This article discusses Model Context Protocol (MCP), an open standard designed to connect AI agents with tools and data. It details the key components of MCP, its benefits (improved interoperability, future-proofing, and modularity), and its adoption in open-source agent frameworks like LangChain, CrewAI, and AutoGen. It also includes case studies of MCP implementation at Block and in developer tools.
Scaling a simple RAG pipeline from simple notes to full books. This post elaborates on how to utilize larger files with your RAG pipeline by adding an extra step to the process — chunking.
This repository contains the source code for the summarize-and-chat project. This project provides a unified document summarization and chat framework with LLMs, aiming to address the challenges of building a scalable solution for document summarization while facilitating natural language interactions through chat interfaces.
An end-to-end raw text-to-graph pipelines. This blog explores the limitations of LangChain extraction when using smaller quantized models, and how BAML can improve extraction success rates.
An article discussing the hidden costs and limitations of popular AI frameworks like LangChain, CrewAI, and PydanticAI, and introducing Atomic Agents as a potential solution.
This article details building a Retrieval-Augmented Generation (RAG) system to assist with research paper tasks, specifically question answering over a PDF document. It covers document loading, splitting, embedding with Sentence Transformers, using ChromaDB as a vector database, and implementing a query interface with LangChain.
This tutorial demonstrates how to build a powerful document search engine using Hugging Face embeddings, Chroma DB, and Langchain for semantic search capabilities.
This article details how to implement Generative User Interfaces (Generative UI) using LangGraph, specifically focusing on integrating React components with LangGraph graphs to create dynamic and interactive applications.
AGNTCY is building the Internet of Agents to be accessible for all, focusing on innovation, development, and maintenance of software components and services for agentic workflows and multi-agent applications.
**Discover:**
**1. Agent directory**
- Registry for agent publishing and discovery
- Tracks reputation and quality
**2. Open agent schema framework**
- Standard metadata format for agent capabilities
- Verification for agent providers
- Specification at github.com/agntcy/oasf
**Compose:**
**1. Agent connect protocol and SDK**
- Standardized agent communication across frameworks
- Manages message passing, state, and context
- Specification at github.com/agntcy/acp-spec
**What could these look like in action?**
A developer can find suitable agents in the directory (using OASF) and enable their communication with the agent connect protocol, regardless of frameworks.
**Discover:**
**1. Agent directory**
- Registry for agent publishing and discovery
- Tracks reputation and quality
**2. Open agent schema framework**
- Standard metadata format for agent capabilities
- Verification for agent providers
- Specification at github.com/agntcy/oasf
**Compose:**
**1. Agent connect protocol and SDK**
- Standardized agent communication across frameworks
- Manages message passing, state, and context
- Specification at github.com/agntcy/acp-spec
**What could these look like in action?**
A developer can find suitable agents in the directory (using OASF) and enable their communication with the agent connect protocol, regardless of frameworks.
AGNTCY is an open-source collective building infrastructure for AI agents to collaborate, led by Cisco, LangChain, Galileo, and other contributors. The initiative aims to create an open, interoperable foundation for agentic AI systems to work together seamlessly across different frameworks and vendors.
AGNTCY plans to develop key components such as an agent directory, an open agent schema framework, and an agent connect protocol to facilitate this interoperability.
AGNTCY plans to develop key components such as an agent directory, an open agent schema framework, and an agent connect protocol to facilitate this interoperability.
