[BUG/CLEANUP][Fixed all grammatical errors in HierarchicalSwarm related files]

README.md

@@ -237,7 +237,7 @@ This feature is perfect for rapid prototyping, complex task decomposition, and c
 | **[MixtureOfAgents (MoA)](https://docs.swarms.world/en/latest/swarms/structs/moa/)** | Utilizes multiple expert agents in parallel and synthesizes their outputs. | Complex problem-solving and achieving state-of-the-art performance through collaboration. |
 | **[GroupChat](https://docs.swarms.world/en/latest/swarms/structs/group_chat/)** | Agents collaborate and make decisions through a conversational interface. | Real-time collaborative decision-making, negotiations, and brainstorming. |
 | **[ForestSwarm](https://docs.swarms.world/en/latest/swarms/structs/forest_swarm/)** | Dynamically selects the most suitable agent or tree of agents for a given task. | Task routing, optimizing for expertise, and complex decision-making trees. |
-| **[HierarchicalSwarm](https://docs.swarms.world/en/latest/swarms/structs/hiearchical_swarm/)** | Orchestrates agents with a director who creates plans and distributes tasks to specialized worker agents. | Complex project management, team coordination, and hierarchical decision-making with feedback loops. |
+| **[HierarchicalSwarm](https://docs.swarms.world/en/latest/swarms/structs/hierarchical_swarm/)** | Orchestrates agents with a director who creates plans and distributes tasks to specialized worker agents. | Complex project management, team coordination, and hierarchical decision-making with feedback loops. |
 | **[HeavySwarm](https://docs.swarms.world/en/latest/swarms/structs/heavy_swarm/)** | Implements a five-phase workflow with specialized agents (Research, Analysis, Alternatives, Verification) for comprehensive task analysis. | Complex research and analysis tasks, financial analysis, strategic planning, and comprehensive reporting. |
 | **[SwarmRouter](https://docs.swarms.world/en/latest/swarms/structs/swarm_router/)** | A universal orchestrator that provides a single interface to run any type of swarm with dynamic selection. | Simplifying complex workflows, switching between swarm strategies, and unified multi-agent management. |
 

docs/examples/index.md

@@ -149,9 +149,9 @@ This index organizes **100+ production-ready examples** from our [Swarms Example
 ### Hierarchical and Sequential Workflows
 | Category | Example | Description |
 |----------|---------|-------------|
-| Hierarchical | [Hierarchical Swarm Example](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/hiearchical_swarm/hiearchical_examples/hierarchical_swarm_example.py) | Multi-level hierarchical agent organization |
-| Hierarchical Basic | [Hierarchical Swarm Basic](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/hiearchical_swarm/hiearchical_swarm-example.py) | Simplified hierarchical swarm implementation |
-| Hierarchical Advanced | [Hierarchical Advanced](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/hiearchical_swarm/hierarchical_swarm_example.py) | Advanced hierarchical swarm with complex agent relationships |
+| Hierarchical | [Hierarchical Swarm Example](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/hierarchical_swarm/hierarchical_examples/hierarchical_swarm_example.py) | Multi-level hierarchical agent organization |
+| Hierarchical Basic | [Hierarchical Swarm Basic](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/hierarchical_swarm/hierarchical_swarm-example.py) | Simplified hierarchical swarm implementation |
+| Hierarchical Advanced | [Hierarchical Advanced](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/hierarchical_swarm/hierarchical_swarm_example.py) | Advanced hierarchical swarm with complex agent relationships |
 | Sequential Workflow | [Sequential Workflow Example](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/sequential_workflow/sequential_workflow_example.py) | Linear workflow with agents processing tasks in sequence |
 | Sequential Swarm | [Sequential Swarm Example](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/sequential_workflow/sequential_swarm_example.py) | Sequential swarm with coordinated task execution |
 

docs/examples/marketing_team.md

@@ -22,7 +22,7 @@ OPENAI_API_KEY=""
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # =============================================================================
 # HEAD OF CONTENT AGENT

