Superagentx - OpenSource Agent AI with Bedrock LLMs initial examples

[RaghavPrabhu]

SuperAgentX

An OpenSource - Autonomous Agentic AGI Framework

SuperAgentX addresses the growing need for highly capable, autonomous AI systems that can perform complex tasks with minimal human intervention. As we approach the limits of narrow AI, an adaptable and scalable framework is needed to bridge the gap toward AGI (Artificial General Intelligence).

It supports all major Generative AI models (LLM), including AWS Bedrock LLMs.

Repository URL: https://github.com/superagentxai/superagentx

In this PR, We have created two initial examples for agents and function calling under open-source-agents/superagentx.

[rsgrewal-aws]

we need to understand the options why this would be benefitial , what specific use case can this solve vs langgraph or crew.ai

[RaghavPrabhu]

@rsgrewal-aws,

SuperAgentx - Agent AI Framework Highlights

1. Open-Source Framework: A lightweight, open-source AI framework built for multi-agent applications with Artificial General Intelligence (AGI) capabilities.
2. Easy Deployment: Offers WebSocket, RESTful API, and IO console interfaces for rapid setup of agent-based AI solutions.
3. Streamlined Architecture: No major dependencies; built independently (not as a Langchain wrapper, like crew.ai).
4. Contextual Memory: Uses SQL + Vector databases to store and retrieve user-specific context effectively.
5. Flexible LLM Configuration: Supports simple configuration options of various Gen AI models, including those on AWS Bedrock.
6. Extendable Handlers: Allows integration with diverse APIs, databases, data warehouses, data lakes, IoT streams, and more, making them accessible for function-calling features.
7. Goal-Oriented Agents: Enables the creation of agents with retry mechanisms to achieve set goals.
8. AWS Compatibility: Offers tools for AWS services like S3 and EC2, with Transcribe and additional services coming soon as SuperAgentX handlers.

SuperAgentX Use Cases

1. Healthcare and Insurance.
2. ⁠Banking.
3. ⁠Service Ops.
4. ⁠Finance.
5. ⁠Supply Chain & Logistics.
6. ⁠Bio & Life Sciences.
7. ⁠HR & IT.

[gowrishankar005]

Hi @rsgrewal-aws

Following up on PR #369 regarding SuperAgentX integration.

To address the earlier questions about differentiation and use cases:

SuperAgentX offers unique advantages compared to LangGraph and Crew.ai:

• Native integration with AWS services and Bedrock LLMs
• A streamlined, Lightweight architecture without Langchain dependencies
• Built-in contextual memory using SQL + Vector databases for user-specific interactions
• Direct WebSocket and REST API interfaces for production deployment
• Native integration support with AWS services and Bedrock LLMs

We've successfully implemented several production-ready use cases including:

1. Healthcare document processing with multiple specialized agents
2. Financial services chatbots with secure AWS service integration
3. Supply chain optimization using goal-oriented agents
4. Security Vulnerabilities validation and recommendation agents

Once merged, this contribution will help AWS community members quickly build and deploy production-ready AI agent applications with AWS Bedrock.

Please let us know if you need specific implementation details or have additional questions. We're happy to provide more concrete examples or technical documentation.

Thanks for reviewing!

[DMZ1921]

Thanks
Maybe we can chat some time pls feel free to say hello

[rsgrewal-aws]

Sure let us sync up post re:invent From: DMZ1921 ***@***.***> Reply-To: aws-samples/amazon-bedrock-samples ***@***.***> Date: Thursday, December 5, 2024 at 9:36 AM To: aws-samples/amazon-bedrock-samples ***@***.***> Cc: "Grewal, Rupinder" ***@***.***>, Mention ***@***.***> Subject: Re: [aws-samples/amazon-bedrock-samples] Superagentx - OpenSource Agent AI with Bedrock LLMs initial examples (PR #369) Thanks Maybe we can chat some time pls feel free to say hello — Reply to this email directly, view it on GitHub<#369 (comment)>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AYMBZRVCKNTTJCDQ2DDDDXL2ECFHVAVCNFSM6AAAAABQUYKS56VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDKMRRGAYTSOBTG4>. You are receiving this because you were mentioned.Message ID: ***@***.***>

[DMZ1921]

IMEAST Coast USA tTZone

…

On Thu, Dec 5, 2024, 2:04 PM rsgrewal-aws ***@***.***> wrote: Sure let us sync up post re:invent From: DMZ1921 ***@***.***> Reply-To: aws-samples/amazon-bedrock-samples ***@***.***> Date: Thursday, December 5, 2024 at 9:36 AM To: aws-samples/amazon-bedrock-samples ***@***.***> Cc: "Grewal, Rupinder" ***@***.***>, Mention ***@***.***> Subject: Re: [aws-samples/amazon-bedrock-samples] Superagentx - OpenSource Agent AI with Bedrock LLMs initial examples (PR #369) Thanks Maybe we can chat some time pls feel free to say hello — Reply to this email directly, view it on GitHub< #369 (comment)>, or unsubscribe< https://github.com/notifications/unsubscribe-auth/AYMBZRVCKNTTJCDQ2DDDDXL2ECFHVAVCNFSM6AAAAABQUYKS56VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDKMRRGAYTSOBTG4>. You are receiving this because you were mentioned.Message ID: ***@***.***> — Reply to this email directly, view it on GitHub <#369 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/BLI6W3CUDQSW7O2I7F7TU3L2ECPUBAVCNFSM6AAAAABQUYKS56VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDKMRRGE4DQOJSGM> . You are receiving this because you commented.Message ID: ***@***.***>

[RaghavPrabhu]

@rsgrewal-aws Happy New Year 2025!

I have created a tutorial series for Agentic AI real-world use cases using the SuperAgentX framework with AWS Bedrock LLMs.

Tutorial Series

• Series - 1 : https://medium.com/@RaghavPrabhu/master-agentic-ai-a-beginners-step-by-step-guide-with-superagentx-tutorial-series-part-1-ba8907c7c2c6
• Series - 2 : https://medium.com/@RaghavPrabhu/master-agentic-ai-doctor-appointment-booking-app-using-superagentx-tutorial-series-part-2-1063e6c623ba

1. SuperAgentX framework's unique features will be explained with examples here as PRs, once this PR is approved! (Important features of SuperAgentX, with the help of our strong & robust Memory management and Feedback loops!)
2. More use case tutorials will be published showcasing AWS Bedrock-based LLMs.

Thank you for taking the time to review!