Feature/update templates

.github/workflows/test_and_publish.yaml

@@ -32,7 +32,7 @@ jobs:
       - name: Setup node
         uses: actions/setup-node@v3
         with:
-          node-version: 16
+          node-version: 22
       - name: Install uv
         uses: astral-sh/setup-uv@v5
         with:

.github/workflows/test_pull_request_branch.yaml

@@ -20,7 +20,7 @@ jobs:
       - name: Setup node
         uses: actions/setup-node@v3
         with:
-          node-version: 16
+          node-version: 22
       - name: Install uv
         uses: astral-sh/setup-uv@v5
         with:

.gitignore

@@ -17,7 +17,7 @@ dist/
 downloads/
 eggs/
 .eggs/
-lib/
+./lib/
 lib64/
 parts/
 sdist/
@@ -61,4 +61,5 @@ demo.db
 test.db
 
 # Templates
-flama/templates
+flama/templates
+templates/out

examples/add_model_component.py

@@ -3,7 +3,7 @@
 
 import flama
 from flama import Flama
-from flama.models import ModelComponent, ModelResource, ModelResourceType
+from flama.models import BaseModelResource, ModelComponent
 from flama.models.base import Model
 from flama.resources import resource_method
 
@@ -19,30 +19,29 @@ def predict(self, x: typing.Any) -> typing.Any:
 class MyCustomModelComponent(ModelComponent):
     def __init__(self, model_path: str):
         self._model_path = model_path
-        self.model = MyCustomModel(None)
+        self.model = None
 
-    def load_model(self):
-        with open(self._model_path, "rb") as f:
-            self.model = MyCustomModel(flama.load(f).model)
+    def load(self):
+        load_model = flama.load(self._model_path)
+        self.model = MyCustomModel(load_model.model, load_model.meta, load_model.artifacts)
 
-    def unload_model(self):
-        self.model = MyCustomModel(None)
+    def reset(self):
+        self.model = None
 
     def resolve(self) -> MyCustomModel:
-        if not self.model.model:
-            self.load_model()
+        if not self.model:
+            self.load()
 
+        assert self.model
         return self.model
 
 
 component = MyCustomModelComponent("sklearn_model.flm")
-
-
 # component = MyCustomModelComponent("pytorch_model.flm")
 # component = MyCustomModelComponent("tensorflow_model.flm")
 
 
-class MyCustomModelResource(ModelResource, metaclass=ModelResourceType):
+class MyCustomModelResource(BaseModelResource[MyCustomModelComponent]):
     name = "custom_model"
     verbose_name = "Lazy-loaded ScikitLearn Model"
     component = component
@@ -61,7 +60,7 @@ def _get_metadata(self):
                 },
                 "custom": {
                     **self.info,
-                    "loaded": self.component.model.model is not None,
+                    "loaded": self.component.model is not None,
                     "date": datetime.now().date(),
                     "time": datetime.now().time(),
                 },
@@ -76,7 +75,7 @@ def unload(self):
         summary:
             Unload the model.
         """
-        self.component.unload_model()
+        self.component.reset()
         return self._get_metadata()
 
     @resource_method("/metadata/", methods=["GET"], name="metadata-method")
@@ -98,7 +97,7 @@ def metadata(self):
     components=[component],
 )
 
-app.models.add_model_resource(path="/model", resource=MyCustomModelResource)
+app.models.add_model_resource(path="/model", resource=MyCustomModelComponent)
 
 if __name__ == "__main__":
     flama.run(flama_app="__main__:app", server_host="0.0.0.0", server_port=8080, server_reload=True)

examples/add_model_resource.py

@@ -1,11 +1,11 @@
-import typing
+import typing as t
 from datetime import datetime
 
-from pydantic import BaseModel, Field
+import pydantic
 
 import flama
-from flama import Flama
-from flama.models import ModelResource, ModelResourceType
+from flama import Flama, schemas
+from flama.models import ModelResource
 from flama.resources import resource_method
 
 app = Flama(
@@ -16,19 +16,19 @@
 )
 