docs/llm.txt

@@ -2493,9 +2493,9 @@ This index organizes **100+ production-ready examples** from our [Swarms Example
 ### Hierarchical and Sequential Workflows
 | Category | Example | Description |
 |----------|---------|-------------|
-| Hierarchical | [Hierarchical Swarm Example](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/hiearchical_swarm/hiearchical_examples/hierarchical_swarm_example.py) | Multi-level hierarchical agent organization |
-| Hierarchical Basic | [Hierarchical Swarm Basic](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/hiearchical_swarm/hiearchical_swarm-example.py) | Simplified hierarchical swarm implementation |
-| Hierarchical Advanced | [Hierarchical Advanced](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/hiearchical_swarm/hierarchical_swarm_example.py) | Advanced hierarchical swarm with complex agent relationships |
+| Hierarchical | [Hierarchical Swarm Example](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/hierarchical_swarm/hierarchical_examples/hierarchical_swarm_example.py) | Multi-level hierarchical agent organization |
+| Hierarchical Basic | [Hierarchical Swarm Basic](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/hierarchical_swarm/hierarchical_swarm-example.py) | Simplified hierarchical swarm implementation |
+| Hierarchical Advanced | [Hierarchical Advanced](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/hierarchical_swarm/hierarchical_swarm_example.py) | Advanced hierarchical swarm with complex agent relationships |
 | Sequential Workflow | [Sequential Workflow Example](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/sequential_workflow/sequential_workflow_example.py) | Linear workflow with agents processing tasks in sequence |
 | Sequential Swarm | [Sequential Swarm Example](https://github.com/kyegomez/swarms/blob/master/examples/multi_agent/sequential_workflow/sequential_swarm_example.py) | Sequential swarm with coordinated task execution |
 
@@ -21048,9 +21048,9 @@ dispute_swarm = SwarmRouter(
 )
 
 
-hybrid_hiearchical_swarm = HybridHierarchicalClusterSwarm(
-    name="hybrid-hiearchical-swarm",
-    description="A hybrid hiearchical swarm that uses a hybrid hiearchical peer model to solve complex tasks.",
+hybrid_hierarchical_swarm = HybridHierarchicalClusterSwarm(
+    name="hybrid-hierarchical-swarm",
+    description="A hybrid hierarchical swarm that uses a hybrid hierarchical peer model to solve complex tasks.",
     swarms=[
         litigation_swarm,
         corporate_swarm,
@@ -21065,7 +21065,7 @@ hybrid_hiearchical_swarm = HybridHierarchicalClusterSwarm(
 
 
 if __name__ == "__main__":
-    hybrid_hiearchical_swarm.run(
+    hybrid_hierarchical_swarm.run(
         "What is the best way to file for a patent? for ai technology "
     )
 
