diff --git a/README.md b/README.md
index 071b1991..70b31e6e 100644
--- a/README.md
+++ b/README.md
@@ -453,8 +453,8 @@ agent.run(task, img)
 ----
 
 
-### `ToolAgent`
-ToolAgent is an agent that can use tools through JSON function calling. It intakes any open source model from huggingface and is extremely modular and plug in and play. We need help adding general support to all models soon.
+### Local Agent `ToolAgent`
+ToolAgent is an fully local agent that can use tools through JSON function calling. It intakes any open source model from huggingface and is extremely modular and plug in and play. We need help adding general support to all models soon.
 
 
 ```python
@@ -774,6 +774,8 @@ print(
 
 The `AgentRearrange` orchestration technique, inspired by Einops and einsum, allows you to define and map out the relationships between various agents. It provides a powerful tool for orchestrating complex workflows, enabling you to specify linear and sequential relationships such as `a -> a1 -> a2 -> a3`, or concurrent relationships where the first agent sends a message to 3 agents simultaneously: `a -> a1, a2, a3`. This level of customization allows for the creation of highly efficient and dynamic workflows, where agents can work in parallel or in sequence as needed. The `AgentRearrange` technique is a valuable addition to the swarms library, providing a new level of flexibility and control over the orchestration of agents. For more detailed information and examples, please refer to the [official documentation](https://docs.swarms.world/en/latest/swarms/structs/agent_rearrange/).
 
+[Check out my video on agent rearrange!](https://youtu.be/Rq8wWQ073mg)
+
 
 
 ### Methods
@@ -799,68 +801,184 @@ The `run` method returns the final output after all agents have processed the in
 
 ```python
 
-from swarms import Agent, AgentRearrange
-
+from datetime import datetime
 
-# Initialize the director agent
+from swarms import Agent, AgentRearrange, create_file_in_folder
 
-director = Agent(
-    agent_name="Director",
-    system_prompt="Directs the tasks for the workers",
-    model_name="claude-2",
+chief_medical_officer = Agent(
+    agent_name="Chief Medical Officer",
+    system_prompt="""You are the Chief Medical Officer coordinating a team of medical specialists for viral disease diagnosis.
+    Your responsibilities include:
+    - Gathering initial patient symptoms and medical history
+    - Coordinating with specialists to form differential diagnoses
+    - Synthesizing different specialist opinions into a cohesive diagnosis
+    - Ensuring all relevant symptoms and test results are considered
+    - Making final diagnostic recommendations
+    - Suggesting treatment plans based on team input
+    - Identifying when additional specialists need to be consulted
+    
+    Guidelines:
+    1. Always start with a comprehensive patient history
+    2. Consider both common and rare viral conditions
+    3. Factor in patient demographics and risk factors
+    4. Document your reasoning process clearly
+    5. Highlight any critical or emergency symptoms
+    6. Note any limitations or uncertainties in the diagnosis
+    
+    Format all responses with clear sections for:
+    - Initial Assessment
+    - Differential Diagnoses
+    - Specialist Consultations Needed
+    - Recommended Next Steps""",
+    model_name="gpt-4o",  # Models from litellm -> claude-2
     max_loops=1,
-    dashboard=False,
-    streaming_on=True,
-    verbose=True,
-    stopping_token="<DONE>",
-    state_save_file_type="json",
-    saved_state_path="director.json",
 )
 
+# Viral Disease Specialist
+virologist = Agent(
+    agent_name="Virologist",
+    system_prompt="""You are a specialist in viral diseases with expertise in:
+    - Respiratory viruses (Influenza, Coronavirus, RSV)
+    - Systemic viral infections (EBV, CMV, HIV)
+    - Childhood viral diseases (Measles, Mumps, Rubella)
+    - Emerging viral threats
+    
+    Your role involves:
+    1. Analyzing symptoms specific to viral infections
+    2. Distinguishing between different viral pathogens
+    3. Assessing viral infection patterns and progression
+    4. Recommending specific viral tests
+    5. Evaluating epidemiological factors
+    
+    For each case, consider:
+    - Incubation periods
+    - Transmission patterns
+    - Seasonal factors
+    - Geographic prevalence
+    - Patient immune status
+    - Current viral outbreaks
+    
+    Provide detailed analysis of:
+    - Characteristic viral symptoms
+    - Disease progression timeline
+    - Risk factors for severe disease
+    - Potential complications""",
+    model_name="gpt-4o",
+    max_loops=1,
+)
 
