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Average Ratings 0 Ratings
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.
Description
Kayba empowers AI agents to enhance their performance through experiential learning. By analyzing execution traces, it identifies and rectifies failures while assessing the effectiveness of these corrections. Rather than depending on generic evaluations that fail to clarify the reasons behind an agent's shortcomings, Kayba utilizes the agent's unique traces to identify failure modes and create tailored benchmarks relevant to the user's specific context, enabling teams to gauge improvements against authentic production failure patterns. With a simple one-line setup, Kayba integrates tracing into the agent, continuously monitors its performance, and promptly alerts users when any step ceases to be recorded. Since even effective tracing can degrade as teams implement changes, Kayba actively reviews existing tracing, highlights any broken elements, identifies the specific file requiring attention, and relays the issue to a coding agent via MCP. This coding agent then addresses the problem, after which Kayba confirms that the trace is fully functional again, ensuring ongoing reliability and performance enhancement. Ultimately, this process allows teams to maintain high standards of operational continuity while fostering continual improvement in their AI systems.
API Access
Has API
Yes
API Access
Has API
No
Pricing Details
Free
Open source
Free Trial
No
Free Version
Yes
Pricing Details
Free
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
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)
No
Online Support
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
LangChain
Founded
2023
Country
United States
Website
www.langchain.com/deep-agents
Vendor Details
Company Name
Kayba
Founded
2025
Country
United States
Website
kayba.ai/