72 lines
2.4 KiB
Python
72 lines
2.4 KiB
Python
import json
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import os
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from fastapi import FastAPI, Request, WebSocket
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from fastapi.templating import Jinja2Templates
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from fastapi.staticfiles import StaticFiles
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import paramiko
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from python_on_whales import DockerClient
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app = FastAPI()
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templates = Jinja2Templates(directory="templates")
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# Speicher für Nodes (einfache JSON-Datei)
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NODES_FILE = "nodes.json"
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def load_nodes():
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if os.path.exists(NODES_FILE):
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with open(NODES_FILE, "r") as f: return json.load(f)
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return {}
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def save_nodes(nodes):
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with open(NODES_FILE, "w") as f: json.dump(nodes, f)
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@app.get("/")
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async def index(request: Request):
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return templates.TemplateResponse("index.html", {"request": request, "nodes": load_nodes()})
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# --- Node Management ---
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@app.post("/add_node")
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async def add_node(data: dict):
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nodes = load_nodes()
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nodes[data['ip']] = {"name": data['name'], "status": "connecting"}
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save_nodes(nodes)
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# Hier würde im Hintergrund der Bootstrap-Prozess starten
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return {"status": "added"}
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# --- SSH & Command Logic ---
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def run_ssh_cmd(ip, user, password, cmd):
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ssh = paramiko.SSHClient()
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ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy())
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try:
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ssh.connect(ip, username=user, password=password, timeout=10)
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stdin, stdout, stderr = ssh.exec_command(f"sudo -n {cmd}")
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output = stdout.read().decode()
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ssh.close()
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return output
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except Exception as e:
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return str(e)
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# --- Chat & AI Logic ---
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@app.websocket("/ws/chat")
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async def chat_endpoint(websocket: WebSocket):
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await websocket.accept()
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while True:
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user_msg = await websocket.receive_text()
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# SIMULATION KI-LOGIK (Hier kommt dein LLM-Aufruf rein)
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# Die KI würde entscheiden: "Ich muss Docker auf Node 192.168.1.10 installieren"
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if "installiere docker" in user_msg.lower():
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# Beispielhafter Ablauf
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ip = "192.168.1.10" # Von KI extrahiert
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await websocket.send_text(f"🤖 Starte Docker-Installation auf {ip}...")
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result = run_ssh_cmd(ip, "pi", "raspberry", "curl -sSL https://get.docker.com | sh")
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await websocket.send_text(f"✅ Ergebnis: {result[:100]}...")
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else:
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await websocket.send_text(f"🤖 Ich habe empfangen: '{user_msg}'. Wie kann ich helfen?")
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=8000) |