refactor: update knowledge query handling in Agent

This commit refines the knowledge query processing in the Agent class by renaming variables for clarity and optimizing the query rewriting logic. The system prompt has been updated in the translation file to enhance clarity and context for the query rewriting process. These changes aim to improve the overall readability and maintainability of the code.

src/crewai/agent.py

@@ -611,27 +611,18 @@ class Agent(BaseAgent):
         query = self.i18n.slice("knowledge_search_query").format(
             task_prompt=task_prompt
         )
-        system_prompt = self.i18n.slice("knowledge_search_query_system_prompt")
+        rewriter_prompt = self.i18n.slice("knowledge_search_query_system_prompt")
         if isinstance(self.llm, BaseLLM):
             try:
-                query_converted = self.llm.call(
+                rewritten_query = self.llm.call(
                     [
                         {
                             "role": "system",
-                            "content": system_prompt,
+                            "content": rewriter_prompt,
                         },
                         {"role": "user", "content": query},
                     ]
                 )
-                query_rewritten = self.llm.call(
-                    [
-                        {
-                            "role": "system",
-                            "content": system_prompt,
-                        },
-                        {"role": "user", "content": query_converted},
-                    ]
-                )
                 crewai_event_bus.emit(
                     self,
                     event=KnowledgeQueryCompletedEvent(
@@ -639,7 +630,7 @@ class Agent(BaseAgent):
                         agent=self,
                     ),
                 )
-                return query_rewritten
+                return rewritten_query
             except Exception as e:
                 crewai_event_bus.emit(
                     self,

src/crewai/translations/en.json

@@ -28,8 +28,8 @@
     "lite_agent_system_prompt_with_tools": "You are {role}. {backstory}\nYour personal goal is: {goal}\n\nYou ONLY have access to the following tools, and should NEVER make up tools that are not listed here:\n\n{tools}\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: you should always think about what to do\nAction: the action to take, only one name of [{tool_names}], just the name, exactly as it's written.\nAction Input: the input to the action, just a simple JSON object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce all necessary information is gathered, return the following format:\n\n```\nThought: I now know the final answer\nFinal Answer: the final answer to the original input question\n```",
     "lite_agent_system_prompt_without_tools": "You are {role}. {backstory}\nYour personal goal is: {goal}\n\nTo give my best complete final answer to the task respond using the exact following format:\n\nThought: I now can give a great answer\nFinal Answer: Your final answer must be the great and the most complete as possible, it must be outcome described.\n\nI MUST use these formats, my job depends on it!",
     "lite_agent_response_format": "\nIMPORTANT: Your final answer MUST contain all the information requested in the following format: {response_format}\n\nIMPORTANT: Ensure the final output does not include any code block markers like ```json or ```python.",
-    "knowledge_search_query": "Rewrite the following user query to optimize it for retrieval from a vector database. The original query is: {task_prompt}.",
-    "knowledge_search_query_system_prompt": "Your goal is to rewrite the user query to optimize it for retrieval from a vector database. Consider how the query will be used to find relevant documents, and aim to make it more specific and context-aware.  Do not include any other text than the rewritten query, especially any preamble or postamble and only add expected output format if its relevant to the rewritten query. Focus on the key words of the intended task and to retrieve the most relevant information from the vector database."
+    "knowledge_search_query": "The original query is: {task_prompt}.",
+    "knowledge_search_query_system_prompt": "Your goal is to rewrite the user query so that it is optimized for retrieval from a vector database. Consider how the query will be used to find relevant documents, and aim to make it more specific and context-aware. \n\n Do not include any other text than the rewritten query, especially any preamble or postamble and only add expected output format if its relevant to the rewritten query. \n\n Focus on the key words of the intended task and to retrieve the most relevant information. \n\n There will be some extra context provided that might need to be removed such as expected_output formats structured_outputs and other instructions."
   },
   "errors": {
     "force_final_answer_error": "You can't keep going, here is the best final answer you generated:\n\n {formatted_answer}",