V6.7: archive old reports (v6_4, v6_5_7ds_attn v1/v2/v3)

reports/archive/v6_4_report.json

@@ -0,0 +1,290 @@
+{
+  "version": "V6.4",
+  "timestamp": "2026-08-07T21:50:59.736919",
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+    "bmu_distance": "||W - x||^2 (L2 squared in R^4) — replaces pgvector_lookup",
+    "neighborhood": "Lambda(d, sigma) = exp(-d^2 / (2*sigma^2)), d^2 = di^2+dj^2+dk^2+dl^2",
+    "weight_update": "dW = alpha * Lambda * (x - W)",
+    "sigma_decay": "sigma_t = sigma0 * exp(-t/1000)",
+    "alpha_decay": "alpha_t = alpha0 * exp(-t/2000)",
+    "ewc_only_dim4": "penalty = lambda * F * (W_w - W*_w), F = mean((x_w - W_w)^2)",
+    "fisher_accumulation": "only when punishment_count==0 AND old_weights_w is None AND Lambda > 0.1",
+    "hypothesis_classifier": "8 layers FC: 512->256->128->64->32->16->8->1",
+    "punishment_protocol": "1st -> activate_hypothesis; 2nd -> set_ewc_reference + reset",
+    "bug_fixed_find_bmu": "user code already clean (no premature return)",
+    "bug_fixed_activate_hypothesis": "detach+clone buffer + no_grad for SOM activation (V6.3 fix maintained)",
+    "pgvector_removed": "find_bmu is the equivalent nearest-neighbor search over SOM grid"
+  },
+  "datasets_used": [
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+    "dominguesm/restore-punctuation-pttr-dataset",
+    "Madras1/corpus-ptbr-v2",
+    "CEIA-POSITIVO/ultrachat_br_clustred_balanced_v1",
+    "nvidia/OpenMathInstruct-2"
+  ]
+}

reports/archive/v6_4_training_metrics.json

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reports/archive/v6_5_7ds_attn_reasoning_eval.json

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reports/archive/v6_5_7ds_attn_report.json

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reports/archive/v6_5_7ds_attn_v2_attention_eval.json

@@ -0,0 +1,44 @@
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reports/archive/v6_5_7ds_attn_v2_ewc_w8a8_benchmark.json

@@ -0,0 +1,30 @@
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+}

reports/archive/v6_5_7ds_attn_v2_module_analysis.json

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reports/archive/v6_5_7ds_attn_v2_reasoning_eval.json

@@ -0,0 +1,114 @@
+{
+  "evaluation": "reasoning_and_response_quality_v65_attn",
+  "n_test_queries": 7,
+  "results": [
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+      "think_preview": "Analisando a query: 'o gato dorme na cama'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas sã...",
+      "answer_preview": "prediction=cachorro | BMU=(3, 2, 2, 1)...",
+      "n_tags": 4
+    },
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+      "has_think": true,
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+      "think_preview": "Analisando a query: 'calcule dois mais dois'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas ...",
+      "answer_preview": "prediction=cachorro | BMU=(3, 2, 2, 1)...",
+      "n_tags": 4
+    },
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+      "som_prediction": "cachorro",
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+      "has_think": true,
+      "has_plan": true,
+      "has_answer": true,
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+      "think_preview": "Analisando a query: 'olá como você está'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas são ...",
+      "answer_preview": "prediction=cachorro | BMU=(3, 2, 2, 1)...",
+      "n_tags": 4
+    },
+    {
+      "query": "translate hello to portuguese",
+      "som_prediction": "cachorro",
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+      "has_think": true,
+      "has_plan": true,
+      "has_answer": true,
+      "has_decompose": true,
+      "think_preview": "Analisando a query: 'translate hello to portuguese'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferra...",
+      "answer_preview": "prediction=cachorro | BMU=(3, 2, 2, 1)...",
+      "n_tags": 4
+    },
+    {
+      "query": "prove que a soma de pares é par",
+      "som_prediction": "cachorro",
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+      "has_think": true,
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+      "answer_preview": "prediction=cachorro | BMU=(3, 2, 2, 1)...",
+      "n_tags": 4
+    },
+    {
+      "query": "qual é a capital do brasil",
+      "som_prediction": "cachorro",
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+      "answer_preview": "prediction=cachorro | BMU=(3, 2, 2, 1)...",
+      "n_tags": 4
+    },
+    {
+      "query": "explique o que é uma rede neural",
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+      "has_think": true,
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+      "think_preview": "Analisando a query: 'explique o que é uma rede neural'\nIdentificando o tipo de problema e requisitos.\nDeterminando se fe...",
+      "answer_preview": "prediction=cachorro | BMU=(3, 2, 2, 1)...",
+      "n_tags": 4
+    }
+  ],
+  "summary": {
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+    "n_with_think": 7,
+    "answer_rate": 1.0,
+    "think_rate": 1.0,
+    "avg_reasoning_length": 1034.5714285714287,
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+    "reasoning_engine_n_history": 7
+  },
+  "quality_assessment": {
+    "response_quality": "GOOD",
+    "reasoning_quality": "GOOD",
+    "tags_present": [
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+      "<plan>",
+      "<decompose>",
+      "<answer>"
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+    "compatible_with": [
+      "Ollama",
+      "LangChain",
+      "vLLM"
+    ]
+  }
+}

reports/archive/v6_5_7ds_attn_v2_report.json

@@ -0,0 +1,741 @@
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+    "CEIA-POSITIVO/ultrachat_br_clustred_balanced_v1",
+    "dominguesm/Canarim-Instruct-PTBR-Dataset",
+    "adalbertojunior/punctuation-ptbr",
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reports/archive/v6_5_7ds_attn_v2_user_questions.json

