infra: update mypy 1.10, ruff 0.5 (#23721)

```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()

```

libs/experimental/tests/unit_tests/conftest.py

@@ -1,4 +1,5 @@
 """Configuration for unit tests."""
+
 from importlib import util
 from typing import Dict, Sequence
 

libs/experimental/tests/unit_tests/fake_llm.py

@@ -1,4 +1,5 @@
 """Fake LLM wrapper for testing purposes."""
+
 from typing import Any, Dict, List, Mapping, Optional, cast
 
 from langchain_core.callbacks.manager import CallbackManagerForLLMRun

libs/experimental/tests/unit_tests/rl_chain/test_pick_best_chain_call.py

@@ -80,7 +80,7 @@ def test_update_with_delayed_score_with_auto_validator_throws() -> None:
     chain = pick_best_chain.PickBest.from_llm(
         llm=llm,
         prompt=PROMPT,
-        selection_scorer=rl_chain.AutoSelectionScorer(llm=auto_val_llm),
+        selection_scorer=rl_chain.AutoSelectionScorer(llm=auto_val_llm),  # type: ignore[call-arg]
         feature_embedder=pick_best_chain.PickBestFeatureEmbedder(
             auto_embed=False, model=MockEncoder()
         ),
@@ -108,7 +108,7 @@ def test_update_with_delayed_score_force() -> None:
     chain = pick_best_chain.PickBest.from_llm(
         llm=llm,
         prompt=PROMPT,
-        selection_scorer=rl_chain.AutoSelectionScorer(llm=auto_val_llm),
+        selection_scorer=rl_chain.AutoSelectionScorer(llm=auto_val_llm),  # type: ignore[call-arg]
         feature_embedder=pick_best_chain.PickBestFeatureEmbedder(
             auto_embed=False, model=MockEncoder()
         ),
@@ -383,7 +383,7 @@ def test_auto_scorer_with_user_defined_llm() -> None:
     chain = pick_best_chain.PickBest.from_llm(
         llm=llm,
         prompt=PROMPT,
-        selection_scorer=rl_chain.AutoSelectionScorer(llm=scorer_llm),
+        selection_scorer=rl_chain.AutoSelectionScorer(llm=scorer_llm),  # type: ignore[call-arg]
         feature_embedder=pick_best_chain.PickBestFeatureEmbedder(
             auto_embed=False, model=MockEncoder()
         ),
@@ -429,7 +429,7 @@ def test_activate_and_deactivate_scorer() -> None:
     chain = pick_best_chain.PickBest.from_llm(
         llm=llm,
         prompt=PROMPT,
-        selection_scorer=pick_best_chain.base.AutoSelectionScorer(llm=scorer_llm),
+        selection_scorer=pick_best_chain.base.AutoSelectionScorer(llm=scorer_llm),  # type: ignore[call-arg]
         feature_embedder=pick_best_chain.PickBestFeatureEmbedder(
             auto_embed=False, model=MockEncoder()
         ),

libs/experimental/tests/unit_tests/test_bash.py

@@ -1,4 +1,5 @@
 """Test the bash utility."""
+
 import re
 import subprocess
 import sys

libs/experimental/tests/unit_tests/test_logical_fallacy.py

@@ -1,4 +1,5 @@
 """Unit tests for the Logical Fallacy chain, same format as CAI"""
+
 from langchain_experimental.fallacy_removal.base import FallacyChain
 
 TEXT_ONE = """ This text is bad.\

libs/experimental/tests/unit_tests/test_pal.py

@@ -1,4 +1,5 @@
 """Test LLM PAL functionality."""
+
 import pytest
 
 from langchain_experimental.pal_chain.base import PALChain, PALValidation

libs/experimental/tests/unit_tests/test_smartllm.py

@@ -1,4 +1,5 @@
 """Test SmartLLM."""
+
 from langchain_community.chat_models import FakeListChatModel
 from langchain_community.llms import FakeListLLM
 from langchain_core.prompts.prompt import PromptTemplate