Merge pull request #234 from MichaelClifford/fix-222

added wav file for audio example
containers · Apr 11, 2024 · 605bfda · 605bfda
2 parents 8292230 + 6a4af8f
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diff --git a/data/jfk.wav b/data/jfk.wav
diff --git a/recipes/audio/audio_to_text/README.md b/recipes/audio/audio_to_text/README.md
@@ -103,20 +103,6 @@ To convert your input audio files to 16-bit WAV format you can use `ffmpeg` like
 ffmpeg -i <input.mp3> -ar 16000 -ac 1 -c:a pcm_s16le <output.wav>
 ```
 
-### Deploy the AI Application
-
-Make sure the Model Service is up and running before starting this container image. When starting the AI Application container image we need to direct it to the correct `MODEL_SERVICE_ENDPOINT`. This could be any appropriately hosted Model Service (running locally or in the cloud) using an OpenAI compatible API. In our case the Model Service is running inside the Podman machine so we need to provide it with the appropriate address `10.88.0.1`. The following Podman command can be used to run your AI Application:
-
-```bash
-podman run --rm -it -p 8501:8501 -e MODEL_SERVICE_ENDPOINT=http://10.88.0.1:8001/v1 codegen
-```
-
-### Interact with the AI Application
-
-Everything should now be up an running with the chat application available at [`http://localhost:8501`](http://localhost:8501). By using this recipe and getting this starting point established, users should now have an easier time customizing and building their own LLM enabled code generation applications.
-
-_Note: Future recipes will demonstrate integration between locally hosted LLM's and developer productivity tools like VSCode._
-
 ### Embed the AI Application in a Bootable Container Image
 
 To build a bootable container image that includes this sample chatbot workload as a service that starts when a system is booted, cd into this folder