langchain/libs/community/tests/integration_tests/embeddings/test_embaas.py
Bagatur a0c2281540
infra: update mypy 1.10, ruff 0.5 (#23721)
```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()

```
2024-07-03 10:33:27 -07:00

60 lines
1.7 KiB
Python

"""Test embaas embeddings."""
import responses
from langchain_community.embeddings.embaas import EMBAAS_API_URL, EmbaasEmbeddings
def test_embaas_embed_documents() -> None:
"""Test embaas embeddings with multiple texts."""
texts = ["foo bar", "bar foo", "foo"]
embedding = EmbaasEmbeddings()
output = embedding.embed_documents(texts)
assert len(output) == 3
assert len(output[0]) == 1024
assert len(output[1]) == 1024
assert len(output[2]) == 1024
def test_embaas_embed_query() -> None:
"""Test embaas embeddings with multiple texts."""
text = "foo"
embeddings = EmbaasEmbeddings()
output = embeddings.embed_query(text)
assert len(output) == 1024
def test_embaas_embed_query_instruction() -> None:
"""Test embaas embeddings with a different instruction."""
text = "Test"
instruction = "query"
embeddings = EmbaasEmbeddings(instruction=instruction)
output = embeddings.embed_query(text)
assert len(output) == 1024
def test_embaas_embed_query_model() -> None:
"""Test embaas embeddings with a different model."""
text = "Test"
model = "instructor-large"
instruction = "Represent the query for retrieval"
embeddings = EmbaasEmbeddings(model=model, instruction=instruction)
output = embeddings.embed_query(text)
assert len(output) == 768
@responses.activate
def test_embaas_embed_documents_response() -> None:
"""Test embaas embeddings with multiple texts."""
responses.add(
responses.POST,
EMBAAS_API_URL,
json={"data": [{"embedding": [0.0] * 1024}]},
status=200,
)
text = "asd"
embeddings = EmbaasEmbeddings()
output = embeddings.embed_query(text)
assert len(output) == 1024