Refactor knowledge configuration parameters in CrewAI

- Renamed `limit` to `results_limit` in `KnowledgeConfig`, `query_knowledge`, and `query` methods for consistency and clarity.
- Updated related documentation to reflect the new parameter name, ensuring users understand the configuration options for knowledge retrieval.

docs/concepts/knowledge.mdx

@@ -163,7 +163,7 @@ You can configure the knowledge configuration for the crew or agent.
 ```python Code
 from crewai.knowledge.knowledge_config import KnowledgeConfig
 
-knowledge_config = KnowledgeConfig(limit=10, score_threshold=0.5)
+knowledge_config = KnowledgeConfig(results_limit=10, score_threshold=0.5)
 
 agent = Agent(
     ...
@@ -172,7 +172,7 @@ agent = Agent(
 ```
 
 <Tip>
-  limit: is the number of relevant documents to return. Default is 3.
+  results_limit: is the number of relevant documents to return. Default is 3.
   score_threshold: is the minimum score for a document to be considered relevant. Default is 0.35.
 </Tip>
 

src/crewai/crew.py

@@ -1135,11 +1135,11 @@ class Crew(BaseModel):
         return result
 
     def query_knowledge(
-        self, query: List[str], limit: int = 3, score_threshold: float = 0.35
+        self, query: List[str], results_limit: int = 3, score_threshold: float = 0.35
     ) -> Union[List[Dict[str, Any]], None]:
         if self.knowledge:
             return self.knowledge.query(
-                query, limit=limit, score_threshold=score_threshold
+                query, results_limit=results_limit, score_threshold=score_threshold
             )
         return None
 

src/crewai/knowledge/knowledge.py

@@ -44,7 +44,7 @@ class Knowledge(BaseModel):
         self._add_sources()
 
     def query(
-        self, query: List[str], limit: int = 3, score_threshold: float = 0.35
+        self, query: List[str], results_limit: int = 3, score_threshold: float = 0.35
     ) -> List[Dict[str, Any]]:
         """
         Query across all knowledge sources to find the most relevant information.
@@ -58,7 +58,7 @@ class Knowledge(BaseModel):
 
         results = self.storage.search(
             query,
-            limit,
+            limit=results_limit,
             score_threshold=score_threshold,
         )
         return results

src/crewai/knowledge/knowledge_config.py

@@ -2,5 +2,5 @@ from pydantic import BaseModel
 
 
 class KnowledgeConfig(BaseModel):
-    limit: int = 3
+    results_limit: int = 3
     score_threshold: float = 0.35