fix: LLM mimicking Unicode responses due to forced Unicode conversion of non-ASCII characters. (#32222)

fix: Fix LLM mimicking Unicode responses due to forced Unicode
conversion of non-ASCII characters.

- **Description:** This PR fixes an issue where the LLM would mimic
Unicode responses due to forced Unicode conversion of non-ASCII
characters in tool calls. The fix involves disabling the `ensure_ascii`
flag in `json.dumps()` when converting tool calls to OpenAI format.
- **Issue:** Fixes ↓↓↓
input：
```json
{'role': 'assistant', 'tool_calls': [{'type': 'function', 'id': 'call_nv9trcehdpihr21zj9po19vq', 'function': {'name': 'create_customer', 'arguments': '{"customer_name": "你好啊集团"}'}}]}
```
output:
```json
{'role': 'assistant', 'tool_calls': [{'type': 'function', 'id': 'call_nv9trcehdpihr21zj9po19vq', 'function': {'name': 'create_customer', 'arguments': '{"customer_name": "\\u4f60\\u597d\\u554a\\u96c6\\u56e2"}'}}]}
```
then:
llm will mimic outputting unicode. Unicode's vast number of symbols can
lengthen LLM responses, leading to slower performance.
<img width="686" height="277" alt="image"
src="https://github.com/user-attachments/assets/28f3b007-3964-4455-bee2-68f86ac1906d"
/>

---------

Co-authored-by: Mason Daugherty <github@mdrxy.com>
Co-authored-by: Mason Daugherty <mason@langchain.dev>

libs/cli/pyproject.toml

@@ -56,7 +56,6 @@ select = [
     "C4",     # flake8-comprehensions
     "COM",    # flake8-commas
     "D",      # pydocstyle
-    "DOC",    # pydoclint
     "E",      # pycodestyle error
     "EM",     # flake8-errmsg
     "F",      # pyflakes

libs/core/langchain_core/messages/utils.py

@@ -1176,7 +1176,9 @@ def convert_to_openai_messages(
                                 "id": block["id"],
                                 "function": {
                                     "name": block["name"],
-                                    "arguments": json.dumps(block["input"]),
+                                    "arguments": json.dumps(
+                                        block["input"], ensure_ascii=False
+                                    ),
                                 },
                             }
                         )
@@ -1550,7 +1552,7 @@ def _convert_to_openai_tool_calls(tool_calls: list[ToolCall]) -> list[dict]:
             "id": tool_call["id"],
             "function": {
                 "name": tool_call["name"],
-                "arguments": json.dumps(tool_call["args"]),
+                "arguments": json.dumps(tool_call["args"], ensure_ascii=False),
             },
         }
         for tool_call in tool_calls

libs/core/tests/unit_tests/messages/test_utils.py

@@ -1121,6 +1121,33 @@ def test_convert_to_openai_messages_tool_use() -> None:
     assert result[0]["tool_calls"][0]["function"]["arguments"] == json.dumps({"a": "b"})
 
 
+def test_convert_to_openai_messages_tool_use_unicode() -> None:
+    """Test that Unicode characters in tool call args are preserved correctly."""
+    messages = [
+        AIMessage(
+            content=[
+                {
+                    "type": "tool_use",
+                    "id": "123",
+                    "name": "create_customer",
+                    "input": {"customer_name": "你好啊集团"},
+                }
+            ]
+        )
+    ]
+    result = convert_to_openai_messages(messages, text_format="block")
+    assert result[0]["tool_calls"][0]["type"] == "function"
+    assert result[0]["tool_calls"][0]["id"] == "123"
+    assert result[0]["tool_calls"][0]["function"]["name"] == "create_customer"
+    # Ensure Unicode characters are preserved, not escaped as \\uXXXX
+    arguments_str = result[0]["tool_calls"][0]["function"]["arguments"]
+    parsed_args = json.loads(arguments_str)
+    assert parsed_args["customer_name"] == "你好啊集团"
+    # Also ensure the raw JSON string contains Unicode, not escaped sequences
+    assert "你好啊集团" in arguments_str
+    assert "\\u4f60" not in arguments_str  # Should not contain escaped Unicode
+
+
 def test_convert_to_openai_messages_json() -> None:
     json_data = {"key": "value"}
     messages = [HumanMessage(content=[{"type": "json", "json": json_data}])]

