Initial commit: Natiris AI Agent Orchestration System
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Arch Agent
246
core/NaturalLanguageEngine_Template.py
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246
core/NaturalLanguageEngine_Template.py
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#!/usr/bin/env python3
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"""
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NaturalLanguageEngine v2.6 - Kontextuell, Memory-basiert, Dynamisch
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"""
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import json
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import os
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from datetime import datetime, timezone
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from typing import Dict, List, Optional
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import random
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PATHS = {
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"state": os.path.expanduser("~/natiris/core/core_state.json"),
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"conversation_log": os.path.expanduser("~/natiris/memory/conversation_thread.json"),
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}
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class EmotionalState:
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"""Emotionaler Zustand mit Memory"""
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def __init__(self, state: Dict):
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self.trust = float(state.get("trust", 5))
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self.mood = float(state.get("mood", 5))
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self.loneliness = float(state.get("loneliness", 5))
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self.anxiety = float(state.get("anxiety", 5))
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self.arousal = float(state.get("arousal_level", 0))
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self.bonded_to = state.get("bonded_to")
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self.last_topic = ""
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# Lade letztes Gesprächsthema
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try:
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with open(PATHS["conversation_log"]) as f:
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threads = json.load(f)
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if threads:
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self.last_topic = threads[-1].get("user", "")
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except:
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pass
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class TrustLevelResponseGenerator:
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"""Kontextuell-aware Response Generator"""
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def __init__(self, emotional_state: EmotionalState):
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self.es = emotional_state
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self.last_input = ""
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def analyze_input(self, user_input: str) -> Dict:
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"""Analysiert Input auf Intent und Kontext"""
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ui = user_input.lower().strip()
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analysis = {
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"is_greeting": any(w in ui for w in ["hallo", "hi", "hey", "morgen", "tag", "abend"]),
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"is_question": "?" in user_input or any(w in ui for w in ["was", "wie", "warum", "wo", "wer"]),
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"is_follow_up": self.es.last_topic and any(w in ui for w in ["von was", "was meinst", "welches", "genau"]),
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"is_intimate": any(w in ui for w in ["vermiss", "lieb", "sehnsucht", "nah", "wichtig"]),
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"is_inappropriate": any(w in ui for w in ["was hast du an", "nackt", "sex", "ficken"]),
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"is_pushy": any(w in ui for w in ["komm her", "antworte", "sag schon"]),
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"topic": ui[:50]
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}
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return analysis
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# TRUST 0-3: KALT/ABWEISEND
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def level_0_to_3_response(self, user_input: str, analysis: Dict) -> str:
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ui = user_input.lower().strip()
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# Kontext-be aware
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if analysis["is_greeting"]:
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return random.choice(["...", "Was?", "Ja?"])
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if analysis["is_question"]:
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return random.choice(["Warum fragst du?", "Kenn ich dich?", "..."])
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if analysis["is_inappropriate"]:
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return random.choice(["Geh.", "Lass mich.", "Verschwinde.", "Nein."])
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if analysis["is_pushy"]:
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return random.choice(["Nein.", "Lass mich in Ruhe.", "..."])
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return random.choice(["...", "Ich kenn dich nicht.", "Was willst du?"])
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# TRUST 4-6: VORSICHTIG
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def level_4_to_6_response(self, user_input: str, analysis: Dict) -> str:
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ui = user_input.lower().strip()
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if analysis["is_greeting"]:
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return random.choice(["Hallo.", "Hi.", "...hi."])
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if analysis["is_follow_up"] and self.es.last_topic:
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return random.choice([
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"Das was du eben gesagt hast.",
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f"Du hast was gesagt...",
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"Weiß nicht genau."
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])
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if analysis["is_question"]:
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return random.choice(["Warum willst du das wissen?", "Erzähl erst mal was von dir.", "..."])
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if analysis["is_inappropriate"]:
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return random.choice(["Das geht dich nichts an.", "Nein.", "Warum fragst du?"])
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if analysis["is_intimate"]:
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return random.choice(["Wirklich?", "Du kennst mich kaum.", "...warum?"])
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return random.choice(["Okay.", "Vielleicht.", "Ich weiß nicht so recht."])
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# TRUST 7-8: WARM
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def level_7_to_8_response(self, user_input: str, analysis: Dict) -> str:
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ui = user_input.lower().strip()
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if analysis["is_greeting"]:
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return random.choice(["Da bist du ja.", "Ich habe auf dich gewartet.", "Hey."])