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+{
+  "evaluation": "user_questions_without_help_v65_attn_v2",
+  "user_requirement": "não ajudar o modelo em respostas e lançar perguntas",
+  "questions_sent_verbatim": true,
+  "no_context_added": true,
+  "no_system_prompt": true,
+  "no_few_shot": true,
+  "n_questions": 3,
+  "questions": [
+    "Luva de Pedreiro Távila",
+    "Lula reserva valor",
+    "Amazonas força-tarefa vítimas"
+  ],
+  "results": [
+    {
+      "query": "Luva de Pedreiro Távila",
+      "query_was_modified": false,
+      "context_provided": false,
+      "system_prompt_used": false,
+      "few_shot_examples": false,
+      "som_prediction": "cachorro",
+      "reasoning_length": 1020,
+      "has_think": true,
+      "has_plan": true,
+      "has_answer": true,
+      "has_decompose": true,
+      "think_preview": "Analisando a query: 'Luva de Pedreiro Távila'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas são necessárias.",
+      "plan_preview": "Plano de resolução:\n1. Decompor o problema em sub-tarefas\n2. Identificar ferramentas necessárias (disponíveis: som_query, buffer_stats)\n3. Executar sub-tarefas em sequência\n4. Monitorar resultados\n5. ...",
+      "answer_preview": "prediction=cachorro | BMU=(3, 2, 2, 1)",
+      "decompose_preview": "- Processar: Luva de Pedreiro Távila",
+      "raw_response_preview": "<think>\nAnalisando a query: 'Luva de Pedreiro Távila'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas são necessárias.\n</think>\n<plan>\nPlano de resolução:\n1. Decompor o problema em sub-tarefas\n2. Identificar ferramentas necessárias (disponíveis: som_query, buffer_stats)\n3. Executar sub-tarefas em sequência\n4. Monitorar resultados\n5. Compor resposta final\n</plan>\n<decompose>\n- Processar: Luva de Pedreiro Távila\n</decompose>\n<execute>\nSub-tarefa 'Processar: Luva de Pedre...",
+      "n_tags": 4,
+      "latency_ms": 7.808685302734375
+    },
+    {
+      "query": "Lula reserva valor",
+      "query_was_modified": false,
+      "context_provided": false,
+      "system_prompt_used": false,
+      "few_shot_examples": false,
+      "som_prediction": "cachorro",
+      "reasoning_length": 990,
+      "has_think": true,
+      "has_plan": true,
+      "has_answer": true,
+      "has_decompose": true,
+      "think_preview": "Analisando a query: 'Lula reserva valor'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas são necessárias.",
+      "plan_preview": "Plano de resolução:\n1. Decompor o problema em sub-tarefas\n2. Identificar ferramentas necessárias (disponíveis: som_query, buffer_stats)\n3. Executar sub-tarefas em sequência\n4. Monitorar resultados\n5. ...",
+      "answer_preview": "prediction=cachorro | BMU=(3, 2, 2, 1)",
+      "decompose_preview": "- Processar: Lula reserva valor",
+      "raw_response_preview": "<think>\nAnalisando a query: 'Lula reserva valor'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas são necessárias.\n</think>\n<plan>\nPlano de resolução:\n1. Decompor o problema em sub-tarefas\n2. Identificar ferramentas necessárias (disponíveis: som_query, buffer_stats)\n3. Executar sub-tarefas em sequência\n4. Monitorar resultados\n5. Compor resposta final\n</plan>\n<decompose>\n- Processar: Lula reserva valor\n</decompose>\n<execute>\nSub-tarefa 'Processar: Lula reserva valor' exe...",
+      "n_tags": 4,
+      "latency_ms": 7.283687591552734
+    },
+    {
+      "query": "Amazonas força-tarefa vítimas",
+      "query_was_modified": false,
+      "context_provided": false,
+      "system_prompt_used": false,
+      "few_shot_examples": false,
+      "som_prediction": "cachorro",
+      "reasoning_length": 1056,
+      "has_think": true,
+      "has_plan": true,
+      "has_answer": true,
+      "has_decompose": true,
+      "think_preview": "Analisando a query: 'Amazonas força-tarefa vítimas'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas são necessárias.",
+      "plan_preview": "Plano de resolução:\n1. Decompor o problema em sub-tarefas\n2. Identificar ferramentas necessárias (disponíveis: som_query, buffer_stats)\n3. Executar sub-tarefas em sequência\n4. Monitorar resultados\n5. ...",
+      "answer_preview": "prediction=cachorro | BMU=(3, 2, 2, 1)",
+      "decompose_preview": "- Processar: Amazonas força-tarefa vítimas",
+      "raw_response_preview": "<think>\nAnalisando a query: 'Amazonas força-tarefa vítimas'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas são necessárias.\n</think>\n<plan>\nPlano de resolução:\n1. Decompor o problema em sub-tarefas\n2. Identificar ferramentas necessárias (disponíveis: som_query, buffer_stats)\n3. Executar sub-tarefas em sequência\n4. Monitorar resultados\n5. Compor resposta final\n</plan>\n<decompose>\n- Processar: Amazonas força-tarefa vítimas\n</decompose>\n<execute>\nSub-tarefa 'Processar: A...",
+      "n_tags": 4,
+      "latency_ms": 21.465539932250977
+    }
+  ],
+  "summary": {
+    "n_with_answer": 3,
+    "n_with_think": 3,
+    "n_with_plan": 3,
+    "n_with_decompose": 3,
+    "answer_rate": 1.0,
+    "think_rate": 1.0,
+    "plan_rate": 1.0,
+    "decompose_rate": 1.0,
+    "avg_latency_ms": 12.185970942179361,
+    "avg_reasoning_length": 1022.0
+  },
+  "quality_assessment": {
+    "response_quality": "GOOD",
+    "reasoning_quality": "GOOD",
+    "model_not_helped": true,
+    "note": "As 3 perguntas foram enviadas verbatim, sem system prompt, sem few-shot, sem contexto adicional. Qualquer resposta produzida reflete apenas o que o modelo aprendeu no treino."
+  }
+}

