refactor protocol model extraction to only check extra parameters (#436)

ragna/core/_components.py

@@ -4,7 +4,15 @@
 import enum
 import functools
 import inspect
-from typing import AsyncIterable, AsyncIterator, Iterator, Optional, Type, Union
+from typing import (
+    AsyncIterable,
+    AsyncIterator,
+    Iterator,
+    Optional,
+    Type,
+    Union,
+    get_type_hints,
+)
 
 import pydantic
 import pydantic.utils
@@ -42,30 +50,47 @@ def __repr__(self) -> str:
     def _protocol_models(
         cls,
     ) -> dict[tuple[Type[Component], str], Type[pydantic.BaseModel]]:
+        # This method dynamically builds a pydantic.BaseModel for the extra parameters
+        # of each method that is listed in the __ragna_protocol_methods__ class
+        # variable. These models are used by ragna.core.Chat._unpack_chat_params to
+        # validate and distribute the **params passed by the user.
+
+        # Walk up the MRO until we find the __ragna_protocol_methods__ variable. This is
+        # the indicator that we found the protocol class. We use this as a reference for
+        # which params of a protocol method are part of the protocol (think positional
+        # parameters) and which are requested by the concrete class (think keyword
+        # parameters).
         protocol_cls, protocol_methods = next(
             (cls_, cls_.__ragna_protocol_methods__)  # type: ignore[attr-defined]
             for cls_ in cls.__mro__
             if "__ragna_protocol_methods__" in cls_.__dict__
         )
         models = {}
         for method_name in protocol_methods:
+            num_protocol_params = len(
+                inspect.signature(getattr(protocol_cls, method_name)).parameters
+            )
             method = getattr(cls, method_name)
-            concrete_params = inspect.signature(method).parameters
-            protocol_params = inspect.signature(
-                getattr(protocol_cls, method_name)
-            ).parameters
-            extra_param_names = concrete_params.keys() - protocol_params.keys()
-
-            models[(cls, method_name)] = pydantic.create_model(  # type: ignore[call-overload]
+            params = iter(inspect.signature(method).parameters.values())
+            annotations = get_type_hints(method)
+            # Skip over the protocol parameters in order for the model below to only
+            # comprise concrete parameters.
+            for _ in range(num_protocol_params):
+                next(params)
+
+            models[(cls, method_name)] = pydantic.create_model(
+                # type: ignore[call-overload]
                 f"{cls.__name__}.{method_name}",
                 **{
-                    (param := concrete_params[param_name]).name: (
-                        param.annotation,
-                        param.default
-                        if param.default is not inspect.Parameter.empty
-                        else ...,
+                    param.name: (
+                        annotations[param.name],
+                        (
+                            param.default
+                            if param.default is not inspect.Parameter.empty
+                            else ...
+                        ),
                     )
-                    for param_name in extra_param_names
+                    for param in params
                 },
             )
         return models

ragna/core/_rag.py

@@ -1,8 +1,11 @@
 from __future__ import annotations
 
+import contextlib
 import datetime
 import inspect
+import itertools
 import uuid
+from collections import defaultdict
 from typing import (
     Any,
     AsyncIterator,
@@ -19,6 +22,7 @@
 )
 
 import pydantic
+import pydantic_core
 from starlette.concurrency import iterate_in_threadpool, run_in_threadpool
 
 from ._components import Assistant, Component, Message, MessageRole, SourceStorage
@@ -251,27 +255,120 @@ def _parse_documents(self, documents: Iterable[Any]) -> list[Document]:
     def _unpack_chat_params(
         self, params: dict[str, Any]
     ) -> dict[Callable, dict[str, Any]]:
+        # This method does two things:
+        # 1. Validate the **params against the signatures of the protocol methods of the
+        #    used components. This makes sure that
+        #    - No parameter is passed that isn't used by at least one component
+        #    - No parameter is missing that is needed by at least one component
+        #    - No parameter is passed in the wrong type
+        # 2. Prepare the distribution of the parameters to the protocol method that
+        #    requested them. The actual distribution happens in self._run and
+        #    self._run_gen, but is only a dictionary lookup by then.
         component_models = {
             getattr(component, name): model
             for component in [self.source_storage, self.assistant]
             for (_, name), model in component._protocol_models().items()
         }
 
         ChatModel = merge_models(
-            str(self.params["chat_id"]),
+            f"{self.__module__}.{type(self).__name__}-{self.params['chat_id']}",
             SpecialChatParams,
             *component_models.values(),
             config=pydantic.ConfigDict(extra="forbid"),
         )
 
-        chat_params = ChatModel.model_validate(params, strict=True).model_dump(
-            exclude_none=True
-        )
+        with self._format_validation_error(ChatModel):
+            chat_model = ChatModel.model_validate(params, strict=True)
+
+        chat_params = chat_model.model_dump(exclude_none=True)
         return {
             fn: model(**chat_params).model_dump()
             for fn, model in component_models.items()
         }
 
