langchain-google-vertexai[patch]: more verbose mypy config (#16307)

Flushing out the `mypy` config in `langchain-google-vertexai` to show
error codes and other warnings

This PR also bumps `mypy` to above version 1's stable release

libs/partners/google-vertexai/langchain_google_vertexai/_utils.py

@@ -4,7 +4,7 @@ from typing import Any, Callable, Dict, Optional, Union
 
 import google.api_core
 from google.api_core.gapic_v1.client_info import ClientInfo
-from google.cloud import storage  # type: ignore
+from google.cloud import storage
 from langchain_core.callbacks import (
     AsyncCallbackManagerForLLMRun,
     CallbackManagerForLLMRun,

libs/partners/google-vertexai/langchain_google_vertexai/functions_utils.py

@@ -11,9 +11,7 @@ from langchain_core.utils.json_schema import dereference_refs
 from vertexai.preview.generative_models import (  # type: ignore
     FunctionDeclaration,
 )
-from vertexai.preview.generative_models import (
-    Tool as VertexTool,  # type: ignore
-)
+from vertexai.preview.generative_models import Tool as VertexTool
 
 
 def _format_pydantic_to_vertex_function(

libs/partners/google-vertexai/langchain_google_vertexai/llms.py

@@ -3,7 +3,7 @@ from __future__ import annotations
 from concurrent.futures import Executor
 from typing import Any, ClassVar, Dict, Iterator, List, Optional, Union
 
-import vertexai  # type: ignore
+import vertexai  # type: ignore[import-untyped]
 from google.api_core.client_options import ClientOptions
 from google.cloud.aiplatform.gapic import (
     PredictionServiceAsyncClient,
@@ -19,18 +19,18 @@ from langchain_core.callbacks.manager import (
 from langchain_core.language_models.llms import BaseLLM
 from langchain_core.outputs import Generation, GenerationChunk, LLMResult
 from langchain_core.pydantic_v1 import BaseModel, Field, root_validator
-from vertexai.language_models import (  # type: ignore
+from vertexai.language_models import (  # type: ignore[import-untyped]
     CodeGenerationModel,
     TextGenerationModel,
 )
-from vertexai.language_models._language_models import (  # type: ignore
+from vertexai.language_models._language_models import (  # type: ignore[import-untyped]
     TextGenerationResponse,
 )
-from vertexai.preview.generative_models import (  # type: ignore
+from vertexai.preview.generative_models import (  # type: ignore[import-untyped]
     GenerativeModel,
     Image,
 )
-from vertexai.preview.language_models import (  # type: ignore
+from vertexai.preview.language_models import (  # type: ignore[import-untyped]
     CodeGenerationModel as PreviewCodeGenerationModel,
 )
 from vertexai.preview.language_models import (
@@ -449,9 +449,7 @@ class VertexAIModelGarden(_VertexAIBase, BaseLLM):
     @property
     def endpoint_path(self) -> str:
         return self.client.endpoint_path(
-            project=self.project,  # type: ignore
-            location=self.location,
-            endpoint=self.endpoint_id,
+            project=self.project, location=self.location, endpoint=self.endpoint_id
         )
 
     @property

libs/partners/google-vertexai/poetry.lock

@@ -486,13 +486,13 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-api-python-client"
-version = "2.114.0"
+version = "2.115.0"
 description = "Google API Client Library for Python"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-api-python-client-2.114.0.tar.gz", hash = "sha256:e041bbbf60e682261281e9d64b4660035f04db1cccba19d1d68eebc24d1465ed"},
-    {file = "google_api_python_client-2.114.0-py2.py3-none-any.whl", hash = "sha256:690e0bb67d70ff6dea4e8a5d3738639c105a478ac35da153d3b2a384064e9e1a"},
+    {file = "google-api-python-client-2.115.0.tar.gz", hash = "sha256:96af11376535236ba600ebbe23588cfe003ec9b74e66dd6ddb53aa3ec87e1b52"},
+    {file = "google_api_python_client-2.115.0-py2.py3-none-any.whl", hash = "sha256:26178e33684763099142e2cad201057bd27d4efefd859a495aac21ab3e6129c2"},
 ]
 
