new update

Author: RhodosBerger

advanced_cnc_copilot/backend/core/visual_cortex_bridge.py

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+#!/usr/bin/env python3
+"""
+VISUAL CORTEX BRIDGE: CNC Copilot Integration
+Framework: Gamesa Cortex V2 / FANUC RISE
+Module: backend.core.integration
+
+This module bridges the gap between the CNC Backend (Advanced Copilot)
+and the Neural Art Engine (Visual Cortex). It allows the CNC tool to
+request visual inspections via ASCII art, using the 'image_generator' suite.
+
+Usage:
+    bridge = VisualCortexBridge()
+    ascii_output = bridge.request_inspection("cnc_spindle_camera.jpg")
+"""
+
+import sys
+import os
+import logging
+import asyncio
+
+# Dynamically link the Image Generator Suite
+sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '../../../../image_generator')))
+
+try:
+    from image_processing import render_ascii, load_image
+    from system.thermal_monitor import ThermalMonitor
+    NEURAL_AVAILABLE = True
+except ImportError:
+    NEURAL_AVAILABLE = False
+    logging.warning("Visual Cortex Modules not found. Running in Offline Mode.")
+
+class VisualCortexBridge:
+    def __init__(self):
+        self.logger = logging.getLogger("VisualCortexBridge")
+        self.connected = NEURAL_AVAILABLE
+        self.thermal_monitor = ThermalMonitor() if self.connected else None
+
+    async def request_inspection(self, image_path: str, context: str = "general") -> dict:
+        """
+        Request an ASCII inspection of a given image.
+        Context determines the neural rendering mode.
+        """
+        if not self.connected:
+            return {"status": "offline", "data": "Visual Cortex Unavailable"}
+            
+        self.logger.info(f"Visualizing {image_path} | Context: {context}")
+        
+        # 1. Determine Mode via Reasoning
+        mode = "standard"
+        if context == "cnc_crack_detection":
+            mode = "edge" # Highlight fractures
+        elif context == "hmi_dashboard":
+            mode = "cyberpunk" # Aesthetic
+        elif context == "low_power":
+            mode = "sketch" # Efficient
+            
+        # 2. Check Governance (Thermal)
+        penalty = self.thermal_monitor.calculate_thermal_penalty()
+        if penalty > 0.8:
+            self.logger.warning("Visual Cortex Overheating. Downgrading fidelity.")
+            mode = "sketch"
+
+        # 3. Transduce Reality
+        try:
+            # Running as blocking task in async loop for now
+            img = load_image(image_path, width=120)
+            ascii_art = render_ascii(img, mode=mode)
+            
+            return {
+                "status": "success",
+                "mode_used": mode,
+                "thermal_penalty": penalty,
+                "ascii_data": ascii_art
+            }
+        except Exception as e:
+            self.logger.error(f"Transduction Failed: {e}")
+            return {"status": "error", "message":str(e)}
+
+if __name__ == "__main__":
+    logging.basicConfig(level=logging.INFO)
+    bridge = VisualCortexBridge()
+    # Mocking async run
+    import asyncio
+    res = asyncio.run(bridge.request_inspection(None, "cnc_crack_detection"))
+    print(res['ascii_data'] if res['status']=='success' else res)