libs/partners/anthropic/pyproject.toml

@@ -67,7 +67,6 @@ select = [
     "C4",     # flake8-comprehensions
     "COM",    # flake8-commas
     "D",      # pydocstyle
-    "DOC",    # pydoclint
     "E",      # pycodestyle error
     "EM",     # flake8-errmsg
     "F",      # pyflakes

libs/partners/chroma/pyproject.toml

@@ -69,7 +69,6 @@ select = [
     "C4",     # flake8-comprehensions
     "COM",    # flake8-commas
     "D",      # pydocstyle
-    "DOC",    # pydoclint
     "E",      # pycodestyle error
     "EM",     # flake8-errmsg
     "F",      # pyflakes

libs/partners/deepseek/pyproject.toml

@@ -55,7 +55,6 @@ select = [
     "C4",     # flake8-comprehensions
     "COM",    # flake8-commas
     "D",      # pydocstyle
-    "DOC",    # pydoclint
     "E",      # pycodestyle error
     "EM",     # flake8-errmsg
     "F",      # pyflakes

libs/partners/exa/README.md

@@ -98,7 +98,7 @@ print("Similar Results:", similar_results)
 All Exa tools support the following common parameters:
 
 - `num_results` (1-100): Number of search results to return
-- `type`: Search type - "neural", "keyword", or "auto" 
+- `type`: Search type - "neural", "keyword", or "auto"
 - `livecrawl`: Live crawling mode - "always", "fallback", or "never"
 - `summary`: Get AI-generated summaries (True/False or custom prompt dict)
 - `text_contents_options`: Dict to limit text length (e.g. `{"max_characters": 2000}`)

libs/partners/exa/pyproject.toml

@@ -54,7 +54,6 @@ select = [
     "C4",     # flake8-comprehensions
     "COM",    # flake8-commas
     "D",      # pydocstyle
-    "DOC",    # pydoclint
     "E",      # pycodestyle error
     "EM",     # flake8-errmsg
     "F",      # pyflakes

libs/partners/fireworks/langchain_fireworks/chat_models.py

@@ -1070,7 +1070,7 @@ def _lc_tool_call_to_fireworks_tool_call(tool_call: ToolCall) -> dict:
         "id": tool_call["id"],
         "function": {
             "name": tool_call["name"],
-            "arguments": json.dumps(tool_call["args"]),
+            "arguments": json.dumps(tool_call["args"], ensure_ascii=False),
         },
     }
 

libs/partners/fireworks/pyproject.toml

@@ -58,7 +58,6 @@ select = [
     "C4",     # flake8-comprehensions
     "COM",    # flake8-commas
     "D",      # pydocstyle
-    "DOC",    # pydoclint
     "E",      # pycodestyle error
     "EM",     # flake8-errmsg
     "F",      # pyflakes

libs/partners/fireworks/uv.lock

@@ -653,7 +653,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "0.3.68"
+version = "0.3.72"
 source = { editable = "../../core" }
 dependencies = [
     { name = "jsonpatch" },
@@ -669,7 +669,7 @@ dependencies = [
 requires-dist = [
     { name = "jsonpatch", specifier = ">=1.33,<2.0" },
     { name = "langsmith", specifier = ">=0.3.45" },
-    { name = "packaging", specifier = ">=23.2,<25" },
+    { name = "packaging", specifier = ">=23.2" },
     { name = "pydantic", specifier = ">=2.7.4" },
     { name = "pyyaml", specifier = ">=5.3" },
     { name = "tenacity", specifier = ">=8.1.0,!=8.4.0,<10.0.0" },

libs/partners/groq/langchain_groq/chat_models.py

@@ -1339,7 +1339,7 @@ def _lc_tool_call_to_groq_tool_call(tool_call: ToolCall) -> dict:
         "id": tool_call["id"],
         "function": {
             "name": tool_call["name"],
-            "arguments": json.dumps(tool_call["args"]),
+            "arguments": json.dumps(tool_call["args"], ensure_ascii=False),
         },
     }
 

libs/partners/groq/pyproject.toml

@@ -51,7 +51,6 @@ select = [
     "C4",     # flake8-comprehensions
     "COM",    # flake8-commas
     "D",      # pydocstyle
-    "DOC",    # pydoclint
     "E",      # pycodestyle error
     "EM",     # flake8-errmsg
     "F",      # pyflakes

