mirror of
https://github.com/hwchase17/langchain.git
synced 2026-04-10 06:23:14 +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()
```
108 lines
3.2 KiB
Python
108 lines
3.2 KiB
Python
"""Test formatting functionality."""
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from typing import Union
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import pytest
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from langchain_core.agents import AgentAction, AgentActionMessageLog, AgentFinish
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from langchain_core.documents import Document
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from langchain_core.messages import (
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AIMessage,
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AIMessageChunk,
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ChatMessage,
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ChatMessageChunk,
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FunctionMessage,
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FunctionMessageChunk,
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HumanMessage,
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HumanMessageChunk,
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SystemMessage,
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SystemMessageChunk,
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)
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from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, Generation
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from langchain_core.prompt_values import ChatPromptValueConcrete, StringPromptValue
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from langchain_core.pydantic_v1 import BaseModel, ValidationError
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def test_serialization_of_wellknown_objects() -> None:
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"""Test that pydantic is able to serialize and deserialize well known objects."""
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class WellKnownLCObject(BaseModel):
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"""A well known LangChain object."""
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__root__: Union[
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Document,
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HumanMessage,
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SystemMessage,
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ChatMessage,
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FunctionMessage,
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AIMessage,
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HumanMessageChunk,
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SystemMessageChunk,
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ChatMessageChunk,
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FunctionMessageChunk,
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AIMessageChunk,
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StringPromptValue,
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ChatPromptValueConcrete,
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AgentFinish,
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AgentAction,
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AgentActionMessageLog,
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ChatGeneration,
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Generation,
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ChatGenerationChunk,
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]
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lc_objects = [
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HumanMessage(content="human"),
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HumanMessageChunk(content="human"),
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AIMessage(content="ai"),
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AIMessageChunk(content="ai"),
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SystemMessage(content="sys"),
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SystemMessageChunk(content="sys"),
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FunctionMessage(
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name="func",
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content="func",
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),
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FunctionMessageChunk(
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name="func",
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content="func",
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),
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ChatMessage(
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role="human",
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content="human",
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),
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ChatMessageChunk(
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role="human",
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content="human",
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),
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StringPromptValue(text="hello"),
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ChatPromptValueConcrete(messages=[HumanMessage(content="human")]),
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Document(page_content="hello"),
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AgentFinish(return_values={}, log=""),
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AgentAction(tool="tool", tool_input="input", log=""),
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AgentActionMessageLog(
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tool="tool",
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tool_input="input",
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log="",
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message_log=[HumanMessage(content="human")],
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),
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Generation(
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text="hello",
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generation_info={"info": "info"},
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),
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ChatGeneration(
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message=HumanMessage(content="human"),
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),
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ChatGenerationChunk(
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message=HumanMessageChunk(content="cat"),
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),
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]
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for lc_object in lc_objects:
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d = lc_object.dict()
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assert "type" in d, f"Missing key `type` for {type(lc_object)}"
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obj1 = WellKnownLCObject.parse_obj(d)
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assert type(obj1.__root__) is type(lc_object), f"failed for {type(lc_object)}"
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with pytest.raises(ValidationError):
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# Make sure that specifically validation error is raised
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WellKnownLCObject.parse_obj({})
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