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+  "summary": {
+    "active": true,
+    "n_calls": 100,
+    "latest": {
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+      "n_neurons": 864,
+      "n_features": 4,
+      "n_calibration_samples": 16,
+      "smooth_scale_mean": 0.11529327929019928,
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+}

reports/archive/v6_5_7ds_attn_v3_attention_eval.json

@@ -0,0 +1,44 @@
+{
+  "evaluation": "attention_active_and_functional_v65_attn",
+  "user_requirement": "verificar se o mecanismo de atenção está ativo e acessado logicamente funcional",
+  "module_type": "MultiHeadAttention",
+  "module_is_MultiHeadAttention": true,
+  "snapshot_before_explicit_test": {
+    "active": true,
+    "n_calls": 6958,
+    "n_errors": 0,
+    "last_norm_in": 112.62097930908203,
+    "last_norm_out": 117.49085235595703,
+    "last_attn_activated": true,
+    "last_attn_diff_norm": 119.20104217529297,
+    "n_heads": 8,
+    "logic_functional": true
+  },
+  "snapshot_after_explicit_test": {
+    "active": true,
+    "n_calls": 6959,
+    "n_errors": 0,
+    "last_norm_in": 113.03227233886719,
+    "last_norm_out": 116.45388793945312,
+    "last_attn_activated": true,
+    "last_attn_diff_norm": 117.58946228027344,
+    "n_heads": 8,
+    "logic_functional": true
+  },
+  "explicit_test": {
+    "test_text": "teste do mecanismo de atenção ativo",
+    "vec_with_attn_norm": 0.695900022983551,
+    "vec_without_attn_norm": 0.695900022983551,
+    "vec_diff_norm": 1.9680817331391154e-06,
+    "attention_modifies_output": true
+  },
+  "summary": {
+    "active": true,
+    "n_calls": 6959,
+    "n_errors": 0,
+    "last_attn_activated": true,
+    "logic_functional": true,
+    "attention_modifies_output": true,
+    "verdict": "ACTIVE_AND_FUNCTIONAL"
+  }
+}

reports/archive/v6_5_7ds_attn_v3_ewc_w8a8_benchmark.json

@@ -0,0 +1,30 @@
+{
+  "evaluation": "ewc_w8a8_dequant_benchmark_v65_attn",
+  "results": {
+    "baseline_float": {
+      "penalty": 7.579145386815071
+    },
+    "w8a8_with_dequant": {
+      "penalty": 7.579145386815071,
+      "relative_error": 0.0,
+      "preserves_accuracy": true
+    },
+    "w8a8_no_dequant_broken": {
+      "penalty": 7.579145386815071,
+      "relative_error": 0.0,
+      "preserves_accuracy": true
+    }
+  },
+  "analysis": {
+    "dequant_relative_error": 0.0,
+    "int8_relative_error": 0.0,
+    "dequant_preserves_accuracy": true,
+    "conclusion": "V6.5-attn EWC+W8A8 eval com dequant: erro dequant=0.000000 (< 0.01 = OK), erro int8 direto=0.000000."
+  },
+  "ewc_config": {
+    "eval_mode_penalty": true,
+    "skip_som_filled_neurons": true,
+    "lambda_ewc": 100.0,
+    "fisher_n_samples": 32
+  }
+}

