better form response str (#98)

Co-authored-by: Elías Snorrason <eliassno@gmail.com>

Author: jwmueller

CHANGELOG.md

@@ -7,6 +7,12 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+## [1.1.20] - 2025-07-28
+
+### Changed
+
+- Updated `TLMChatCompletion.score()` to use `form_response_string_chat_completions` instead of `form_response_string_chat_completions_api`
+
 ## [1.1.19] - 2025-07-25
 
 ### Added
@@ -273,7 +279,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Release of the Cleanlab TLM Python client.
 
 
-[Unreleased]: https://github.com/cleanlab/cleanlab-tlm/compare/v1.1.19...HEAD
+[Unreleased]: https://github.com/cleanlab/cleanlab-tlm/compare/v1.1.20...HEAD
+[1.1.20]: https://github.com/cleanlab/cleanlab-tlm/compare/v1.1.19...v1.1.20
 [1.1.19]: https://github.com/cleanlab/cleanlab-tlm/compare/v1.1.18...v1.1.19
 [1.1.18]: https://github.com/cleanlab/cleanlab-tlm/compare/v1.1.17...v1.1.18
 [1.1.17]: https://github.com/cleanlab/cleanlab-tlm/compare/v1.1.16...v1.1.17

src/cleanlab_tlm/__about__.py

@@ -1,2 +1,2 @@
 # SPDX-License-Identifier: MIT
-__version__ = "1.1.19"
+__version__ = "1.1.20"

src/cleanlab_tlm/utils/chat.py

@@ -9,7 +9,7 @@
 from typing import TYPE_CHECKING, Any, Literal, Optional, Union, cast
 
 if TYPE_CHECKING:
-    from openai.types.chat import ChatCompletionMessage, ChatCompletionMessageParam
+    from openai.types.chat import ChatCompletion, ChatCompletionMessage, ChatCompletionMessageParam
 
 # Define message prefixes
 _SYSTEM_PREFIX = "System: "
@@ -443,11 +443,36 @@ def form_prompt_string(
     )
 
 
+def form_response_string_chat_completions(response: "ChatCompletion") -> str:
+    """Form a single string representing the response, out of the raw response object returned by OpenAI's Chat Completions API.
+
+    This function extracts the assistant's response message from a ChatCompletion object
+    and formats it into a single string representation using the Chat Completions API format.
+    It handles both text content and tool calls, formatting them consistently with the
+    format used in other functions in this module.
+
+    Args:
+        response (ChatCompletion): A ChatCompletion object returned by OpenAI's
+            chat.completions.create(). The function uses the first choice
+            from the response (response.choices[0].message).
+
+    Returns:
+        str: A formatted string containing the response content and any tool calls.
+             Tool calls are formatted as XML tags containing JSON with function
+             name and arguments, consistent with the format used in form_prompt_string.
+
+    See also:
+        [form_response_string_chat_completions_api](#function-form_response_string_chat_completions_api)
+    """
+    response_msg = response.choices[0].message
+    return form_response_string_chat_completions_api(response_msg)
+
+
 def form_response_string_chat_completions_api(response: Union[dict[str, Any], "ChatCompletionMessage"]) -> str:
     """
-    Format an assistant response message dictionary from the Chat Completions API into a single string.
+    Form a single string representing the response, out of an assistant response message dictionary in Chat Completions API format.
 
-    Given a ChatCompletion object `response` from `chat.completions.create()`,
+    Given a ChatCompletion object `response` from OpenAI's `chat.completions.create()`,
     this function can take either a ChatCompletionMessage object from `response.choices[0].message`
     or a dictionary from `response.choices[0].message.to_dict()`.
 