 [package.dependencies]
@@ -1015,7 +1015,7 @@ files = [
 
 [[package]]
 name = "langchain"
-version = "0.1.1"
+version = "0.1.3"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = ">=3.8.1,<4.0"
@@ -1027,9 +1027,9 @@ aiohttp = "^3.8.3"
 async-timeout = {version = "^4.0.0", markers = "python_version < \"3.11\""}
 dataclasses-json = ">= 0.5.7, < 0.7"
 jsonpatch = "^1.33"
-langchain-community = ">=0.0.13,<0.1"
-langchain-core = ">=0.1.9,<0.2"
-langsmith = "~0.0.77"
+langchain-community = ">=0.0.14,<0.1"
+langchain-core = ">=0.1.14,<0.2"
+langsmith = ">=0.0.83,<0.1"
 numpy = "^1"
 pydantic = ">=1,<3"
 PyYAML = ">=5.3"
@@ -1058,20 +1058,20 @@ url = "../../langchain"
 
 [[package]]
 name = "langchain-community"
-version = "0.0.13"
+version = "0.0.15"
 description = "Community contributed LangChain integrations."
 optional = false
 python-versions = ">=3.8.1,<4.0"
 files = [
-    {file = "langchain_community-0.0.13-py3-none-any.whl", hash = "sha256:655196e446e7f37f4882221b6f3f791d6add28ea596d521ccf6f4507386b9a13"},
-    {file = "langchain_community-0.0.13.tar.gz", hash = "sha256:cf66c6ff7fcbeb582f5e88ee00decea7fdeca5ccddda725046f28efc697c41a7"},
+    {file = "langchain_community-0.0.15-py3-none-any.whl", hash = "sha256:2b830c79366e192aed2a997a11a69b62505fb2ee8d08a85f3df7bd3ab62473f1"},
+    {file = "langchain_community-0.0.15.tar.gz", hash = "sha256:b027d7765661300edced958228e78077780d96332efe63c5949bc5e435cc7c2b"},
 ]
 
 [package.dependencies]
 aiohttp = ">=3.8.3,<4.0.0"
 dataclasses-json = ">=0.5.7,<0.7"
-langchain-core = ">=0.1.9,<0.2"
-langsmith = ">=0.0.63,<0.1.0"
+langchain-core = ">=0.1.14,<0.2"
+langsmith = ">=0.0.83,<0.1"
 numpy = ">=1,<2"
 PyYAML = ">=5.3"
 requests = ">=2,<3"
@@ -1080,11 +1080,11 @@ tenacity = ">=8.1.0,<9.0.0"
 
