Merge pull request #59 from bmritz/48-allow-function-calls-with-non-k…

…eyword-args

closes #47: Add in the ability to call ghostfunctions with non-keyword arguments

src/ai_ghostfunctions/ghostfunctions.py

@@ -19,9 +19,13 @@
 
 
 def _make_chatgpt_message_from_function(
-    f: Callable[..., Any], **kwargs: Any
+    f: Callable[..., Any], *args: Any, **kwargs: Any
 ) -> Message:
     sig = inspect.signature(f)
+    if args:
+        params = list(sig.parameters)
+        for i, arg in enumerate(args):
+            kwargs[params[i]] = arg
     if not f.__doc__:
         raise ValueError("The function must have a docstring.")
     prompt = (
@@ -41,7 +45,9 @@ def _make_chatgpt_message_from_function(
     return Message(role=USER, content=prompt)
 
 
-def _default_prompt_creation(f: Callable[..., Any], **kwargs: Any) -> List[Message]:
+def _default_prompt_creation(
+    f: Callable[..., Any], *args: Any, **kwargs: Any
+) -> List[Message]:
     return [
         Message(
             role=SYSTEM,
@@ -64,7 +70,7 @@ def _default_prompt_creation(f: Callable[..., Any], **kwargs: Any) -> List[Messa
                 " I will return the output, and nothing else."
             ),
         ),
-        _make_chatgpt_message_from_function(f, **kwargs),
+        _make_chatgpt_message_from_function(f, *args, **kwargs),
     ]
 
 
@@ -148,8 +154,8 @@ def ghostfunction(
         return_type_annotation = get_type_hints(function)["return"]
 
         @wraps(function)
-        def wrapper(**kwargs_inner: Any) -> Any:
-            prompt = prompt_function(function, **kwargs_inner)  # type: ignore[arg-type]
+        def wrapper(*args_inner: Any, **kwargs_inner: Any) -> Any:
+            prompt = prompt_function(function, *args_inner, **kwargs_inner)  # type: ignore[arg-type]
             ai_result = ai_callable(messages=prompt, **kwargs)  # type: ignore[misc]
             return _parse_ai_result(
                 ai_result=ai_result, expected_return_type=return_type_annotation

tests/test_ghostfunctions.py

@@ -148,6 +148,39 @@ def generate_n_random_words(n: int, startswith: str) -> annotation:
     assert result == expected_result
 
 
+@pytest.mark.parametrize(
+    "expected_result,annotation",
+    [
+        ("return a string", str),
+    ],
+)
+def test_ghostfunction_can_be_called_with_positional_arguments(
+    expected_result: Any, annotation: Any
+) -> None:
+    mock_return_result = str(expected_result)
+
+    mock_callable = Mock(
+        return_value=openai.openai_object.OpenAIObject.construct_from(
+            {"choices": [{"message": {"content": mock_return_result}}]}
+        )
+    )
+    with patch.object(
+        ai_ghostfunctions.ghostfunctions,
+        "_default_ai_callable",
+        return_value=mock_callable,
+    ):
+
+        @ghostfunction
+        def generate_n_random_words(n: int, startswith: str) -> annotation:
+            """Return a list of `n` random words that start with `startswith`."""
+            pass
+
+        result = generate_n_random_words(5, "goo")
+        result2 = generate_n_random_words(5, startswith="goo")
+
+    assert result == result2 == expected_result
+
+
 def test_ghostfunction_decorator_errors_if_no_return_type_annotation() -> None:
     expected_result = "returned value from openai"