 
-class X(BaseModel):
-    input: list[typing.Any] = Field(title="input", description="Model input")
+class X(pydantic.BaseModel):
+    input: list[t.Any] = pydantic.Field(title="input", description="Model input")
 
 
-class Y(BaseModel):
-    output: list[typing.Any] = Field(title="output", description="Model output")
+class Y(pydantic.BaseModel):
+    output: list[t.Any] = pydantic.Field(title="output", description="Model output")
 
 
 app.schema.register_schema("X", X)
 app.schema.register_schema("Y", Y)
 
 
-class MySKModel(ModelResource, metaclass=ModelResourceType):
+class MySKModel(ModelResource):
     # special names:
     name = "sk_model"
     verbose_name = "My ScikitLearn Model"
@@ -41,7 +41,9 @@ class MySKModel(ModelResource, metaclass=ModelResourceType):
     }
 
     @resource_method("/predict/", methods=["POST"], name="model-predict")
-    def predict(self, data: X) -> Y:
+    def predict(
+        self, data: t.Annotated[schemas.SchemaType, schemas.SchemaMetadata(X)]
+    ) -> t.Annotated[schemas.SchemaType, schemas.SchemaMetadata(Y)]:
         """
         tags:
             - My ScikitLearn Model

examples/add_models.py

@@ -1,7 +1,7 @@
 import logging
 
 import flama
-from flama import Flama, Route
+from flama import Flama, routing
 
 
 class AppStatus:
@@ -64,9 +64,9 @@ def user(username: str):
     version="0.1.0",
     description="Machine learning API using Flama 🔥",
     routes=[
-        Route("/", home),
-        Route("/user/me", user_me),
-        Route("/user/{username}", user),
+        routing.Route("/", home),
+        routing.Route("/user/me", user_me),
+        routing.Route("/user/{username}", user),
     ],
     events={"startup": [startup], "shutdown": [shutdown]},
 )

examples/background.py

@@ -1,7 +1,7 @@
 import asyncio
 
 import flama
-from flama import BackgroundThreadTask, Flama
+from flama import Flama, background
 from flama.http import JSONResponse
 
 app = Flama()
@@ -13,9 +13,9 @@ async def sleep_task(value: int):
 
 @app.route("/")
 async def test():
-    task = BackgroundThreadTask(sleep_task, 10)
+    task = background.BackgroundThreadTask(sleep_task, 10)
     return JSONResponse("hello", background=task)
 
 
 if __name__ == "__main__":
-    flama.run(app, host="0.0.0.0", port=8000)
+    flama.run(flama_app=app, server_host="0.0.0.0", server_port=8080)

examples/components.py

@@ -40,4 +40,4 @@ def person(person: Person):
 
 
 if __name__ == "__main__":
-    flama.run(app, host="0.0.0.0", port=8000)
+    flama.run(flama_app=app, server_host="0.0.0.0", server_port=8080)

examples/data_schema.py

@@ -1,7 +1,9 @@
-from pydantic import BaseModel, validator
+import typing as t
+
+import pydantic
 
 import flama
-from flama import Flama
+from flama import Flama, schemas
 
 app = Flama(
     title="Puppy Register",  # API title
@@ -12,12 +14,12 @@
 )
 
 
-class Puppy(BaseModel):
+class Puppy(pydantic.BaseModel):
     id: int
     name: str
     age: int
 
-    @validator("age")
+    @pydantic.field_validator("age")
     def minimum_age_validation(cls, v):
         if v < 0:
             raise ValueError("Age must be positive")
@@ -32,7 +34,7 @@ def home():
     return {"hello": "world"}
 
 
-def list_puppies(name: str = None) -> list[Puppy]:
+def list_puppies(name: t.Optional[str] = None) -> t.Annotated[list[schemas.SchemaType], schemas.SchemaMetadata(Puppy)]:
     """
     tags:
         - puppy
@@ -48,7 +50,9 @@ def list_puppies(name: str = None) -> list[Puppy]:
     ...
 
