fix: seed history with config messages at init instead of prepending per call

Config messages (system prompt, instructions) are added once when the runner
is constructed, not re-injected on every run() call. OpenAI collapses
_config_messages into _history at init; LangChain seeds InMemoryChatMessageHistory
with the converted messages so they appear naturally at the start of the thread.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

Author: jsonbailey

packages/ai-providers/server-ai-langchain/src/ldai_langchain/langchain_model_runner.py

@@ -27,8 +27,9 @@ class LangChainModelRunner(Runner):
 
     def __init__(self, llm: BaseChatModel, config_messages: Optional[List[LDMessage]] = None):
         self._llm = llm
-        self._config_messages: List[LDMessage] = list(config_messages or [])
-        self._chat_history = InMemoryChatMessageHistory()
+        self._chat_history = InMemoryChatMessageHistory(
+            messages=convert_messages_to_langchain(config_messages or [])
+        )
 
     def get_llm(self) -> BaseChatModel:
         """
@@ -46,10 +47,10 @@ async def run(
         """
         Run the LangChain model with the given input.
 
-        Prepends config messages and accumulated conversation history (stored as
-        native LangChain messages via InMemoryChatMessageHistory) before the user
-        message. On success, appends the exchange to chat history so subsequent
-        calls include prior context.
+        Sends the full chat history (seeded with config messages at construction
+        time via InMemoryChatMessageHistory) plus the new user message. On
+        success, appends the user/assistant exchange so subsequent calls include
+        prior context.
 
         :param input: A string prompt
         :param output_type: Optional JSON schema dict requesting structured output.
@@ -58,11 +59,7 @@ async def run(
         :return: :class:`RunnerResult` containing ``content``, ``metrics``,
             ``raw`` and (when ``output_type`` is set) ``parsed``.
         """
-        langchain_messages = (
-            convert_messages_to_langchain(self._config_messages)
-            + self._chat_history.messages
-            + [HumanMessage(content=input)]
-        )
+        langchain_messages = self._chat_history.messages + [HumanMessage(content=input)]
 
         if output_type is not None:
             result = await self._run_structured(langchain_messages, output_type)

packages/ai-providers/server-ai-openai/src/ldai_openai/openai_model_runner.py

@@ -33,8 +33,7 @@ def __init__(
         self._client = client
         self._model_name = model_name
         self._parameters = parameters
-        self._config_messages: List[LDMessage] = list(config_messages or [])
-        self._history: List[LDMessage] = []
+        self._history: List[LDMessage] = list(config_messages or [])
 
     async def run(
         self,
@@ -44,9 +43,9 @@ async def run(
         """
         Run the OpenAI model with the given input.
 
-        Prepends config messages and accumulated conversation history before the
-        user message. On success, appends the user/assistant exchange to history
-        so subsequent calls include prior context.
+        Sends the full conversation history (seeded with config messages at
+        construction time) plus the new user message. On success, appends the
+        user/assistant exchange to history so subsequent calls include prior context.
 
         :param input: A string prompt
         :param output_type: Optional JSON schema dict requesting structured output.
@@ -56,7 +55,7 @@ async def run(
             ``raw`` and (when ``output_type`` is set) ``parsed``.
         """
         user_message = LDMessage(role='user', content=input)
-        messages = self._config_messages + self._history + [user_message]
+        messages = self._history + [user_message]
 
         if output_type is not None:
             result = await self._run_structured(messages, output_type)