From 12190ad7284f9cff6757a7dc7a133623c2e6368a Mon Sep 17 00:00:00 2001
From: Yuki Oshima <39944763+os1ma@users.noreply.github.com>
Date: Thu, 11 Apr 2024 01:51:38 +0900
Subject: [PATCH] openai[patch]: Fix langchain-openai unknown parameter error
 with gpt-4-turbo (#20271)

**Description:**

I fixed langchain-openai unknown parameter error with gpt-4-turbo.

It seems that the behavior of the Chat Completions API implicitly
changed when using the latest gpt-4-turbo model, differing from previous
models. It now appears to reject parameters that are not listed in the
[API
Reference](https://platform.openai.com/docs/api-reference/chat/create).
So I found some errors and fixed them.

**Issue:** https://github.com/langchain-ai/langchain/issues/20264

**Dependencies:** none

**Twitter handle:** https://twitter.com/oshima_123
---
 .../openai/langchain_openai/chat_models/base.py   | 11 ++++++++++-
 .../integration_tests/chat_models/test_base.py    | 15 +++++++++++----
 2 files changed, 21 insertions(+), 5 deletions(-)

diff --git a/libs/partners/openai/langchain_openai/chat_models/base.py b/libs/partners/openai/langchain_openai/chat_models/base.py
index 09e6ac1052a..ea4df089692 100644
--- a/libs/partners/openai/langchain_openai/chat_models/base.py
+++ b/libs/partners/openai/langchain_openai/chat_models/base.py
@@ -177,6 +177,12 @@ def _convert_message_to_dict(message: BaseMessage) -> dict:
             # If tool calls only, content is None not empty string
             if message_dict["content"] == "":
                 message_dict["content"] = None
+
+            tool_call_supported_props = {"id", "type", "function"}
+            message_dict["tool_calls"] = [
+                {k: v for k, v in tool_call.items() if k in tool_call_supported_props}
+                for tool_call in message_dict["tool_calls"]
+            ]
     elif isinstance(message, SystemMessage):
         message_dict["role"] = "system"
     elif isinstance(message, FunctionMessage):
@@ -808,7 +814,10 @@ class ChatOpenAI(BaseChatModel):
                         "function": {"name": tool_choice},
                     }
             elif isinstance(tool_choice, bool):
-                tool_choice = formatted_tools[0]
+                tool_choice = {
+                    "type": "function",
+                    "function": {"name": formatted_tools[0]["function"]["name"]},
+                }
             elif isinstance(tool_choice, dict):
                 if (
                     formatted_tools[0]["function"]["name"]
diff --git a/libs/partners/openai/tests/integration_tests/chat_models/test_base.py b/libs/partners/openai/tests/integration_tests/chat_models/test_base.py
index c400831e9aa..03cdcbee6c6 100644
--- a/libs/partners/openai/tests/integration_tests/chat_models/test_base.py
+++ b/libs/partners/openai/tests/integration_tests/chat_models/test_base.py
@@ -479,7 +479,7 @@ class GenerateUsername(BaseModel):
 
 
 def test_tool_use() -> None:
-    llm = ChatOpenAI(model="gpt-3.5-turbo", temperature=0)
+    llm = ChatOpenAI(model="gpt-4-turbo", temperature=0)
     llm_with_tool = llm.bind_tools(tools=[GenerateUsername], tool_choice=True)
     msgs: List = [HumanMessage("Sally has green hair, what would her username be?")]
     ai_msg = llm_with_tool.invoke(msgs)
@@ -490,6 +490,12 @@ def test_tool_use() -> None:
     tool_call = ai_msg.tool_calls[0]
     assert "args" in tool_call
 
+    tool_msg = ToolMessage(
+        "sally_green_hair", tool_call_id=ai_msg.additional_kwargs["tool_calls"][0]["id"]
+    )
+    msgs.extend([ai_msg, tool_msg])
+    llm_with_tool.invoke(msgs)
+
     # Test streaming
     ai_messages = llm_with_tool.stream(msgs)
     first = True
@@ -505,10 +511,11 @@ def test_tool_use() -> None:
     tool_call_chunk = gathered.tool_call_chunks[0]
     assert "args" in tool_call_chunk
 
-    tool_msg = ToolMessage(
-        "sally_green_hair", tool_call_id=ai_msg.additional_kwargs["tool_calls"][0]["id"]
+    streaming_tool_msg = ToolMessage(
+        "sally_green_hair",
+        tool_call_id=gathered.additional_kwargs["tool_calls"][0]["id"],
     )
-    msgs.extend([ai_msg, tool_msg])
+    msgs.extend([gathered, streaming_tool_msg])
     llm_with_tool.invoke(msgs)