feat: LLM - CodeChat - Added support for context

PiperOrigin-RevId: 563934372

tests/unit/aiplatform/test_language_models.py

@@ -2038,6 +2038,7 @@ def test_code_chat(self):
         )
 
         code_chat = model.start_chat(
+            context="We're working on large-scale production system.",
             max_output_tokens=128,
             temperature=0.2,
             stop_sequences=["\n"],

vertexai/language_models/_language_models.py

@@ -1287,6 +1287,7 @@ class CodeChatModel(_ChatModelBase):
         code_chat_model = CodeChatModel.from_pretrained("codechat-bison@001")
 
         code_chat = code_chat_model.start_chat(
+            context="I'm writing a large-scale enterprise application.",
             max_output_tokens=128,
             temperature=0.2,
         )
@@ -1301,6 +1302,7 @@ class CodeChatModel(_ChatModelBase):
     def start_chat(
         self,
         *,
+        context: Optional[str] = None,
         max_output_tokens: Optional[int] = None,
         temperature: Optional[float] = None,
         message_history: Optional[List[ChatMessage]] = None,
@@ -1309,6 +1311,9 @@ def start_chat(
         """Starts a chat session with the code chat model.
 
         Args:
+            context: Context shapes how the model responds throughout the conversation.
+                For example, you can use context to specify words the model can or
+                cannot use, topics to focus on or avoid, or the response format or style.
             max_output_tokens: Max length of the output text in tokens. Range: [1, 1000].
             temperature: Controls the randomness of predictions. Range: [0, 1].
             stop_sequences: Customized stop sequences to stop the decoding process.
@@ -1318,6 +1323,7 @@ def start_chat(
         """
         return CodeChatSession(
             model=self,
+            context=context,
             max_output_tokens=max_output_tokens,
             temperature=temperature,
             message_history=message_history,
@@ -1653,13 +1659,15 @@ class CodeChatSession(_ChatSessionBase):
     def __init__(
         self,
         model: CodeChatModel,
+        context: Optional[str] = None,
         max_output_tokens: Optional[int] = None,
         temperature: Optional[float] = None,
         message_history: Optional[List[ChatMessage]] = None,
         stop_sequences: Optional[List[str]] = None,
     ):
         super().__init__(
             model=model,
+            context=context,
             max_output_tokens=max_output_tokens,
             temperature=temperature,
             message_history=message_history,