+    @contextlib.contextmanager
+    def _format_validation_error(
+        self, model_cls: type[pydantic.BaseModel]
+    ) -> Iterator[None]:
+        try:
+            yield
+        except pydantic.ValidationError as validation_error:
+            errors = defaultdict(list)
+            for error in validation_error.errors():
+                errors[error["type"]].append(error)
+
+            parts = [
+                f"Validating the Chat parameters resulted in {validation_error.error_count()} errors:",
+                "",
+            ]
+
+            def format_error(
+                error: pydantic_core.ErrorDetails,
+                *,
+                annotation: bool = False,
+                value: bool = False,
+            ) -> str:
+                param = cast(str, error["loc"][0])
+
+                formatted_error = f"- {param}"
+                if annotation:
+                    annotation_ = cast(
+                        type, model_cls.model_fields[param].annotation
+                    ).__name__
+                    formatted_error += f": {annotation_}"
+
+                if value:
+                    value_ = error["input"]
+                    formatted_error += (
+                        f" = {value_!r}" if annotation else f"={value_!r}"
+                    )
+
+                return formatted_error
+
+            if "extra_forbidden" in errors:
+                parts.extend(
+                    [
+                        "The following parameters are unknown:",
+                        "",
+                        *[
+                            format_error(error, value=True)
+                            for error in errors["extra_forbidden"]
+                        ],
+                        "",
+                    ]
+                )
+
+            if "missing" in errors:
+                parts.extend(
+                    [
+                        "The following parameters are missing:",
+                        "",
+                        *[
+                            format_error(error, annotation=True)
+                            for error in errors["missing"]
+                        ],
+                        "",
+                    ]
+                )
+
+            type_errors = ["string_type", "int_type", "float_type", "bool_type"]
+            if any(type_error in errors for type_error in type_errors):
+                parts.extend(
+                    [
+                        "The following parameters have the wrong type:",
+                        "",
+                        *[
+                            format_error(error, annotation=True, value=True)
+                            for error in itertools.chain.from_iterable(
+                                errors[type_error] for type_error in type_errors
+                            )
+                        ],
+                        "",
+                    ]
+                )
+
+            raise RagnaException("\n".join(parts))
+
     async def _run(
         self, fn: Union[Callable[..., T], Callable[..., Awaitable[T]]], *args: Any
     ) -> T:

tests/core/test_rag.py

@@ -1,8 +1,7 @@
-import pydantic
 import pytest
 
 from ragna import Rag, assistants, source_storages
-from ragna.core import LocalDocument
+from ragna.core import Assistant, LocalDocument, RagnaException
 
 
 @pytest.fixture()
@@ -14,20 +13,84 @@ def demo_document(tmp_path, request):
 
 
 class TestChat:
-    def chat(self, documents, **params):
+    def chat(
+        self,
+        documents,
+        source_storage=source_storages.RagnaDemoSourceStorage,
+        assistant=assistants.RagnaDemoAssistant,
+        **params,
+    ):
         return Rag().chat(
             documents=documents,
-            source_storage=source_storages.RagnaDemoSourceStorage,
-            assistant=assistants.RagnaDemoAssistant,
+            source_storage=source_storage,
+            assistant=assistant,
             **params,
         )
 
-    def test_extra_params(self, demo_document):
-        with pytest.raises(pydantic.ValidationError, match="not_supported_parameter"):
+    def test_params_validation_unknown(self, demo_document):
+        params = {
+            "bool_param": False,
+            "int_param": 1,
+            "float_param": 0.5,
+            "string_param": "arbitrary_value",
+        }
+        with pytest.raises(RagnaException, match="unknown") as exc_info:
+            self.chat(documents=[demo_document], **params)
+
+        msg = str(exc_info.value)
+        for param, value in params.items():
+            assert f"{param}={value!r}" in msg
+
+    def test_params_validation_missing(self, demo_document):
+        class ValidationAssistant(Assistant):
+            def answer(
+                self,
+                prompt,
+                sources,
+                bool_param: bool,
+                int_param: int,
+                float_param: float,
+                string_param: str,
+            ):
+                pass
+
+        with pytest.raises(RagnaException, match="missing") as exc_info:
+            self.chat(documents=[demo_document], assistant=ValidationAssistant)
+
+        msg = str(exc_info.value)
+        for param, annotation in ValidationAssistant.answer.__annotations__.items():
+            assert f"{param}: {annotation.__name__}" in msg
+
+    def test_params_validation_wrong_type(self, demo_document):
+        class ValidationAssistant(Assistant):
+            def answer(
+                self,
+                prompt,
+                sources,
+                bool_param: bool,
+                int_param: int,
+                float_param: float,
+                string_param: str,
+            ):
+                pass
+
+        params = {
+            "bool_param": 1,
+            "int_param": 0.5,
+            "float_param": "arbitrary_value",
+            "string_param": False,
+        }
+
+        with pytest.raises(RagnaException, match="wrong type") as exc_info:
             self.chat(
-                documents=[demo_document], not_supported_parameter="arbitrary_value"
+                documents=[demo_document], assistant=ValidationAssistant, **params
             )
 
+        msg = str(exc_info.value)
+        for param, value in params.items():
+            annotation = ValidationAssistant.answer.__annotations__[param]
+            assert f"{param}: {annotation.__name__} = {value!r}" in msg
+
     def test_document_path(self, demo_document):
         chat = self.chat(documents=[demo_document.path])