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# Swarms – The Ultimate Multi-Agent LLM Framework for Developers
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Swarms aims to be the definitive and most reliable multi-agent LLM framework, offering developers the tools to automate business operations effortlessly. It provides a vast array of swarm architectures, seamless third-party integration, and unparalleled ease of use. With Swarms, developers can orchestrate intelligent, scalable agent ecosystems that can automate complex business processes.
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### Key Features for Developers:
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1. **Architectural Flexibility** – Choose from a wide variety of pre-built swarm architectures or build custom agent frameworks. Swarms allows developers to define flexible workflows for specific use cases, providing both sequential and concurrent task execution.
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2. **Third-Party Integration** – Swarms makes it simple to integrate with external APIs, databases, and other platforms. By supporting extreme integration capabilities, it ensures your agents work effortlessly within any workflow.
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3. **Developer-Centric APIs** – The Swarms API is built with developers in mind, offering an intuitive, simple-to-use interface. Developers can orchestrate agent swarms with minimal code and maximum control.
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---
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### Code Examples
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#### 1. Basic Financial Analysis Agent:
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This example demonstrates a simple financial agent setup that responds to financial questions, such as establishing a ROTH IRA, using OpenAI's GPT-based model.
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```python
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import os
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from swarms import Agent
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from swarm_models import OpenAIChat
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from swarms.prompts.finance_agent_sys_prompt import (
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FINANCIAL_AGENT_SYS_PROMPT,
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)
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from dotenv import load_dotenv
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# Load environment variables
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load_dotenv()
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# Get OpenAI API key from environment
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api_key = os.getenv("OPENAI_API_KEY")
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# Initialize OpenAIChat model with desired parameters
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model = OpenAIChat(
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openai_api_key=api_key, model_name="gpt-4o-mini", temperature=0.1
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)
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# Initialize the Financial Analysis Agent
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agent = Agent(
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agent_name="Financial-Analysis-Agent",
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system_prompt=FINANCIAL_AGENT_SYS_PROMPT,
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llm=model,
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max_loops=1,
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autosave=True,
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dashboard=False,
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verbose=True,
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dynamic_temperature_enabled=True,
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saved_state_path="finance_agent.json",
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user_name="swarms_corp",
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retry_attempts=1,
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context_length=200000,
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return_step_meta=False,
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)
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# Example task for the agent
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out = agent.run(
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"How can I establish a ROTH IRA to buy stocks and get a tax break? What are the criteria?"
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)
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# Output the agent's result
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print(out)
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```
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#### 2. Agent Orchestration with AgentRearrange:
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The following example showcases how to use the `AgentRearrange` class to manage a multi-agent system. It sets up a director agent to orchestrate two workers—one to generate a transcript and another to summarize it.
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```python
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from swarms import Agent, AgentRearrange
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from swarm_models import Anthropic
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# Initialize the Director agent
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director = Agent(
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agent_name="Director",
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system_prompt="Directs the tasks for the workers",
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llm=Anthropic(),
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max_loops=1,
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dashboard=False,
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streaming_on=True,
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verbose=True,
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stopping_token="<DONE>",
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state_save_file_type="json",
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saved_state_path="director.json",
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)
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# Initialize Worker 1 agent (transcript generation)
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worker1 = Agent(
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agent_name="Worker1",
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system_prompt="Generates a transcript for a YouTube video on what swarms are",
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llm=Anthropic(),
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max_loops=1,
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dashboard=False,
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streaming_on=True,
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verbose=True,
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stopping_token="<DONE>",
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state_save_file_type="json",
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saved_state_path="worker1.json",
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)
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# Initialize Worker 2 agent (summarizes transcript)
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worker2 = Agent(
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agent_name="Worker2",
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system_prompt="Summarizes the transcript generated by Worker1",
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llm=Anthropic(),
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max_loops=1,
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dashboard=False,
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streaming_on=True,
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verbose=True,
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stopping_token="<DONE>",
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state_save_file_type="json",
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saved_state_path="worker2.json",
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)
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# Create a list of agents
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agents = [director, worker1, worker2]
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# Define the workflow pattern (sequential flow)
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flow = "Director -> Worker1 -> Worker2"
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# Using AgentRearrange to orchestrate the agents
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agent_system = AgentRearrange(agents=agents, flow=flow)
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# Running the system with a sample task
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output = agent_system.run(
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"Create a format to express and communicate swarms of LLMs in a structured manner for YouTube"
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)
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# Output the result
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print(output)
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```
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### Mermaid Diagram Examples
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#### 1. Basic Agent Flow:
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Here’s a visual representation of the basic workflow using Mermaid to display the sequential flow between agents.
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```mermaid
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flowchart TD
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A[Director] --> B[Worker 1: Generate Transcript]
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B --> C[Worker 2: Summarize Transcript]
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```
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In this diagram:
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- The **Director** agent assigns tasks.
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- **Worker 1** generates a transcript for a YouTube video.
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- **Worker 2** summarizes the transcript.
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#### 2. Concurrent Agent Communication:
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This diagram showcases a concurrent agent setup where one agent sends tasks to multiple agents at the same time.
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```mermaid
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flowchart TD
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A[Director] --> B1[Worker 1]
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A --> B2[Worker 2]
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A --> B3[Worker 3]
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```
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In this setup:
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- The **Director** agent sends tasks concurrently to **Worker 1**, **Worker 2**, and **Worker 3**.
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### Why Developers Should Choose Swarms:
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#### **Highly Customizable and Scalable:**
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Swarms is designed with flexibility at its core. Developers can create custom architectures and workflows, enabling extreme control over how agents interact with each other. Whether it’s a linear process or a complex mesh of agent communications, Swarms handles it efficiently.
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#### **Seamless Integration:**
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With support for extreme third-party integration, Swarms makes it easy for developers to plug into external systems, such as APIs or internal databases. This allows agents to act on live data, process external inputs, and execute actions in real time, making it a powerful tool for real-world applications.
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#### **Effortless Orchestration:**
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Swarms abstracts the complexity of managing multiple agents with orchestration tools like `AgentRearrange`. Developers can define workflows that execute tasks concurrently or sequentially, depending on the problem at hand. This makes it easy to build and maintain large-scale automation systems.
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### Conclusion:
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Swarms is not just another multi-agent framework; it's built specifically for developers who need powerful tools to automate complex, large-scale business operations. With flexible architecture, deep integration capabilities, and developer-friendly APIs, Swarms is the ultimate solution for businesses looking to streamline operations and future-proof their workflows.
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Your Name
3 months ago