Normalize chat messages sent to gemini funcs to work with prompt tracer

Previously messages passed to gemini (chat) completion functions
got a little of Gemini specific formatting mixed in.

These functions expect a message of type list[ChatMessage] to work
with prompt tracer etc.

Move the code to format messages of type list[ChatMessage] into gemini
specific format down to the gemini (chat) completion functions.

This allows the rest of the functionality like prompt tracing to work
with normalize list[ChatMesssage] type of chat messages across
providers

src/khoj/processor/conversation/google/gemini_chat.py

@@ -134,8 +134,6 @@ def gemini_send_message_to_model(
     """
     Send message to model
     """
-    messages_for_gemini, system_prompt = format_messages_for_gemini(messages)
-
     model_kwargs = {}
 
     # This caused unwanted behavior and terminates response early for gemini 1.5 series. Monitor for flakiness with 2.0 series.
@@ -145,8 +143,8 @@ def gemini_send_message_to_model(
 
     # Get Response from Gemini
     return gemini_completion_with_backoff(
-        messages=messages_for_gemini,
-        system_prompt=system_prompt,
+        messages=messages,
+        system_prompt="",
         model_name=model,
         api_key=api_key,
         api_base_url=api_base_url,
@@ -244,12 +242,11 @@ def converse_gemini(
         program_execution_context=program_execution_context,
     )
 
-    messages_for_gemini, system_prompt = format_messages_for_gemini(messages, system_prompt)
     logger.debug(f"Conversation Context for Gemini: {messages_to_print(messages)}")
 
     # Get Response from Google AI
     return gemini_chat_completion_with_backoff(
-        messages=messages_for_gemini,
+        messages=messages,
         compiled_references=references,
         online_results=online_results,
         model_name=model,

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

@@ -80,6 +80,8 @@ def gemini_completion_with_backoff(
         client = get_gemini_client(api_key, api_base_url)
         gemini_clients[api_key] = client
 
+    formatted_messages, system_prompt = format_messages_for_gemini(messages, system_prompt)
+
     seed = int(os.getenv("KHOJ_LLM_SEED")) if os.getenv("KHOJ_LLM_SEED") else None
     config = gtypes.GenerateContentConfig(
         system_instruction=system_prompt,
@@ -91,8 +93,6 @@ def gemini_completion_with_backoff(
         seed=seed,
     )
 
-    formatted_messages = [gtypes.Content(role=message.role, parts=message.content) for message in messages]
-
     try:
         # Generate the response
         response = client.models.generate_content(model=model_name, config=config, contents=formatted_messages)
@@ -165,6 +165,8 @@ def gemini_llm_thread(
             client = get_gemini_client(api_key, api_base_url)
             gemini_clients[api_key] = client
 
+        formatted_messages, system_prompt = format_messages_for_gemini(messages, system_prompt)
+
         seed = int(os.getenv("KHOJ_LLM_SEED")) if os.getenv("KHOJ_LLM_SEED") else None
         config = gtypes.GenerateContentConfig(
             system_instruction=system_prompt,
@@ -176,7 +178,6 @@ def gemini_llm_thread(
         )
 
         aggregated_response = ""
-        formatted_messages = [gtypes.Content(role=message.role, parts=message.content) for message in messages]
 
         for chunk in client.models.generate_content_stream(
             model=model_name, config=config, contents=formatted_messages
@@ -300,4 +301,5 @@ def format_messages_for_gemini(
     if len(messages) == 1:
         messages[0].role = "user"
 
-    return messages, system_prompt
+    formatted_messages = [gtypes.Content(role=message.role, parts=message.content) for message in messages]
+    return formatted_messages, system_prompt