Refine custom embedder configuration support

- Update custom embedder configuration method to handle custom embedding functions
- Modify type hints for embedder configuration
- Remove unused model_name parameter in custom embedder configuration

docs/concepts/llms.mdx

@@ -463,32 +463,26 @@ Learn how to get the most out of your LLM configuration:
 
   <Accordion title="Google">
     ```python Code
-    # Option 1: Gemini accessed with an API key.
+    # Option 1. Gemini accessed with an API key.
     # https://ai.google.dev/gemini-api/docs/api-key
     GEMINI_API_KEY=<your-api-key>
 
-    # Option 2: Vertex AI IAM credentials for Gemini, Anthropic, and Model Garden.
+    # Option 2. Vertex AI IAM credentials for Gemini, Anthropic, and anything in the Model Garden.
     # https://cloud.google.com/vertex-ai/generative-ai/docs/overview
     ```
 
-    Get credentials:
-    ```python Code
-    import json
-
+    ## GET CREDENTIALS 
     file_path = 'path/to/vertex_ai_service_account.json'
 
     # Load the JSON file
     with open(file_path, 'r') as file:
         vertex_credentials = json.load(file)
 
-    # Convert the credentials to a JSON string
+    # Convert to JSON string
     vertex_credentials_json = json.dumps(vertex_credentials)
-    ```
 
     Example usage:
     ```python Code
-    from crewai import LLM
-
     llm = LLM(
         model="gemini/gemini-1.5-pro-latest",
         temperature=0.7,

src/crewai/agent.py

@@ -16,6 +16,7 @@ from crewai.memory.contextual.contextual_memory import ContextualMemory
 from crewai.task import Task
 from crewai.tools import BaseTool
 from crewai.tools.agent_tools.agent_tools import AgentTools
+from crewai.tools.base_tool import Tool
 from crewai.utilities import Converter, Prompts
 from crewai.utilities.constants import TRAINED_AGENTS_DATA_FILE, TRAINING_DATA_FILE
 from crewai.utilities.converter import generate_model_description
@@ -145,7 +146,7 @@ class Agent(BaseAgent):
     def _set_knowledge(self):
         try:
             if self.knowledge_sources:
-                full_pattern = re.compile(r"[^a-zA-Z0-9\-_\r\n]|(\.\.)")
+                full_pattern = re.compile(r'[^a-zA-Z0-9\-_\r\n]|(\.\.)')
                 knowledge_agent_name = f"{re.sub(full_pattern, '_', self.role)}"
                 if isinstance(self.knowledge_sources, list) and all(
                     isinstance(k, BaseKnowledgeSource) for k in self.knowledge_sources

src/crewai/cli/reset_memories_command.py

@@ -3,6 +3,11 @@ import subprocess
 import click
 
 from crewai.cli.utils import get_crew
+from crewai.knowledge.storage.knowledge_storage import KnowledgeStorage
+from crewai.memory.entity.entity_memory import EntityMemory
+from crewai.memory.long_term.long_term_memory import LongTermMemory
+from crewai.memory.short_term.short_term_memory import ShortTermMemory
+from crewai.utilities.task_output_storage_handler import TaskOutputStorageHandler
 
 
 def reset_memories_command(

src/crewai/crew.py

@@ -1,6 +1,7 @@
 import asyncio
 import json
 import re
+import sys
 import uuid
 import warnings
 from concurrent.futures import Future
@@ -439,6 +440,7 @@ class Crew(BaseModel):
                         )
         return self
 
+
     @property
     def key(self) -> str:
         source = [agent.key for agent in self.agents] + [

src/crewai/memory/entity/entity_memory.py

@@ -1,4 +1,4 @@
-from typing import Optional
+from typing import Any, Optional
 
 from pydantic import PrivateAttr
 

src/crewai/memory/memory.py

@@ -1,7 +1,9 @@
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, List, Optional, Union
 
 from pydantic import BaseModel
 
+from crewai.memory.storage.rag_storage import RAGStorage
+
 
 class Memory(BaseModel):
     """