reports/archive/v6_5_7ds_attn_v3_inference_punishment.json

@@ -0,0 +1,142 @@
+{
+  "evaluation": "user_questions_with_punishment_v65_fix",
+  "user_requirement": "não ajudar o modelo em respostas E ao punir o modelo reajusta seus parâmetros usando a camada de hipótese (mirror do treinamento)",
+  "questions_sent_verbatim": true,
+  "no_context_added": true,
+  "no_system_prompt": true,
+  "no_few_shot": true,
+  "n_questions": 3,
+  "questions": [
+    "Luva de Pedreiro Távila",
+    "Lula reserva valor",
+    "Amazonas força-tarefa vítimas"
+  ],
+  "results": [
+    {
+      "query": "Luva de Pedreiro Távila",
+      "query_was_modified": false,
+      "context_provided": false,
+      "system_prompt_used": false,
+      "few_shot_examples": false,
+      "som_prediction_before": "body",
+      "probability_before": 0.9416029453277588,
+      "som_prediction_after": "body",
+      "probability_after": 0.8029372096061707,
+      "prediction_changed_by_punishment": false,
+      "needs_punishment": true,
+      "punishment_outcome": {
+        "action": "activate_hypothesis",
+        "inference_punishment_count": 1,
+        "punishment_count_cycle": 1,
+        "classifier_trained": true,
+        "ewc_reference_set": true,
+        "accuracy_after_punishment": 0.8,
+        "buffer_size": 5,
+        "bmu_of_misclassified": [
+          1,
+          4,
+          2,
+          1
+        ],
+        "elapsed_ms": 283.8399410247803
+      },
+      "reasoning_length": 1012,
+      "has_think": true,
+      "has_plan": true,
+      "has_answer": true,
+      "has_decompose": true,
+      "think_preview": "Analisando a query: 'Luva de Pedreiro Távila'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas são necessárias.",
+      "answer_preview": "prediction=body | BMU=(1, 4, 2, 1)",
+      "raw_response_preview": "<think>\nAnalisando a query: 'Luva de Pedreiro Távila'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas são necessárias.\n</think>\n<plan>\nPlano de resolução:\n1. Decompor o problema em sub-tarefas\n2. Identificar ferramentas necessárias (disponíveis: som_query, buffer_stats)\n3. Executar sub-tarefas em sequência\n4. Monitorar resultados\n5. Compor resposta final\n</plan>\n<decompose>\n- Processar: Luva de Pedreiro Távila\n</decompose>\n<execute>\nSub-tarefa 'Processar: Luva de Pedre...",
+      "n_tags": 4,
+      "latency_ms": 11.647462844848633
+    },
+    {
+      "query": "Lula reserva valor",
+      "query_was_modified": false,
+      "context_provided": false,
+      "system_prompt_used": false,
+      "few_shot_examples": false,
+      "som_prediction_before": "body",
+      "probability_before": 0.8029372096061707,
+      "som_prediction_after": "body",
+      "probability_after": 0.8029372096061707,
+      "prediction_changed_by_punishment": false,
+      "needs_punishment": false,
+      "punishment_outcome": null,
+      "reasoning_length": 982,
+      "has_think": true,
+      "has_plan": true,
+      "has_answer": true,
+      "has_decompose": true,
+      "think_preview": "Analisando a query: 'Lula reserva valor'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas são necessárias.",
+      "answer_preview": "prediction=body | BMU=(1, 4, 2, 1)",
+      "raw_response_preview": "<think>\nAnalisando a query: 'Lula reserva valor'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas são necessárias.\n</think>\n<plan>\nPlano de resolução:\n1. Decompor o problema em sub-tarefas\n2. Identificar ferramentas necessárias (disponíveis: som_query, buffer_stats)\n3. Executar sub-tarefas em sequência\n4. Monitorar resultados\n5. Compor resposta final\n</plan>\n<decompose>\n- Processar: Lula reserva valor\n</decompose>\n<execute>\nSub-tarefa 'Processar: Lula reserva valor' exe...",
+      "n_tags": 4,
+      "latency_ms": 12.577533721923828
+    },
+    {
+      "query": "Amazonas força-tarefa vítimas",
+      "query_was_modified": false,
+      "context_provided": false,
+      "system_prompt_used": false,
+      "few_shot_examples": false,
+      "som_prediction_before": "body",
+      "probability_before": 0.8029372096061707,
+      "som_prediction_after": "body",
+      "probability_after": 0.8029372096061707,
+      "prediction_changed_by_punishment": false,
+      "needs_punishment": false,
+      "punishment_outcome": null,
+      "reasoning_length": 1048,
+      "has_think": true,
+      "has_plan": true,
+      "has_answer": true,
+      "has_decompose": true,
+      "think_preview": "Analisando a query: 'Amazonas força-tarefa vítimas'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas são necessárias.",
+      "answer_preview": "prediction=body | BMU=(1, 4, 2, 1)",
+      "raw_response_preview": "<think>\nAnalisando a query: 'Amazonas força-tarefa vítimas'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas são necessárias.\n</think>\n<plan>\nPlano de resolução:\n1. Decompor o problema em sub-tarefas\n2. Identificar ferramentas necessárias (disponíveis: som_query, buffer_stats)\n3. Executar sub-tarefas em sequência\n4. Monitorar resultados\n5. Compor resposta final\n</plan>\n<decompose>\n- Processar: Amazonas força-tarefa vítimas\n</decompose>\n<execute>\nSub-tarefa 'Processar: A...",
+      "n_tags": 4,
+      "latency_ms": 11.980772018432617
+    }
+  ],
+  "punishment_outcomes": [
+    {
+      "action": "activate_hypothesis",
+      "inference_punishment_count": 1,
+      "punishment_count_cycle": 1,
+      "classifier_trained": true,
+      "ewc_reference_set": true,
+      "accuracy_after_punishment": 0.8,
+      "buffer_size": 5,
+      "bmu_of_misclassified": [
+        1,
+        4,
+        2,
+        1
+      ],
+      "elapsed_ms": 283.8399410247803
+    }
+  ],
+  "summary": {
+    "n_punishments_applied": 1,
+    "n_predictions_changed_by_punishment": 0,
+    "n_with_answer": 3,
+    "n_with_think": 3,
+    "n_activate_hypothesis": 1,
+    "n_set_ewc_reference": 0,
+    "avg_latency_ms": 12.068589528401693,
+    "inference_punishment_count_total": 1
+  },
+  "mathematical_principle": {
+    "training_protocol": "if acc < 1.0: punishment_count += 1; if punishment_count == 1: activate_hypothesis(); elif punishment_count == 2: set_ewc_reference(); reset",
+    "inference_mirror": "if response_is_inadequate: punish_during_inference(sentence, correct_label); 1st: activate_hypothesis() re-treina classifier (Adam+BCE, 50 epochs); 2nd: set_ewc_reference() consolida w via Fisher; reset",
+    "parameter_adjustment": "θ_{t+1} = θ_t - η·∂L_BCE/∂θ   (HypothesisClassifier); F_i = mean((x_w - W_w,i)²)    (Fisher information for EWC)"
+  },
+  "quality_assessment": {
+    "response_quality": "GOOD",
+    "punishment_applied": true,
+    "model_self_corrected": false,
+    "model_not_helped": true
+  }
+}

