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features
design
support

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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

LangMem is a versatile and lightweight Python SDK developed by LangChain that empowers AI agents by providing them with the ability to maintain long-term memory. This enables these agents to capture, store, modify, and access significant information from previous interactions, allowing them to enhance their intelligence and personalization over time. The SDK features three distinct types of memory and includes tools for immediate memory management as well as background processes for efficient updates outside of active user sessions. With its storage-agnostic core API, LangMem can integrate effortlessly with various backends, and it boasts native support for LangGraph’s long-term memory store, facilitating type-safe memory consolidation through Pydantic-defined schemas. Developers can easily implement memory functionalities into their agents using straightforward primitives, which allows for smooth memory creation, retrieval, and prompt optimization during conversational interactions. This flexibility and ease of use make LangMem a valuable tool for enhancing the capability of AI-driven applications.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

LangGraph No 
LangSmith Yes 
PydanticAI No 
Python No 
dcode Yes 

Integrations

LangGraph Yes 
LangSmith No 
PydanticAI Yes 
Python Yes 
dcode No 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version 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 

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 Yes 
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 Yes 

Vendor Details

Company Name

LangChain

Founded

2023

Country

United States

Website

www.langchain.com/deep-agents

Vendor Details

Company Name

LangChain

Founded

2022

Country

United States

Website

langchain-ai.github.io/langmem/

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