fix: 🐛 [#17555] fix openai.BadRequestError: Invalid value for 'content': expected a string, got null.

llama-index-integrations/llms/llama-index-llms-openai/llama_index/llms/openai/utils.py

@@ -2,7 +2,13 @@
 import os
 from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple, Type, Union
 
+import openai
 from deprecated import deprecated
+from openai.types.chat import ChatCompletionMessageParam, ChatCompletionMessageToolCall
+from openai.types.chat.chat_completion_chunk import ChoiceDeltaToolCall
+from openai.types.chat.chat_completion_message import ChatCompletionMessage
+from openai.types.chat.chat_completion_token_logprob import ChatCompletionTokenLogprob
+from openai.types.completion_choice import Logprobs
 from tenacity import (
     before_sleep_log,
     retry,
@@ -14,20 +20,9 @@
 )
 from tenacity.stop import stop_base
 
-import openai
 from llama_index.core.base.llms.generic_utils import get_from_param_or_env
-from llama_index.core.base.llms.types import (
-    ChatMessage,
-    ImageBlock,
-    LogProb,
-    TextBlock,
-)
+from llama_index.core.base.llms.types import ChatMessage, ImageBlock, LogProb, TextBlock
 from llama_index.core.bridge.pydantic import BaseModel
-from openai.types.chat import ChatCompletionMessageParam, ChatCompletionMessageToolCall
-from openai.types.chat.chat_completion_chunk import ChoiceDeltaToolCall
-from openai.types.chat.chat_completion_message import ChatCompletionMessage
-from openai.types.chat.chat_completion_token_logprob import ChatCompletionTokenLogprob
-from openai.types.completion_choice import Logprobs
 
 DEFAULT_OPENAI_API_TYPE = "open_ai"
 DEFAULT_OPENAI_API_BASE = "https://api.openai.com/v1"
@@ -292,20 +287,18 @@ def to_openai_message_dict(
             msg = f"Unsupported content block type: {type(block).__name__}"
             raise ValueError(msg)
 
-    # NOTE: Sending a blank string to openai will cause an error.
-    # This will commonly happen with tool calls.
-    content_txt = None if content_txt == "" else content_txt
-
     # NOTE: Despite what the openai docs say, if the role is ASSISTANT, SYSTEM
     # or TOOL, 'content' cannot be a list and must be string instead.
     # Furthermore, if all blocks are text blocks, we can use the content_txt
     # as the content. This will avoid breaking openai-like APIs.
     message_dict = {
         "role": message.role.value,
-        "content": content_txt
-        if message.role.value in ("assistant", "tool", "system")
-        or all(isinstance(block, TextBlock) for block in message.blocks)
-        else content,
+        "content": (
+            content_txt
+            if message.role.value in ("assistant", "tool", "system")
+            or all(isinstance(block, TextBlock) for block in message.blocks)
+            else content
+        ),
     }
 
     # TODO: O1 models do not support system prompts

llama-index-integrations/llms/llama-index-llms-openai/tests/test_openai_utils.py

@@ -59,15 +59,15 @@ def chat_messages_with_function_calling() -> List[ChatMessage]:
 
 
 @pytest.fixture()
-def openi_message_dicts_with_function_calling() -> List[ChatCompletionMessageParam]:
+def openai_message_dicts_with_function_calling() -> List[ChatCompletionMessageParam]:
     return [
         {
             "role": "user",
             "content": "test question with functions",
         },
         {
             "role": "assistant",
-            "content": None,
+            "content": "",
             "function_call": {
                 "name": "get_current_weather",
                 "arguments": '{ "location": "Boston, MA"}',
@@ -158,19 +158,19 @@ def test_to_openai_message_dicts_basic_string() -> None:
 
 def test_to_openai_message_dicts_function_calling(
     chat_messages_with_function_calling: List[ChatMessage],
-    openi_message_dicts_with_function_calling: List[ChatCompletionMessageParam],
+    openai_message_dicts_with_function_calling: List[ChatCompletionMessageParam],
 ) -> None:
     message_dicts = to_openai_message_dicts(
         chat_messages_with_function_calling,
     )
-    assert message_dicts == openi_message_dicts_with_function_calling
+    assert message_dicts == openai_message_dicts_with_function_calling
 
 
 def test_from_openai_message_dicts_function_calling(
-    openi_message_dicts_with_function_calling: List[ChatCompletionMessageParam],
+    openai_message_dicts_with_function_calling: List[ChatCompletionMessageParam],
     chat_messages_with_function_calling: List[ChatMessage],
 ) -> None:
-    chat_messages = from_openai_message_dicts(openi_message_dicts_with_function_calling)  # type: ignore
+    chat_messages = from_openai_message_dicts(openai_message_dicts_with_function_calling)  # type: ignore
 
     # assert attributes match
     for chat_message, chat_message_with_function_calling in zip(