libs/partners/groq/uv.lock

@@ -331,7 +331,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "0.3.68"
+version = "0.3.72"
 source = { editable = "../../core" }
 dependencies = [
     { name = "jsonpatch" },
@@ -347,7 +347,7 @@ dependencies = [
 requires-dist = [
     { name = "jsonpatch", specifier = ">=1.33,<2.0" },
     { name = "langsmith", specifier = ">=0.3.45" },
-    { name = "packaging", specifier = ">=23.2,<25" },
+    { name = "packaging", specifier = ">=23.2" },
     { name = "pydantic", specifier = ">=2.7.4" },
     { name = "pyyaml", specifier = ">=5.3" },
     { name = "tenacity", specifier = ">=8.1.0,!=8.4.0,<10.0.0" },

libs/partners/huggingface/langchain_huggingface/chat_models/huggingface.py

@@ -88,7 +88,7 @@ def _lc_tool_call_to_hf_tool_call(tool_call: ToolCall) -> dict:
         "id": tool_call["id"],
         "function": {
             "name": tool_call["name"],
-            "arguments": json.dumps(tool_call["args"]),
+            "arguments": json.dumps(tool_call["args"], ensure_ascii=False),
         },
     }
 

libs/partners/huggingface/pyproject.toml

@@ -65,7 +65,6 @@ select = [
     "C4",     # flake8-comprehensions
     "COM",    # flake8-commas
     "D",      # pydocstyle
-    "DOC",    # pydoclint
     "E",      # pycodestyle error
     "EM",     # flake8-errmsg
     "F",      # pyflakes

libs/partners/mistralai/langchain_mistralai/chat_models.py

@@ -296,7 +296,7 @@ def _format_tool_call_for_mistral(tool_call: ToolCall) -> dict:
     result: dict[str, Any] = {
         "function": {
             "name": tool_call["name"],
-            "arguments": json.dumps(tool_call["args"]),
+            "arguments": json.dumps(tool_call["args"], ensure_ascii=False),
         }
     }
     if _id := tool_call.get("id"):

libs/partners/mistralai/pyproject.toml

@@ -55,7 +55,6 @@ select = [
     "C4",     # flake8-comprehensions
     "COM",    # flake8-commas
     "D",      # pydocstyle
-    "DOC",    # pydoclint
     "E",      # pycodestyle error
     "EM",     # flake8-errmsg
     "F",      # pyflakes

libs/partners/mistralai/uv.lock

@@ -350,7 +350,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "0.3.68"
+version = "0.3.72"
 source = { editable = "../../core" }
 dependencies = [
     { name = "jsonpatch" },
@@ -366,7 +366,7 @@ dependencies = [
 requires-dist = [
     { name = "jsonpatch", specifier = ">=1.33,<2.0" },
     { name = "langsmith", specifier = ">=0.3.45" },
-    { name = "packaging", specifier = ">=23.2,<25" },
+    { name = "packaging", specifier = ">=23.2" },
     { name = "pydantic", specifier = ">=2.7.4" },
     { name = "pyyaml", specifier = ">=5.3" },
     { name = "tenacity", specifier = ">=8.1.0,!=8.4.0,<10.0.0" },

libs/partners/nomic/pyproject.toml

@@ -51,7 +51,6 @@ select = [
     "C4",     # flake8-comprehensions
     "COM",    # flake8-commas
     "D",      # pydocstyle
-    "DOC",    # pydoclint
     "E",      # pycodestyle error
     "EM",     # flake8-errmsg
     "F",      # pyflakes

libs/partners/ollama/pyproject.toml

@@ -54,7 +54,6 @@ select = [
     "C4",     # flake8-comprehensions
     "COM",    # flake8-commas
     "D",      # pydocstyle
-    "DOC",    # pydoclint
     "E",      # pycodestyle error
     "EM",     # flake8-errmsg
     "F",      # pyflakes

libs/partners/openai/langchain_openai/chat_models/_compat.py

@@ -211,7 +211,7 @@ def _convert_from_v03_ai_message(message: AIMessage) -> AIMessage:
         function_call = {
             "type": "function_call",
             "name": tool_call["name"],
-            "arguments": json.dumps(tool_call["args"]),
+            "arguments": json.dumps(tool_call["args"], ensure_ascii=False),
             "call_id": tool_call["id"],
         }
         if function_call_ids is not None and (

