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This Guidance demonstrates how to securely run Model Context Protocol (MCP) servers on the AWS Cloud using containerized architecture. It helps organizations implement industry-standard OAuth 2.0 a…
Visual testing tool for MCP servers
Model Context Protocol Servers
The official Python SDK for Model Context Protocol servers and clients
Specification and documentation for the Model Context Protocol
Example Jupyter notebooks 📓 and code scripts 💻 for using Amazon Bedrock Agents 🤖 and its functionalities
Open source platform for AI Engineering: OpenTelemetry-native LLM Observability, GPU Monitoring, Guardrails, Evaluations, Prompt Management, Vault, Playground. 🚀💻 Integrates with 50+ LLM Providers,…
Build Agentic AI solutions using the new Agent Stack
🤗 smolagents: a barebones library for agents that think in code.
Agent Framework / shim to use Pydantic with LLMs
Integrate cutting-edge LLM technology quickly and easily into your apps
Full-stack framework for building Multi-Agent Systems with memory, knowledge and reasoning.
A programming framework for agentic AI 🤖 PyPi: autogen-agentchat Discord: https://aka.ms/autogen-discord Office Hour: https://aka.ms/autogen-officehour
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
LlamaIndex is the leading framework for building LLM-powered agents over your data.
Build resilient language agents as graphs.
🦜🔗 Build context-aware reasoning applications
A generative AI-powered framework for testing virtual agents.
Anthropic's Interactive Prompt Engineering Tutorial
Build a custom user interface for more tailored, controlled, and consolidated interactions with Amazon Q business.
This repository contains examples for customers to get started using the Amazon Bedrock Service. This contains examples for all available foundational models
Mistral on AWS examples for Bedrock & SageMaker
Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama mode…
Supercharge Your LLM Application Evaluations 🚀
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.