Improve naming of models.py -> Feels like ML models, not datamodels. …

…Use __init__ level so it's improted as .datamodel instead

libs/core/kiln_ai/adapters/base_adapter.py

@@ -2,8 +2,8 @@
 from abc import ABCMeta, abstractmethod
 from typing import Dict
 
+from kiln_ai.datamodel import Task
 from kiln_ai.datamodel.json_schema import validate_schema
-from kiln_ai.datamodel.models import Task
 
 
 class BaseAdapter(metaclass=ABCMeta):

libs/core/kiln_ai/adapters/langchain_adapters.py

@@ -1,6 +1,6 @@
 from typing import Dict
 
-import kiln_ai.datamodel.models as models
+import kiln_ai.datamodel as datamodel
 from kiln_ai.adapters.prompt_builders import SimplePromptBuilder
 from langchain_core.language_models.chat_models import BaseChatModel
 from langchain_core.messages import HumanMessage, SystemMessage
@@ -13,7 +13,7 @@
 class LangChainPromptAdapter(BaseAdapter):
     def __init__(
         self,
-        kiln_task: models.Task,
+        kiln_task: datamodel.Task,
         custom_model: BaseChatModel | None = None,
         model_name: str | None = None,
         provider: str | None = None,

libs/core/kiln_ai/adapters/test_prompt_adaptors.py

@@ -1,7 +1,7 @@
 import os
 from pathlib import Path
 
-import kiln_ai.datamodel.models as models
+import kiln_ai.datamodel as datamodel
 import pytest
 from kiln_ai.adapters.langchain_adapters import LangChainPromptAdapter
 from kiln_ai.adapters.ml_model_list import built_in_models, ollama_online
@@ -95,30 +95,30 @@ async def test_all_built_in_models(tmp_path):
 
 
 def build_test_task(tmp_path: Path):
-    project = models.Project(name="test", path=tmp_path / "test.kiln")
+    project = datamodel.Project(name="test", path=tmp_path / "test.kiln")
     project.save_to_file()
     assert project.name == "test"
 
-    task = models.Task(parent=project, name="test task")
+    task = datamodel.Task(parent=project, name="test task")
     task.save_to_file()
     assert task.name == "test task"
     task.instruction = (
         "You are an assistant which performs math tasks provided in plain text."
     )
 
-    r1 = models.TaskRequirement(
+    r1 = datamodel.TaskRequirement(
         parent=task,
         name="BEDMAS",
         instruction="You follow order of mathematical operation (BEDMAS)",
     )
     r1.save_to_file()
-    r2 = models.TaskRequirement(
+    r2 = datamodel.TaskRequirement(
         parent=task,
         name="only basic math",
         instruction="If the problem has anything other than addition, subtraction, multiplication, division, and brackets, you will not answer it. Reply instead with 'I'm just a basic calculator, I don't know how to do that'.",
     )
     r2.save_to_file()
-    r3 = models.TaskRequirement(
+    r3 = datamodel.TaskRequirement(
         parent=task,
         name="Answer format",
         instruction="The answer can contain any content about your reasoning, but at the end it should include the final answer in numerals in square brackets. For example if the answer is one hundred, the end of your response should be [100].",
@@ -133,7 +133,7 @@ async def run_simple_test(tmp_path: Path, model_name: str, provider: str | None
     return await run_simple_task(task, model_name, provider)
 
 
-async def run_simple_task(task: models.Task, model_name: str, provider: str):
+async def run_simple_task(task: datamodel.Task, model_name: str, provider: str):
     adapter = LangChainPromptAdapter(task, model_name=model_name, provider=provider)
 
     answer = await adapter.invoke(

libs/core/kiln_ai/adapters/test_prompt_builders.py

@@ -4,7 +4,7 @@
 from kiln_ai.adapters.prompt_builders import MultiShotPromptBuilder, SimplePromptBuilder
 from kiln_ai.adapters.test_prompt_adaptors import build_test_task
 from kiln_ai.adapters.test_structured_output import build_structured_output_test_task
-from kiln_ai.datamodel.models import (
+from kiln_ai.datamodel import (
     Example,
     ExampleOutput,
     ExampleSource,

