mirror of
https://github.com/hwchase17/langchain.git
synced 2025-05-08 08:38:48 +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()
```
52 lines
1.7 KiB
Python
52 lines
1.7 KiB
Python
"""Wrapper for Rememberizer APIs."""
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from typing import Dict, List, Optional, cast
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import requests
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from langchain_core.documents import Document
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from langchain_core.pydantic_v1 import BaseModel, root_validator
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from langchain_core.utils import get_from_dict_or_env
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class RememberizerAPIWrapper(BaseModel):
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"""Wrapper for Rememberizer APIs."""
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top_k_results: int = 10
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rememberizer_api_key: Optional[str] = None
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@root_validator(pre=True)
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def validate_environment(cls, values: Dict) -> Dict:
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"""Validate that api key in environment."""
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rememberizer_api_key = get_from_dict_or_env(
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values, "rememberizer_api_key", "REMEMBERIZER_API_KEY"
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)
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values["rememberizer_api_key"] = rememberizer_api_key
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return values
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def search(self, query: str) -> dict:
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"""Search for a query in the Rememberizer API."""
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url = f"https://api.rememberizer.ai/api/v1/documents/search?q={query}&n={self.top_k_results}"
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response = requests.get(
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url, headers={"x-api-key": cast(str, self.rememberizer_api_key)}
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)
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data = response.json()
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if response.status_code != 200:
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raise ValueError(f"API Error: {data}")
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matched_chunks = data.get("matched_chunks", [])
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return matched_chunks
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def load(self, query: str) -> List[Document]:
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matched_chunks = self.search(query)
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docs = []
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for matched_chunk in matched_chunks:
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docs.append(
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Document(
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page_content=matched_chunk["matched_content"],
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metadata=matched_chunk["document"],
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)
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)
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return docs
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