 
-def create_puppy(puppy: Puppy) -> Puppy:
+def create_puppy(
+    puppy: t.Annotated[schemas.SchemaType, schemas.SchemaMetadata(Puppy)],
+) -> t.Annotated[schemas.SchemaType, schemas.SchemaMetadata(Puppy)]:
     """
     tags:
         - puppy
@@ -68,4 +72,4 @@ def create_puppy(puppy: Puppy) -> Puppy:
 app.add_route("/puppy/", create_puppy, methods=["POST"])
 
 if __name__ == "__main__":
-    flama.run(app, host="0.0.0.0", port=8000)
+    flama.run(flama_app=app, server_host="0.0.0.0", server_port=8080)

examples/error.py

@@ -1,6 +1,7 @@
 import flama
+from flama import Flama, routing
 
-app = flama.Flama(
+app = Flama(
     title="Hello-🔥",
     version="1.0",
     description="My first API",
@@ -26,13 +27,13 @@ def home():
     return {"message": "Hello 🔥"}
 
 
-error_app = flama.Router()
+error_app = routing.Router()
 
 
 class FooException(Exception): ...
 
 
-@error_app.route("/500")
+@error_app.route("/500/")
 def error_500():
     """
     tags:
@@ -51,7 +52,7 @@ def error_500():
 app.mount("/error", app=error_app)
 
 # Mount a complex urls tree to illustrate in 404 error page
-bar_app = flama.Router()
+bar_app = routing.Router()
 
 
 @bar_app.route("/foobar/")
@@ -62,10 +63,10 @@ def foobar(): ...
 def barfoo(): ...
 
 
-foo_app = flama.Router()
+foo_app = routing.Router()
 foo_app.mount("/bar/", bar_app)
 
 app.mount("/foo/", foo_app)
 
 if __name__ == "__main__":
-    flama.run(app, host="0.0.0.0", port=8000)
+    flama.run(flama_app=app, server_host="0.0.0.0", server_port=8080)

examples/ml_responsive_pytorch.py

@@ -2,6 +2,7 @@
 
 import torch
 
+import flama
 from flama import Flama
 from flama.models import ModelComponent, ModelResource, ModelResourceType
 from flama.models.base import Model
@@ -63,3 +64,6 @@ class CustomModelResource(ModelResource, metaclass=ModelResourceType):
 
 app.add_component(component)
 app.models.add_model_resource("/", CustomModelResource)
+
+if __name__ == "__main__":
+    flama.run(flama_app=app, server_host="0.0.0.0", server_port=8080)

examples/ml_responsive_sklearn.py

@@ -2,6 +2,7 @@
 
 from sklearn.linear_model import LogisticRegression
 
+import flama
 from flama import Flama
 from flama.models import ModelComponent, ModelResource, ModelResourceType
 from flama.models.base import Model
@@ -58,3 +59,6 @@ class CustomModelResource(ModelResource, metaclass=ModelResourceType):
 
 app.add_component(component)
 app.models.add_model_resource("/", CustomModelResource)
+
+if __name__ == "__main__":
+    flama.run(flama_app=app, server_host="0.0.0.0", server_port=8080)

examples/ml_responsive_tensorflow.py

@@ -2,6 +2,7 @@
 
 import tensorflow as tf
 
+import flama
 from flama import Flama
 from flama.models import ModelComponent, ModelResource, ModelResourceType
 from flama.models.base import Model
@@ -64,3 +65,6 @@ class CustomModelResource(ModelResource, metaclass=ModelResourceType):
 
 app.add_component(component)
 app.models.add_model_resource("/", CustomModelResource)
+
+if __name__ == "__main__":
+    flama.run(flama_app=app, server_host="0.0.0.0", server_port=8080)