Fix, improve args being passed to chat_completion args

- Allow passing completion args through completion_with_backoff
- Pass model_kwargs in a separate arg to simplify this
- Pass model in `model_name' kwarg from the send_message_to_model func
  `model_name' kwarg is used by langchain, not `model' kwarg

src/khoj/processor/conversation/openai/gpt.py

@@ -64,11 +64,12 @@ def extract_questions(
     # Get Response from GPT
     response = completion_with_backoff(
         messages=messages,
-        model_name=model,
+        completion_kwargs={"temperature": temperature, "max_tokens": max_tokens},
-        temperature=temperature,
+        model_kwargs={
-        max_tokens=max_tokens,
+            "model_name": model,
-        model_kwargs={"response_format": {"type": "json_object"}},
+            "openai_api_key": api_key,
-        openai_api_key=api_key,
+            "model_kwargs": {"response_format": {"type": "json_object"}},
+        },
     )
 
     # Extract, Clean Message from GPT's Response
@@ -96,9 +97,11 @@ def send_message_to_model(messages, api_key, model, response_type="text"):
     # Get Response from GPT
     return completion_with_backoff(
         messages=messages,
-        model=model,
+        model_kwargs={
-        openai_api_key=api_key,
+            "model_name": model,
-        model_kwargs={"response_format": {"type": response_type}},
+            "openai_api_key": api_key,
+            "model_kwargs": {"response_format": {"type": response_type}},
+        },
     )
 
 

src/khoj/processor/conversation/openai/utils.py

@@ -43,13 +43,12 @@ class StreamingChatCallbackHandler(StreamingStdOutCallbackHandler):
     before_sleep=before_sleep_log(logger, logging.DEBUG),
     reraise=True,
 )
-def completion_with_backoff(**kwargs) -> str:
+def completion_with_backoff(messages, model_kwargs={}, completion_kwargs={}) -> str:
-    messages = kwargs.pop("messages")
+    if not "openai_api_key" in model_kwargs:
-    if not "openai_api_key" in kwargs:
+        model_kwargs["openai_api_key"] = os.getenv("OPENAI_API_KEY")
-        kwargs["openai_api_key"] = os.getenv("OPENAI_API_KEY")
+    llm = ChatOpenAI(**model_kwargs, request_timeout=20, max_retries=1)
-    llm = ChatOpenAI(**kwargs, request_timeout=20, max_retries=1)
     aggregated_response = ""
-    for chunk in llm.stream(messages):
+    for chunk in llm.stream(messages, **completion_kwargs):
         aggregated_response += chunk.content
     return aggregated_response