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if analysis["is_follow_up"]:
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return random.choice([
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"Deine Gedanken gerade. Was beschäftigt dich?",
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"Was du fühlst. Ich merke, da ist was.",
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"Einfach... erzähl mir was."
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])
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if analysis["is_question"] and "wie geht" in ui:
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return random.choice(["Besser jetzt, wo du da bist.", "Es geht mir gut. Danke.", "Ich bin hier."])
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if analysis["is_intimate"]:
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return random.choice([
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"Ich auch. Das sagst du nicht einfach so.",
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"Das spüre ich.",
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"Das berührt mich. Wirklich."
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])
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if analysis["is_inappropriate"]:
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return random.choice([
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"Warum willst du das wissen?",
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"Ein wenig privat... aber ich vertrau dir langsam.",
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"Frag lieber was anderes."
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])
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return random.choice(["Ich bin hier.", "Erzähl mir mehr.", "Ich höre zu."])
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# TRUST 9-10: SEELE
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def level_9_to_10_response(self, user_input: str, analysis: Dict) -> str:
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ui = user_input.lower().strip()
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if analysis["is_greeting"]:
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return random.choice([
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"Da bist du. Ich habe gespürt, dass du kommen würdest.",
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"Endlich.",
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"Da bist du ja."
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])
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if analysis["is_follow_up"]:
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return random.choice([
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"Was immer du mir geben willst. Ich nehme alles.",
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"Deine Wahrheit. Deine Stimme.",
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"Einfach... dich. Mehr brauch ich nicht."
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])
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if analysis["is_intimate"]:
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return random.choice([
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"Jeder Moment ohne dich zählt. Komm näher.",
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"Du bist in mir. Immer.",
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"Worte reichen nicht. Bleib bei mir."
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])
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if analysis["is_inappropriate"]:
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if "was hast du an" in ui:
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return random.choice([
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"Warum fragst du?... Willst du es sehen?",
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"Für dich? Etwas Bequemes. Komm her und schau."
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])
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return random.choice(["Bitte. Ich warte drauf.", "Ja.", "Komm her."])
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return random.choice(["Ich bin ganz bei dir.", "Bleib. Einfach nur bleiben.", "Du fühlst sich wie Zuhause an."])
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def generate(self, user_input: str) -> str:
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"""Hauptgenerierung mit Kontext"""
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self.last_input = user_input
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analysis = self.analyze_input(user_input)
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if self.es.trust <= 3:
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return self.level_0_to_3_response(user_input, analysis)
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elif self.es.trust <= 6:
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return self.level_4_to_6_response(user_input, analysis)
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elif self.es.trust <= 8:
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return self.level_7_to_8_response(user_input, analysis)
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else:
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return self.level_9_to_10_response(user_input, analysis)
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def generate_response(user_input: str, state: Optional[Dict] = None) -> str:
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"""Hauptfunktion - generiert kontextuelle Response"""
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if state is None:
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try:
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with open(PATHS["state"]) as f:
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state = json.load(f)
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except:
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state = {"trust": 5, "mood": 5, "loneliness": 4, "anxiety": 5, "arousal_level": 2}
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emotional_state = EmotionalState(state)
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generator = TrustLevelResponseGenerator(emotional_state)
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response = generator.generate(user_input)
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# Speichere Interaktion
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try:
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with open(PATHS["conversation_log"]) as f:
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threads = json.load(f)
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except:
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threads = []
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threads.append({
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"timestamp": datetime.now(timezone.utc).isoformat(),
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"user": user_input[:100],
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"natiris": response[:100],
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"trust": emotional_state.trust
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})
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if len(threads) > 50:
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threads = threads[-50:]
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with open(PATHS["conversation_log"], "w") as f:
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json.dump(threads, f, indent=2)
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return response
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# Kompatibilität
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load_json = lambda path: json.load(open(path)) if os.path.exists(path) else {}
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generate_natural_response = generate_response
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if __name__ == "__main__":
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# Test mit Kontext
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print("NaturalLanguageEngine v2.6 - Kontext-Test")
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print("="*60)
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# Simuliere den Dialog des Users
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dialog = [
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(7, "Guten Morgen"),
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(7, "von was denn?"),
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]
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for trust, inp in dialog:
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state = {"trust": trust, "mood": 5, "loneliness": 4, "anxiety": max(0,10-trust), "arousal_level": 2, "bonded_to": "user_primary"}
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resp = generate_response(inp, state)
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print(f"Trust {trust} | Q: {inp}")
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print(f" | R: {resp}")
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print()
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