feat(examples): update tts (#55)

advanced/tts/README.md

@@ -8,34 +8,20 @@ With this demo, you will be able to run deepfloyd and get results like follows:
 
 and you can check out more details in the `tts.ipynb` notebook.
 
-## Implementation note: mounting a gradio server
-
-In is demo, we will not only show how to create multiple paths for a photon, but also include a Gradio UI:
-```python
-@Photon.handler(mount=True)
-def ui(self):
-    blocks = gr.Blocks()
-    ... # misc code that defines the blocks
-    return blocks
-```
-The UI will then be available at the `/ui/` address. For example, if you are running locally, it would be something like `http://0.0.0.0:8080/ui/`.
-
 ## Run tts locally
 
 Ensure that you have installed the required dependencies via `pip install -r requirements.txt`. Then, run:
 ```shell
-python tts.py
+python tts_main.py
 ```
-Note that if you have a GPU, things will run much faster. When the program runs, visit `http://0.0.0.0:8080/ui/` for the web UI, or use the client to access it in a programmatical way.
+Note that if you have a GPU, things will run much faster. When the program runs, visit `http://0.0.0.0:8080/doc/` for the openapi doc, or use the client to access it in a programmatical way.
 
 ## Run tts in the cloud
 
 Similar to other examples, you can run tts with the following command:
 
 ```shell
-lep photon create -n tts -m tts.py
-lep photon push -n tts
-lep photon run -n tts --resource-shape gpu.t4
+lep photon run -n tts -m tts_main.py --resource-shape gpu.t4
 ```
 
 And visit [dashboard.lepton.ai](https://dashboard.lepton.ai/) to try out the model.
@@ -47,3 +33,7 @@ lep deployment update -n tts --public
 ```
 
 You can then use tts either via the UI or via the client. See the notebook example for more details.
+
+## XTTS
+
+We also include an XTTS example that can be used to do voice cloning. More details to be written.

advanced/tts/requirements.txt

@@ -1,3 +1,3 @@
-gradio
 leptonai
-TTS
+TTS
+deepspeed