refactor: openai completions message creation

Similar to the corresponding change to responses, we make sure that openai user messages combine related content into the same message where possible

Author: teamdandelion

python/mirascope/llm/clients/openai/completions/_utils/encode.py

@@ -46,29 +46,52 @@ class ChatCompletionCreateKwargs(TypedDict, total=False):
 def _encode_user_message(
     message: UserMessage,
 ) -> list[openai_types.ChatCompletionMessageParam]:
-    """Convert Mirascope `UserMessage` to a list of OpenAI `ChatCompletionMessageParam`."""
+    """Convert Mirascope `UserMessage` to a list of OpenAI `ChatCompletionMessageParam`.
+
+    Multiple text content parts are combined into a single user message.
+    Tool outputs become separate tool messages.
+    """
+    current_content: list[openai_types.ChatCompletionContentPartTextParam] = []
+    result: list[openai_types.ChatCompletionMessageParam] = []
+
+    def flush_message_content() -> None:
+        nonlocal current_content
+        if current_content:
+            content: str | list[openai_types.ChatCompletionContentPartTextParam]
+            if len(current_content) == 1:
+                content = current_content[0]["text"]
+            else:
+                content = current_content
+            result.append(
+                openai_types.ChatCompletionUserMessageParam(
+                    role="user", content=content
+                )
+            )
+            current_content = []
 
-    message_params: list[openai_types.ChatCompletionMessageParam] = []
     for part in message.content:
         if part.type == "text":
-            message_params.append(
-                openai_types.ChatCompletionUserMessageParam(
-                    role="user",
-                    content=part.text,
+            current_content.append(
+                openai_types.ChatCompletionContentPartTextParam(
+                    text=part.text, type="text"
                 )
             )
         elif part.type == "tool_output":
-            message_params.append(
+            flush_message_content()
+            result.append(
                 openai_types.ChatCompletionToolMessageParam(
                     role="tool",
                     content=str(part.value),
                     tool_call_id=part.id,
                 )
             )
         else:
-            raise NotImplementedError
+            raise NotImplementedError(
+                f"Unsupported user content part type: {part.type}"
+            )
+    flush_message_content()
 
-    return message_params
+    return result
 
 
 def _encode_assistant_message(

python/tests/e2e/input/snapshots/test_call_with_image_content/openai_completions_gpt_4o_snapshots.py

@@ -1,3 +1,10 @@
 from inline_snapshot import snapshot
 
-test_snapshot = snapshot({"exception": {"type": "NotImplementedError", "args": "()"}})
+test_snapshot = snapshot(
+    {
+        "exception": {
+            "type": "NotImplementedError",
+            "args": "('Unsupported user content part type: image',)",
+        }
+    }
+)

python/tests/e2e/input/snapshots/test_call_with_image_url/openai_completions_gpt_4o_snapshots.py

@@ -1,3 +1,10 @@
 from inline_snapshot import snapshot
 
-test_snapshot = snapshot({"exception": {"type": "NotImplementedError", "args": "()"}})
+test_snapshot = snapshot(
+    {
+        "exception": {
+            "type": "NotImplementedError",
+            "args": "('Unsupported user content part type: image',)",
+        }
+    }
+)

python/tests/llm/clients/openai/test_completions_client.py

@@ -8,6 +8,44 @@
 from mirascope.llm.clients.openai.completions._utils import encode_request
 
 
+def test_prepare_message_multiple_user_text_parts() -> None:
+    """Test preparing an OpenAI request with multiple text parts in a user message.
+
+    Included for code coverage.
+    """
+
+    messages = [
+        llm.messages.user(["Hello there", "fellow humans"]),
+    ]
+    assert encode_request(
+        model_id="gpt-4o", messages=messages, format=None, tools=None, params={}
+    ) == snapshot(
+        (
+            [
+                llm.UserMessage(
+                    content=[
+                        llm.Text(text="Hello there"),
+                        llm.Text(text="fellow humans"),
+                    ]
+                )
+            ],
+            None,
+            {
+                "model": "gpt-4o",
+                "messages": [
+                    {
+                        "role": "user",
+                        "content": [
+                            {"text": "Hello there", "type": "text"},
+                            {"text": "fellow humans", "type": "text"},
+                        ],
+                    }
+                ],
+            },
+        )
+    )
+
+
 def test_prepare_message_multiple_assistant_text_parts() -> None:
     """Test preparing an OpenAI request with multiple text parts in an assistant message.