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a1365f7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 | from __future__ import annotations
import asyncio
import hashlib
import os
import time
from datetime import datetime
from typing import Dict, Any
from src.cognition.curriculum import CurriculumManager, CurriculumTask
from src.memory.ledger import QuantumResistantLedger
from src.engine.validator import ArtifactValidator
from src.cognition._constants import logger
from src.core.lfm_controller import LFMController
class QuadruflowOrchestrator:
"""The Neurosynthetic Quadruflow Engine implementing four discrete cognitive flows."""
def __init__(self, random_seed: int | None = None):
logger.info("Initializing Quadruflow Engine Core...")
self.curriculum = CurriculumManager(random_seed=random_seed)
self.ledger = QuantumResistantLedger()
self.validator = ArtifactValidator()
candidates = [
os.path.expanduser("~/.vitalis/models/Llama-3.2-3B-Instruct-Q4_K_M.gguf"),
os.path.expanduser("~/.vitalis/models/LFM2.5-1.2B-Instruct-Q4_K_M.gguf"),
"Llama-3.2-3B-Instruct-Q4_K_M.gguf",
"LFM2.5-1.2B-Instruct-Q4_K_M.gguf",
]
model_path = ""
for c in candidates:
if os.path.exists(c):
model_path = c
break
if not model_path:
model_path = candidates[0]
logger.info("Wiring LFMController -> %s", model_path)
self.controller = LFMController(
model_path=model_path,
n_ctx=8192,
n_threads=6,
n_gpu_layers=-1,
)
if not self.ledger.verify_integrity():
raise SecurityError("Critical Error: Cryptographic ledger validation failed during boot sequence.")
logger.info("[Evaluation Ready] Core engine verified and integrated with evaluation hooks.")
def _normalize_val_report(self, v_out) -> dict:
if isinstance(v_out, dict):
return v_out
if isinstance(v_out, tuple) and len(v_out) == 2:
valid, reason = v_out
valid = bool(valid)
return {
"valid": valid,
"errors": [] if valid else [str(reason)],
"score_components": {
"schema": 1.0 if valid else 0.0,
"semantics": 1.0 if valid else 0.0,
"length": 1.0,
},
}
return {
"valid": getattr(v_out, "valid", False),
"errors": getattr(v_out, "errors", []),
"score_components": getattr(v_out, "score_components", {"schema": 0.0, "semantics": 0.0, "length": 0.0}),
}
def flow1_ingest(self, state: dict) -> dict:
if "task_id" not in state or "prompt" not in state:
raise ValueError("Schema validation failed: missing task_id or prompt")
return {
"task_id": str(state["task_id"]),
"prompt": str(state["prompt"]),
"expected_type": state.get("expected_type", "code"),
"provenance": "vitalis_devcore_ingest",
}
def flow2_simulate(self, state: dict, seed: int) -> dict:
formatted_prompt = f"<|im_start|>user\n{state['prompt']}<|im_end|>\n<|im_start|>assistant\n"
text = self.controller.execute_raw(formatted_prompt, max_tokens=256, temperature=0.0)
return {"text": text, "task_id": state["task_id"]}
def flow3_debug(self, candidate: dict, errors: list) -> tuple[dict, dict]:
repair_prompt = (
f"Fix the following errors in your previous output:\n"
f"Errors: {', '.join(errors)}\n"
f"Previous Output:\n{candidate['text']}"
)
return (
{"task_id": candidate["task_id"], "prompt": repair_prompt},
{"repair_prompt": repair_prompt, "previous_errors": errors},
)
def flow4_attest(self, candidate: dict, corrections: dict | None, val_report: dict, retries: int, runtime_ms: float, attested: bool, rejection_reason: str | None = None) -> dict:
det_hash = hashlib.sha256(candidate["text"].encode("utf-8")).hexdigest()
return {
"artifact_id": f"art_{candidate['task_id']}_{int(time.time())}",
"task_id": candidate["task_id"],
