https://labelstud.io/guide/ml#Allow-the-ML-backend-to-access-Label-Studio-data). For information about finding your Label Studio API key, see [Access token](https://labelstud.io/guide/user_account#Access-token).
 
 ## Running with Docker (recommended)
 
@@ -99,4 +99,4 @@ The following common parameters are available:
 
 ## Customization
 
-The ML backend can be customized by adding your own models and logic inside `./nemo_asr/model.py`. 
+The ML backend can be customized by adding your own models and logic inside `./nemo_asr/model.py`.