fix!: ModelResponse was replaced by RunnerResult (#157)

fix!: StructuredResponse replaced by RunnerResult with new "parsed"
property
fix!: AgentResult replaced by RunnerResult and Managed Result
fix!: Removed ModelRunner and AgentRunner protocols
fix!: Removed invoke_method, invoke_structured_model from AIProvider
base class.

Author: jsonbailey

packages/sdk/server-ai/src/ldai/__init__.py

@@ -35,8 +35,6 @@
     AgentGraphResult,
     AgentGraphRunner,
     AgentGraphRunnerResult,
-    AgentResult,
-    AgentRunner,
     GraphMetrics,
     GraphMetricSummary,
     ManagedGraphResult,
@@ -51,9 +49,7 @@
 __all__ = [
     'LDAIClient',
     'Evaluator',
-    'AgentRunner',
     'AgentGraphRunner',
-    'AgentResult',
     'AgentGraphResult',
     'AgentGraphRunnerResult',
     'GraphMetrics',

packages/sdk/server-ai/src/ldai/managed_model.py

@@ -4,7 +4,7 @@
 from ldai import log
 from ldai.models import AICompletionConfig, LDMessage
 from ldai.providers.runner import Runner
-from ldai.providers.types import JudgeResult, ManagedResult
+from ldai.providers.types import JudgeResult, ManagedResult, RunnerResult
 from ldai.tracker import LDAIConfigTracker
 
 
@@ -46,7 +46,7 @@ async def run(self, prompt: str) -> ManagedResult:
         config_messages = self._ai_config.messages or []
         all_messages = config_messages + self._messages
 
-        result = await tracker.track_metrics_of_async(
+        result: RunnerResult = await tracker.track_metrics_of_async(
             lambda r: r.metrics,
             lambda: self._model_runner.run(all_messages),
         )

packages/sdk/server-ai/src/ldai/providers/__init__.py

@@ -1,22 +1,17 @@
 from ldai.providers.agent_graph_runner import AgentGraphRunner
-from ldai.providers.agent_runner import AgentRunner
 from ldai.providers.ai_provider import AIProvider
-from ldai.providers.model_runner import ModelRunner
 from ldai.providers.runner import Runner
 from ldai.providers.runner_factory import RunnerFactory
 from ldai.providers.types import (
     AgentGraphResult,
     AgentGraphRunnerResult,
-    AgentResult,
     GraphMetrics,
     GraphMetricSummary,
     JudgeResult,
     LDAIMetrics,
     ManagedGraphResult,
     ManagedResult,
-    ModelResponse,
     RunnerResult,
-    StructuredResponse,
     ToolRegistry,
 )
 
@@ -25,19 +20,14 @@
     'AgentGraphResult',
     'AgentGraphRunner',
     'AgentGraphRunnerResult',
-    'AgentResult',
-    'AgentRunner',
     'GraphMetrics',
     'GraphMetricSummary',
     'JudgeResult',
     'LDAIMetrics',
     'ManagedGraphResult',
     'ManagedResult',
-    'ModelResponse',
-    'ModelRunner',
     'Runner',
     'RunnerFactory',
     'RunnerResult',
-    'StructuredResponse',
     'ToolRegistry',
 ]

packages/sdk/server-ai/src/ldai/providers/agent_runner.py

@@ -1,9 +1,8 @@
 from abc import ABC
-from typing import Any, Dict, List, Optional
+from typing import Any, Optional
 
 from ldai import log
-from ldai.models import LDMessage
-from ldai.providers.types import ModelResponse, StructuredResponse, ToolRegistry
+from ldai.providers.types import ToolRegistry
 
 
 class AIProvider(ABC):
@@ -16,51 +15,6 @@ class AIProvider(ABC):
     create_model(), create_agent(), and create_agent_graph().
     """
 
-    async def invoke_model(self, messages: List[LDMessage]) -> ModelResponse:
-        """
-        Invoke the chat model with an array of messages.
-
-        Default implementation takes no action and returns a placeholder response.
-        Provider implementations should override this method.
-
-        :param messages: Array of LDMessage objects representing the conversation
-        :return: ModelResponse containing the model's response
-        """
-        log.warning('invoke_model not implemented by this provider')
-
-        from ldai.models import LDMessage
-        from ldai.providers.types import LDAIMetrics
-
-        return ModelResponse(
-            message=LDMessage(role='assistant', content=''),
-            metrics=LDAIMetrics(success=False, usage=None),
-        )
-
-    async def invoke_structured_model(
-        self,
-        messages: List[LDMessage],
-        response_structure: Dict[str, Any],
-    ) -> StructuredResponse:
-        """
-        Invoke the chat model with structured output support.
-
-        Default implementation takes no action and returns a placeholder response.
-        Provider implementations should override this method.
-
-        :param messages: Array of LDMessage objects representing the conversation
-        :param response_structure: Dictionary of output configurations keyed by output name
-        :return: StructuredResponse containing the structured data
-        """
-        log.warning('invoke_structured_model not implemented by this provider')
-
-        from ldai.providers.types import LDAIMetrics
-
-        return StructuredResponse(
-            data={},
-            raw_response='',
-            metrics=LDAIMetrics(success=False, usage=None),
-        )
-
     def create_model(self, config: Any) -> Optional[Any]:
         """
         Create a configured model executor for the given AI config.

