"""Test OpenAI API wrapper.""" from pathlib import Path from typing import Generator import pytest from langchain.llms.loading import load_llm from langchain.llms.openai import OpenAI def test_openai_call() -> None: """Test valid call to openai.""" llm = OpenAI(max_tokens=10) output = llm("Say foo:") assert isinstance(output, str) def test_openai_extra_kwargs() -> None: """Test extra kwargs to openai.""" # Check that foo is saved in extra_kwargs. llm = OpenAI(foo=3, max_tokens=10) assert llm.max_tokens == 10 assert llm.model_kwargs == {"foo": 3} # Test that if extra_kwargs are provided, they are added to it. llm = OpenAI(foo=3, model_kwargs={"bar": 2}) assert llm.model_kwargs == {"foo": 3, "bar": 2} # Test that if provided twice it errors with pytest.raises(ValueError): OpenAI(foo=3, model_kwargs={"foo": 2}) def test_openai_stop_valid() -> None: """Test openai stop logic on valid configuration.""" query = "write an ordered list of five items" first_llm = OpenAI(stop="3", temperature=0) first_output = first_llm(query) second_llm = OpenAI(temperature=0) second_output = second_llm(query, stop=["3"]) # Because it stops on new lines, shouldn't return anything assert first_output == second_output def test_openai_stop_error() -> None: """Test openai stop logic on bad configuration.""" llm = OpenAI(stop="3", temperature=0) with pytest.raises(ValueError): llm("write an ordered list of five items", stop=["\n"]) def test_saving_loading_llm(tmp_path: Path) -> None: """Test saving/loading an OpenAPI LLM.""" llm = OpenAI(max_tokens=10) llm.save(file_path=tmp_path / "openai.yaml") loaded_llm = load_llm(tmp_path / "openai.yaml") assert loaded_llm == llm def test_openai_streaming() -> None: """Test streaming tokens from OpenAI.""" llm = OpenAI(max_tokens=10) generator = llm.stream("I'm Pickle Rick") assert isinstance(generator, Generator) for token in generator: assert isinstance(token["choices"][0]["text"], str) def test_openai_streaming_error() -> None: """Test error handling in stream.""" llm = OpenAI(best_of=2) with pytest.raises(ValueError): llm.stream("I'm Pickle Rick")