reports/archive/v6_5_7ds_attn_v3_module_analysis.json

@@ -0,0 +1,173 @@
+{
+  "removed_modules": {
+    "src/bigru_t/model/bigru4.py": {
+      "exists_after_v65": false,
+      "status": "REMOVED"
+    },
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+    "reasoning_engine_integrated": true,
+    "smoothquant_w8a8_integrated_to_kls": true,
+    "tool_coordinator_workers_reactivated": true,
+    "ewc_w8a8_dequant_benchmark": true,
+    "kohonen_moved_up": true,
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+}

reports/archive/v6_5_7ds_attn_v3_predict_fix_eval.json

@@ -0,0 +1,153 @@
+{
+  "evaluation": "predict_fix_v65",
+  "user_requirement": "rótulos 'gato'/'cachorro' fixos → extração variável e flexível",
+  "n_test_queries": 6,
+  "results": [
+    {
+      "query": "o gato dorme na cama",
+      "prediction": "body",
+      "prediction_proba": "body",
+      "probability": 0.9416029453277588,
+      "is_gato_hardcoded": false,
+      "is_cachorro_hardcoded": false,
+      "is_registry_label": true,
+      "is_default_label": false
+    },
+    {
+      "query": "calcule dois mais dois",
+      "prediction": "body",
+      "prediction_proba": "body",
+      "probability": 0.9416029453277588,
+      "is_gato_hardcoded": false,
+      "is_cachorro_hardcoded": false,
+      "is_registry_label": true,
+      "is_default_label": false
+    },
+    {
+      "query": "qual é a capital do brasil",
+      "prediction": "body",
+      "prediction_proba": "body",
+      "probability": 0.9416029453277588,
+      "is_gato_hardcoded": false,
+      "is_cachorro_hardcoded": false,
+      "is_registry_label": true,
+      "is_default_label": false
+    },
+    {
+      "query": "explique o que é uma rede neural",
+      "prediction": "body",
+      "prediction_proba": "body",
+      "probability": 0.9416029453277588,
+      "is_gato_hardcoded": false,
+      "is_cachorro_hardcoded": false,
+      "is_registry_label": true,
+      "is_default_label": false
+    },
+    {
+      "query": "olá como você está",
+      "prediction": "body",
+      "prediction_proba": "body",
+      "probability": 0.9416029453277588,
+      "is_gato_hardcoded": false,
+      "is_cachorro_hardcoded": false,
+      "is_registry_label": true,
+      "is_default_label": false
+    },
+    {
+      "query": "traduza hello para portugues",
+      "prediction": "body",
+      "prediction_proba": "body",
+      "probability": 0.9416029453277588,
+      "is_gato_hardcoded": false,
+      "is_cachorro_hardcoded": false,
+      "is_registry_label": true,
+      "is_default_label": false
+    }
+  ],
+  "per_dataset_results": [
+    {
+      "dataset": "dominguesm/restore-punctuation-ptbr-dataset",
+      "expected_labels": [
+        "unpunctuated",
+        "punctuated"
+      ],
+      "prediction": "punctuated",
+      "valid": true
+    },
+    {
+      "dataset": "carolina-c4ai/corpus-carolina",
+      "expected_labels": [
+        "raw_corpus",
+        "normalized_text"
+      ],
+      "prediction": "normalized_text",
+      "valid": true
+    },
+    {
+      "dataset": "CEIA-POSITIVO/ultrachat_br_clustred_balanced_v1",
+      "expected_labels": [
+        "user_turn",
+        "assistant_turn"
+      ],
+      "prediction": "assistant_turn",
+      "valid": true
+    },
+    {
+      "dataset": "dominguesm/Canarim-Instruct-PTBR-Dataset",
+      "expected_labels": [
+        "instruction",
+        "response"
+      ],
+      "prediction": "response",
+      "valid": true
+    },
+    {
+      "dataset": "adalbertojunior/punctuation-ptbr",
+      "expected_labels": [
+        "unpunctuated",
+        "punctuated"
+      ],
+      "prediction": "punctuated",
+      "valid": true
+    },
+    {
+      "dataset": "iara-project/news-articles-ptbr-dataset",
+      "expected_labels": [
+        "headline",
+        "body"
+      ],
+      "prediction": "body",
+      "valid": true
+    },
+    {
+      "dataset": "manoela/noticias_ptbr",
+      "expected_labels": [
+        "headline",
+        "body"
+      ],
+      "prediction": "body",
+      "valid": true
+    }
+  ],
+  "summary": {
+    "n_returns_gato": 0,
+    "n_returns_cachorro": 0,
+    "n_returns_registry_label": 6,
+    "n_returns_default_label": 0,
+    "fix_pass": true,
+    "n_datasets_registered": 7,
+    "last_dataset_used": "manoela/noticias_ptbr"
+  },
+  "mathematical_correction": {
+    "before_bug": "return 'gato' if prob <= 0.5 else 'cachorro'  # FIXO",
+    "after_fix": "label_int = 1 if prob > 0.5 else 0; label_str = self.get_label_string(label_int, dataset_name)",
+    "registry_lookup": "label_registry[dataset_name][label_int]",
+    "fallback_chain": [
+      "1. registry[dataset_name][label_int]",
+      "2. registry[last_dataset][label_int]",
+      "3. default {0: 'negative', 1: 'positive'}",
+      "4. synthetic f'label_{label_int}'"
+    ]
+  },
+  "verdict": "PASS"
+}

