Fix agenerate behaviour

src/agentics/core/agentics.py

@@ -94,7 +94,7 @@ class AG(BaseModel, Generic[T]):
         None,
         description="""Python code for the used type""",
     )
-    states: List[BaseModel] = []
+    states: List[BaseModel] = Field(default_factory=list)
     tools: Optional[List[Any]] = Field(None, exclude=True)
     transduce_fields: Optional[List[str]] = Field(
         None,
@@ -549,6 +549,48 @@ async def llm_call(input: AGString) -> AGString:
             if self.transduce_fields
             else self.atype
         )
+
+        # If self has no states, we need to initialize with empty states based on the input
+        if len(self.states) == 0:
+            # Helper function to create an empty state, handling required fields
+            def create_empty_state():
+                try:
+                    return self.atype()
+                except Exception:
+                    # If the model has required fields, use model_construct with defaults
+                    # Get default values for all fields
+                    defaults = {}
+                    for field_name, field_info in self.atype.model_fields.items():
+                        if field_info.is_required():
+                            # Provide sensible defaults based on field type
+                            if hasattr(field_info.annotation, "__origin__"):
+                                origin = field_info.annotation.__origin__
+                                if origin is list:
+                                    defaults[field_name] = []
+                                elif origin is dict:
+                                    defaults[field_name] = {}
+                                else:
+                                    defaults[field_name] = None
+                            else:
+                                defaults[field_name] = None
+                    return self.atype.model_construct(**defaults)
+
+            if isinstance(other, AG):
+                # Match the number of states in other
+                self.states = [create_empty_state() for _ in range(len(other.states))]
+            elif is_str_or_list_of_str(other):
+                # For strings or list of strings, create one state per input
+                if isinstance(other, str):
+                    self.states = [create_empty_state()]
+                else:
+                    self.states = [create_empty_state() for _ in range(len(other))]
+            elif isinstance(other, list):
+                # For other lists, create one state per item
+                self.states = [create_empty_state() for _ in range(len(other))]
+            else:
+                # For single non-list inputs, create one state
+                self.states = [create_empty_state()]
+
         if isinstance(other, AG):
             if other.prompt_template:
                 prompt_template = PromptTemplate.from_template(other.prompt_template)
@@ -673,19 +715,37 @@ async def llm_call(input: AGString) -> AGString:
                 )
                 allowed = self.atype.model_fields.keys()  # pydantic v2
                 filtered = {k: v for k, v in data.items() if k in allowed}
-                merged = self.atype(**filtered)
+                try:
+                    merged = self.atype(**filtered)
+                except Exception:
+                    # If validation fails due to missing required fields, use model_construct with defaults
+                    defaults = {}
+                    for field_name, field_info in self.atype.model_fields.items():
+                        if field_info.is_required() and field_name not in filtered:
+                            # Provide sensible defaults based on field type
+                            if hasattr(field_info.annotation, "__origin__"):
+                                origin = field_info.annotation.__origin__
+                                if origin is list:
+                                    defaults[field_name] = []
+                                elif origin is dict:
+                                    defaults[field_name] = {}
+                                else:
+                                    defaults[field_name] = None
+                            else:
+                                defaults[field_name] = None
+                    merged = self.atype.model_construct(**{**defaults, **filtered})
 
                 output.states.append(merged)
         # elif is_str_or_list_of_str(other):
         elif isinstance(other, list):
             for i in range(len(other)):
-                if isinstance(output_states[i], self.atype):
+                if i < len(output_states) and isinstance(output_states[i], self.atype):
                     output.states.append(self.atype(**output_states[i].model_dump()))
                 else:
                     output.states.append(self.atype())
         else:
-            if isinstance(output_states[0], self.atype):
-                output.states.append(self.atype(**output_states[i].model_dump()))
+            if len(output_states) > 0 and isinstance(output_states[0], self.atype):
+                output.states.append(self.atype(**output_states[0].model_dump()))
 
         if self.provide_explanations and isinstance(other, AG):
             target_explanation = AG(atype=Explanation)

tests/official_tests/transducible_functions.py

@@ -37,4 +37,4 @@ async def write_an_email(state: GenericInput) -> Email:
         )
     )
 )
-print(single_mail.model_dump_json(indent=2))
+print(single_mail.value.model_dump_json(indent=2))

tutorials/transducible_functions.ipynb

@@ -281,7 +281,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.12"
+   "version": "3.11.14"
   }
  },
  "nbformat": 4,