mirror of
https://github.com/hwchase17/langchain.git
synced 2025-05-05 23:28:47 +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()
```
72 lines
2.1 KiB
Python
72 lines
2.1 KiB
Python
"""Test EdenAI Chat API wrapper."""
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from typing import List
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import pytest
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from langchain_core.messages import (
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BaseMessage,
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HumanMessage,
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SystemMessage,
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ToolMessage,
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)
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from langchain_community.chat_models.edenai import (
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_extract_edenai_tool_results_from_messages,
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_format_edenai_messages,
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_message_role,
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)
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@pytest.mark.parametrize(
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("messages", "expected"),
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[
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(
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[
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SystemMessage(content="Translate the text from English to French"),
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HumanMessage(content="Hello how are you today?"),
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],
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{
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"text": "Hello how are you today?",
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"previous_history": [],
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"chatbot_global_action": "Translate the text from English to French",
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"tool_results": [],
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},
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)
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],
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)
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def test_edenai_messages_formatting(messages: List[BaseMessage], expected: str) -> None:
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result = _format_edenai_messages(messages)
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assert result == expected
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@pytest.mark.parametrize(
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("role", "role_response"),
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[("ai", "assistant"), ("human", "user"), ("chat", "user")],
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)
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def test_edenai_message_role(role: str, role_response) -> None: # type: ignore[no-untyped-def]
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role = _message_role(role)
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assert role == role_response
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def test_extract_edenai_tool_results_mixed_messages() -> None:
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fake_other_msg = BaseMessage(content="content", type="other message")
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messages = [
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fake_other_msg,
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ToolMessage(tool_call_id="id1", content="result1"),
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fake_other_msg,
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ToolMessage(tool_call_id="id2", content="result2"),
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ToolMessage(tool_call_id="id3", content="result3"),
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]
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expected_tool_results = [
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{"id": "id2", "result": "result2"},
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{"id": "id3", "result": "result3"},
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]
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expected_other_messages = [
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fake_other_msg,
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ToolMessage(tool_call_id="id1", content="result1"),
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fake_other_msg,
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]
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tool_results, other_messages = _extract_edenai_tool_results_from_messages(messages)
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assert tool_results == expected_tool_results
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assert other_messages == expected_other_messages
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