src/cleanlab_tlm/utils/chat_completions.py

@@ -16,7 +16,7 @@
 )
 from cleanlab_tlm.internal.types import TLMQualityPreset
 from cleanlab_tlm.tlm import TLM, TLMOptions, TLMScore
-from cleanlab_tlm.utils.chat import _form_prompt_chat_completions_api, form_response_string_chat_completions_api
+from cleanlab_tlm.utils.chat import _form_prompt_chat_completions_api, form_response_string_chat_completions
 
 if TYPE_CHECKING:
     from openai.types.chat import ChatCompletion, ChatCompletionMessage
@@ -114,7 +114,7 @@ def score(
         tools = openai_kwargs.get("tools", None)
 
         prompt_text = _form_prompt_chat_completions_api(messages, tools)
-        response_text = form_response_string_chat_completions_api(response=self._get_response_message(response))
+        response_text = form_response_string_chat_completions(response=response)
 
         return cast(TLMScore, self._tlm.get_trustworthiness_score(prompt_text, response_text))
 

tests/test_chat.py

@@ -1,13 +1,15 @@
 from typing import TYPE_CHECKING, Any, cast
 
 import pytest
-from openai.types.chat import ChatCompletionMessage
+from openai.types.chat import ChatCompletion, ChatCompletionMessage
+from openai.types.chat.chat_completion import Choice
 from openai.types.chat.chat_completion_message_tool_call import ChatCompletionMessageToolCall, Function
 
 from cleanlab_tlm.utils.chat import (
     _form_prompt_chat_completions_api,
     _form_prompt_responses_api,
     form_prompt_string,
+    form_response_string_chat_completions,
     form_response_string_chat_completions_api,
 )
 
@@ -1589,3 +1591,91 @@ def test_form_response_string_chat_completions_api_chatcompletion_message_none_c
     expected = ""
     result = form_response_string_chat_completions_api(message)
     assert result == expected
+
+
+def test_form_response_string_chat_completions_just_content() -> None:
+    """Test form_response_string_chat_completions with ChatCompletion containing just content."""
+
+    content = "Hello, how can I help you today?"
+
+    message = ChatCompletionMessage(role="assistant", content=content)
+    response = ChatCompletion(
+        id="test",
+        choices=[
+            Choice(
+                index=0,
+                message=message,
+                finish_reason="stop",
+            )
+        ],
+        created=1234567890,
+        model="test-model",
+        object="chat.completion",
+    )
+
+    result = form_response_string_chat_completions(response)
+    assert result == content
+
+    assert result == form_response_string_chat_completions_api(message)
+
+
+def test_form_response_string_chat_completions_multiple_choices() -> None:
+    """Test form_response_string_chat_completions with ChatCompletion containing multiple choices."""
+
+    content_first = "Hello, how can I help you today?"
+    content_second = "Hi there! What can I do for you?"
+
+    message_first = ChatCompletionMessage(role="assistant", content=content_first)
+    message_second = ChatCompletionMessage(role="assistant", content=content_second)
+    response = ChatCompletion(
+        id="test",
+        choices=[
+            Choice(
+                index=0,
+                message=message_first,
+                finish_reason="stop",
+            ),
+            Choice(
+                index=1,
+                message=message_second,
+                finish_reason="stop",
+            ),
+        ],
+        created=1234567890,
+        model="test-model",
+        object="chat.completion",
+    )
+
+    result = form_response_string_chat_completions(response)
+    assert result == content_first
+
+    assert result == form_response_string_chat_completions_api(message_first)
+
+
+def test_form_response_string_chat_completions_uses_api_function() -> None:
+    """Test that form_response_string_chat_completions calls form_response_string_chat_completions_api."""
+    from unittest.mock import patch
+
+    message = ChatCompletionMessage(role="assistant", content="Test response")
+    response = ChatCompletion(
+        id="test",
+        choices=[
+            Choice(
+                index=0,
+                message=message,
+                finish_reason="stop",
+            )
+        ],
+        created=1234567890,
+        model="test-model",
+        object="chat.completion",
+    )
+
+    # Mock the api function and test that it's called
+    with patch("cleanlab_tlm.utils.chat.form_response_string_chat_completions_api") as mock_api_func:
+        mock_api_func.return_value = "Mocked response"
+
+        result = form_response_string_chat_completions(response)
+
+        mock_api_func.assert_called_once_with(message)
+        assert result == "Mocked response"