| """ | |
| Langflow A2A Service Patch | |
| ========================== | |
| This patch adds A2A (Agent-to-Agent) protocol support to Langflow. | |
| Required for using the A2A Server Agent component. | |
| Installation: | |
| 1. Create directory: langflow/services/a2a/ | |
| 2. Add the files below to that directory |
This guide explains how to replicate the A2A Deep Research system on another machine using Ollama for local LLM inference.
The A2A Deep Research system is a multi-agent research framework that:
| """Requirements: pip install a2a-sdk httpx""" | |
| from __future__ import annotations | |
| import uuid | |
| from typing import TYPE_CHECKING, Any | |
| from langflow.custom import Component | |
| from langflow.io import ( | |
| IntInput, | |
| MessageInput, |
| """Requirements: pip install a2a-sdk""" | |
| from __future__ import annotations | |
| import uuid | |
| from typing import TYPE_CHECKING | |
| from langflow.components.langchain_utilities.tool_calling import ToolCallingAgentComponent | |
| from langflow.io import BoolInput, FloatInput, IntInput, Output, StrInput | |
| from langflow.schema.message import Message |
Research findings on Anthropic's Skills system for Claude Code.
Skills are a filesystem-based mechanism for extending Claude's capabilities with domain-specific expertise. Each skill is a directory containing a SKILL.md file with optional supporting resources.
A technical guide explaining the fine-tuning process for domain-specific LLMs, with rationale for each step.
Goal: Fine-tune Qwen2.5-Coder-14B for TagUI (browser automation DSL)
Why Fine-Tuning?: Base models don't know domain-specific syntax. Qwen-Coder is excellent at Python/JS but generates invalid TagUI code. Fine-tuning teaches the specific DSL patterns.
| { | |
| "name": "Claude Flow Development", | |
| "image": "mcr.microsoft.com/devcontainers/base:debian", | |
| "features": { | |
| "ghcr.io/devcontainers/features/node:1": {}, | |
| "ghcr.io/devcontainers/features/python:1": {}, | |
| "ghcr.io/devcontainers/features/docker-in-docker:2.12.2": { | |
| "version": "latest", | |
| "moby": true | |
| } |
Change any part of the paths to match your folders.
A comprehensive guide to setting up and using Claude-Flow with swarms in GitHub Codespaces, based on real community discussions and proven workflows.
| """ | |
| OpenAI Agent SDK & MCP Example: Rental Listings Orchestration | |
| This script demonstrates orchestrating multiple AI agents using the OpenAI Agent SDK (`agents` library) | |
| and its Model Context Protocol (MCP) extension (`openai-agents-mcp`) | |
| to automate the process of finding rental listings and notifying users. | |
| Key Concepts Illustrated: | |
| - Agent Definition: Defining specialized agents (`ListingURLsAgent`, `IndividualListingAgent`, `EmailMetadataAgent`, `OrchestratorAgent`) | |
| using both the core `agents.Agent` and MCP-enabled `agents_mcp.Agent` classes. |