Change Anthropic LLM and Chat to be LangFlow friendly

libs/langchain/langchain/chat_models/anthropic.py

@@ -76,7 +76,8 @@ class ChatAnthropic(BaseChatModel, _AnthropicCommon):
 
             import anthropic
             from langchain.chat_models import ChatAnthropic
-            model = ChatAnthropic(model="<model_name>", anthropic_api_key="my-api-key")
+            model = ChatAnthropic(model_name="<model_name>",
+                                  anthropic_api_key="my-api-key")
     """
 
     class Config:

libs/langchain/langchain/llms/anthropic.py

@@ -21,7 +21,7 @@
 class _AnthropicCommon(BaseLanguageModel):
     client: Any = None  #: :meta private:
     async_client: Any = None  #: :meta private:
-    model: str = Field(default="claude-2", alias="model_name")
+    model_name: str = Field(default="claude-2", alias="model_name")
     """Model name to use."""
 
     max_tokens_to_sample: int = Field(default=256, alias="max_tokens")
@@ -30,6 +30,9 @@ class _AnthropicCommon(BaseLanguageModel):
     temperature: Optional[float] = None
     """A non-negative float that tunes the degree of randomness in generation."""
 
+    max_tokens: int = 256
+    """Denotes the number of tokens to predict per generation."""
+
     top_k: Optional[int] = None
     """Number of most likely tokens to consider at each step."""
 
@@ -60,6 +63,15 @@ def build_extra(cls, values: Dict) -> Dict:
         )
         return values
 
+    # Backwards compatibility for change to common model_name property.
+    @property
+    def model(self) -> str:
+        return self.model_name
+
+    @model.setter
+    def model(self, value: str) -> None:
+        self.model_name = value
+
     @root_validator()
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
@@ -103,8 +115,8 @@ def validate_environment(cls, values: Dict) -> Dict:
     def _default_params(self) -> Mapping[str, Any]:
         """Get the default parameters for calling Anthropic API."""
         d = {
-            "max_tokens_to_sample": self.max_tokens_to_sample,
-            "model": self.model,
+            "max_tokens_to_sample": self.max_tokens,
+            "model": self.model_name,
         }
         if self.temperature is not None:
             d["temperature"] = self.temperature
@@ -144,8 +156,7 @@ class Anthropic(LLM, _AnthropicCommon):
 
             import anthropic
             from langchain.llms import Anthropic
-
-            model = Anthropic(model="<model_name>", anthropic_api_key="my-api-key")
+            model = Anthropic(model_name="<model_name>", anthropic_api_key="my-api-key")
 
             # Simplest invocation, automatically wrapped with HUMAN_PROMPT
             # and AI_PROMPT.

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

@@ -14,6 +14,15 @@
 
 
 def test_anthropic_call() -> None:
+    """Test valid call to anthropic."""
+    chat = ChatAnthropic(model_name="test")
+    message = HumanMessage(content="Hello")
+    response = chat([message])
+    assert isinstance(response, AIMessage)
+    assert isinstance(response.content, str)
+
+
+def test_anthropic_call_using_model() -> None:
     """Test valid call to anthropic."""
     chat = ChatAnthropic(model="test")
     message = HumanMessage(content="Hello")
@@ -40,7 +49,7 @@ def test_anthropic_generate() -> None:
 
 def test_anthropic_streaming() -> None:
     """Test streaming tokens from anthropic."""
-    chat = ChatAnthropic(model="test", streaming=True)
+    chat = ChatAnthropic(model_name="test", streaming=True)
     message = HumanMessage(content="Hello")
     response = chat([message])
     assert isinstance(response, AIMessage)
@@ -52,7 +61,7 @@ def test_anthropic_streaming_callback() -> None:
     callback_handler = FakeCallbackHandler()
     callback_manager = CallbackManager([callback_handler])
     chat = ChatAnthropic(
-        model="test",
+        model_name="test",
         streaming=True,
         callback_manager=callback_manager,
         verbose=True,
@@ -68,7 +77,7 @@ async def test_anthropic_async_streaming_callback() -> None:
     callback_handler = FakeCallbackHandler()
     callback_manager = CallbackManager([callback_handler])
     chat = ChatAnthropic(
-        model="test",
+        model_name="test",
         streaming=True,
         callback_manager=callback_manager,
         verbose=True,

libs/langchain/tests/integration_tests/llms/test_anthropic.py

@@ -23,14 +23,14 @@ def test_anthropic_model_param() -> None:
 
 def test_anthropic_call() -> None:
     """Test valid call to anthropic."""
-    llm = Anthropic(model="claude-instant-1")
+    llm = Anthropic(model_name="claude-instant-1")
     output = llm("Say foo:")
     assert isinstance(output, str)
 
 
 def test_anthropic_streaming() -> None:
     """Test streaming tokens from anthropic."""
-    llm = Anthropic(model="claude-instant-1")
+    llm = Anthropic(model_name="claude-instant-1")
     generator = llm.stream("I'm Pickle Rick")
 
     assert isinstance(generator, Generator)