Add optional model kwargs to ChatAnthropic to allow overrides (#9013)

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>

libs/langchain/langchain/llms/anthropic.py

@@ -2,7 +2,7 @@ import re
 import warnings
 from typing import Any, AsyncIterator, Callable, Dict, Iterator, List, Mapping, Optional
 
-from pydantic import root_validator
+from pydantic import Field, root_validator
 
 from langchain.callbacks.manager import (
     AsyncCallbackManagerForLLMRun,
@@ -11,7 +11,12 @@ from langchain.callbacks.manager import (
 from langchain.llms.base import LLM
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.schema.output import GenerationChunk
-from langchain.utils import check_package_version, get_from_dict_or_env
+from langchain.utils import (
+    check_package_version,
+    get_from_dict_or_env,
+    get_pydantic_field_names,
+)
+from langchain.utils.utils import build_extra_kwargs
 
 
 class _AnthropicCommon(BaseLanguageModel):
@@ -45,6 +50,16 @@ class _AnthropicCommon(BaseLanguageModel):
     HUMAN_PROMPT: Optional[str] = None
     AI_PROMPT: Optional[str] = None
     count_tokens: Optional[Callable[[str], int]] = None
+    model_kwargs: Dict[str, Any] = Field(default_factory=dict)
+
+    @root_validator(pre=True)
+    def build_extra(cls, values: Dict) -> Dict:
+        extra = values.get("model_kwargs", {})
+        all_required_field_names = get_pydantic_field_names(cls)
+        values["model_kwargs"] = build_extra_kwargs(
+            extra, values, all_required_field_names
+        )
+        return values
 
     @root_validator()
     def validate_environment(cls, values: Dict) -> Dict:
@@ -77,6 +92,7 @@ class _AnthropicCommon(BaseLanguageModel):
             values["HUMAN_PROMPT"] = anthropic.HUMAN_PROMPT
             values["AI_PROMPT"] = anthropic.AI_PROMPT
             values["count_tokens"] = values["client"].count_tokens
+
         except ImportError:
             raise ImportError(
                 "Could not import anthropic python package. "
@@ -97,7 +113,7 @@ class _AnthropicCommon(BaseLanguageModel):
             d["top_k"] = self.top_k
         if self.top_p is not None:
             d["top_p"] = self.top_p
-        return d
+        return {**d, **self.model_kwargs}
 
     @property
     def _identifying_params(self) -> Mapping[str, Any]:

libs/langchain/poetry.lock

@@ -13608,7 +13608,7 @@ clarifai = ["clarifai"]
 cohere = ["cohere"]
 docarray = ["docarray"]
 embeddings = ["sentence-transformers"]
-extended-testing = ["amazon-textract-caller", "atlassian-python-api", "beautifulsoup4", "bibtexparser", "cassio", "chardet", "esprima", "feedparser", "geopandas", "gitpython", "gql", "html2text", "jinja2", "jq", "lxml", "mwparserfromhell", "mwxml", "newspaper3k", "openai", "openai", "pandas", "pdfminer-six", "pgvector", "psychicapi", "py-trello", "pymupdf", "pypdf", "pypdfium2", "pyspark", "rank-bm25", "rapidfuzz", "requests-toolbelt", "scikit-learn", "streamlit", "sympy", "telethon", "tqdm", "xata", "xinference", "xmltodict", "zep-python"]
+extended-testing = ["amazon-textract-caller", "anthropic", "atlassian-python-api", "beautifulsoup4", "bibtexparser", "cassio", "chardet", "esprima", "feedparser", "geopandas", "gitpython", "gql", "html2text", "jinja2", "jq", "lxml", "mwparserfromhell", "mwxml", "newspaper3k", "openai", "openai", "pandas", "pdfminer-six", "pgvector", "psychicapi", "py-trello", "pymupdf", "pypdf", "pypdfium2", "pyspark", "rank-bm25", "rapidfuzz", "requests-toolbelt", "scikit-learn", "streamlit", "sympy", "telethon", "tqdm", "xata", "xinference", "xmltodict", "zep-python"]
 javascript = ["esprima"]
 llms = ["anthropic", "clarifai", "cohere", "huggingface_hub", "manifest-ml", "nlpcloud", "openai", "openllm", "openlm", "torch", "transformers", "xinference"]
 openai = ["openai", "tiktoken"]
@@ -13619,4 +13619,4 @@ text-helpers = ["chardet"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8.1,<4.0"
-content-hash = "a8bc3bc0555543de183b659147b47d4b686843bb80a2be94ef5c319af3cb1ed0"
+content-hash = "a8fd5dbcab821e39c502724e13a2f85b718f3e06c7c3f98062de01a44cf1ff6e"

libs/langchain/pyproject.toml

@@ -373,6 +373,7 @@ extended_testing = [
  "feedparser",
  "xata",
  "xmltodict",
+ "anthropic",
 ]
 
 scheduled_testing = [

libs/langchain/tests/unit_tests/chat_models/test_anthropic.py

@@ -0,0 +1,27 @@
+"""Test Anthropic Chat API wrapper."""
+import os
+
+import pytest
+
+from langchain.chat_models import ChatAnthropic
+
+os.environ["ANTHROPIC_API_KEY"] = "foo"
+
+
+@pytest.mark.requires("anthropic")
+def test_anthropic_model_kwargs() -> None:
+    llm = ChatAnthropic(model_kwargs={"foo": "bar"})
+    assert llm.model_kwargs == {"foo": "bar"}
+
+
+@pytest.mark.requires("anthropic")
+def test_anthropic_invalid_model_kwargs() -> None:
+    with pytest.raises(ValueError):
+        ChatAnthropic(model_kwargs={"max_tokens_to_sample": 5})
+
+
+@pytest.mark.requires("anthropic")
+def test_anthropic_incorrect_field() -> None:
+    with pytest.warns(match="not default parameter"):
+        llm = ChatAnthropic(foo="bar")
+    assert llm.model_kwargs == {"foo": "bar"}