Unifies parameters to instantiate llm while incorporating model params (

jupyterlab#632)

* Unifies parameters to instantiate llm while incorporating model params

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

packages/jupyter-ai/jupyter_ai/chat_handlers/ask.py

@@ -43,8 +43,11 @@ def __init__(self, retriever, *args, **kwargs):
     def create_llm_chain(
         self, provider: Type[BaseProvider], provider_params: Dict[str, str]
     ):
-        model_parameters = self.get_model_parameters(provider, provider_params)
-        self.llm = provider(**provider_params, **model_parameters)
+        unified_parameters = {
+            **provider_params,
+            **(self.get_model_parameters(provider, provider_params)),
+        }
+        self.llm = provider(**unified_parameters)
         memory = ConversationBufferWindowMemory(
             memory_key="chat_history", return_messages=True, k=2
         )

packages/jupyter-ai/jupyter_ai/chat_handlers/default.py

@@ -23,8 +23,11 @@ def __init__(self, *args, **kwargs):
     def create_llm_chain(
         self, provider: Type[BaseProvider], provider_params: Dict[str, str]
     ):
-        model_parameters = self.get_model_parameters(provider, provider_params)
-        llm = provider(**provider_params, **model_parameters)
+        unified_parameters = {
+            **provider_params,
+            **(self.get_model_parameters(provider, provider_params)),
+        }
+        llm = provider(**unified_parameters)
 
         prompt_template = llm.get_chat_prompt_template()
         self.memory = ConversationBufferWindowMemory(

packages/jupyter-ai/jupyter_ai/chat_handlers/generate.py

@@ -236,8 +236,11 @@ def __init__(self, preferred_dir: str, log_dir: Optional[str], *args, **kwargs):
     def create_llm_chain(
         self, provider: Type[BaseProvider], provider_params: Dict[str, str]
     ):
-        model_parameters = self.get_model_parameters(provider, provider_params)
-        llm = provider(**provider_params, **model_parameters)
+        unified_parameters = {
+            **provider_params,
+            **(self.get_model_parameters(provider, provider_params)),
+        }
+        llm = provider(**unified_parameters)
 
         self.llm = llm
         return llm

packages/jupyter-ai/jupyter_ai/completions/handlers/default.py

@@ -28,8 +28,11 @@ def __init__(self, *args, **kwargs):
     def create_llm_chain(
         self, provider: Type[BaseProvider], provider_params: Dict[str, str]
     ):
-        model_parameters = self.get_model_parameters(provider, provider_params)
-        llm = provider(**provider_params, **model_parameters)
+        unified_parameters = {
+            **provider_params,
+            **(self.get_model_parameters(provider, provider_params)),
+        }
+        llm = provider(**unified_parameters)
 
         prompt_template = llm.get_completion_prompt_template()