LLM Stack

Agent Building Frameworks and Platforms

What is LLM Stack?

No-code platform enabling flexible generative AI agent creation. Supports complex workflow building without programming expertise. Integrates multiple data sources and AI models seamlessly.

Features

No-code platform for building LLM Agents and workflows

Supports major model providers like OpenAI and Hugging Face

Builds generative AI agents like SDRs and Research Analysts

Connects to internal/external tools and web browsing

Links

Website GitHub

Pros and Cons of LLM Stack

Pros

Supports diverse data import from multiple sources

Enables multi-model chaining without coding knowledge

Provides out-of-the-box vector database infrastructure

Supports cloud and on-premise deployment options

Offers multi-tenant organizational access controls

Cons

Potential complexity in advanced agent configuration

Dependence on specific platform's AI capabilities

May have performance limitations compared to custom solutions

LLM Stack Use Cases

Automated sales development representative workflows

Custom research report generation systems

Enterprise process automation with AI agents

Multimedia content generation across different domains

Similar AI Agents

Eidolon

Eidolon is an open-source SDK for building and deploying agent-based services. Provides flexible, modular agent developm...

View Details

ChatArena

ChatArena is a library that facilitates research on autonomous language model agents and their social interactions throu...

View Details

CrewAI

CrewAI is a Python framework for building sophisticated multi-agent AI systems. It enables collaborative intelligence th...

View Details

Superagent

Superagent is an open-source AI assistant framework enabling developers to create powerful, customizable AI applications...

View Details