fix!: Remove stale ManagedModel message management and AgentGraphResult type (#170)

Author: jsonbailey

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

@@ -32,7 +32,6 @@
     ProviderConfig,
 )
 from ldai.providers import (
-    AgentGraphResult,
     AgentGraphRunner,
     AgentGraphRunnerResult,
     GraphMetrics,
@@ -50,7 +49,6 @@
     'LDAIClient',
     'Evaluator',
     'AgentGraphRunner',
-    'AgentGraphResult',
     'AgentGraphRunnerResult',
     'GraphMetrics',
     'GraphMetricSummary',

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

@@ -2,7 +2,7 @@
 from typing import List
 
 from ldai import log
-from ldai.models import AICompletionConfig, LDMessage
+from ldai.models import AICompletionConfig
 from ldai.providers.runner import Runner
 from ldai.providers.types import JudgeResult, ManagedResult, RunnerResult
 from ldai.tracker import LDAIConfigTracker
@@ -12,9 +12,10 @@ class ManagedModel:
     """
     LaunchDarkly managed wrapper for AI model invocations.
 
-    Holds a Runner. Handles conversation management, judge evaluation
-    dispatch, and tracking automatically via ``create_tracker()``.
-    Obtain an instance via ``LDAIClient.create_model()``.
+    Holds a Runner. Handles judge evaluation dispatch and tracking
+    automatically via ``create_tracker()``. Conversation history is
+    managed by the runner. Obtain an instance via
+    ``LDAIClient.create_model()``.
     """
 
     def __init__(
@@ -24,37 +25,26 @@ def __init__(
     ):
         self._ai_config = ai_config
         self._model_runner = model_runner
-        self._messages: List[LDMessage] = []
 
     async def run(self, prompt: str) -> ManagedResult:
         """
         Run the model with a prompt string.
 
-        Appends the prompt to the conversation history, prepends any
-        system messages from the config, delegates to the runner, and
-        appends the response to the history.
+        Delegates to the runner, then dispatches judge evaluations and
+        records tracking metrics.
 
         :param prompt: The user prompt to send to the model
         :return: ManagedResult containing the model's response, metric summary,
             and an optional evaluations task
         """
         tracker = self._ai_config.create_tracker()
 
-        user_message = LDMessage(role='user', content=prompt)
-        self._messages.append(user_message)
-
         result: RunnerResult = await tracker.track_metrics_of_async(
             lambda r: r.metrics,
             lambda: self._model_runner.run(prompt),
         )
 
-        assistant_message = LDMessage(role='assistant', content=result.content)
-
-        input_text = '\r\n'.join(m.content for m in self._messages) if self._messages else ''
-
-        evaluations_task = self._track_judge_results(tracker, input_text, result.content)
-
-        self._messages.append(assistant_message)
+        evaluations_task = self._track_judge_results(tracker, prompt, result.content)
 
         return ManagedResult(
             content=result.content,
@@ -88,25 +78,6 @@ async def _run_and_track(eval_task: asyncio.Task) -> List[JudgeResult]:
 
         return asyncio.create_task(_run_and_track(evaluator_task))
 
-    def get_messages(self, include_config_messages: bool = False) -> List[LDMessage]:
-        """
-        Get all messages in the conversation history.
-
-        :param include_config_messages: When True, prepends config messages.
-        :return: List of conversation messages.
-        """
-        if include_config_messages:
-            return (self._ai_config.messages or []) + self._messages
-        return list(self._messages)
-
-    def append_messages(self, messages: List[LDMessage]) -> None:
-        """
-        Append messages to the conversation history without invoking the model.
-
-        :param messages: Messages to append.
-        """
-        self._messages.extend(messages)
-
     def get_model_runner(self) -> Runner:
         """
         Return the underlying runner for advanced use.

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

@@ -3,7 +3,6 @@
 from ldai.providers.runner import Runner
 from ldai.providers.runner_factory import RunnerFactory
 from ldai.providers.types import (
-    AgentGraphResult,
     AgentGraphRunnerResult,
     GraphMetrics,
     GraphMetricSummary,
@@ -17,7 +16,6 @@
 
 __all__ = [
     'AIProvider',
-    'AgentGraphResult',
     'AgentGraphRunner',
     'AgentGraphRunnerResult',
     'GraphMetrics',

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

@@ -204,20 +204,3 @@ def to_dict(self) -> Dict[str, Any]:
         if self.error_message is not None:
             result['errorMessage'] = self.error_message
         return result
-
-
-@dataclass
-class AgentGraphResult:
-    """Contains the result of an agent graph run."""
-
-    output: str
-    """The agent graph's final output content."""
-
-    raw: Any
-    """The provider-native response object from the graph run."""
-
-    metrics: LDAIMetrics
-    """Metrics recorded during the graph run."""
-
-    evaluations: Optional[List[JudgeResult]] = None
-    """Optional list of judge evaluation results produced for the graph run."""

packages/sdk/server-ai/tests/test_runner_abcs.py

@@ -1,7 +1,6 @@
 import pytest
 
 from ldai.providers import (
-    AgentGraphResult,
     AgentGraphRunner,
     AgentGraphRunnerResult,
     ToolRegistry,
@@ -78,6 +77,5 @@ def test_tool_registry_is_dict_of_callables():
 def test_top_level_exports():
     import ldai
     assert hasattr(ldai, 'AgentGraphRunner')
-    assert hasattr(ldai, 'AgentGraphResult')
     assert hasattr(ldai, 'RunnerResult')
     assert hasattr(ldai, 'ToolRegistry')