feat(llms): add missing params to huggingface text-generation (#9724)

This small PR aims at supporting the following missing parameters in the
`HuggingfaceTextGen` LLM:
- `return_full_text` - sometimes useful for completion tasks
- `do_sample` - quite handy to control the randomness of the model.
- `watermark`

@hwchase17 @baskaryan

---------

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

libs/langchain/langchain/llms/huggingface_text_gen_inference.py

@@ -80,6 +80,7 @@ class HuggingFaceTextGenInference(LLM):
     typical_p: Optional[float] = 0.95
     temperature: float = 0.8
     repetition_penalty: Optional[float] = None
+    return_full_text: bool = False
     truncate: Optional[int] = None
     stop_sequences: List[str] = Field(default_factory=list)
     seed: Optional[int] = None
@@ -87,6 +88,8 @@ class HuggingFaceTextGenInference(LLM):
     timeout: int = 120
     server_kwargs: Dict[str, Any] = Field(default_factory=dict)
     streaming: bool = False
+    do_sample: bool = False
+    watermark: bool = False
     client: Any
     async_client: Any
 
@@ -134,9 +137,12 @@ class HuggingFaceTextGenInference(LLM):
             "typical_p": self.typical_p,
             "temperature": self.temperature,
             "repetition_penalty": self.repetition_penalty,
+            "return_full_text": self.return_full_text,
             "truncate": self.truncate,
             "stop_sequences": self.stop_sequences,
             "seed": self.seed,
+            "do_sample": self.do_sample,
+            "watermark": self.watermark,
         }
 
     def _invocation_params(