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Planergesteuerte Agenten-Workflows mit Microsoft Semantic Kerne…

Erstelle wiederholbare Python-, .NET- oder Java-Agenten-Workflows mit Microsoft Semantic Kernel, indem Prompts, Plugins, Speicher, Planer und Konnektoren kombiniert werden.

Was ist Planergesteuerte Agenten-Workflows mit Microsoft Semantic Kerne…?

Diese Fähigkeit ermöglicht es Entwicklern, planergesteuerte Agenten-Workflows mit Microsoft Semantic Kernel zu erstellen. Semantic Kernel ist ein Open-Source-SDK, das die Integration von KI-Modellen in Anwendungen erleichtert, indem es Prompts, Plugins, Speicher, Planer und Konnektoren kombiniert. Die Fähigkeit unterstützt die Sprachen Python, .NET und Java, sodass Entwickler in ihrer bevorzugten Umgebung arbeiten können. Voraussetzung sind die Installation des SDKs, eine unterstützte Laufzeitumgebung sowie Anmeldeinformationen für einen LLM-Anbieter (z. B. Azure OpenAI oder Ollama). Nutzer können lokale Bereitstellungsoptionen wie Ollama, LMStudio oder ONNX verwenden und über Umgebungsvariablen eine Verbindung zu ihren KI-Diensten herstellen. Der Workflow ermöglicht es, wiederholbare und modulare Agenten-Workflows zu entwickeln, die komplexe Aufgaben automatisieren und anpassen können.

Funktioniert mit~Claude Code✓Codex CLI~Cursor

npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/build-planner-driven-agent-workflows-with-microsoft-semantic-kernel

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Vorschau

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Python-Paket

Dokumentation

Planergesteuerte Agenten-Workflows mit Microsoft Semantic Kernel erstellen

Erstelle wiederholbare Python-, .NET- oder Java-Agenten-Workflows mit Microsoft Semantic Kernel, indem Prompts, Plugins, Speicher, Planer und Konnektoren kombiniert werden.

Voraussetzungen

Microsoft Semantic Kernel; Python 3.10+, .NET 10.0+ oder Java 17+ je nach Laufzeit; Anmeldeinformationen für den LLM-Anbieter, die vom gewählten Konnektor benötigt werden

Installation

Verwende den Upstream-Installations- oder Einrichtungspfad, der zu deiner Umgebung passt:

pip install semantic-kernel

Anforderungen und Hinweise aus dem Upstream:

Python: 3.10+
Python

Grundlegende Nutzung oder erste Schritte:

Lokale Bereitstellung: Führe mit Ollama, LMStudio oder ONNX aus
Lege zuerst die Umgebungsvariable für deine KI-Dienste fest:
Azure OpenAI:
Quelle: https://github.com/microsoft/semantic-kernel
Aus den Upstream-Dokumenten extrahiert: https://raw.githubusercontent.com/microsoft/semantic-kernel/HEAD/README.md

Dokumentation

https://learn.microsoft.com/semantic-kernel/

Quelle

Agent Skill Exchange

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