Pass context in separate message from user query to research chat actor

src/khoj/processor/conversation/prompts.py

@@ -673,10 +673,7 @@ Which of the tool AIs listed below would you use to answer my question? You **on
 
 Return the next tool AI to use and the query to ask it. Your response should always be a valid JSON object. Do not say anything else.
 Response format:
-{{"scratchpad": "<your_scratchpad_to_reason_about_which_tool_to_use>", "tool": "<name_of_tool_ai>", "query": "<your_query_for_the_tool_ai>"}}
-
-User: {query}
-Khoj:
+{{"scratchpad": "<your_scratchpad_to_reason_about_which_tool_to_use>", "tool": "<name_of_tool_ai>", "query": "<your_detailed_query_for_the_tool_ai>"}}
 """.strip()
 )
 

src/khoj/routers/helpers.py

@@ -799,7 +799,7 @@ async def generate_excalidraw_diagram_from_description(
 
     with timer("Chat actor: Generate excalidraw diagram", logger):
         raw_response = await send_message_to_model_wrapper(
-            message=excalidraw_diagram_generation, user=user, tracer=tracer
+            query=excalidraw_diagram_generation, user=user, tracer=tracer
         )
         raw_response = raw_response.strip()
         raw_response = remove_json_codeblock(raw_response)
@@ -879,11 +879,12 @@ async def generate_better_image_prompt(
 
 
 async def send_message_to_model_wrapper(
-    message: str,
+    query: str,
     system_message: str = "",
     response_type: str = "text",
     user: KhojUser = None,
     query_images: List[str] = None,
+    context: str = "",
     tracer: dict = {},
 ):
     conversation_config: ChatModelOptions = await ConversationAdapters.aget_default_conversation_config(user)
@@ -914,7 +915,8 @@ async def send_message_to_model_wrapper(
 
         loaded_model = state.offline_chat_processor_config.loaded_model
         truncated_messages = generate_chatml_messages_with_context(
-            user_message=message,
+            user_message=query,
+            context_message=context,
             system_message=system_message,
             model_name=chat_model,
             loaded_model=loaded_model,
@@ -939,7 +941,8 @@ async def send_message_to_model_wrapper(
         api_key = openai_chat_config.api_key
         api_base_url = openai_chat_config.api_base_url
         truncated_messages = generate_chatml_messages_with_context(
-            user_message=message,
+            user_message=query,
+            context_message=context,
             system_message=system_message,
             model_name=chat_model,
             max_prompt_size=max_tokens,
@@ -960,7 +963,8 @@ async def send_message_to_model_wrapper(
     elif model_type == ChatModelOptions.ModelType.ANTHROPIC:
         api_key = conversation_config.openai_config.api_key
         truncated_messages = generate_chatml_messages_with_context(
-            user_message=message,
+            user_message=query,
+            context_message=context,
             system_message=system_message,
             model_name=chat_model,
             max_prompt_size=max_tokens,
@@ -979,7 +983,8 @@ async def send_message_to_model_wrapper(
     elif model_type == ChatModelOptions.ModelType.GOOGLE:
         api_key = conversation_config.openai_config.api_key
         truncated_messages = generate_chatml_messages_with_context(
-            user_message=message,
+            user_message=query,
+            context_message=context,
             system_message=system_message,
             model_name=chat_model,
             max_prompt_size=max_tokens,

src/khoj/routers/research.py

@@ -77,7 +77,6 @@ async def apick_next_tool(
     username = prompts.user_name.format(name=user_name) if user_name else ""
 
     function_planning_prompt = prompts.plan_function_execution.format(
-        query=query,
         tools=tool_options_str,
         chat_history=chat_history,
         personality_context=personality_context,
@@ -91,7 +90,8 @@ async def apick_next_tool(
 
     with timer("Chat actor: Infer information sources to refer", logger):
         response = await send_message_to_model_wrapper(
-            function_planning_prompt,
+            query=query,
+            context=function_planning_prompt,
             response_type="json_object",
             user=user,
             query_images=query_images,