fix deployment docs

pull/1043/head
Kye Gomez 2 weeks ago
parent 327f344cf1
commit 8b6d021f34

@ -5,15 +5,9 @@ This section covers various deployment strategies for Swarms agents and multi-ag
## Deployment Types Comparison & Documentation
| Deployment Type | Use Case | Complexity | Scalability | Cost | Best For | Documentation Link | Status |
|------------------------|---------------------------|------------|-------------|--------------|----------------------------------------|------------------------------------------------------------------------------------|---------------|
|------------------------|---------------------|------------|-------------|-----------|----------------------------------|-----------------------------------------------------------------------------|------------|
| **FastAPI + Uvicorn** | REST API endpoints | Low | Medium | Low | Quick prototypes, internal tools | [FastAPI Agent API Guide](fastapi_agent_api.md) | Available |
| **Cron Jobs** | Scheduled tasks | Low | Low | Very Low | Batch processing, periodic tasks | [Cron Job Examples](../../examples/deployment_solutions/cron_job_examples/) | Available |
| **Docker Containers** | Containerized deployment | Medium | High | Low | Production, portability | [Docker Deployment Guide](docker_deployment.md) | Coming Soon |
| **Kubernetes** | Orchestrated containers | High | Very High | Medium | Enterprise, auto-scaling | [Kubernetes Deployment Guide](kubernetes_deployment.md) | Coming Soon |
| **Cloud Functions** | Serverless execution | Low | High | Pay-per-use | Event-driven, cost-effective | [Cloud Deployment Guide](cloud_deployment.md) | Coming Soon |
| **Cloud Run** | Containerized serverless | Medium | High | Pay-per-use | Production, auto-scaling | [Cloud Deployment Guide](cloud_deployment.md) | Coming Soon |
| **Traditional VMs** | Full control deployment | Medium | Medium | Medium | Custom requirements, full control | [Cloud Deployment Guide](cloud_deployment.md) | Coming Soon |
## Quick Start Guide
@ -38,14 +32,6 @@ This section covers various deployment strategies for Swarms agents and multi-ag
- **Examples**: [Cron Job Examples](../../examples/deployment_solutions/cron_job_examples/)
### 3. Docker (Recommended for production)
- **Best for**: Consistent deployment across environments
- **Setup time**: 10-15 minutes
- **Documentation**: [Docker Deployment](docker_deployment.md)
## Deployment Considerations

@ -406,32 +406,21 @@ For more on the philosophy and architecture, see [Development Philosophy & Princ
## Further Reading & References
- [Swarms Docs Home](https://docs.swarms.world/en/latest/)
- [Quickstart for Agents](https://docs.swarms.world/en/latest/swarms/agents/)
- [Agent API Reference](https://docs.swarms.world/en/latest/swarms/structs/agent/)
- [Tools Overview](https://docs.swarms.world/en/latest/swarms_tools/overview/)
- [BaseTool Reference](https://docs.swarms.world/en/latest/swarms/tools/base_tool/)
- [Reasoning Agents Overview](https://docs.swarms.world/en/latest/swarms/agents/reasoning_agents_overview/)
- [Multi-Agent Architectures Overview](https://docs.swarms.world/en/latest/swarms/concept/swarm_architectures/)
- [Examples Overview](https://docs.swarms.world/en/latest/examples/index/)
- [CLI Documentation](https://docs.swarms.world/en/latest/swarms/cli/main/)
- [Prompts Management](https://docs.swarms.world/en/latest/swarms/prompts/main/)
- [Development Philosophy & Principles](https://docs.swarms.world/en/latest/swarms/concept/philosophy/)
- [Understanding Swarms Architecture](https://docs.swarms.world/en/latest/swarms/concept/framework_architecture/)
- [SIP Guidelines and Template](https://docs.swarms.world/en/latest/protocol/sip/)
| Resource Name | Link | Description |
|-------------------------------------- |----------------------------------------------------------------------------------------|--------------------------------------------------|
| Swarms Docs Home | [Swarms Docs Home](https://docs.swarms.world/en/latest/) | Main documentation homepage |
| Quickstart for Agents | [Quickstart for Agents](https://docs.swarms.world/en/latest/swarms/agents/) | Getting started with Swarms agents |
| Agent API Reference | [Agent API Reference](https://docs.swarms.world/en/latest/swarms/structs/agent/) | API reference for Agent class |
| Tools Overview | [Tools Overview](https://docs.swarms.world/en/latest/swarms_tools/overview/) | Overview of available tools |
| BaseTool Reference | [BaseTool Reference](https://docs.swarms.world/en/latest/swarms/tools/base_tool/) | Reference for the BaseTool class |
| Reasoning Agents Overview | [Reasoning Agents Overview](https://docs.swarms.world/en/latest/swarms/agents/reasoning_agents_overview/) | Overview of reasoning agents |
| Multi-Agent Architectures Overview | [Multi-Agent Architectures Overview](https://docs.swarms.world/en/latest/swarms/concept/swarm_architectures/) | Multi-agent system architectures |
| Examples Overview | [Examples Overview](https://docs.swarms.world/en/latest/examples/index/) | Example projects and use cases |
| CLI Documentation | [CLI Documentation](https://docs.swarms.world/en/latest/swarms/cli/main/) | Command-line interface documentation |
| Prompts Management | [Prompts Management](https://docs.swarms.world/en/latest/swarms/prompts/main/) | Managing and customizing prompts |
| Development Philosophy & Principles | [Development Philosophy & Principles](https://docs.swarms.world/en/latest/swarms/concept/philosophy/) | Framework philosophy and guiding principles |
| Understanding Swarms Architecture | [Understanding Swarms Architecture](https://docs.swarms.world/en/latest/swarms/concept/framework_architecture/) | In-depth look at Swarms architecture |
| SIP Guidelines and Template | [SIP Guidelines and Template](https://docs.swarms.world/en/latest/protocol/sip/) | Swarms Improvement Proposal process and template |
# Conclusion

@ -43,4 +43,5 @@ agent = Agent(
out = agent.run(
task="What are the best top 3 etfs for gold coverage?"
)
print(out)

@ -0,0 +1,6 @@
from swarms.sims.senator_assembly import (
SenatorAssembly,
_create_senator_agents,
)
__all__ = ["SenatorAssembly", "_create_senator_agents"]

@ -1,11 +1,3 @@
"""
US Senate Simulation with Specialized Senator Agents
This simulation creates specialized AI agents representing all current US Senators,
each with detailed backgrounds, political positions, and comprehensive system prompts
that reflect their real-world characteristics, voting patterns, and policy priorities.
"""
from functools import lru_cache
from typing import Dict, List, Optional
@ -3483,3 +3475,9 @@ class SenatorAssembly:
self, task: str, img: Optional[str] = None, *args, **kwargs
):
return self.simulate_vote_concurrent(bill_description=task)
def batched_run(
self,
tasks: List[str],
):
[self.run(task) for task in tasks]

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