[FIX AGENT LOADER DOCS]

docs/mkdocs.yml

@@ -272,7 +272,7 @@ nav:
       - Benefits: "swarms/concept/why.md"
       - Choosing Multi Agent Architecture: "swarms/concept/how_to_choose_swarms.md"
 
-      - Documentation:
+      - Reference Documentation:
         - Overview: "swarms/structs/overview.md"
         - Custom Multi Agent Architectures: "swarms/structs/custom_swarm.md"
         - Debate Multi-Agent Architectures: "swarms/structs/orchestration_methods.md"
@@ -296,8 +296,6 @@ nav:
           - Swarm Matcher: "swarms/structs/swarm_matcher.md"
           - Board of Directors: "swarms/structs/BoardOfDirectors.md"
 
-        # - Multi-Agent Multi-Modal Structures:
-        #   - ImageAgentBatchProcessor: "swarms/structs/image_batch_agent.md"
 
         - Routers:
           - SwarmRouter: "swarms/structs/swarm_router.md"
@@ -317,14 +315,12 @@ nav:
           - SequentialWorkflow: "swarms/structs/sequential_workflow.md"
           - GraphWorkflow: "swarms/structs/graph_workflow.md"
 
-        - Storage:
-          - AgentRegistry: "swarms/structs/agent_registry.md"
-
-        - Agent Loader:
-          - Agent Loader: "swarms/utils/agent_loader.md"
-
         - Communication Structure: "swarms/structs/conversation.md"
 
+    - Utilities:
+      - Agent Loader: "swarms/utils/agent_loader.md"
+      - AgentRegistry: "swarms/structs/agent_registry.md"
+
     - Tools:
       - Overview: "swarms_tools/overview.md"
       - BaseTool Reference: "swarms/tools/base_tool.md"

examples/agent_loader/agent_loader_demo.py

@@ -2,6 +2,4 @@ from swarms.utils import load_agent_from_markdown
 
 agent = load_agent_from_markdown("finance_advisor.md")
 
-agent.run(
-    task="Analyze the financial market trends for 2023."
-)
+agent.run(task="Analyze the financial market trends for 2023.")

examples/agent_loader/multi_agents_loader_demo.py

@@ -1,22 +1,21 @@
 from swarms.utils import load_agents_from_markdown
 
-agents = load_agents_from_markdown([
-    "market_researcher.md",
-    "financial_analyst.md", 
-    "risk_analyst.md"
-])
+agents = load_agents_from_markdown(
+    [
+        "market_researcher.md",
+        "financial_analyst.md",
+        "risk_analyst.md",
+    ]
+)
 
 # Example 3: Use agents in a workflow
 from swarms.structs.sequential_workflow import SequentialWorkflow
 
-workflow = SequentialWorkflow(
-    agents=agents,
-    max_loops=1
-)
+workflow = SequentialWorkflow(agents=agents, max_loops=1)
 
 task = """
 Analyze the AI healthcare market for a $50M investment opportunity.
 Focus on market size, competition, financials, and risks.
 """
 
-result = workflow.run(task)
+result = workflow.run(task)

swarms/utils/agent_loader.py

@@ -50,7 +50,7 @@ class MarkdownAgentConfig(BaseModel):
                 "System prompt must be a non-empty string"
             )
         return v
-    
+
 
 class AgentLoader:
     """
@@ -224,7 +224,7 @@ class AgentLoader:
         try:
             # Lazy import to avoid circular dependency
             from swarms.structs.agent import Agent
-            
+
             logger.info(
                 f"Creating agent '{config.name}' from {file_path}"
             )