great

Author: koaning

smartfunc/__init__.py

@@ -1,3 +1,4 @@
+import datetime 
 from functools import wraps
 import inspect
 from typing import Callable, get_type_hints, Any, Optional, Type
@@ -66,6 +67,19 @@ def _process_response(response_text: str, return_type: Optional[Type[BaseModel]]
         return json.loads(response_text)
     return response_text
 
+def _prepare_debug_info(backend, func: Callable, all_kwargs: dict, formatted_docstring: str, return_type: Optional[Type[BaseModel]] = None) -> dict:
+    if return_type:
+        return_type = return_type.model_json_schema()
+    return {
+        "template": func.__doc__,
+        "func_name": func.__name__,
+        "prompt": formatted_docstring,
+        "system": backend.system,
+        "template_inputs": all_kwargs,
+        "backend_kwargs": backend.kwargs,
+        "datetime": datetime.datetime.now().isoformat(),
+        "return_type": return_type,
+    }
 
 class backend:
     """Synchronous backend decorator for LLM-powered functions.
@@ -109,18 +123,14 @@ def wrapper(*args, **kwargs):
                 formatted_docstring,
                 system=self.system,
                 schema=return_type,
-                **kwargs
+                **self.kwargs
             )
             out = _process_response(resp.text(), return_type)
 
             if self.debug:
                 if isinstance(out, str):
                     out = {"result": out}
-                out["_debug"] = {
-                    "prompt": formatted_docstring,
-                    "system": self.system,
-                    "kwargs": all_kwargs,
-                }
+                out["_debug"] = _prepare_debug_info(self, func, all_kwargs, formatted_docstring, return_type)
 
             return out
 
@@ -167,23 +177,21 @@ def __init__(self, name, system=None, debug=False, **kwargs):
     def __call__(self, func: Callable) -> Callable:
         @wraps(func)
         async def wrapper(*args, **kwargs):
-            formatted_docstring, _, return_type = _prepare_function_call(func, args, kwargs)
+            formatted_docstring, all_kwargs, return_type = _prepare_function_call(func, args, kwargs)
 
             resp = await self.model.prompt(
                 formatted_docstring,
                 system=self.system,
                 schema=return_type,
-                **kwargs
+                **self.kwargs
             )
             text = await resp.text()
             out = _process_response(text, return_type)
 
             if self.debug:
-                out["_debug"] = {
-                    "prompt": formatted_docstring,
-                    "system": self.system,
-                    "kwargs": kwargs,
-                }
+                if isinstance(out, str):
+                    out = {"result": out}
+                out["_debug"] = _prepare_debug_info(self, func, all_kwargs, formatted_docstring, return_type)
 
             return out
 

tests/test_basic.py

@@ -40,7 +40,7 @@ def generate_summary(t):
 
     assert isinstance(result, dict)
     assert result["_debug"]["prompt"] == "Generate a summary of the following text: Hello, world!"
-    assert result["_debug"]["kwargs"] == {"t": "Hello, world!"}
+    assert result["_debug"]["template_inputs"] == {"t": "Hello, world!"}
     assert result["_debug"]["system"] == "You are a helpful assistant."
     assert result["result"]
 
@@ -56,7 +56,41 @@ def generate_summary(a, b, c):
 
     assert isinstance(result, dict)
     assert result["_debug"]["prompt"] == "Generate a summary of the following text: Hello world !"
-    assert result["_debug"]["kwargs"] == {"a": "Hello", "b": "world", "c": "!"}
+    assert result["_debug"]["template_inputs"] == {"a": "Hello", "b": "world", "c": "!"}
     assert result["_debug"]["system"] == "You are a helpful assistant."
     assert result["result"]
-    
+
+
+def test_debug_info_keys():
+    """Test that all expected debug info keys are present with correct types"""
+    @backend("markov", debug=True, system="You are a helpful assistant.")
+    def generate_summary(text):
+        """Generate a summary of the following text: {{ text }}"""
+        pass
+
+    result = generate_summary("Hello, world!")
+    debug_info = result["_debug"]
+    
+    # Check all expected keys are present
+    expected_keys = {
+        "template": str,  # Original docstring template
+        "func_name": str,  # Name of the function
+        "prompt": str,    # Rendered prompt
+        "system": str,    # System prompt
+        "template_inputs": dict,  # Arguments used in template
+        "backend_kwargs": dict,   # Backend configuration
+        "datetime": str,   # ISO format datetime
+        "return_type": type(None)  # None since no return type specified
+    }
+    
+    for key, expected_type in expected_keys.items():
+        assert key in debug_info, f"Missing debug key: {key}"
+        assert isinstance(debug_info[key], expected_type), f"Incorrect type for {key}: expected {expected_type}, got {type(debug_info[key])}"
+    
+    # Check specific values
+    assert debug_info["template"] == "Generate a summary of the following text: {{ text }}"
+    assert debug_info["func_name"] == "generate_summary"
+    assert debug_info["prompt"] == "Generate a summary of the following text: Hello, world!"
+    assert debug_info["system"] == "You are a helpful assistant."
+    assert debug_info["template_inputs"] == {"text": "Hello, world!"}
+    assert debug_info["return_type"] is None