 [package.extras]
 cli = ["typer (>=0.9.0,<0.10.0)"]
-extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.0,<3.0.0)", "anthropic (>=0.3.11,<0.4.0)", "arxiv (>=1.4,<2.0)", "assemblyai (>=0.17.0,<0.18.0)", "atlassian-python-api (>=3.36.0,<4.0.0)", "azure-ai-documentintelligence (>=1.0.0b1,<2.0.0)", "beautifulsoup4 (>=4,<5)", "bibtexparser (>=1.4.0,<2.0.0)", "cassio (>=0.1.0,<0.2.0)", "chardet (>=5.1.0,<6.0.0)", "cohere (>=4,<5)", "dashvector (>=1.0.1,<2.0.0)", "databricks-vectorsearch (>=0.21,<0.22)", "datasets (>=2.15.0,<3.0.0)", "dgml-utils (>=0.3.0,<0.4.0)", "esprima (>=4.0.1,<5.0.0)", "faiss-cpu (>=1,<2)", "feedparser (>=6.0.10,<7.0.0)", "fireworks-ai (>=0.9.0,<0.10.0)", "geopandas (>=0.13.1,<0.14.0)", "gitpython (>=3.1.32,<4.0.0)", "google-cloud-documentai (>=2.20.1,<3.0.0)", "gql (>=3.4.1,<4.0.0)", "gradientai (>=1.4.0,<2.0.0)", "hologres-vector (>=0.0.6,<0.0.7)", "html2text (>=2020.1.16,<2021.0.0)", "javelin-sdk (>=0.1.8,<0.2.0)", "jinja2 (>=3,<4)", "jq (>=1.4.1,<2.0.0)", "jsonschema (>1)", "lxml (>=4.9.2,<5.0.0)", "markdownify (>=0.11.6,<0.12.0)", "motor (>=3.3.1,<4.0.0)", "msal (>=1.25.0,<2.0.0)", "mwparserfromhell (>=0.6.4,<0.7.0)", "mwxml (>=0.3.3,<0.4.0)", "newspaper3k (>=0.2.8,<0.3.0)", "numexpr (>=2.8.6,<3.0.0)", "openai (<2)", "openapi-pydantic (>=0.3.2,<0.4.0)", "oracle-ads (>=2.9.1,<3.0.0)", "pandas (>=2.0.1,<3.0.0)", "pdfminer-six (>=20221105,<20221106)", "pgvector (>=0.1.6,<0.2.0)", "praw (>=7.7.1,<8.0.0)", "psychicapi (>=0.8.0,<0.9.0)", "py-trello (>=0.19.0,<0.20.0)", "pymupdf (>=1.22.3,<2.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pypdfium2 (>=4.10.0,<5.0.0)", "pyspark (>=3.4.0,<4.0.0)", "rank-bm25 (>=0.2.2,<0.3.0)", "rapidfuzz (>=3.1.1,<4.0.0)", "rapidocr-onnxruntime (>=1.3.2,<2.0.0)", "requests-toolbelt (>=1.0.0,<2.0.0)", "rspace_client (>=2.5.0,<3.0.0)", "scikit-learn (>=1.2.2,<2.0.0)", "sqlite-vss (>=0.1.2,<0.2.0)", "streamlit (>=1.18.0,<2.0.0)", "sympy (>=1.12,<2.0)", "telethon (>=1.28.5,<2.0.0)", "timescale-vector (>=0.0.1,<0.0.2)", "tqdm (>=4.48.0)", "upstash-redis (>=0.15.0,<0.16.0)", "xata (>=1.0.0a7,<2.0.0)", "xmltodict (>=0.13.0,<0.14.0)", "zhipuai (>=1.0.7,<2.0.0)"]
+extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.0,<3.0.0)", "anthropic (>=0.3.11,<0.4.0)", "arxiv (>=1.4,<2.0)", "assemblyai (>=0.17.0,<0.18.0)", "atlassian-python-api (>=3.36.0,<4.0.0)", "azure-ai-documentintelligence (>=1.0.0b1,<2.0.0)", "beautifulsoup4 (>=4,<5)", "bibtexparser (>=1.4.0,<2.0.0)", "cassio (>=0.1.0,<0.2.0)", "chardet (>=5.1.0,<6.0.0)", "cohere (>=4,<5)", "dashvector (>=1.0.1,<2.0.0)", "databricks-vectorsearch (>=0.21,<0.22)", "datasets (>=2.15.0,<3.0.0)", "dgml-utils (>=0.3.0,<0.4.0)", "elasticsearch (>=8.12.0,<9.0.0)", "esprima (>=4.0.1,<5.0.0)", "faiss-cpu (>=1,<2)", "feedparser (>=6.0.10,<7.0.0)", "fireworks-ai (>=0.9.0,<0.10.0)", "geopandas (>=0.13.1,<0.14.0)", "gitpython (>=3.1.32,<4.0.0)", "google-cloud-documentai (>=2.20.1,<3.0.0)", "gql (>=3.4.1,<4.0.0)", "gradientai (>=1.4.0,<2.0.0)", "hologres-vector (>=0.0.6,<0.0.7)", "html2text (>=2020.1.16,<2021.0.0)", "javelin-sdk (>=0.1.8,<0.2.0)", "jinja2 (>=3,<4)", "jq (>=1.4.1,<2.0.0)", "jsonschema (>1)", "lxml (>=4.9.2,<5.0.0)", "markdownify (>=0.11.6,<0.12.0)", "motor (>=3.3.1,<4.0.0)", "msal (>=1.25.0,<2.0.0)", "mwparserfromhell (>=0.6.4,<0.7.0)", "mwxml (>=0.3.3,<0.4.0)", "newspaper3k (>=0.2.8,<0.3.0)", "numexpr (>=2.8.6,<3.0.0)", "openai (<2)", "openapi-pydantic (>=0.3.2,<0.4.0)", "oracle-ads (>=2.9.1,<3.0.0)", "pandas (>=2.0.1,<3.0.0)", "pdfminer-six (>=20221105,<20221106)", "pgvector (>=0.1.6,<0.2.0)", "praw (>=7.7.1,<8.0.0)", "psychicapi (>=0.8.0,<0.9.0)", "py-trello (>=0.19.0,<0.20.0)", "pymupdf (>=1.22.3,<2.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pypdfium2 (>=4.10.0,<5.0.0)", "pyspark (>=3.4.0,<4.0.0)", "rank-bm25 (>=0.2.2,<0.3.0)", "rapidfuzz (>=3.1.1,<4.0.0)", "rapidocr-onnxruntime (>=1.3.2,<2.0.0)", "requests-toolbelt (>=1.0.0,<2.0.0)", "rspace_client (>=2.5.0,<3.0.0)", "scikit-learn (>=1.2.2,<2.0.0)", "sqlite-vss (>=0.1.2,<0.2.0)", "streamlit (>=1.18.0,<2.0.0)", "sympy (>=1.12,<2.0)", "telethon (>=1.28.5,<2.0.0)", "timescale-vector (>=0.0.1,<0.0.2)", "tqdm (>=4.48.0)", "upstash-redis (>=0.15.0,<0.16.0)", "xata (>=1.0.0a7,<2.0.0)", "xmltodict (>=0.13.0,<0.14.0)", "zhipuai (>=1.0.7,<2.0.0)"]
 