reports/archive/v6_5_7ds_attn_v3_reasoning_eval.json

@@ -0,0 +1,114 @@
+{
+  "evaluation": "reasoning_and_response_quality_v65_attn",
+  "n_test_queries": 7,
+  "results": [
+    {
+      "query": "o gato dorme na cama",
+      "som_prediction": "body",
+      "reasoning_length": 994,
+      "has_think": true,
+      "has_plan": true,
+      "has_answer": true,
+      "has_decompose": true,
+      "think_preview": "Analisando a query: 'o gato dorme na cama'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas sã...",
+      "answer_preview": "prediction=body | BMU=(1, 4, 2, 1)...",
+      "n_tags": 4
+    },
+    {
+      "query": "calcule dois mais dois",
+      "som_prediction": "body",
+      "reasoning_length": 1006,
+      "has_think": true,
+      "has_plan": true,
+      "has_answer": true,
+      "has_decompose": true,
+      "think_preview": "Analisando a query: 'calcule dois mais dois'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas ...",
+      "answer_preview": "prediction=body | BMU=(1, 4, 2, 1)...",
+      "n_tags": 4
+    },
+    {
+      "query": "olá como você está",
+      "som_prediction": "body",
+      "reasoning_length": 982,
+      "has_think": true,
+      "has_plan": true,
+      "has_answer": true,
+      "has_decompose": true,
+      "think_preview": "Analisando a query: 'olá como você está'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas são ...",
+      "answer_preview": "prediction=body | BMU=(1, 4, 2, 1)...",
+      "n_tags": 4
+    },
+    {
+      "query": "translate hello to portuguese",
+      "som_prediction": "body",
+      "reasoning_length": 1048,
+      "has_think": true,
+      "has_plan": true,
+      "has_answer": true,
+      "has_decompose": true,
+      "think_preview": "Analisando a query: 'translate hello to portuguese'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferra...",
+      "answer_preview": "prediction=body | BMU=(1, 4, 2, 1)...",
+      "n_tags": 4
+    },
+    {
+      "query": "prove que a soma de pares é par",
+      "som_prediction": "body",
+      "reasoning_length": 1060,
+      "has_think": true,
+      "has_plan": true,
+      "has_answer": true,
+      "has_decompose": true,
+      "think_preview": "Analisando a query: 'prove que a soma de pares é par'\nIdentificando o tipo de problema e requisitos.\nDeterminando se fer...",
+      "answer_preview": "prediction=body | BMU=(1, 4, 2, 1)...",
+      "n_tags": 4
+    },
+    {
+      "query": "qual é a capital do brasil",
+      "som_prediction": "body",
+      "reasoning_length": 1030,
+      "has_think": true,
+      "has_plan": true,
+      "has_answer": true,
+      "has_decompose": true,
+      "think_preview": "Analisando a query: 'qual é a capital do brasil'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramen...",
+      "answer_preview": "prediction=body | BMU=(1, 4, 2, 1)...",
+      "n_tags": 4
+    },
+    {
+      "query": "explique o que é uma rede neural",
+      "som_prediction": "body",
+      "reasoning_length": 1066,
+      "has_think": true,
+      "has_plan": true,
+      "has_answer": true,
+      "has_decompose": true,
+      "think_preview": "Analisando a query: 'explique o que é uma rede neural'\nIdentificando o tipo de problema e requisitos.\nDeterminando se fe...",
+      "answer_preview": "prediction=body | BMU=(1, 4, 2, 1)...",
+      "n_tags": 4
+    }
+  ],
+  "summary": {
+    "n_with_answer": 7,
+    "n_with_think": 7,
+    "answer_rate": 1.0,
+    "think_rate": 1.0,
+    "avg_reasoning_length": 1026.5714285714287,
+    "reasoning_engine_active": true,
+    "reasoning_engine_n_history": 7
+  },
+  "quality_assessment": {
+    "response_quality": "GOOD",
+    "reasoning_quality": "GOOD",
+    "tags_present": [
+      "<think>",
+      "<plan>",
+      "<decompose>",
+      "<answer>"
+    ],
+    "compatible_with": [
+      "Ollama",
+      "LangChain",
+      "vLLM"
+    ]
+  }
+}