"result": {"output": candidate["text"]},
"validator": {
"valid": val_report.get("valid", False),
"errors": val_report.get("errors", []),
"score_components": val_report.get("score_components", {"schema": 0.0, "semantics": 0.0, "length": 0.0}),
},
"attestation": {
"hash": det_hash,
"signature": "<placeholder>",
"timestamp": datetime.utcnow().isoformat() + "Z",
"attested": attested,
},
"meta": {
"retries": retries,
"runtime_ms": int(runtime_ms),
"rejection_reason": rejection_reason,
},
}
def run_cognitive_cycle(self, task: CurriculumTask, seed: int) -> dict:
start_time = time.time()
initial_state = {
"task_id": task.task_id,
"prompt": getattr(task, "prompt", f"Complete task {task.task_id}"),
"expected_type": task.expected_type,
}
state = self.flow1_ingest(initial_state)
retries = 0
rejection_reason = None
candidate = {"text": "", "task_id": task.task_id}
corrections = None
val_report: dict = {
"valid": False,
"errors": [],
"score_components": {"schema": 0.0, "semantics": 0.0, "length": 0.0},
}
while retries <= 2:
candidate = self.flow2_simulate(state, seed)
v_out = self.validator.validate(candidate["text"])
val_report = self._normalize_val_report(v_out)
if val_report.get("valid"):
break
retries += 1
if retries <= 2:
state, corrections = self.flow3_debug(candidate, val_report.get("errors", []))
else:
rejection_reason = "Max retries exceeded without valid artifact"
runtime_ms = (time.time() - start_time) * 1000
attested = val_report.get("valid", False) and (rejection_reason is None)
artifact = self.flow4_attest(candidate, corrections, val_report, min(retries, 2), runtime_ms, attested, rejection_reason)
sc = val_report.get("score_components", {"schema": 0.0, "semantics": 0.0, "length": 0.0})
risk = (
0.5 * (1.0 - sc.get("schema", 0.0))
+ 0.3 * (1.0 - sc.get("semantics", 0.0))
+ 0.2 * (min(retries, 2) / 2.0)
)
metrics_payload = (
f"status={'SUCCESS' if attested else 'REJECTED'}"
f"|risk={round(risk, 4)}"
f"|duration={int(runtime_ms)}"
f"|attested={str(attested).lower()}"
f"|rejection_reason={rejection_reason}"
)
block = self.ledger.append_record(task_id=task.task_id, outcome_metrics=metrics_payload)
artifact["attestation"]["signature"] = getattr(block, "signature", "<placeholder>")
self.curriculum.record_result(success=attested, risk_encountered=risk)
return artifact
async def execute_closed_loop_cycle(self) -> Dict[str, Any]:
task: CurriculumTask = self.curriculum.generate_next_task()
logger.info("Executing Task Channel: %s [Tier %d]", task.task_id, task.tier)
loop = asyncio.get_running_loop()
try:
artifact = await loop.run_in_executor(None, lambda: self.run_cognitive_cycle(task, 42))
success = artifact["attestation"]["attested"]
sig = artifact["attestation"]["signature"]
block_idx = artifact.get("ledger_block_index", 1)
except Exception as err:
logger.error("Execution exception encountered on %s: %s", task.task_id, str(err))
block = self.ledger.append_record(
task_id=task.task_id,
outcome_metrics="status=CRASHED|risk=1.0|duration=0|attested=false|rejection_reason=catastrophic_failure",
)
success = False
sig = getattr(block, "signature", "<placeholder>")
block_idx = getattr(block, "index", 1)
return {
"task_id": task.task_id,
"success": success,
"ledger_block_index": block_idx,
"ledger_signature": sig,
"curriculum_state": self.curriculum.export_state(),
}
def verify_system_health(self) -> bool:
return self.ledger.verify_integrity()
def shutdown(self) -> None:
self.controller.shutdown()
class SecurityError(Exception):
"""Raised when cryptographic data structures show validation failures."""
|