 [[package]]
 name = "langchain-core"
-version = "0.1.12"
+version = "0.1.15"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = ">=3.8.1,<4.0"
@@ -1094,7 +1094,7 @@ develop = true
 [package.dependencies]
 anyio = ">=3,<5"
 jsonpatch = "^1.33"
-langsmith = "~0.0.63"
+langsmith = ">=0.0.83,<0.1"
 packaging = "^23.2"
 pydantic = ">=1,<3"
 PyYAML = ">=5.3"
@@ -1110,13 +1110,13 @@ url = "../../core"
 
 [[package]]
 name = "langsmith"
-version = "0.0.81"
+version = "0.0.83"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = ">=3.8.1,<4.0"
 files = [
-    {file = "langsmith-0.0.81-py3-none-any.whl", hash = "sha256:eb816ad456776ec4c6005ddce8a4c315a1a582ed4d079979888e9f8a1db209b3"},
-    {file = "langsmith-0.0.81.tar.gz", hash = "sha256:5838e5a4bb1939e9794eb3f802f7c390247a847bd603e31442be5be00068e504"},
+    {file = "langsmith-0.0.83-py3-none-any.whl", hash = "sha256:a5bb7ac58c19a415a9d5f51db56dd32ee2cd7343a00825bbc2018312eb3d122a"},
+    {file = "langsmith-0.0.83.tar.gz", hash = "sha256:94427846b334ad9bdbec3266fee12903fe9f5448f628667689d0412012aaf392"},
 ]
 
 [package.dependencies]
@@ -1228,52 +1228,49 @@ files = [
 
 [[package]]
 name = "mypy"
-version = "0.991"
+version = "1.8.0"
 description = "Optional static typing for Python"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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+    {file = "mypy-1.8.0-py3-none-any.whl", hash = "sha256:538fd81bb5e430cc1381a443971c0475582ff9f434c16cd46d2c66763ce85d9d"},
+    {file = "mypy-1.8.0.tar.gz", hash = "sha256:6ff8b244d7085a0b425b56d327b480c3b29cafbd2eff27316a004f9a7391ae07"},
 ]
 
 [package.dependencies]
-mypy-extensions = ">=0.4.3"
+mypy-extensions = ">=1.0.0"
 tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
-typing-extensions = ">=3.10"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 dmypy = ["psutil (>=4.0)"]
 install-types = ["pip"]
-python2 = ["typed-ast (>=1.4.0,<2)"]
+mypyc = ["setuptools (>=50)"]
 reports = ["lxml"]
 
 [[package]]
@@ -1378,13 +1375,13 @@ files = [
 
 [[package]]
 name = "pluggy"
-version = "1.3.0"
+version = "1.4.0"
 description = "plugin and hook calling mechanisms for python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "pluggy-1.3.0-py3-none-any.whl", hash = "sha256:d89c696a773f8bd377d18e5ecda92b7a3793cbe66c87060a6fb58c7b6e1061f7"},
-    {file = "pluggy-1.3.0.tar.gz", hash = "sha256:cf61ae8f126ac6f7c451172cf30e3e43d3ca77615509771b3a984a0730651e12"},
+    {file = "pluggy-1.4.0-py3-none-any.whl", hash = "sha256:7db9f7b503d67d1c5b95f59773ebb58a8c1c288129a88665838012cfb07b8981"},
+    {file = "pluggy-1.4.0.tar.gz", hash = "sha256:8c85c2876142a764e5b7548e7d9a0e0ddb46f5185161049a79b7e974454223be"},
 ]
 
 [package.extras]
@@ -1785,28 +1782,28 @@ pyasn1 = ">=0.1.3"
 
 [[package]]
 name = "ruff"
-version = "0.1.13"
+version = "0.1.14"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 files = [
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-    {file = "ruff-0.1.13-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b13ba5d7156daaf3fd08b6b993360a96060500aca7e307d95ecbc5bb47a69296"},
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+    {file = "ruff-0.1.14.tar.gz", hash = "sha256:ad3f8088b2dfd884820289a06ab718cde7d38b94972212cc4ba90d5fbc9955f3"},
 ]
 