packages/sdk/server-ai/src/ldai/providers/ai_provider.py

@@ -6,7 +6,6 @@
 from dataclasses import dataclass, field
 from typing import Any, Callable, Dict, List, Optional
 
-from ldai.models import LDMessage
 from ldai.tracker import LDAIMetricSummary, TokenUsage
 
 # Type alias for a registry of tools available to an agent.
@@ -87,33 +86,6 @@ class ManagedResult:
     """Optional asyncio Task that resolves to the list of :class:`JudgeResult` instances when awaited."""
 
 
-@dataclass
-class ModelResponse:
-    """
-    Response from a model invocation.
-
-    .. deprecated::
-        Use :class:`RunnerResult` (from a runner) and :class:`ManagedResult`
-        (from the managed layer) instead.
-    """
-    message: LDMessage
-    metrics: LDAIMetrics
-    evaluations: Optional[asyncio.Task[List[JudgeResult]]] = None
-
-
-@dataclass
-class StructuredResponse:
-    """
-    Structured response from AI models.
-
-    .. deprecated::
-        Structured output is now represented by :attr:`RunnerResult.parsed`.
-    """
-    data: Dict[str, Any]
-    raw_response: str
-    metrics: LDAIMetrics
-
-
 @dataclass
 class GraphMetrics:
     """Contains raw metrics from a single agent graph run."""
@@ -234,20 +206,6 @@ def to_dict(self) -> Dict[str, Any]:
         return result
 
 
-@dataclass
-class AgentResult:
-    """
-    Result from a single-agent run.
-
-    .. deprecated::
-        Use :class:`ManagedResult` (managed layer) or :class:`RunnerResult`
-        (runner layer) instead.
-    """
-    output: str
-    raw: Any
-    metrics: LDAIMetrics
-
-
 @dataclass
 class AgentGraphResult:
     """Contains the result of an agent graph run."""

packages/sdk/server-ai/src/ldai/providers/model_runner.py

@@ -1,20 +1,11 @@
 import pytest
 
-from ldai.providers import AgentGraphResult, AgentGraphRunner, AgentRunner, ToolRegistry
+from ldai.providers import AgentGraphResult, AgentGraphRunner, ToolRegistry
 from ldai.providers.types import LDAIMetrics, RunnerResult
 
 
 # --- Concrete test doubles ---
 
-class ConcreteAgentRunner:
-    async def run(self, input):
-        return RunnerResult(
-            content=f"agent response to: {input}",
-            metrics=LDAIMetrics(success=True),
-            raw={"raw": input},
-        )
-
-
 class ConcreteAgentGraphRunner:
     async def run(self, input):
         return AgentGraphResult(
@@ -28,26 +19,6 @@ class MissingRunMethod:
     pass
 
 
-# --- AgentRunner ---
-
-def test_agent_runner_structural_check_passes():
-    assert isinstance(ConcreteAgentRunner(), AgentRunner)
-
-
-def test_agent_runner_structural_check_fails_when_run_missing():
-    assert not isinstance(MissingRunMethod(), AgentRunner)
-
-
-@pytest.mark.asyncio
-async def test_agent_runner_run_returns_runner_result():
-    runner = ConcreteAgentRunner()
-    result = await runner.run("hello")
-    assert isinstance(result, RunnerResult)
-    assert result.content == "agent response to: hello"
-    assert result.raw == {"raw": "hello"}
-    assert result.metrics.success is True
-
-
 @pytest.mark.asyncio
 async def test_runner_result_fields():
     metrics = LDAIMetrics(success=True)
@@ -101,7 +72,6 @@ def test_tool_registry_is_dict_of_callables():
 
 def test_top_level_exports():
     import ldai
-    assert hasattr(ldai, 'AgentRunner')
     assert hasattr(ldai, 'AgentGraphRunner')
     assert hasattr(ldai, 'AgentGraphResult')
     assert hasattr(ldai, 'RunnerResult')