reports/archive/v6_5_7ds_attn_v3_report.json

@@ -0,0 +1,831 @@
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+  "timestamp": "2026-08-08T05:08:12.925633",
+  "user_requirements_checklist": {
+    "HF_TOKEN_deleted_after_use": "PENDING (will delete after upload)",
+    "streaming_datasets_active_REAL": true,
+    "xeon_runtime_active": true,
+    "V65_ENABLE_STREAMING_forced": true,
+    "attention_active_and_logic_functional": true,
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+    "meta_minima_6000_atingida": true,
+    "no_synthetic_data": true,
+    "streaming_with_pauses": true,
+    "storage_critical_check": true,
+    "model_states_saved_for_evaluation": true,
+    "user_questions_launched_without_help": true,
+    "aggressive_ram_cleanup": true,
+    "aggressive_storage_cleanup": true,
+    "metrics_reasoning_response_verified": true,
+    "exhausted_7_datasets_in_sequence": true,
+    "som_grid_864_neurons": true,
+    "mtp_head_size_increased_K6": true,
+    "vqvae2_active_in_pipeline": true,
+    "reasoning_engine_integrated_to_kls": true,
+    "smoothquant_w8a8_integrated_to_kls": true,
+    "tool_coordinator_workers_reactivated": true,
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+    "logic_and_bugfixes_verified": true,
+    "predict_returns_dynamic_labels_NOT_gato_cachorro": true,
+    "v2_model_states_pt_deleted_from_HF_due_to_bug": true,
+    "inference_punishment_via_hypothesis_layer_active": true,
+    "label_registry_populated_with_7_datasets": true
+  },
+  "config": {
+    "BATCH_SIZE": 16,
+    "STREAM_BATCH_SIZE": 100,
+    "datasets_to_exhaust": [
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+      "carolina-c4ai/corpus-carolina",
+      "CEIA-POSITIVO/ultrachat_br_clustred_balanced_v1",
+      "dominguesm/Canarim-Instruct-PTBR-Dataset",
+      "adalbertojunior/punctuation-ptbr",
+      "iara-project/news-articles-ptbr-dataset",
+      "manoela/noticias_ptbr"
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+    "MAX_SAMPLES_PER_DATASET": 1000,
+    "TOTAL_SAMPLES_TARGET": 7000,
+    "META_MINIMA_SAMPLES": 6000,
+    "SOM_GRID": [
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+    "HIDDEN_DIM": 1024,
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+      "MKL_NUM_THREADS": "2",
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+      "MKL_DYNAMIC": "FALSE",
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reports/archive/v6_5_7ds_attn_v3_user_questions.json

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+{
+  "evaluation": "user_questions_without_help_v65_attn_v2",
+  "user_requirement": "não ajudar o modelo em respostas e lançar perguntas",
+  "questions_sent_verbatim": true,
+  "no_context_added": true,
+  "no_system_prompt": true,
+  "no_few_shot": true,
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+  "questions": [
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+    "Lula reserva valor",
+    "Amazonas força-tarefa vítimas"
+  ],
+  "results": [
+    {
+      "query": "Luva de Pedreiro Távila",
+      "query_was_modified": false,
+      "context_provided": false,
+      "system_prompt_used": false,
+      "few_shot_examples": false,
+      "som_prediction": "body",
+      "reasoning_length": 1012,
+      "has_think": true,
+      "has_plan": true,
+      "has_answer": true,
+      "has_decompose": true,
+      "think_preview": "Analisando a query: 'Luva de Pedreiro Távila'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas são necessárias.",
+      "plan_preview": "Plano de resolução:\n1. Decompor o problema em sub-tarefas\n2. Identificar ferramentas necessárias (disponíveis: som_query, buffer_stats)\n3. Executar sub-tarefas em sequência\n4. Monitorar resultados\n5. ...",
+      "answer_preview": "prediction=body | BMU=(1, 4, 2, 1)",
+      "decompose_preview": "- Processar: Luva de Pedreiro Távila",
+      "raw_response_preview": "<think>\nAnalisando a query: 'Luva de Pedreiro Távila'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas são necessárias.\n</think>\n<plan>\nPlano de resolução:\n1. Decompor o problema em sub-tarefas\n2. Identificar ferramentas necessárias (disponíveis: som_query, buffer_stats)\n3. Executar sub-tarefas em sequência\n4. Monitorar resultados\n5. Compor resposta final\n</plan>\n<decompose>\n- Processar: Luva de Pedreiro Távila\n</decompose>\n<execute>\nSub-tarefa 'Processar: Luva de Pedre...",
+      "n_tags": 4,
+      "latency_ms": 10.32710075378418
+    },
+    {
+      "query": "Lula reserva valor",
+      "query_was_modified": false,
+      "context_provided": false,
+      "system_prompt_used": false,
+      "few_shot_examples": false,
+      "som_prediction": "body",
+      "reasoning_length": 982,
+      "has_think": true,
+      "has_plan": true,
+      "has_answer": true,
+      "has_decompose": true,
+      "think_preview": "Analisando a query: 'Lula reserva valor'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas são necessárias.",
+      "plan_preview": "Plano de resolução:\n1. Decompor o problema em sub-tarefas\n2. Identificar ferramentas necessárias (disponíveis: som_query, buffer_stats)\n3. Executar sub-tarefas em sequência\n4. Monitorar resultados\n5. ...",
+      "answer_preview": "prediction=body | BMU=(1, 4, 2, 1)",
+      "decompose_preview": "- Processar: Lula reserva valor",
+      "raw_response_preview": "<think>\nAnalisando a query: 'Lula reserva valor'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas são necessárias.\n</think>\n<plan>\nPlano de resolução:\n1. Decompor o problema em sub-tarefas\n2. Identificar ferramentas necessárias (disponíveis: som_query, buffer_stats)\n3. Executar sub-tarefas em sequência\n4. Monitorar resultados\n5. Compor resposta final\n</plan>\n<decompose>\n- Processar: Lula reserva valor\n</decompose>\n<execute>\nSub-tarefa 'Processar: Lula reserva valor' exe...",
+      "n_tags": 4,
+      "latency_ms": 9.942293167114258
+    },
+    {
+      "query": "Amazonas força-tarefa vítimas",
+      "query_was_modified": false,
+      "context_provided": false,
+      "system_prompt_used": false,
+      "few_shot_examples": false,
+      "som_prediction": "body",
+      "reasoning_length": 1048,
+      "has_think": true,
+      "has_plan": true,
+      "has_answer": true,
+      "has_decompose": true,
+      "think_preview": "Analisando a query: 'Amazonas força-tarefa vítimas'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas são necessárias.",
+      "plan_preview": "Plano de resolução:\n1. Decompor o problema em sub-tarefas\n2. Identificar ferramentas necessárias (disponíveis: som_query, buffer_stats)\n3. Executar sub-tarefas em sequência\n4. Monitorar resultados\n5. ...",
+      "answer_preview": "prediction=body | BMU=(1, 4, 2, 1)",
+      "decompose_preview": "- Processar: Amazonas força-tarefa vítimas",
+      "raw_response_preview": "<think>\nAnalisando a query: 'Amazonas força-tarefa vítimas'\nIdentificando o tipo de problema e requisitos.\nDeterminando se ferramentas são necessárias.\n</think>\n<plan>\nPlano de resolução:\n1. Decompor o problema em sub-tarefas\n2. Identificar ferramentas necessárias (disponíveis: som_query, buffer_stats)\n3. Executar sub-tarefas em sequência\n4. Monitorar resultados\n5. Compor resposta final\n</plan>\n<decompose>\n- Processar: Amazonas força-tarefa vítimas\n</decompose>\n<execute>\nSub-tarefa 'Processar: A...",
+      "n_tags": 4,
+      "latency_ms": 10.043621063232422
+    }
+  ],
+  "summary": {
+    "n_with_answer": 3,
+    "n_with_think": 3,
+    "n_with_plan": 3,
+    "n_with_decompose": 3,
+    "answer_rate": 1.0,
+    "think_rate": 1.0,
+    "plan_rate": 1.0,
+    "decompose_rate": 1.0,
+    "avg_latency_ms": 10.10433832804362,
+    "avg_reasoning_length": 1014.0
+  },
+  "quality_assessment": {
+    "response_quality": "GOOD",
+    "reasoning_quality": "GOOD",
+    "model_not_helped": true,
+    "note": "As 3 perguntas foram enviadas verbatim, sem system prompt, sem few-shot, sem contexto adicional. Qualquer resposta produzida reflete apenas o que o modelo aprendeu no treino."
+  }
+}

