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@ -107,24 +107,17 @@ class KamazAI: |
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score += self.WEIGHTS['steam_identity'] * identity_score |
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# 2. Причина (точное совпадение) |
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try: |
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reason_score = 1.0 if report1['reasons'] == report2['reasons'] else 0.0 |
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score += self.WEIGHTS['reason'] * reason_score |
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except: |
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print("Skip reason calc", report1, report2) |
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traceback.print_exc() |
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reason_score = 1.0 if report1['reasons'] == report2['reasons'] else 0.0 |
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score += self.WEIGHTS['reason'] * reason_score |
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# 3. Права |
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try: |
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perm_score = 0.0 |
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if report1['a_permition'] == report2['a_permition']: |
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perm_score += 0.5 |
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if report1['r_permition'] == report2['r_permition']: |
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perm_score += 0.5 |
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score += self.WEIGHTS['permissions'] * perm_score |
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except: |
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print("Skip permition calc", report1, report2) |
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traceback.print_exc() |
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perm_score = 0.0 |
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if report1['a_permition'] == report2['a_permition']: |
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perm_score += 0.5 |
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if report1['r_permition'] == report2['r_permition']: |
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perm_score += 0.5 |
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score += self.WEIGHTS['permissions'] * perm_score |
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# 4. Числовые поля (нормированное евклидово расстояние -> сходство) |
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num_fields = ['a_kills', 'a_deads', 'a_seconds', 'r_kills', 'r_deads', 'r_seconds', 'online'] |
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@ -150,14 +143,18 @@ class KamazAI: |
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srv_score = 1.0 if report1['srv'] == report2['srv'] else 0.0 |
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score += self.WEIGHTS['server'] * srv_score |
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return score |
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return [score, |
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{ |
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"reason_score": reason_score, |
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"perm_score": perm_score, |
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"num_similarity": num_similarity}] |
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async def predict(self, new_report): |
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# Вычисляем сходство со всеми историческими заявками |
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similarities = [] |
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for hist in self.historical_reports: |
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sim = await self.similarity(new_report, hist, self.numeric_stats) |
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similarities.append((hist['id'], sim)) |
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s_container = await self.similarity(new_report, hist, self.numeric_stats) |
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similarities.append((hist['id'], s_container[0], s_container[1])) |
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# Сортируем по убыванию сходства |
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similarities.sort(key=lambda x: x[1], reverse=True) |
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@ -167,7 +164,7 @@ class KamazAI: |
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# Собираем все действия, назначенные на эти заявки |
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action_counter = Counter() |
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similar_report_ids = [] |
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for rid, sim in top_k: |
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for rid, sim, score_rate in top_k: |
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#print(rid, sim) |
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if sim > 0: # можно задать порог, чтобы отсечь шум |
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similar_report_ids.append(rid) |
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@ -185,7 +182,7 @@ class KamazAI: |
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}) |
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else: |
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# Если ни одного похожего – предложение "inspect" по умолчанию |
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suggestions.append({'action': 'inspect', 'confidence': 1.0}) |
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suggestions.append({'action': 'none', 'confidence': 1.0}) |
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return { |
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'suggestions': suggestions, |
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@ -204,7 +201,8 @@ class Extension: |
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'author_kick': "кикнуть автора репорта", |
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'mute': "замьютить игрока", |
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'unban': "разбанить игрока если тот в бане, ебанутое решение", |
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'author_inspect': 'глянуть профиль автора репорта' |
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'author_inspect': 'глянуть профиль автора репорта', |
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'none': 'ничего не делать, лучше не лезть' |
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} |
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def __init__(self, core): |
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gsd
4 weeks ago