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Average Ratings 0 Ratings

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support 0 out of 5 stars

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Description

CAMEL-AI represents the inaugural framework for multi-agent systems based on large language models and fosters an open-source community focused on investigating the scaling dynamics of agents. This innovative platform allows users to design customizable agents through modular components that are specifically suited for particular tasks, thereby promoting the creation of multi-agent systems that tackle issues related to autonomous collaboration. Serving as a versatile foundation for a wide range of applications, the framework is ideal for tasks like automation, data generation, and simulations of various environments. By conducting extensive studies on agents, CAMEL-AI.org seeks to uncover critical insights into their behaviors, capabilities, and the potential risks they may pose. The community prioritizes thorough research and seeks to strike a balance between the urgency of findings and the patience required for in-depth exploration, while also welcoming contributions that enhance its infrastructure, refine documentation, and bring innovative research ideas to life. The platform is equipped with a suite of components, including models, tools, memory systems, and prompts, designed to empower agents, and it also facilitates integration with a wide array of external tools and services, thereby expanding its utility and effectiveness in real-world applications. As the community grows, it aims to inspire further advancements in the field of artificial intelligence and collaborative systems.

Description

Deep Agents serves as an open-source library and agent framework designed for the creation of LLM-driven agents capable of executing multi-step tasks. This library features an agent loop equipped with functionalities such as planning, persistent memory, file-system access, and the ability to delegate tasks to subagents, while also enabling developers to connect various model providers and tools seamlessly. Aimed at software developers and teams focused on crafting tailored agent applications, it supports diverse workflows including research, programming, and other scenarios necessitating planning and action across multiple steps. Additionally, developers have the flexibility to enhance the framework's capabilities by incorporating custom tools, middleware, and backends, while also integrating with LangGraph and LangSmith for effective orchestration, tracing, and deployment processes. Ultimately, Deep Agents functions as a foundational software development framework, empowering users to create and operate agents within their specific applications and environments, rather than providing a pre-built agent for end-users. This versatility makes it an invaluable asset for those looking to innovate in the realm of agent-based application development.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

LangSmith No 
OWL Yes 
OpenAgents Yes 
TraceRoot.AI Yes 
dcode No 

Integrations

LangSmith Yes 
OWL No 
OpenAgents No 
TraceRoot.AI No 
dcode Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

CAMEL-AI

Founded

2023

Country

United States

Website

www.camel-ai.org

Vendor Details

Company Name

LangChain

Founded

2023

Country

United States

Website

www.langchain.com/deep-agents

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