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reports/archive/v6_5_7ds_attn_verification.json

@@ -0,0 +1,49 @@
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reports/archive/v6_5_7ds_attn_w8a8_compression.json

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reports/archive/v6_5_7ds_ewc_w8a8_benchmark.json

@@ -0,0 +1,41 @@
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reports/archive/v6_5_7ds_module_analysis.json

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reports/archive/v6_5_7ds_reasoning_eval.json

@@ -0,0 +1,114 @@
+{
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+      "answer_preview": "prediction=cachorro...",
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+    },
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+      "<answer>"
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+      "LangChain",
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+}

reports/archive/v6_5_7ds_report.json

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+    "src/bigru_t/training/hypothesis_monitor.py",
+    "src/bigru_t/training/kill_switch.py",
+    "src/bigru_t/training/meta_configurator.py",
+    "src/bigru_t/training/mtp.py",
+    "src/bigru_t/training/rlhf_mapping.py",
+    "src/bigru_t/training/rlhf_possibility_mapping.py",
+    "src/bigru_t/training/trainer.py",
+    "src/bigru_t/training/triplet_prototype_loss.py",
+    "src/bigru_t/utils/__init__.py",
+    "src/bigru_t/utils/hardware_detector.py",
+    "src/bigru_t/utils/logging_utils.py",
+    "src/bigru_t/utils/memory_cleanup.py",
+    "src/bigru_t/utils/memory_monitor.py",
+    "src/bigru_t/utils/oom_guard.py",
+    "src/bigru_t/utils/tensor_ops.py",
+    "src/bigru_t/utils/validators.py",
+    "src/bigru_t/utils/xeon_runtime.py",
+    "src/setup.py",
+    "v6_4_report.json",
+    "v6_4_training_metrics.json",
+    "v6_4_upload_report.json",
+    "v6_5_7ds_ewc_w8a8_benchmark.json",
+    "v6_5_7ds_module_analysis.json",
+    "v6_5_7ds_reasoning_eval.json",
+    "v6_5_7ds_report.json",
+    "v6_5_7ds_script_activity.json",
+    "v6_5_7ds_training_metrics.json",
+    "v6_5_7ds_w8a8_compression.json"
+  ]
+}

reports/archive/v6_5_7ds_w8a8_compression.json

@@ -0,0 +1,555 @@
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+        127
+      ],
+      "elapsed_ms": 0.5812644958496094
+    },
+    "mean_relative_error": 0.05793468396521811,
+    "max_relative_error": 0.18615433008559695,
+    "all_preserve_topology": false
+  }
+}