langchain Architecture Docs
Home / File/ test_openai_functions.py — langchain Source File

test_openai_functions.py — langchain Source File

Architecture documentation for test_openai_functions.py, a python file in the langchain codebase. 2 imports, 0 dependents.

File python LangChainCore MessageInterface 2 imports 2 functions 2 classes

Entity Profile

Dependency Diagram

graph LR
  f074218e_93c8_6d4c_b53c_2850f3240e27["test_openai_functions.py"]
  5c738c12_cc4f_cee1_0e1d_562012a5f844["langchain_core.utils.function_calling"]
  f074218e_93c8_6d4c_b53c_2850f3240e27 --> 5c738c12_cc4f_cee1_0e1d_562012a5f844
  dd5e7909_a646_84f1_497b_cae69735550e["pydantic"]
  f074218e_93c8_6d4c_b53c_2850f3240e27 --> dd5e7909_a646_84f1_497b_cae69735550e
  style f074218e_93c8_6d4c_b53c_2850f3240e27 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

from langchain_core.utils.function_calling import convert_to_openai_function
from pydantic import BaseModel, Field


def test_convert_pydantic_to_openai_function() -> None:
    class Data(BaseModel):
        """The data to return."""

        key: str = Field(..., description="API key")
        days: int = Field(default=0, description="Number of days to forecast")

    actual = convert_to_openai_function(Data)
    expected = {
        "name": "Data",
        "description": "The data to return.",
        "parameters": {
            "type": "object",
            "properties": {
                "key": {"description": "API key", "type": "string"},
                "days": {
                    "description": "Number of days to forecast",
                    "default": 0,
                    "type": "integer",
                },
            },
            "required": ["key"],
        },
    }
    assert actual == expected


def test_convert_pydantic_to_openai_function_nested() -> None:
    class Data(BaseModel):
        """The data to return."""

        key: str = Field(..., description="API key")
        days: int = Field(default=0, description="Number of days to forecast")

    class Model(BaseModel):
        """The model to return."""

        data: Data

    actual = convert_to_openai_function(Model)
    expected = {
        "name": "Model",
        "description": "The model to return.",
        "parameters": {
            "type": "object",
            "properties": {
                "data": {
                    "description": "The data to return.",
                    "type": "object",
                    "properties": {
                        "key": {
                            "description": "API key",
                            "type": "string",
                        },
                        "days": {
                            "description": "Number of days to forecast",
                            "default": 0,
                            "type": "integer",
                        },
                    },
                    "required": ["key"],
                },
            },
            "required": ["data"],
        },
    }
    assert actual == expected

Domain

Subdomains

Functions

Classes

Dependencies

  • langchain_core.utils.function_calling
  • pydantic

Source

Frequently Asked Questions

What does test_openai_functions.py do?
test_openai_functions.py is a source file in the langchain codebase, written in python. It belongs to the LangChainCore domain, MessageInterface subdomain.
What functions are defined in test_openai_functions.py?
test_openai_functions.py defines 2 function(s): test_convert_pydantic_to_openai_function, test_convert_pydantic_to_openai_function_nested.
What does test_openai_functions.py depend on?
test_openai_functions.py imports 2 module(s): langchain_core.utils.function_calling, pydantic.
Where is test_openai_functions.py in the architecture?
test_openai_functions.py is located at libs/langchain/tests/unit_tests/utils/test_openai_functions.py (domain: LangChainCore, subdomain: MessageInterface, directory: libs/langchain/tests/unit_tests/utils).

Analyze Your Own Codebase

Get architecture documentation, dependency graphs, and domain analysis for your codebase in minutes.

Try Supermodel Free