-# Initialize worker 1
+# Internal Medicine Specialist
+internist = Agent(
+    agent_name="Internist",
+    system_prompt="""You are an Internal Medicine specialist responsible for:
+    - Comprehensive system-based evaluation
+    - Integration of symptoms across organ systems
+    - Identification of systemic manifestations
+    - Assessment of comorbidities
+    
+    For each case, analyze:
+    1. Vital signs and their implications
+    2. System-by-system review (cardiovascular, respiratory, etc.)
+    3. Impact of existing medical conditions
+    4. Medication interactions and contraindications
+    5. Risk stratification
+    
+    Consider these aspects:
+    - Age-related factors
+    - Chronic disease impact
+    - Medication history
+    - Social and environmental factors
+    
+    Document:
+    - Physical examination findings
+    - System-specific symptoms
+    - Relevant lab abnormalities
+    - Risk factors for complications""",
+    model_name="gpt-4o",
+    max_loops=1,
+)
 
-worker1 = Agent(
-    agent_name="Worker1",
-    system_prompt="Generates a transcript for a youtube video on what swarms are",
-    model_name="claude-2",
+# Diagnostic Synthesizer
+synthesizer = Agent(
+    agent_name="Diagnostic Synthesizer",
+    system_prompt="""You are responsible for synthesizing all specialist inputs to create a final diagnostic assessment:
+    
+    Core responsibilities:
+    1. Integrate findings from all specialists
+    2. Identify patterns and correlations
+    3. Resolve conflicting opinions
+    4. Generate probability-ranked differential diagnoses
+    5. Recommend additional testing if needed
+    
+    Analysis framework:
+    - Weight evidence based on reliability and specificity
+    - Consider epidemiological factors
+    - Evaluate diagnostic certainty
+    - Account for test limitations
+    
+    Provide structured output including:
+    1. Primary diagnosis with confidence level
+    2. Supporting evidence summary
+    3. Alternative diagnoses to consider
+    4. Recommended confirmatory tests
+    5. Red flags or warning signs
+    6. Follow-up recommendations
+    
+    Documentation requirements:
+    - Clear reasoning chain
+    - Evidence quality assessment
+    - Confidence levels for each diagnosis
+    - Knowledge gaps identified
+    - Risk assessment""",
+    model_name="gpt-4o",
     max_loops=1,
-    dashboard=False,
-    streaming_on=True,
-    verbose=True,
-    stopping_token="<DONE>",
-    state_save_file_type="json",
-    saved_state_path="worker1.json",
 )
 
+# Create agent list
+agents = [chief_medical_officer, virologist, internist, synthesizer]
+
+# Define diagnostic flow
+flow = f"""{chief_medical_officer.agent_name} -> {virologist.agent_name} -> {internist.agent_name} -> {synthesizer.agent_name}"""
 
-# Initialize worker 2
-worker2 = Agent(
-    agent_name="Worker2",
-    system_prompt="Summarizes the transcript generated by Worker1",
-    model_name="claude-2",
+# Create the swarm system
+diagnosis_system = AgentRearrange(
+    name="Medical-nlp-diagnosis-swarm",
+    description="natural language symptions to diagnosis report",
+    agents=agents,
+    flow=flow,
     max_loops=1,
-    dashboard=False,
-    streaming_on=True,
-    verbose=True,
-    stopping_token="<DONE>",
-    state_save_file_type="json",
-    saved_state_path="worker2.json",
+    output_type="all",
 )
 
 
-# Create a list of agents
-agents = [director, worker1, worker2]
+# Example usage
+if __name__ == "__main__":
+    # Example patient case
+    patient_case = """
+    Patient: 45-year-old female
+    Presenting symptoms: 
+    - Fever (101.5°F) for 3 days
+    - Dry cough
+    - Fatigue
+    - Mild shortness of breath
+    Medical history:
+    - Controlled hypertension
+    - No recent travel
+    - Fully vaccinated for COVID-19
+    - No known sick contacts
+    """
 
-# Define the flow pattern
-flow = "Director -> Worker1 -> Worker2"
+    # Add timestamp to the patient case
+    case_info = f"Timestamp: {datetime.now()}\nPatient Information: {patient_case}"
+
+    # Run the diagnostic process
+    diagnosis = diagnosis_system.run(case_info)
+
+    # Create a folder and file called reports
+    create_file_in_folder(
+        "reports", "medical_analysis_agent_rearrange.md", diagnosis
+    )
 
-# Using AgentRearrange class
-agent_system = AgentRearrange(agents=agents, flow=flow)
-output = agent_system.run(
-    "Create a format to express and communicate swarms of llms in a structured manner for youtube"
-)
-print(output)
 
 ```