libs/core/kiln_ai/adapters/test_structured_output.py

@@ -3,7 +3,7 @@
 
 import jsonschema
 import jsonschema.exceptions
-import kiln_ai.datamodel.models as models
+import kiln_ai.datamodel as datamodel
 import pytest
 from kiln_ai.adapters.base_adapter import BaseAdapter
 from kiln_ai.adapters.langchain_adapters import LangChainPromptAdapter
@@ -51,7 +51,7 @@ async def test_structured_output_ollama_llama(tmp_path):
 
 
 class MockAdapter(BaseAdapter):
-    def __init__(self, kiln_task: models.Task, response: Dict | str | None):
+    def __init__(self, kiln_task: datamodel.Task, response: Dict | str | None):
         super().__init__(kiln_task)
         self.response = response
 
@@ -79,8 +79,8 @@ async def test_mock_unstructred_response(tmp_path):
         answer = await adapter.invoke("You are a mock, send me the response!")
 
     # Should error, expecting a string, not a dict
-    project = models.Project(name="test", path=tmp_path / "test.kiln")
-    task = models.Task(parent=project, name="test task")
+    project = datamodel.Project(name="test", path=tmp_path / "test.kiln")
+    task = datamodel.Task(parent=project, name="test task")
     task.instruction = (
         "You are an assistant which performs math tasks provided in plain text."
     )
@@ -112,9 +112,9 @@ async def test_all_built_in_models_structured_output(tmp_path):
 
 
 def build_structured_output_test_task(tmp_path: Path):
-    project = models.Project(name="test", path=tmp_path / "test.kiln")
+    project = datamodel.Project(name="test", path=tmp_path / "test.kiln")
     project.save_to_file()
-    task = models.Task(
+    task = datamodel.Task(
         parent=project,
         name="test task",
         instruction="You are an assistant which tells a joke, given a subject.",
@@ -148,9 +148,9 @@ async def run_structured_output_test(tmp_path: Path, model_name: str, provider:
 
 
 def build_structured_input_test_task(tmp_path: Path):
-    project = models.Project(name="test", path=tmp_path / "test.kiln")
+    project = datamodel.Project(name="test", path=tmp_path / "test.kiln")
     project.save_to_file()
-    task = models.Task(
+    task = datamodel.Task(
         parent=project,
         name="test task",
         instruction="You are an assistant which classifies a triangle given the lengths of its sides. If all sides are of equal length, the triangle is equilateral. If two sides are equal, the triangle is isosceles. Otherwise, it is scalene.\n\nAt the end of your response return the result in double square brackets. It should be plain text. It should be exactly one of the three following strings: '[[equilateral]]', or '[[isosceles]]', or '[[scalene]]'.",

libs/core/kiln_ai/datamodel/models.py → libs/core/kiln_ai/datamodel/__init__.py

@@ -13,7 +13,7 @@
 from .json_schema import validate_schema
 
 if TYPE_CHECKING:
-    from .models import Task
+    from . import Task
 
 # Conventions:
 # 1) Names are filename safe as they may be used as file names. They are informational and not to be used in prompts/training/validation.

libs/core/kiln_ai/datamodel/test_example_models.py

@@ -1,7 +1,7 @@
 import json
 
 import pytest
-from kiln_ai.datamodel.models import (
+from kiln_ai.datamodel import (
     Example,
     ExampleOutput,
     ExampleOutputSource,

libs/core/kiln_ai/datamodel/test_models.py

@@ -1,7 +1,7 @@
 import json
 
 import pytest
-from kiln_ai.datamodel.models import Priority, Project, Task, TaskDeterminism
+from kiln_ai.datamodel import Priority, Project, Task, TaskDeterminism
 from kiln_ai.datamodel.test_json_schema import json_joke_schema
 from pydantic import ValidationError