lmmx
commented
9 months ago I get the impression from your description/branch name you saw this as a v2 regression @chamini2 but this reproduces on main actually.
The hello_dataclass function does not actually serialise successfully in Pydantic 1.x from what I can see: but the serve=True parameter hides this by successfully starting a Uvicorn server.
There might indeed be problems with Pydantic 2, but I'd think it'd be best to start from a working v1.x baseline here.
Click to show edited version of the repro script
```py from __future__ import annotations from fal import cached, function @cached def my_cached_function(): import datetime print("Cached function") return datetime.datetime.now() @function(machine_type="S", serve=False) def hello_query(): name: str = "Louis" started_at = my_cached_function() print(started_at, f"Messaged by: {name}") return f"Hello, {name}" # Now with pydantic dataclasses for the payload from pydantic.dataclasses import dataclass @dataclass class HelloModel: name: str @function(machine_type="S", serve=False) def hello_dataclass(): data: HelloModel = HelloModel(name="Louis") started_at = my_cached_function() print(started_at, f"Messaged by: {data.name}") return f"Hello, {data.name}" ```- I changed the decorator param to
serve=Falseto reproduce a little more minimally. - I removed the string/dataclass from the function signatures just to simplify calling it.
We can run hello_query
$ fal fn run demo.py hello_query
2024-01-18 22:11:38.933 [stdout ] Cached function
2024-01-18 22:11:38.933 [stdout ] 2024-01-18 22:11:38.932910 Messaged by: LouisWe cannot run hello_dataclass
$ fal fn run demo.py hello_dataclass
Error while serializing the given objectI would try a debugging approach that stays in Python rather than CLI (shell level) to get more visibility.
The stack trace shows it's emerging from dill
What's more if I use a Pydantic model it fails more verbosely [error shown with no --debug flag] and seems to indicate that the virtualenv cached directory does not have the necessary Pydantic module...
$ fal fn run demo.py hello_data_model
2024-01-18 22:38:55.311 [error ] Traceback (most recent call last):
File "/root/.cache/isolate/virtualenv/dd85ba8a65db645667152bcadfce1749d4fbd40765c63ba1d368c48eafe9c34e/lib/python3.11/site-packages/isolate/connections/common.py", line 40, in _step
yield
File "/root/.cache/isolate/virtualenv/dd85ba8a65db645667152bcadfce1749d4fbd40765c63ba1d368c48eafe9c34e/lib/python3.11/site-packages/isolate/connections/common.py", line 77, in load_serialized_object
result = serialization_backend.loads(raw_object)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/.cache/isolate/virtualenv/dd85ba8a65db645667152bcadfce1749d4fbd40765c63ba1d368c48eafe9c34e/lib/python3.11/site-packages/dill/_dill.py", line 301, in loads
return load(file, ignore, **kwds)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/.cache/isolate/virtualenv/dd85ba8a65db645667152bcadfce1749d4fbd40765c63ba1d368c48eafe9c34e/lib/python3.11/site-packages/dill/_dill.py", line 287, in load
return Unpickler(file, ignore=ignore, **kwds).load()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/.cache/isolate/virtualenv/dd85ba8a65db645667152bcadfce1749d4fbd40765c63ba1d368c48eafe9c34e/lib/python3.11/site-packages/dill/_dill.py", line 442, in load
obj = StockUnpickler.load(self)
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/.cache/isolate/virtualenv/dd85ba8a65db645667152bcadfce1749d4fbd40765c63ba1d368c48eafe9c34e/lib/python3.11/site-packages/dill/_dill.py", line 432, in find_class
return StockUnpickler.find_class(self, module, name)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ModuleNotFoundError: No module named 'pydantic'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/venv/lib/python3.11/site-packages/isolate/connections/grpc/agent.py", line 113, in execute_function
function = from_grpc(function)
^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/functools.py", line 909, in wrapper
return dispatch(args[0].__class__)(*args, **kw)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/.cache/isolate/virtualenv/dd85ba8a65db645667152bcadfce1749d4fbd40765c63ba1d368c48eafe9c34e/lib/python3.11/site-packages/isolate/connections/grpc/interface.py", line 29, in _
return load_serialized_object(
^^^^^^^^^^^^^^^^^^^^^^^
File "/root/.cache/isolate/virtualenv/dd85ba8a65db645667152bcadfce1749d4fbd40765c63ba1d368c48eafe9c34e/lib/python3.11/site-packages/isolate/connections/common.py", line 76, in load_serialized_object
with _step("deserializing the given object"):
File "/usr/local/lib/python3.11/contextlib.py", line 158, in __exit__
self.gen.throw(typ, value, traceback)
File "/root/.cache/isolate/virtualenv/dd85ba8a65db645667152bcadfce1749d4fbd40765c63ba1d368c48eafe9c34e/lib/python3.11/site-packages/isolate/connections/common.py", line 42, in _step
raise SerializationError("Error while " + message) from exception
isolate.connections.common.SerializationError: Error while deserializing the given object
Function execution quit unexpectedly. Error contents: The function function could not be deserialized.I get the impression this is the same error as the one raised from the Pydantic dataclass, but a bit clearer (no need to --debug to see it)
I checked and in fact this seems to have been cut off from the traceback you shared, it's the upstream cause of the 2nd exception in both cases though.
Tested with the diff https://github.com/fal-ai/fal/compare/main...matteo/pydantic2-test
I was trying out what the migration to Pydantic 2 could look like and I get the following:
Runing the query version it works as expected and can be used
But when I try to use the dataclass version I get an error
Notice this error while deserializing seems to be local (gRPC deserializing?)
Specifically, running the above command with
--debugI get