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Deploy mindnet to llm-node / deploy (push) Successful in 4s
65 lines
1.9 KiB
Python
65 lines
1.9 KiB
Python
import requests
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import json
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import sys
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import time
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# Konfiguration
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BASE_URL = "http://localhost:8001"
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QUERY_URL = f"{BASE_URL}/query"
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FEEDBACK_URL = f"{BASE_URL}/feedback"
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def run_test():
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print(f"--- 1. Sende Suchanfrage an {QUERY_URL} ---")
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query_payload = {
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"query": "mindnet architecture",
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"mode": "hybrid",
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"top_k": 2,
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"explain": True # Wir wollen auch Breakdown loggen
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}
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try:
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r = requests.post(QUERY_URL, json=query_payload)
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r.raise_for_status()
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res_data = r.json()
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except Exception as e:
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print(f"ERROR bei Suche: {e}")
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sys.exit(1)
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query_id = res_data.get("query_id")
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results = res_data.get("results", [])
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if not query_id:
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print("FAIL: Keine query_id in der Antwort erhalten!")
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sys.exit(1)
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if not results:
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print("WARNUNG: Keine Treffer gefunden, Test kann Feedback nur simuliert senden.")
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target_node_id = "fake-node-id"
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else:
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target_node_id = results[0].get("node_id")
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print(f"SUCCESS: Suche OK. Erhaltene Query-ID: {query_id}")
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print(f"Target Node für Feedback: {target_node_id}")
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# Kurze Pause, damit Background-Task Zeit hat zu schreiben (nur für Log-Check relevant)
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time.sleep(0.5)
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print(f"\n--- 2. Sende Feedback an {FEEDBACK_URL} ---")
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feedback_payload = {
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"query_id": query_id,
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"node_id": target_node_id,
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"score": 1,
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"comment": "Automatisierter Smoke-Test: Dieser Treffer war hilfreich."
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}
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try:
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r_fb = requests.post(FEEDBACK_URL, json=feedback_payload)
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r_fb.raise_for_status()
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print(f"SUCCESS: Feedback gesendet. Status: {r_fb.status_code}")
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print(f"Response: {r_fb.json()}")
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except Exception as e:
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print(f"ERROR bei Feedback: {e}")
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sys.exit(1)
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if __name__ == "__main__":
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run_test() |