import os
from unittest.mock import patch

import pytest

from langchain_openai import OpenAIEmbeddings

os.environ["OPENAI_API_KEY"] = "foo"


def test_openai_invalid_model_kwargs() -> None:
    with pytest.raises(ValueError):
        OpenAIEmbeddings(model_kwargs={"model": "foo"})


def test_openai_incorrect_field() -> None:
    with pytest.warns(match="not default parameter"):
        llm = OpenAIEmbeddings(foo="bar")  # type: ignore[call-arg]
    assert llm.model_kwargs == {"foo": "bar"}


def test_embed_documents_with_custom_chunk_size() -> None:
    embeddings = OpenAIEmbeddings(chunk_size=2)
    texts = ["text1", "text2", "text3", "text4"]
    custom_chunk_size = 3

    with patch.object(embeddings.client, "create") as mock_create:
        mock_create.side_effect = [
            {"data": [{"embedding": [0.1, 0.2]}, {"embedding": [0.3, 0.4]}]},
            {"data": [{"embedding": [0.5, 0.6]}, {"embedding": [0.7, 0.8]}]},
        ]

        result = embeddings.embed_documents(texts, chunk_size=custom_chunk_size)
        _, tokens, __ = embeddings._tokenize(texts, custom_chunk_size)
        mock_create.call_args
        mock_create.assert_any_call(input=tokens[0:3], **embeddings._invocation_params)
        mock_create.assert_any_call(input=tokens[3:4], **embeddings._invocation_params)

    assert result == [[0.1, 0.2], [0.3, 0.4], [0.5, 0.6], [0.7, 0.8]]


def test_embed_documents_with_custom_chunk_size_no_check_ctx_length() -> None:
    embeddings = OpenAIEmbeddings(chunk_size=2, check_embedding_ctx_length=False)
    texts = ["text1", "text2", "text3", "text4"]
    custom_chunk_size = 3

    with patch.object(embeddings.client, "create") as mock_create:
        mock_create.side_effect = [
            {"data": [{"embedding": [0.1, 0.2]}, {"embedding": [0.3, 0.4]}]},
            {"data": [{"embedding": [0.5, 0.6]}, {"embedding": [0.7, 0.8]}]},
        ]

        result = embeddings.embed_documents(texts, chunk_size=custom_chunk_size)

        mock_create.call_args
        mock_create.assert_any_call(input=texts[0:3], **embeddings._invocation_params)
        mock_create.assert_any_call(input=texts[3:4], **embeddings._invocation_params)

    assert result == [[0.1, 0.2], [0.3, 0.4], [0.5, 0.6], [0.7, 0.8]]


def test_embed_with_kwargs() -> None:
    embeddings = OpenAIEmbeddings(
        model="text-embedding-3-small", check_embedding_ctx_length=False
    )
    texts = ["text1", "text2"]
    with patch.object(embeddings.client, "create") as mock_create:
        mock_create.side_effect = [
            {"data": [{"embedding": [0.1, 0.2, 0.3]}, {"embedding": [0.4, 0.5, 0.6]}]}
        ]

        result = embeddings.embed_documents(texts, dimensions=3)
        mock_create.assert_any_call(
            input=texts, dimensions=3, **embeddings._invocation_params
        )

    assert result == [[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]]


async def test_embed_with_kwargs_async() -> None:
    embeddings = OpenAIEmbeddings(
        model="text-embedding-3-small",
        check_embedding_ctx_length=False,
        dimensions=4,  # also check that runtime kwargs take precedence
    )
    texts = ["text1", "text2"]
    with patch.object(embeddings.async_client, "create") as mock_create:
        mock_create.side_effect = [
            {"data": [{"embedding": [0.1, 0.2, 0.3]}, {"embedding": [0.4, 0.5, 0.6]}]}
        ]

        result = await embeddings.aembed_documents(texts, dimensions=3)
        client_kwargs = embeddings._invocation_params.copy()
        assert client_kwargs["dimensions"] == 4
        client_kwargs["dimensions"] = 3
        mock_create.assert_any_call(input=texts, **client_kwargs)

    assert result == [[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]]

import os
from unittest.mock import patch

import pytest

from langchain_openai import OpenAIEmbeddings

os.environ["OPENAI_API_KEY"] = "foo"


def test_openai_invalid_model_kwargs() -> None:
    with pytest.raises(ValueError):
        OpenAIEmbeddings(model_kwargs={"model": "foo"})


def test_openai_incorrect_field() -> None:
    with pytest.warns(match="not default parameter"):
        llm = OpenAIEmbeddings(foo="bar")  # type: ignore[call-arg]
    assert llm.model_kwargs == {"foo": "bar"}


def test_embed_documents_with_custom_chunk_size() -> None:
    embeddings = OpenAIEmbeddings(chunk_size=2)
    texts = ["text1", "text2", "text3", "text4"]
    custom_chunk_size = 3

    with patch.object(embeddings.client, "create") as mock_create:
        mock_create.side_effect = [
            {"data": [{"embedding": [0.1, 0.2]}, {"embedding": [0.3, 0.4]}]},
            {"data": [{"embedding": [0.5, 0.6]}, {"embedding": [0.7, 0.8]}]},
        ]

        result = embeddings.embed_documents(texts, chunk_size=custom_chunk_size)
        _, tokens, __ = embeddings._tokenize(texts, custom_chunk_size)
        mock_create.call_args
        mock_create.assert_any_call(input=tokens[0:3], **embeddings._invocation_params)
        mock_create.assert_any_call(input=tokens[3:4], **embeddings._invocation_params)

    assert result == [[0.1, 0.2], [0.3, 0.4], [0.5, 0.6], [0.7, 0.8]]


def test_embed_documents_with_custom_chunk_size_no_check_ctx_length() -> None:
    embeddings = OpenAIEmbeddings(chunk_size=2, check_embedding_ctx_length=False)
    texts = ["text1", "text2", "text3", "text4"]
    custom_chunk_size = 3

    with patch.object(embeddings.client, "create") as mock_create:
        mock_create.side_effect = [
            {"data": [{"embedding": [0.1, 0.2]}, {"embedding": [0.3, 0.4]}]},
            {"data": [{"embedding": [0.5, 0.6]}, {"embedding": [0.7, 0.8]}]},
        ]

        result = embeddings.embed_documents(texts, chunk_size=custom_chunk_size)

        mock_create.call_args
        mock_create.assert_any_call(input=texts[0:3], **embeddings._invocation_params)
        mock_create.assert_any_call(input=texts[3:4], **embeddings._invocation_params)

    assert result == [[0.1, 0.2], [0.3, 0.4], [0.5, 0.6], [0.7, 0.8]]
