Added support for examples for VertexAI chat models. (#7636)

#5278

Co-authored-by: Leonid Kuligin <kuligin@google.com>

langchain/chat_models/vertexai.py

@@ -23,7 +23,7 @@ from langchain.schema.messages import (
 from langchain.utilities.vertexai import raise_vertex_import_error
 
 if TYPE_CHECKING:
-    from vertexai.language_models import ChatMessage
+    from vertexai.language_models import ChatMessage, InputOutputTextPair
 
 
 @dataclass
@@ -65,6 +65,36 @@ def _parse_chat_history(history: List[BaseMessage]) -> _ChatHistory:
     return chat_history
 
 
+def _parse_examples(examples: List[BaseMessage]) -> List["InputOutputTextPair"]:
+    from vertexai.language_models import InputOutputTextPair
+
+    if len(examples) % 2 != 0:
+        raise ValueError(
+            f"Expect examples to have an even amount of messages, got {len(examples)}."
+        )
+    example_pairs = []
+    input_text = None
+    for i, example in enumerate(examples):
+        if i % 2 == 0:
+            if not isinstance(example, HumanMessage):
+                raise ValueError(
+                    f"Expected the first message in a part to be from human, got "
+                    f"{type(example)} for the {i}th message."
+                )
+            input_text = example.content
+        if i % 2 == 1:
+            if not isinstance(example, AIMessage):
+                raise ValueError(
+                    f"Expected the second message in a part to be from AI, got "
+                    f"{type(example)} for the {i}th message."
+                )
+            pair = InputOutputTextPair(
+                input_text=input_text, output_text=example.content
+            )
+            example_pairs.append(pair)
+    return example_pairs
+
+
 class ChatVertexAI(_VertexAICommon, BaseChatModel):
     """Wrapper around Vertex AI large language models."""
 
@@ -120,13 +150,16 @@ class ChatVertexAI(_VertexAICommon, BaseChatModel):
         history = _parse_chat_history(messages[:-1])
         context = history.context if history.context else None
         params = {**self._default_params, **kwargs}
+        examples = kwargs.get("examples", None)
+        if examples:
+            params["examples"] = _parse_examples(examples)
         if not self.is_codey_model:
             chat = self.client.start_chat(
                 context=context, message_history=history.history, **params
             )
         else:
             chat = self.client.start_chat(**params)
-        response = chat.send_message(question.content, **params)
+        response = chat.send_message(question.content)
         text = self._enforce_stop_words(response.text, stop)
         return ChatResult(generations=[ChatGeneration(message=AIMessage(content=text))])
 

tests/integration_tests/chat_models/test_vertexai.py

@@ -7,12 +7,12 @@ pip install google-cloud-aiplatform>=1.25.0
 Your end-user credentials would be used to make the calls (make sure you've run 
 `gcloud auth login` first).
 """
-from unittest.mock import Mock, patch
+from unittest.mock import MagicMock, Mock, patch
 
 import pytest
 
 from langchain.chat_models import ChatVertexAI
-from langchain.chat_models.vertexai import _parse_chat_history
+from langchain.chat_models.vertexai import _parse_chat_history, _parse_examples
 from langchain.schema.messages import AIMessage, HumanMessage, SystemMessage
 
 
@@ -42,6 +42,20 @@ def test_vertexai_single_call_with_context() -> None:
     assert isinstance(response.content, str)
 
 
+def test_vertexai_single_call_with_examples() -> None:
+    model = ChatVertexAI()
+    raw_context = "My name is Ned. You are my personal assistant."
+    question = "2+2"
+    text_question, text_answer = "4+4", "8"
+    inp = HumanMessage(content=text_question)
+    output = AIMessage(content=text_answer)
+    context = SystemMessage(content=raw_context)
+    message = HumanMessage(content=question)
+    response = model([context, message], examples=[inp, output])
+    assert isinstance(response, AIMessage)
+    assert isinstance(response.content, str)
+
+
 def test_parse_chat_history_correct() -> None:
     from vertexai.language_models import ChatMessage
 
@@ -92,17 +106,50 @@ def test_vertexai_args_passed() -> None:
 
     # Mock the library to ensure the args are passed correctly
     with patch(
-        "vertexai.language_models._language_models.ChatSession.send_message"
-    ) as send_message:
+        "vertexai.language_models._language_models.ChatModel.start_chat"
+    ) as start_chat:
         mock_response = Mock(text=response_text)
-        send_message.return_value = mock_response
+        mock_chat = MagicMock()
+        start_chat.return_value = mock_chat
+        mock_send_message = MagicMock(return_value=mock_response)
+        mock_chat.send_message = mock_send_message
 
         model = ChatVertexAI(**prompt_params)
         message = HumanMessage(content=user_prompt)
         response = model([message])
 
         assert response.content == response_text
-        send_message.assert_called_once_with(
-            user_prompt,
-            **prompt_params,
+        mock_send_message.assert_called_once_with(user_prompt)
+        start_chat.assert_called_once_with(
+            context=None, message_history=[], **prompt_params
+        )
+
+
+def test_parse_examples_correct() -> None:
+    from vertexai.language_models import InputOutputTextPair
+
+    text_question = (
+        "Hello, could you recommend a good movie for me to watch this evening, please?"
+    )
+    question = HumanMessage(content=text_question)
+    text_answer = (
+        "Sure, You might enjoy The Lord of the Rings: The Fellowship of the Ring "
+        "(2001): This is the first movie in the Lord of the Rings trilogy."
+    )
+    answer = AIMessage(content=text_answer)
+    examples = _parse_examples([question, answer, question, answer])
+    assert len(examples) == 2
+    assert examples == [
+        InputOutputTextPair(input_text=text_question, output_text=text_answer),
+        InputOutputTextPair(input_text=text_question, output_text=text_answer),
+    ]
+
+
+def test_parse_exmaples_failes_wrong_sequence() -> None:
+    with pytest.raises(ValueError) as exc_info:
+        _ = _parse_examples([AIMessage(content="a")])
+    print(str(exc_info.value))
+    assert (
+        str(exc_info.value)
+        == "Expect examples to have an even amount of messages, got 1."
     )