mirror of
https://github.com/hwchase17/langchain.git
synced 2025-06-19 21:33:51 +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()
```
91 lines
4.3 KiB
Python
91 lines
4.3 KiB
Python
# flake8: noqa
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from langchain_core.prompts import (
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ChatPromptTemplate,
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HumanMessagePromptTemplate,
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)
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from langchain_core.messages import SystemMessage
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JOIN_SIMILAR_VIDEO_MODELS_TEMPLATE = """
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I will provide you with several descriptions depicting events in one scene.
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Your task is to combine these descriptions into one description that contains only the important details from all descriptions.
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Especially if the two descriptions are very similar, make sure your response doesn't repeat itself.
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IMPORTANT: Do not make up a description. Do not make up events or anything that happened outside of the descriptions I am to provide you.
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I will now provide an example for you to learn from:
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Example: Description 1: The cat is at the beach, Description 2: The cat is eating lunch, Description 3: The cat is enjoying his time with friends
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Result: The cat is at the beach, eating lunch with his friends
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Now that I gave you the example, I will explain to you what exactly you need to return:
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Just give back one description, the description which is a combination of the descriptions you are provided with.
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Do not include anything else in your response other than the combined description.
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IMPORTANT: the output in your response should be 'Result:text', where text is the description you generated.
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Here is the data for you to work with in order to formulate your response:
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"""
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JOIN_SIMILAR_VIDEO_MODELS_PROMPT = ChatPromptTemplate( # type: ignore[call-arg]
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messages=[
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SystemMessage(content=JOIN_SIMILAR_VIDEO_MODELS_TEMPLATE),
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HumanMessagePromptTemplate.from_template("{descriptions}"),
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]
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)
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REMOVE_VIDEO_MODEL_DESCRIPTION_TEMPLATE = """
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Given a closed-caption description of an image or scene, remove any common prefixes like "an image of," "a scene of," or "footage of."
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For instance, if the description is "an image of a beautiful landscape," the modified version should be "a beautiful landscape."
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IMPORTANT: the output in your response should be 'Result:text', where text is the description you generated.
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Here are some examples:
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Input: an image of a beautiful landscape
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Result: a beautiful landscape
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Input: a scene of people enjoying a picnic
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Result: people enjoying a picnic
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Below is the input for you to generate the result from:
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"""
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REMOVE_VIDEO_MODEL_DESCRIPTION_PROMPT = ChatPromptTemplate( # type: ignore[call-arg]
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messages=[
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SystemMessage(content=REMOVE_VIDEO_MODEL_DESCRIPTION_TEMPLATE),
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HumanMessagePromptTemplate.from_template("Input: {description}"),
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]
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)
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VALIDATE_AND_ADJUST_DESCRIPTION_TEMPLATE = """
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You are tasked with enhancing closed-caption descriptions based on corresponding subtitles from the audio of a real movie clip.
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Assignment details, from highest to lowest priority:
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1) If the subtitle exceeds Limit characters, creatively rewrite the description to not exceed the character limit, preserving as many details as you can.
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If you feel that you cannot complete the response under the character limit, you must omit details in order to remain below the character limit.
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2) If the details in the subtitle provide meaningful additional information to its closed-caption description, incorporate those details into the description.
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Enhance the closed-caption description by integrating details from the subtitle if they contribute meaningful information.
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Example:
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Subtitle: car screeching, tires squealing
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Closed-Caption Description: A car speeds down the street.
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Output: Result: A car speeds down the street, its tires screeching and squealing.
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**IMPORTANT**: Remember your assignment details when formulating your response! YOU MUST NOT EXCEED LIMIT CHARACTERS at human message.
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***IMPORTANT***: You must only return the following text in your response. You may not return a response that does not follow the exact format in the next line:
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Result: Text
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**** YOU MUST PROVIDE ME WITH THE BEST ANSWER YOU CAN COME UP WITH,
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**** EVEN IF YOU DEEM THAT IT IS A BAD ONE. YOU MUST ONLY RESPOND IN THE FORMAT IN THE NEXT LINE:
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Result: Text
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Below is the data provided, generate a response using this data:
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"""
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VALIDATE_AND_ADJUST_DESCRIPTION_PROMPT = ChatPromptTemplate( # type: ignore[call-arg]
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messages=[
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SystemMessage(content=VALIDATE_AND_ADJUST_DESCRIPTION_TEMPLATE),
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HumanMessagePromptTemplate.from_template(
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"Limit: {limit}\nSubtitle: {subtitle}\nClosed-Caption Description: {description}"
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),
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]
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)
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