@@ -21083,7 +21083,7 @@ This page provides simple, practical examples of how to use the `HierarchicalSwa
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create specialized financial analysis agents
 market_research_agent = Agent(
@@ -21131,7 +21131,7 @@ print(result)
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create specialized development agents
 frontend_developer_agent = Agent(
@@ -21179,7 +21179,7 @@ print(result)
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create analysis agents
 market_agent = Agent(
@@ -21213,7 +21213,7 @@ print("Director Feedback:", feedback)
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create analysis agents
 market_agent = Agent(
@@ -21253,7 +21253,7 @@ for i, result in enumerate(results):
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create specialized research agents
 research_manager = Agent(
@@ -41395,7 +41395,7 @@ flowchart TD
 ```python
 
 from swarms import Agent, SwarmRouter
-from swarms.structs.hybrid_hiearchical_peer_swarm import (
+from swarms.structs.hybrid_hierarchical_peer_swarm import (
     HybridHierarchicalClusterSwarm,
 )
 
@@ -41493,9 +41493,9 @@ dispute_swarm = SwarmRouter(
 )
 
 
-hybrid_hiearchical_swarm = HybridHierarchicalClusterSwarm(
-    name="hybrid-hiearchical-swarm",
-    description="A hybrid hiearchical swarm that uses a hybrid hiearchical peer model to solve complex tasks.",
+hybrid_hierarchical_swarm = HybridHierarchicalClusterSwarm(
+    name="hybrid-hierarchical-swarm",
+    description="A hybrid hierarchical swarm that uses a hybrid hierarchical peer model to solve complex tasks.",
     swarms=[
         litigation_swarm,
         corporate_swarm,
@@ -41510,7 +41510,7 @@ hybrid_hiearchical_swarm = HybridHierarchicalClusterSwarm(
 
 
 if __name__ == "__main__":
-    hybrid_hiearchical_swarm.run(
+    hybrid_hierarchical_swarm.run(
         "What is the best way to file for a patent? for ai technology "
     )
 
@@ -41788,7 +41788,7 @@ Executes the hierarchical swarm for a specified number of feedback loops, proces
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create specialized agents
 research_agent = Agent(
@@ -41841,7 +41841,7 @@ Runs a single step of the hierarchical swarm, executing one complete cycle of pl
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create development agents
 frontend_agent = Agent(
@@ -41894,7 +41894,7 @@ Executes the hierarchical swarm for a list of tasks, processing each task throug
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create analysis agents
 market_agent = Agent(
@@ -41936,7 +41936,7 @@ for i, result in enumerate(results):
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create specialized financial agents
 market_research_agent = Agent(
@@ -41984,7 +41984,7 @@ print(result)
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create specialized development agents
 frontend_developer_agent = Agent(
@@ -42392,7 +42392,7 @@ Hierarchical architectures enable structured, iterative, and scalable problem-so
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create specialized agents
 research_agent = Agent(

docs/swarms/examples/hhcs_examples.md

@@ -104,9 +104,9 @@ dispute_swarm = SwarmRouter(
 )
 
 
-hybrid_hiearchical_swarm = HybridHierarchicalClusterSwarm(
-    name="hybrid-hiearchical-swarm",
-    description="A hybrid hiearchical swarm that uses a hybrid hiearchical peer model to solve complex tasks.",
+hybrid_hierarchical_swarm = HybridHierarchicalClusterSwarm(
+    name="hybrid-hierarchical-swarm",
+    description="A hybrid hierarchical swarm that uses a hybrid hierarchical peer model to solve complex tasks.",
     swarms=[
         litigation_swarm,
         corporate_swarm,
@@ -121,7 +121,7 @@ hybrid_hiearchical_swarm = HybridHierarchicalClusterSwarm(
 
 
 if __name__ == "__main__":
-    hybrid_hiearchical_swarm.run(
+    hybrid_hierarchical_swarm.run(
         "What is the best way to file for a patent? for ai technology "
     )
 

docs/swarms/examples/hierarchical_swarm_example.md

@@ -6,7 +6,7 @@ This page provides simple, practical examples of how to use the `HierarchicalSwa
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create specialized financial analysis agents
 market_research_agent = Agent(
@@ -54,7 +54,7 @@ print(result)
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create specialized development agents
 frontend_developer_agent = Agent(
@@ -102,7 +102,7 @@ print(result)
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create analysis agents
 market_agent = Agent(
@@ -136,7 +136,7 @@ print("Director Feedback:", feedback)
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create analysis agents
 market_agent = Agent(
@@ -176,7 +176,7 @@ for i, result in enumerate(results):
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create specialized research agents
 research_manager = Agent(
@@ -221,7 +221,7 @@ You can visualize the hierarchical structure of your swarm before executing task
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create specialized agents
 research_agent = Agent(

docs/swarms/structs/hhcs.md

@@ -101,7 +101,7 @@ flowchart TD
 ```python
 
 from swarms import Agent, SwarmRouter
-from swarms.structs.hybrid_hiearchical_peer_swarm import (
+from swarms.structs.hybrid_hierarchical_peer_swarm import (
     HybridHierarchicalClusterSwarm,
 )
 
@@ -199,9 +199,9 @@ dispute_swarm = SwarmRouter(
 )
 
