last modal version required some syntax changes

backend.py

@@ -1,4 +1,4 @@
-import modal
+from modal import App, Volume, Image, Mount
 
 from typing import List, Dict, Tuple, Union, Callable
 # from preprocessing import FileIO
@@ -9,18 +9,19 @@ from typing import List, Dict, Tuple, Union, Callable
 #     remote_path="./data",
 # )
 
-stub = modal.Stub("vector-search-project")
-vector_search = modal.Image.debian_slim().pip_install(
+app = App("vector-search-project")
+vector_search = Image.debian_slim().pip_install(
     "sentence_transformers==2.2.2", "llama_index==0.9.6.post1", "angle_emb==0.1.5"
     )
 
-stub.volume = modal.Volume.new()
+vol = Volume.from_name("vector-search-volume")
+# ^ volume must be created manually with CLI: modal volume create vector-search-volume 
 
 
-@stub.function(image=vector_search, 
+@app.function(image=vector_search, 
                gpu="A100", 
                timeout=600,
-               volumes={"/root/models": stub.volume}
+               volumes={"/root/models": vol}
                # secrets are available in the environment with os.environ["SECRET_NAME"]
                # secret=modal.Secret.from_name("my-huggingface-secret")
                )
@@ -91,11 +92,11 @@ def encode_content_splits(content_splits,
     return emb
 
 
-@stub.function(image=vector_search, gpu="A100", timeout=240,
-               mounts=[modal.Mount.from_local_dir("./data",
+@app.function(image=vector_search, gpu="A100", timeout=240,
+               mounts=[Mount.from_local_dir("./data",
                                                   remote_path="/root/data", 
                                                   condition=lambda pth: ".json" in pth)],
-               volumes={"/root/models": stub.volume}
+               volumes={"/root/models": vol}
 )
 def finetune(training_path='./data/training_data_300.json', 
              valid_path='./data/validation_data_100.json', 
@@ -149,7 +150,7 @@ def finetune(training_path='./data/training_data_300.json',
         print(f"GPU processing lasted {end:.2f} seconds")
         
         print(os.listdir('/root/models'))
-        stub.volume.commit()  # Persist changes, ie the finetumed model
+        app.volume.commit()  # Persist changes, ie the finetumed model
         
         # TODO SHARE THE MODEL ON HUGGINGFACE
         # https://huggingface.co/docs/transformers/v4.15.0/model_sharing
@@ -174,7 +175,7 @@ def finetune(training_path='./data/training_data_300.json',
         return "Finetuning failed"
     
     
-@stub.local_entrypoint()
+@app.local_entrypoint()
 def test_method(content_splits=[["a"]]):
     output = encode_content_splits.remote(content_splits)
     return output