From 258f0a69857c2b518544181302d09cac6daabc87 Mon Sep 17 00:00:00 2001
From: Christo Olivier <mail@christoolivier.com>
Date: Tue, 9 Jul 2024 13:23:32 +0100
Subject: [PATCH] Updated readme with Anthropic details. Update AnthropicModel
 to deepcopy settings.

---
 README.md                         |  6 ++++++
 pyproject.toml                    |  2 +-
 src/modelsmith/language_models.py | 15 ++++++++++-----
 3 files changed, 17 insertions(+), 6 deletions(-)

diff --git a/README.md b/README.md
index 893deb8..bc21cbe 100644
--- a/README.md
+++ b/README.md
@@ -31,6 +31,12 @@ Install Modelsmith using pip or your favourite python package manager.
 pip install modelsmith
 ```
 
+## Anthropic Authentication
+
+Authentication to Anthropic is done via the Anthropic flow. See the [Anthropic documentation](https://docs.anthropic.com/en/docs/quickstart#set-your-api-key) for more details. 
+
+The `AnthropicModel` class takes an optional `api_key` parameter. If not provided, the `ANTHROPIC_API_KEY` environment variable will be used.
+
 ## Google Cloud Authentication
 
 Authentication to Google Cloud is done via the Application Default Credentials flow. So make sure you have ADC configured. See [Google's documentation](https://cloud.google.com/docs/authentication/provide-credentials-adc) for more details.
diff --git a/pyproject.toml b/pyproject.toml
index 4d044ed..1016ca1 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "modelsmith"
-version = "0.6.0"
+version = "0.6.1"
 description = "Get Pydantic models and Python types as LLM responses from Google Vertex AI and OpenAI models."
 authors = ["Christo Olivier <mail@christoolivier.com>"]
 maintainers = ["Christo Olivier <mail@christoolivier.com>"]
diff --git a/src/modelsmith/language_models.py b/src/modelsmith/language_models.py
index 64a4b9f..5fbd462 100644
--- a/src/modelsmith/language_models.py
+++ b/src/modelsmith/language_models.py
@@ -1,3 +1,4 @@
+import copy
 from abc import ABC, abstractmethod
 from typing import Any
 
@@ -34,6 +35,10 @@ class AnthropicModel(BaseLanguageModel):
     def __init__(self, model_name: str, api_key: str | None = None) -> None:
         """
         Create a new synchronous anthropic client instance.
+
+        This automatically infers the following arguments from their corresponding
+        environment variables if they are not provided:
+        - `api_key` from ANTHROPIC_API_KEY
         """
         self.model_name = model_name
         self._client = Anthropic(api_key=api_key)
@@ -48,15 +53,15 @@ def send(self, input: str, model_settings: dict[str, Any] | None = None) -> str:
         :return: The response from the LLM.
         """
         # If `max_tokens` not provided in model settings then set it to the default
-        # of 1024
-        model_settings = model_settings or {}
-        if "max_tokens" not in model_settings:
-            model_settings["max_tokens"] = DEFAULT_MAX_TOKENS
+        # of 1024. Do a deep copy so that the original model settings are not modified.
+        settings = copy.deepcopy(model_settings) if model_settings else {}
+        if "max_tokens" not in settings:
+            settings["max_tokens"] = DEFAULT_MAX_TOKENS
 
         response = self._client.messages.create(
             model=self.model_name,
             messages=[{"role": "user", "content": input}],
-            **(model_settings or {}),
+            **settings,
         )
 
         return response.content[0].text