 [[package]]
@@ -2264,4 +2261,4 @@ multidict = ">=4.0"
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8.1,<4.0"
-content-hash = "a031be3cb062d347bc7b9e1ec95f37c5e0a5184f46c935cc77fbeac9b64bad62"
+content-hash = "2a339af4051981fb8aefc0d0ad4016bfb53c6f2d9b11abbfc22ae548fef91481"

libs/partners/google-vertexai/pyproject.toml

@@ -53,7 +53,7 @@ optional = true
 ruff = "^0.1.5"
 
 [tool.poetry.group.typing.dependencies]
-mypy = "^0.991"
+mypy = "^1"
 langchain-core = {path = "../../core", develop = true}
 types-google-cloud-ndb = "^2.2.0.20240106"
 
@@ -71,7 +71,16 @@ select = [
 ]
 
 [tool.mypy]
-disallow_untyped_defs = "True"
+check_untyped_defs = true
+error_summary = false
+pretty = true
+show_column_numbers = true
+show_error_codes = true
+show_error_context = true
+warn_redundant_casts = true
+warn_unreachable = true
+warn_unused_configs = true
+warn_unused_ignores = true
 
 [tool.coverage.run]
 omit = [

libs/partners/google-vertexai/tests/integration_tests/test_tools.py

@@ -44,11 +44,11 @@ class _TestOutputParser(BaseOutputParser):
 
 
 def test_tools() -> None:
-    from langchain.agents import AgentExecutor  # type: ignore
-    from langchain.agents.format_scratchpad import (  # type: ignore
+    from langchain.agents import AgentExecutor  # type: ignore[import-not-found]
+    from langchain.agents.format_scratchpad import (  # type: ignore[import-not-found]
         format_to_openai_function_messages,
     )
-    from langchain.chains import LLMMathChain  # type: ignore
+    from langchain.chains import LLMMathChain  # type: ignore[import-not-found]
 
     llm = ChatVertexAI(model_name="gemini-pro")
     math_chain = LLMMathChain.from_llm(llm=llm)
@@ -68,7 +68,7 @@ def test_tools() -> None:
     llm_with_tools = llm.bind(functions=tools)
 
     agent = (
-        {  # type: ignore
+        {  # type: ignore[var-annotated]
             "input": lambda x: x["input"],
             "agent_scratchpad": lambda x: format_to_openai_function_messages(
                 x["intermediate_steps"]
@@ -112,12 +112,12 @@ def test_stream() -> None:
 
 
 def test_multiple_tools() -> None:
-    from langchain.agents import AgentExecutor  # type: ignore
-    from langchain.agents.format_scratchpad import (
-        format_to_openai_function_messages,  # type: ignore
+    from langchain.agents import AgentExecutor
+    from langchain.agents.format_scratchpad import format_to_openai_function_messages
+    from langchain.chains import LLMMathChain
+    from langchain.utilities import (  # type: ignore[import-not-found]
+        GoogleSearchAPIWrapper,
     )
-    from langchain.chains import LLMMathChain  # type: ignore
-    from langchain.utilities import GoogleSearchAPIWrapper  # type: ignore
 
     llm = ChatVertexAI(model_name="gemini-pro", max_output_tokens=1024)
     math_chain = LLMMathChain.from_llm(llm=llm)
@@ -150,7 +150,7 @@ def test_multiple_tools() -> None:
     llm_with_tools = llm.bind(functions=tools)
 
     agent = (
-        {  # type: ignore
+        {  # type: ignore[var-annotated]
             "input": lambda x: x["input"],
             "agent_scratchpad": lambda x: format_to_openai_function_messages(
                 x["intermediate_steps"]

libs/partners/google-vertexai/tests/unit_tests/test_chat_models.py

@@ -1,5 +1,5 @@
 """Test chat model integration."""
-from typing import Optional
+from typing import Any, Dict, Optional
 from unittest.mock import MagicMock, Mock, patch
 
 import pytest
@@ -49,7 +49,7 @@ def test_parse_examples_failes_wrong_sequence() -> None:
 def test_vertexai_args_passed(stop: Optional[str]) -> None:
     response_text = "Goodbye"
     user_prompt = "Hello"
-    prompt_params = {
+    prompt_params: Dict[str, Any] = {
         "max_output_tokens": 1,
         "temperature": 10000.0,
         "top_k": 10,
@@ -69,7 +69,7 @@ def test_vertexai_args_passed(stop: Optional[str]) -> None:
         mock_model.start_chat = mock_start_chat
         mg.return_value = mock_model
 
-        model = ChatVertexAI(**prompt_params)  # type: ignore
+        model = ChatVertexAI(**prompt_params)
         message = HumanMessage(content=user_prompt)
         if stop:
             response = model([message], stop=[stop])