libs/partners/openai/langchain_openai/chat_models/base.py

@@ -3178,7 +3178,7 @@ def _lc_tool_call_to_openai_tool_call(tool_call: ToolCall) -> dict:
         "id": tool_call["id"],
         "function": {
             "name": tool_call["name"],
-            "arguments": json.dumps(tool_call["args"]),
+            "arguments": json.dumps(tool_call["args"], ensure_ascii=False),
         },
     }
 

libs/partners/openai/tests/unit_tests/chat_models/test_base.py

@@ -2530,6 +2530,32 @@ def test_make_computer_call_output_from_message() -> None:
     }
 
 
+def test_lc_tool_call_to_openai_tool_call_unicode() -> None:
+    """Test that Unicode characters in tool call args are preserved correctly."""
+    from langchain_openai.chat_models.base import _lc_tool_call_to_openai_tool_call
+
+    tool_call = ToolCall(
+        id="call_123",
+        name="create_customer",
+        args={"customer_name": "你好啊集团"},
+        type="tool_call",
+    )
+
+    result = _lc_tool_call_to_openai_tool_call(tool_call)
+
+    assert result["type"] == "function"
+    assert result["id"] == "call_123"
+    assert result["function"]["name"] == "create_customer"
+
+    # Ensure Unicode characters are preserved, not escaped as \\uXXXX
+    arguments_str = result["function"]["arguments"]
+    parsed_args = json.loads(arguments_str)
+    assert parsed_args["customer_name"] == "你好啊集团"
+    # Also ensure the raw JSON string contains Unicode, not escaped sequences
+    assert "你好啊集团" in arguments_str
+    assert "\\u4f60" not in arguments_str  # Should not contain escaped Unicode
+
+
 def test_extra_body_parameter() -> None:
     """Test that extra_body parameter is properly included in request payload."""
     llm = ChatOpenAI(

libs/partners/openai/uv.lock

@@ -480,7 +480,7 @@ wheels = [
 
 [[package]]
 name = "langchain-core"
-version = "0.3.70"
+version = "0.3.72"
 source = { editable = "../../core" }
 dependencies = [
     { name = "jsonpatch" },

libs/standard-tests/langchain_tests/integration_tests/chat_models.py

@@ -127,6 +127,20 @@ def _validate_tool_call_message_no_args(message: BaseMessage) -> None:
     assert tool_call.get("type") == "tool_call"
 
 
+@tool
+def unicode_customer(customer_name: str, description: str) -> str:
+    """Tool for creating a customer with Unicode name.
+
+    Args:
+        customer_name: The customer's name in their native language.
+        description: Description of the customer.
+
+    Returns:
+        A confirmation message about the customer creation.
+    """
+    return f"Created customer: {customer_name} - {description}"
+
+
 class ChatModelIntegrationTests(ChatModelTests):
     """Base class for chat model integration tests.
 
