mirror of
https://github.com/hwchase17/langchain.git
synced 2025-08-16 16:11:02 +00:00
a0c2281540
```python
"""python scripts/update_mypy_ruff.py"""
import glob
import tomllib
from pathlib import Path
import toml
import subprocess
import re
ROOT_DIR = Path(__file__).parents[1]
def main():
for path in glob.glob(str(ROOT_DIR / "libs/**/pyproject.toml"), recursive=True):
print(path)
with open(path, "rb") as f:
pyproject = tomllib.load(f)
try:
pyproject["tool"]["poetry"]["group"]["typing"]["dependencies"]["mypy"] = (
"^1.10"
)
pyproject["tool"]["poetry"]["group"]["lint"]["dependencies"]["ruff"] = (
"^0.5"
)
except KeyError:
continue
with open(path, "w") as f:
toml.dump(pyproject, f)
cwd = "/".join(path.split("/")[:-1])
completed = subprocess.run(
"poetry lock --no-update; poetry install --with typing; poetry run mypy . --no-color",
cwd=cwd,
shell=True,
capture_output=True,
text=True,
)
logs = completed.stdout.split("\n")
to_ignore = {}
for l in logs:
if re.match("^(.*)\:(\d+)\: error:.*\[(.*)\]", l):
path, line_no, error_type = re.match(
"^(.*)\:(\d+)\: error:.*\[(.*)\]", l
).groups()
if (path, line_no) in to_ignore:
to_ignore[(path, line_no)].append(error_type)
else:
to_ignore[(path, line_no)] = [error_type]
print(len(to_ignore))
for (error_path, line_no), error_types in to_ignore.items():
all_errors = ", ".join(error_types)
full_path = f"{cwd}/{error_path}"
try:
with open(full_path, "r") as f:
file_lines = f.readlines()
except FileNotFoundError:
continue
file_lines[int(line_no) - 1] = (
file_lines[int(line_no) - 1][:-1] + f" # type: ignore[{all_errors}]\n"
)
with open(full_path, "w") as f:
f.write("".join(file_lines))
subprocess.run(
"poetry run ruff format .; poetry run ruff --select I --fix .",
cwd=cwd,
shell=True,
capture_output=True,
text=True,
)
if __name__ == "__main__":
main()
```
103 lines
3.3 KiB
Python
103 lines
3.3 KiB
Python
"""Test embedding model integration."""
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from typing import List
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from unittest.mock import Mock
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import pytest
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from ai21 import AI21Client, MissingApiKeyError
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from ai21.models import EmbedResponse, EmbedResult, EmbedType
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from pytest_mock import MockerFixture
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from langchain_ai21.embeddings import AI21Embeddings
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from tests.unit_tests.conftest import DUMMY_API_KEY, temporarily_unset_api_key
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_EXAMPLE_EMBEDDING_0 = [1.0, 2.0, 3.0]
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_EXAMPLE_EMBEDDING_1 = [4.0, 5.0, 6.0]
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_EXAMPLE_EMBEDDING_2 = [7.0, 8.0, 9.0]
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_EXAMPLE_EMBEDDING_RESPONSE = EmbedResponse(
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results=[
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EmbedResult(_EXAMPLE_EMBEDDING_0),
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EmbedResult(_EXAMPLE_EMBEDDING_1),
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EmbedResult(_EXAMPLE_EMBEDDING_2),
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],
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id="test_id",
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)
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def test_initialization__when_no_api_key__should_raise_exception() -> None:
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"""Test integration initialization."""
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with temporarily_unset_api_key():
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with pytest.raises(MissingApiKeyError):
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AI21Embeddings()
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@pytest.fixture
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def mock_client_with_embeddings(mocker: MockerFixture) -> Mock:
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mock_client = mocker.MagicMock(spec=AI21Client)
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mock_client.embed = mocker.MagicMock()
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mock_client.embed.create.return_value = _EXAMPLE_EMBEDDING_RESPONSE
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return mock_client
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def test_embed_query(mock_client_with_embeddings: Mock) -> None:
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llm = AI21Embeddings(client=mock_client_with_embeddings, api_key=DUMMY_API_KEY) # type: ignore[arg-type]
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text = "Hello embeddings world!"
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response = llm.embed_query(text=text)
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assert response == _EXAMPLE_EMBEDDING_0
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mock_client_with_embeddings.embed.create.assert_called_once_with(
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texts=[text],
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type=EmbedType.QUERY,
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)
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def test_embed_documents(mock_client_with_embeddings: Mock) -> None:
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llm = AI21Embeddings(client=mock_client_with_embeddings, api_key=DUMMY_API_KEY) # type: ignore[arg-type]
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texts = ["Hello embeddings world!", "Some other text", "Some more text"]
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response = llm.embed_documents(texts=texts)
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assert response == [
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_EXAMPLE_EMBEDDING_0,
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_EXAMPLE_EMBEDDING_1,
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_EXAMPLE_EMBEDDING_2,
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]
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mock_client_with_embeddings.embed.create.assert_called_once_with(
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texts=texts,
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type=EmbedType.SEGMENT,
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)
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@pytest.mark.parametrize(
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ids=[
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"empty_texts",
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"chunk_size_greater_than_texts_length",
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"chunk_size_equal_to_texts_length",
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"chunk_size_less_than_texts_length",
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"chunk_size_one_with_multiple_texts",
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"chunk_size_greater_than_texts_length",
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],
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argnames=["texts", "chunk_size", "expected_internal_embeddings_calls"],
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argvalues=[
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([], 3, 0),
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(["text1", "text2", "text3"], 5, 1),
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(["text1", "text2", "text3"], 3, 1),
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(["text1", "text2", "text3", "text4", "text5"], 2, 3),
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(["text1", "text2", "text3"], 1, 3),
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(["text1", "text2", "text3"], 10, 1),
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],
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)
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def test_get_len_safe_embeddings(
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mock_client_with_embeddings: Mock,
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texts: List[str],
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chunk_size: int,
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expected_internal_embeddings_calls: int,
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) -> None:
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llm = AI21Embeddings(client=mock_client_with_embeddings, api_key=DUMMY_API_KEY) # type: ignore[arg-type]
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llm.embed_documents(texts=texts, batch_size=chunk_size)
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assert (
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mock_client_with_embeddings.embed.create.call_count
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== expected_internal_embeddings_calls
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)
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