Files
crewAI/src/crewai/utilities/pydantic_schema_parser.py
Lorenze Jay 5ac7050f7a Patch/non gpt model pydantic output (#1003)
* patching for non-gpt model

* removal of json_object tool name assignment

* fixed issue for smaller models due to instructions prompt

* fixing for ollama llama3 models

* closing brackets

* removed not used and fixes
2024-07-26 10:57:56 -07:00

43 lines
1.6 KiB
Python

from typing import Type, get_args, get_origin
from pydantic import BaseModel
class PydanticSchemaParser(BaseModel):
model: Type[BaseModel]
def get_schema(self) -> str:
"""
Public method to get the schema of a Pydantic model.
:param model: The Pydantic model class to generate schema for.
:return: String representation of the model schema.
"""
return self._get_model_schema(self.model)
def _get_model_schema(self, model, depth=0) -> str:
indent = " " * depth
lines = [f"{indent}{{"]
for field_name, field in model.model_fields.items():
field_type_str = self._get_field_type(field, depth + 1)
lines.append(f"{indent} {field_name}: {field_type_str},")
lines[-1] = lines[-1].rstrip(",") # Remove trailing comma from last item
lines.append(f"{indent}}}")
return "\n".join(lines)
def _get_field_type(self, field, depth) -> str:
field_type = field.annotation
if get_origin(field_type) is list:
list_item_type = get_args(field_type)[0]
if isinstance(list_item_type, type) and issubclass(
list_item_type, BaseModel
):
nested_schema = self._get_model_schema(list_item_type, depth + 1)
return f"List[\n{nested_schema}\n{' ' * 4 * depth}]"
else:
return f"List[{list_item_type.__name__}]"
elif issubclass(field_type, BaseModel):
return self._get_model_schema(field_type, depth)
else:
return field_type.__name__