add unasync to project dependencies (#56)

* add unasync and isort to project dependencies

* replace isort with ruff

* update poetry.lock

* revert elasticsearch client to 8.15.1 for now

libs/elasticsearch/pyproject.toml

@@ -57,6 +57,8 @@ optional = true
 
 [tool.poetry.group.test_integration.dependencies]
 
+[tool.poetry.group.codegen.dependencies]
+unasync = "^0.6.0"
 
 [tool.ruff]
 select = [

libs/elasticsearch/scripts/run_unasync.py

@@ -111,7 +111,7 @@ def main(check=False):
     for dir in source_dirs:
         output_dir = f"{dir[0]}_sync_check/" if check else dir[1]
         subprocess.check_call(["ruff", "format", "--target-version=py38", output_dir])
-        subprocess.check_call(["isort", output_dir])
+        subprocess.check_call(["ruff", "check", "--fix", "--select", "I", output_dir])
         for file in glob("*.py", root_dir=dir[0]):
             subprocess.check_call(
                 [

libs/elasticsearch/tests/integration_tests/_sync/_test_utilities.py

@@ -2,7 +2,12 @@
 from typing import Any, Dict, List, Optional
 
 from elastic_transport import Transport
-from elasticsearch import BadRequestError, ConflictError, Elasticsearch, NotFoundError
+from elasticsearch import (
+    BadRequestError,
+    ConflictError,
+    Elasticsearch,
+    NotFoundError,
+)
 
 
 def read_env() -> Dict:

libs/elasticsearch/tests/integration_tests/_sync/test_cache.py

@@ -6,7 +6,10 @@
 from langchain.globals import set_llm_cache
 from langchain_core.language_models import BaseChatModel
 
-from langchain_elasticsearch import ElasticsearchCache, ElasticsearchEmbeddingsCache
+from langchain_elasticsearch import (
+    ElasticsearchCache,
+    ElasticsearchEmbeddingsCache,
+)
 
 from ._test_utilities import clear_test_indices, create_es_client, read_env
 

libs/elasticsearch/tests/unit_tests/_sync/test_cache.py

@@ -11,7 +11,10 @@
 from langchain_core.load import dumps
 from langchain_core.outputs import Generation
 
-from langchain_elasticsearch import ElasticsearchCache, ElasticsearchEmbeddingsCache
+from langchain_elasticsearch import (
+    ElasticsearchCache,
+    ElasticsearchEmbeddingsCache,
+)
 
 
 def serialize_encode_vector(vector: Any) -> str: