Exclude max_tokens from request if it's None (#14334)

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We found a request with `max_tokens=None` results in the following error
in Anthropic:

```
HTTPError: 400 Client Error: Bad Request for url: https://oregon.staging.cloud.databricks.com/serving-endpoints/corey-anthropic/invocations. 
Response text: {"error_code":"INVALID_PARAMETER_VALUE","message":"INVALID_PARAMETER_VALUE: max_tokens was not of type Integer: null"}
```

This PR excludes `max_tokens` if it's None.

libs/langchain/langchain/chat_models/mlflow.py

@@ -115,13 +115,13 @@ def _generate(
             "messages": message_dicts,
             "temperature": self.temperature,
             "n": self.n,
-            "stop": stop or self.stop,
-            "max_tokens": self.max_tokens,
             **self.extra_params,
             **kwargs,
         }
         if stop := self.stop or stop:
             data["stop"] = stop
+        if self.max_tokens is not None:
+            data["max_tokens"] = self.max_tokens
         resp = self._client.predict(endpoint=self.endpoint, inputs=data)
         return ChatMlflow._create_chat_result(resp)
 

libs/langchain/langchain/llms/databricks.py

@@ -334,13 +334,14 @@ class Config:
 
     @property
     def _llm_params(self) -> Dict[str, Any]:
-        params = {
+        params: Dict[str, Any] = {
             "temperature": self.temperature,
             "n": self.n,
-            "stop": self.stop,
-            "max_tokens": self.max_tokens,
-            **(self.model_kwargs or self.extra_params),
         }
+        if self.stop:
+            params["stop"] = self.stop
+        if self.max_tokens is not None:
+            params["max_tokens"] = self.max_tokens
         return params
 
     @validator("cluster_id", always=True)
@@ -457,11 +458,9 @@ def _call(
         request: Dict[str, Any] = {"prompt": prompt}
         if self._client.llm:
             request.update(self._llm_params)
-            request.update(self.model_kwargs or self.extra_params)
-        else:
-            request.update(self.model_kwargs or self.extra_params)
+        request.update(self.model_kwargs or self.extra_params)
         request.update(kwargs)
-        if stop := self.stop or stop:
+        if stop:
             request["stop"] = stop
 
         if self.transform_input_fn:

libs/langchain/langchain/llms/mlflow.py

@@ -106,12 +106,14 @@ def _call(
             "prompt": prompt,
             "temperature": self.temperature,
             "n": self.n,
-            "max_tokens": self.max_tokens,
             **self.extra_params,
             **kwargs,
         }
         if stop := self.stop or stop:
             data["stop"] = stop
+        if self.max_tokens is not None:
+            data["max_tokens"] = self.max_tokens
+
         resp = self._client.predict(endpoint=self.endpoint, inputs=data)
         return resp["choices"][0]["text"]