mirror of
https://github.com/hwchase17/langchain.git
synced 2025-06-08 07:57:07 +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()
```
94 lines
3.6 KiB
Python
94 lines
3.6 KiB
Python
"""Test SQL Database Chain."""
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from langchain_community.llms.openai import OpenAI
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from langchain_community.utilities.sql_database import SQLDatabase
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from sqlalchemy import Column, Integer, MetaData, String, Table, create_engine, insert
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from langchain_experimental.sql.base import (
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SQLDatabaseChain,
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SQLDatabaseSequentialChain,
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)
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metadata_obj = MetaData()
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user = Table(
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"user",
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metadata_obj,
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Column("user_id", Integer, primary_key=True),
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Column("user_name", String(16), nullable=False),
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Column("user_company", String(16), nullable=False),
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)
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def test_sql_database_run() -> None:
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"""Test that commands can be run successfully and returned in correct format."""
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engine = create_engine("sqlite:///:memory:")
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metadata_obj.create_all(engine)
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stmt = insert(user).values(user_id=13, user_name="Harrison", user_company="Foo")
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with engine.connect() as conn:
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conn.execute(stmt)
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db = SQLDatabase(engine)
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db_chain = SQLDatabaseChain.from_llm(OpenAI(temperature=0), db)
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output = db_chain.run("What company does Harrison work at?")
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expected_output = " Harrison works at Foo."
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assert output == expected_output
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def test_sql_database_run_update() -> None:
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"""Test that update commands run successfully and returned in correct format."""
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engine = create_engine("sqlite:///:memory:")
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metadata_obj.create_all(engine)
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stmt = insert(user).values(user_id=13, user_name="Harrison", user_company="Foo")
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with engine.connect() as conn:
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conn.execute(stmt)
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db = SQLDatabase(engine)
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db_chain = SQLDatabaseChain.from_llm(OpenAI(temperature=0), db)
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output = db_chain.run("Update Harrison's workplace to Bar")
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expected_output = " Harrison's workplace has been updated to Bar."
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assert output == expected_output
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output = db_chain.run("What company does Harrison work at?")
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expected_output = " Harrison works at Bar."
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assert output == expected_output
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def test_sql_database_sequential_chain_run() -> None:
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"""Test that commands can be run successfully SEQUENTIALLY
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and returned in correct format."""
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engine = create_engine("sqlite:///:memory:")
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metadata_obj.create_all(engine)
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stmt = insert(user).values(user_id=13, user_name="Harrison", user_company="Foo")
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with engine.connect() as conn:
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conn.execute(stmt)
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db = SQLDatabase(engine)
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db_chain = SQLDatabaseSequentialChain.from_llm(OpenAI(temperature=0), db)
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output = db_chain.run("What company does Harrison work at?")
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expected_output = " Harrison works at Foo."
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assert output == expected_output
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def test_sql_database_sequential_chain_intermediate_steps() -> None:
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"""Test that commands can be run successfully SEQUENTIALLY and returned
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in correct format. switch Intermediate steps"""
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engine = create_engine("sqlite:///:memory:")
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metadata_obj.create_all(engine)
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stmt = insert(user).values(user_id=13, user_name="Harrison", user_company="Foo")
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with engine.connect() as conn:
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conn.execute(stmt)
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db = SQLDatabase(engine)
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db_chain = SQLDatabaseSequentialChain.from_llm(
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OpenAI(temperature=0), db, return_intermediate_steps=True
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)
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output = db_chain("What company does Harrison work at?")
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expected_output = " Harrison works at Foo."
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assert output["result"] == expected_output
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query = output["intermediate_steps"][0]
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expected_query = (
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" SELECT user_company FROM user WHERE user_name = 'Harrison' LIMIT 1;"
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)
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assert query == expected_query
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query_results = output["intermediate_steps"][1]
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expected_query_results = "[('Foo',)]"
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assert query_results == expected_query_results
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