[CLEANUP]

example.py

@@ -1,6 +1,4 @@
-from swarms import Agent
-from langchain_community.llms.anthropic import Anthropic
-
+from swarms import Agent, Anthropic
 
 def calculate_profit(revenue: float, expenses: float):
     """
@@ -30,24 +28,6 @@ def generate_report(company_name: str, profit: float):
     return f"The profit for {company_name} is ${profit}."
 
 
-def write_memory_to_rag(memory_name: str, memory: str):
-    """
-    Writes the memory to the RAG model for fine-tuning.
-
-    Args:
-        memory_name (str): The name of the memory.
-        memory (str): The memory to be written to the RAG model.
-    """
-    # Write the memory to the RAG model for fine-tuning
-    from playground.memory.chromadb_example import ChromaDB
-
-    db = ChromaDB(output_dir=memory_name)
-
-    db.add(memory)
-
-    return None
-
-
 # Initialize the agent
 agent = Agent(
     agent_name="Accounting Assistant",

json_log_cleanup.py

@@ -58,4 +58,4 @@ def cleanup_json_logs(name: str = None):
 
 
 # Call the function
-cleanup_json_logs("sequential_workflow_agents")
+cleanup_json_logs("social_media_swarm")

playground/demos/social_media_content_generators_swarm/agents.py

@@ -12,18 +12,6 @@
 
 from swarms import Agent, OpenAIChat
 
-# # Memory
-# memory = ChromaDB(
-#     output_dir="social_media_marketing",
-#     docs_folder="docs",
-# )
-
-# Memory for instagram
-# memory = ChromaDB(
-#     output_dir="social_media_marketing",
-#     docs_folder="docs",
-# )
-
 llm = OpenAIChat(max_tokens=4000)