mirror of
https://github.com/hwchase17/langchain.git
synced 2025-05-08 00:28:47 +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()
```
67 lines
2.2 KiB
Python
67 lines
2.2 KiB
Python
"""Util that calls SceneXplain.
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In order to set this up, you need API key for the SceneXplain API.
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You can obtain a key by following the steps below.
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- Sign up for a free account at https://scenex.jina.ai/.
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- Navigate to the API Access page (https://scenex.jina.ai/api) and create a new API key.
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"""
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from typing import Dict
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import requests
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from langchain_core.pydantic_v1 import BaseModel, BaseSettings, Field, root_validator
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from langchain_core.utils import get_from_dict_or_env
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class SceneXplainAPIWrapper(BaseSettings, BaseModel):
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"""Wrapper for SceneXplain API.
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In order to set this up, you need API key for the SceneXplain API.
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You can obtain a key by following the steps below.
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- Sign up for a free account at https://scenex.jina.ai/.
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- Navigate to the API Access page (https://scenex.jina.ai/api)
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and create a new API key.
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"""
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scenex_api_key: str = Field(..., env="SCENEX_API_KEY")
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scenex_api_url: str = "https://api.scenex.jina.ai/v1/describe"
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def _describe_image(self, image: str) -> str:
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headers = {
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"x-api-key": f"token {self.scenex_api_key}",
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"content-type": "application/json",
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}
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payload = {
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"data": [
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{
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"image": image,
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"algorithm": "Ember",
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"languages": ["en"],
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}
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]
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}
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response = requests.post(self.scenex_api_url, headers=headers, json=payload)
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response.raise_for_status()
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result = response.json().get("result", [])
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img = result[0] if result else {}
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return img.get("text", "")
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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 exists in environment."""
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scenex_api_key = get_from_dict_or_env(
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values, "scenex_api_key", "SCENEX_API_KEY"
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)
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values["scenex_api_key"] = scenex_api_key
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return values
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def run(self, image: str) -> str:
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"""Run SceneXplain image explainer."""
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description = self._describe_image(image)
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if not description:
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return "No description found."
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return description
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