 
-hybrid_hiearchical_swarm = HybridHierarchicalClusterSwarm(
-    name="hybrid-hiearchical-swarm",
-    description="A hybrid hiearchical swarm that uses a hybrid hiearchical peer model to solve complex tasks.",
+hybrid_hierarchical_swarm = HybridHierarchicalClusterSwarm(
+    name="hybrid-hierarchical-swarm",
+    description="A hybrid hierarchical swarm that uses a hybrid hierarchical peer model to solve complex tasks.",
     swarms=[
         litigation_swarm,
         corporate_swarm,
@@ -216,7 +216,7 @@ hybrid_hiearchical_swarm = HybridHierarchicalClusterSwarm(
 
 
 if __name__ == "__main__":
-    hybrid_hiearchical_swarm.run(
+    hybrid_hierarchical_swarm.run(
         "What is the best way to file for a patent? for ai technology "
     )
 

docs/swarms/structs/hierarchical_swarm.md

@@ -85,7 +85,7 @@ Displays a visual tree representation of the hierarchical swarm structure, showi
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create specialized agents
 research_agent = Agent(
@@ -160,7 +160,7 @@ Executes the hierarchical swarm for a specified number of feedback loops, proces
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create specialized agents
 research_agent = Agent(
@@ -194,7 +194,7 @@ print(result)
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 def streaming_callback(agent_name: str, chunk: str, is_final: bool):
     """Callback function for real-time streaming of agent outputs."""
@@ -270,7 +270,7 @@ Execute the hierarchical swarm for multiple tasks in sequence. Processes a list
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create analysis agents
 market_agent = Agent(
@@ -312,7 +312,7 @@ for i, result in enumerate(results):
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create specialized financial agents
 market_research_agent = Agent(
@@ -360,7 +360,7 @@ print(result)
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create specialized development agents
 frontend_developer_agent = Agent(

docs/swarms/structs/index.md

@@ -45,7 +45,7 @@ Hierarchical architectures enable structured, iterative, and scalable problem-so
 
 ```python
 from swarms import Agent
-from swarms.structs.hiearchical_swarm import HierarchicalSwarm
+from swarms.structs.hierarchical_swarm import HierarchicalSwarm
 
 # Create specialized agents
 research_agent = Agent(

examples/README.md

@@ -85,7 +85,7 @@ This directory contains comprehensive examples demonstrating various capabilitie
 
 - **[guides/](guides/)** - Comprehensive guides and tutorials including demos, generation length blog, geo guesser agent, graph workflow guide, hackathon examples, hierarchical marketing team, nano banana Jarvis agent, smart database, web scraper agents, workshops, x402 examples, and workshop examples (840_update, 850_workshop).
   - [README.md](guides/README.md) - Guides documentation
-  - [hiearchical_marketing_team.py](guides/hiearchical_marketing_team.py) - Hierarchical marketing team example
+  - [hierarchical_marketing_team.py](guides/hierarchical_marketing_team.py) - Hierarchical marketing team example
   - [demos/](guides/demos/) - Various demonstration examples
   - [hackathons/](guides/hackathons/) - Hackathon project examples
   - [workshops/](guides/workshops/) - Workshop examples
@@ -140,7 +140,7 @@ This directory contains comprehensive examples demonstrating various capabilitie
 ### Multi-Agent Patterns
 
 - [Duo Agent](multi_agent/duo_agent.py) - Two-agent collaboration
-- [Hierarchical Swarm](multi_agent/hiearchical_swarm/hierarchical_swarm_example.py) - Hierarchical agent structures
+- [Hierarchical Swarm](multi_agent/hierarchical_swarm/hierarchical_swarm_example.py) - Hierarchical agent structures
 - [Group Chat](multi_agent/groupchat/interactive_groupchat_example.py) - Multi-agent conversations
 - [Graph Workflow](multi_agent/graphworkflow_examples/graph_workflow_example.py) - Graph-based workflows
 - [Social Algorithms](multi_agent/social_algorithms_examples/) - Various social algorithm patterns

examples/guides/README.md

@@ -20,7 +20,7 @@ This directory contains comprehensive guides and tutorials for using Swarms effe
 - [setup_and_test.py](graphworkflow_guide/setup_and_test.py) - Setup and testing utilities
 
 ## Hierarchical Marketing Team
-- [hiearchical_marketing_team.py](hiearchical_marketing_team.py) - Marketing team hierarchy example
+- [hierarchical_marketing_team.py](hierarchical_marketing_team.py) - Marketing team hierarchy example
 
 ## Nano Banana Jarvis Agent
 - [img_gen_nano_banana.py](nano_banana_jarvis_agent/img_gen_nano_banana.py) - Image generation with Nano Banana