test_chat_models.py — langchain Source File

Source Code

"""Test chat model integration."""

from __future__ import annotations

from typing import Any, Literal
from unittest.mock import MagicMock

from langchain_core.messages import AIMessageChunk, ToolMessage
from langchain_tests.unit_tests import ChatModelUnitTests
from openai import BaseModel
from openai.types.chat import ChatCompletionMessage
from pydantic import BaseModel as PydanticBaseModel
from pydantic import Field, SecretStr

from langchain_deepseek.chat_models import DEFAULT_API_BASE, ChatDeepSeek

MODEL_NAME = "deepseek-chat"


class MockOpenAIResponse(BaseModel):
    """Mock OpenAI response model."""

    choices: list
    error: None = None

    def model_dump(  # type: ignore[override]
        self,
        *,
        mode: Literal["json", "python"] | str = "python",  # noqa: PYI051
        include: Any = None,
        exclude: Any = None,
        by_alias: bool = False,
        exclude_unset: bool = False,
        exclude_defaults: bool = False,
        exclude_none: bool = False,
        round_trip: bool = False,
        warnings: Literal["none", "warn", "error"] | bool = True,
        context: dict[str, Any] | None = None,
        serialize_as_any: bool = False,
    ) -> dict[str, Any]:
        """Convert to dictionary, ensuring `reasoning_content` is included."""
        choices_list = []
        for choice in self.choices:
            if isinstance(choice.message, ChatCompletionMessage):
                message_dict = choice.message.model_dump()
                # Ensure model_extra fields are at top level
                if "model_extra" in message_dict:
                    message_dict.update(message_dict["model_extra"])
            else:
                message_dict = {
                    "role": "assistant",
                    "content": choice.message.content,
                }
                # Add reasoning_content if present
                if hasattr(choice.message, "reasoning_content"):
                    message_dict["reasoning_content"] = choice.message.reasoning_content
                # Add model_extra fields at the top level if present
                if hasattr(choice.message, "model_extra"):
                    message_dict.update(choice.message.model_extra)
                    message_dict["model_extra"] = choice.message.model_extra
// ... (257 more lines)