@@ -2900,3 +2914,95 @@ class ChatModelIntegrationTests(ChatModelTests):
     def invoke_with_cache_creation_input(self, *, stream: bool = False) -> AIMessage:
         """:private:"""
         raise NotImplementedError
+
+    def test_unicode_tool_call_integration(
+        self,
+        model: BaseChatModel,
+        *,
+        tool_choice: Optional[str] = None,
+        force_tool_call: bool = True,
+    ) -> None:
+        """Generic integration test for Unicode characters in tool calls.
+
+        Args:
+            model: The chat model to test
+            tool_choice: Tool choice parameter to pass to bind_tools (provider-specific)
+            force_tool_call: Whether to force a tool call (use tool_choice=True if None)
+
+        Tests that Unicode characters in tool call arguments are preserved correctly,
+        not escaped as \\uXXXX sequences.
+        """
+        if not self.has_tool_calling:
+            pytest.skip("Test requires tool calling support.")
+
+        # Configure tool choice based on provider capabilities
+        if tool_choice is None and force_tool_call:
+            tool_choice = "any"
+
+        if tool_choice is not None:
+            llm_with_tool = model.bind_tools(
+                [unicode_customer], tool_choice=tool_choice
+            )
+        else:
+            llm_with_tool = model.bind_tools([unicode_customer])
+
+        # Test with Chinese characters
+        msgs = [
+            HumanMessage(
+                "Create a customer named '你好啊集团' (Hello Group) - a Chinese "
+                "technology company"
+            )
+        ]
+        ai_msg = llm_with_tool.invoke(msgs)
+
+        assert isinstance(ai_msg, AIMessage)
+        assert isinstance(ai_msg.tool_calls, list)
+
+        if force_tool_call:
+            assert len(ai_msg.tool_calls) >= 1, (
+                f"Expected at least 1 tool call, got {len(ai_msg.tool_calls)}"
+            )
+
+        if ai_msg.tool_calls:
+            tool_call = ai_msg.tool_calls[0]
+            assert tool_call["name"] == "unicode_customer"
+            assert "args" in tool_call
+
+            # Verify Unicode characters are properly handled
+            args = tool_call["args"]
+            assert "customer_name" in args
+            customer_name = args["customer_name"]
+
+            # The model should include the Unicode characters, not escaped sequences
+            assert (
+                "你好" in customer_name
+                or "你" in customer_name
+                or "好" in customer_name
+            ), f"Unicode characters not found in: {customer_name}"
+
+        # Test with additional Unicode examples - Japanese
+        msgs_jp = [
+            HumanMessage(
+                "Create a customer named 'こんにちは株式会社' (Hello Corporation) - a "
+                "Japanese company"
+            )
+        ]
+        ai_msg_jp = llm_with_tool.invoke(msgs_jp)
+
+        assert isinstance(ai_msg_jp, AIMessage)
+
+        if force_tool_call:
+            assert len(ai_msg_jp.tool_calls) >= 1
+
+        if ai_msg_jp.tool_calls:
+            tool_call_jp = ai_msg_jp.tool_calls[0]
+            args_jp = tool_call_jp["args"]
+            customer_name_jp = args_jp["customer_name"]
+
+            # Verify Japanese Unicode characters are preserved
+            assert (
+                "こんにちは" in customer_name_jp
+                or "株式会社" in customer_name_jp
+                or "こ" in customer_name_jp
+                or "ん" in customer_name_jp
+            ), f"Japanese Unicode characters not found in: {customer_name_jp}"

libs/standard-tests/tests/unit_tests/custom_chat_model.py

@@ -68,6 +68,9 @@ class ChatParrotLink(BaseChatModel):
         """
         # Replace this with actual logic to generate a response from a list
         # of messages.
+        _ = stop  # Mark as used to avoid unused variable warning
+        _ = run_manager  # Mark as used to avoid unused variable warning
+        _ = kwargs  # Mark as used to avoid unused variable warning
         last_message = messages[-1]
         tokens = last_message.content[: self.parrot_buffer_length]
         ct_input_tokens = sum(len(message.content) for message in messages)
@@ -114,6 +117,8 @@ class ChatParrotLink(BaseChatModel):
                   downstream and understand why generation stopped.
             run_manager: A run manager with callbacks for the LLM.
         """
+        _ = stop  # Mark as used to avoid unused variable warning
+        _ = kwargs  # Mark as used to avoid unused variable warning
         last_message = messages[-1]
         tokens = str(last_message.content[: self.parrot_buffer_length])
         ct_input_tokens = sum(len(message.content) for message in messages)

libs/standard-tests/tests/unit_tests/test_custom_chat_model.py

@@ -1,5 +1,10 @@
 """Test the standard tests on the custom chat model in the docs."""
 
+from typing import Optional
+
+import pytest
+from langchain_core.language_models.chat_models import BaseChatModel
+
 from langchain_tests.integration_tests import ChatModelIntegrationTests
 from langchain_tests.unit_tests import ChatModelUnitTests
 
@@ -24,3 +29,12 @@ class TestChatParrotLinkIntegration(ChatModelIntegrationTests):
     @property
     def chat_model_params(self) -> dict:
         return {"model": "bird-brain-001", "temperature": 0, "parrot_buffer_length": 50}
+
+    @pytest.mark.xfail(reason="ChatParrotLink doesn't implement bind_tools method")
+    def test_unicode_tool_call_integration(
+        self,
+        model: BaseChatModel,
+        tool_choice: Optional[str] = None,
+        force_tool_call: bool = True,
+    ) -> None:
+        """Expected failure as ChatParrotLink doesn't support tool calling yet."""