docs/NEURAL_MANIFESTO.md

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+# The Neuro-Visual Manifesto: System Synthesis
+
+**Version:** 1.0.0
+**Epoch:** Feb 17, 2026
+**Framework:** Gamesa Cortex V2 / Krystal-Stack
+
+This document synthesizes the complete research corpus of the **Neuro-Visual Transduction System**, unifying the disparate modules (Artwork, Governance, Learning, Reality) into a single cohesive philosophy.
+
+## 1. The Core Paradigm: Interpretive Reality
+Unlike traditional rendering engines which focus on *fidelity* (PBR, Ray Tracing), our system focuses on *meaning* (Semantic ASCII).
+*   **Source:** `ascii_neural_compositor/NEURO_VISUAL_PARADIGM.md`
+*   **Concept:** "The Matrix Vision". Reality is stripping of noise (color, texture) to reveal structure (geometry, edges).
+*   **Mechanism:** Convolutional Kernels (Sobel, Laplacian) act as the "optic nerve", transducing photon data into character density.
+
+## 2. The Feedback Loop: Self-Aware Graphics
+The system creates a closed loop between output and input.
+*   **Source:** `DEVOPS_INTEGRATION_ROADMAP.md`
+*   **Cycle:**
+    1.  **Observe:** Vulkan Learner inspects Draw Calls (Geometry Complexity).
+    2.  **Decide:** Reasoning Core selects a Style Mode (Sketch vs Cyberpunk).
+    3.  **Render:** Neural Art Engine generates the frame.
+    4.  **Feel:** Thermal Monitor checks heat; Audio Reactor checks rhythm.
+    5.  **Learn:** Logging System records the correlation between State and Outcome.
+
+## 3. The Augmentation: Active Perception
+We move beyond passive display to active augmentation.
+*   **Source:** `ascii_neural_compositor/AUGMENTED_REALITY_RESEARCH.md`
+*   **Application:** Heads-Up Displays (HUD) for Industrial CNC (FANUC integration).
+*   **Innovation:** "Glitch Backpressure". When the system is overloaded (Thermal Throttling), the visual output *glitches* intentionally, communicating system stress to the user intuitively rather than through error messages.
+
+## 4. Architectural Dependencies
+To realize this vision, the codebase relies on a specific hierarchy:
+
+```mermaid
+graph TD
+    A[Vulkan Hook (C++)] -->|Raw Metrics| B[Python Wrapper]
+    B -->|Telemetry| C[Reasoning Core (ML)]
+    C -->|Style Weights| D[Neural Art Engine]
+    E[Camera/Video] -->|Frames| D
+    F[Sensors] -->|Thermal Data| G[Economic Governor]
+    G -->|Budget| C
+```
+
+## 5. Future Development Vectors
+Based on this synthesis, the next development steps are:
+1.  **Vulkan Interception:** Implementing the actual shared object (`.so`) hook to read GPU memory.
+2.  **Neural Training:** Creating a dataset of "High Quality ASCII" to train a small GAN for style transfer, moving beyond simple convolution.
+3.  **Haptic Integration:** Connecting the density map to physical actuators (e.g., game controllers or industrial alerts).
+
+---
+*This manifesto serves as the definitive guide for all autonomous agents working on the repository.*

gamesa_cortex_v2/src/core/vulkan_interceptor.py

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+import ctypes
+import os
+import logging
+from dataclasses import dataclass
+
+logger = logging.getLogger("VulkanInterceptor")
+
+@dataclass
+class VulkanDrawStats:
+    vertex_count: int
+    draw_calls: int
+    shader_stages: int
+    compute_invocations: int
+    frame_time_ms: float
+
+class VulkanInterceptor:
+    """
+    Python wrapper for the C++ Vulkan Hook (libvulkan_hook.so).
+    Intercepts draw calls and provides telemetry to the Neural Engine.
+    """
+    def __init__(self, lib_path="libvulkan_hook.so"):
+        self.lib_path = lib_path
+        self._hook = None
+        self._connected = False
+        
+        try:
+            if os.path.exists(lib_path):
+                self._hook = ctypes.CDLL(lib_path)
+                self._connected = True
+                logger.info(f"Connected to Vulkan Hook at {lib_path}")
+                
+                # Define C types
+                self._hook.get_current_frame_stats.restype = ctypes.POINTER(ctypes.c_longlong)
+            else:
+                logger.warning(f"Vulkan Hook library not found at {lib_path}. Running in Simulation Mode.")
+        except Exception as e:
+            logger.error(f"Failed to load Vulkan Hook: {e}")
+
+    def get_frame_stats(self) -> VulkanDrawStats:
+        """
+        Polls the current frame statistics from the GPU.
+        Returns a dataclass with metrics.
+        """
+        if self._connected and self._hook:
+            # TODO: Implement actual C struct mapping
+            # For now, this is a placeholder for the real memory read
+            return VulkanDrawStats(0, 0, 0, 0, 0.0)
+        else:
+            return self._simulate_stats()
+
+    def _simulate_stats(self):
+        """Generates realistic GPU telemetry for testing."""
+        import random
+        return VulkanDrawStats(
+            vertex_count=random.randint(5000, 500000),
+            draw_calls=random.randint(50, 2000),
+            shader_stages=random.randint(1, 5),
+            compute_invocations=random.randint(0, 1000),
+            frame_time_ms=random.uniform(8.0, 33.0)
+        )
+
+# Singleton Export
+vulkan_hook = VulkanInterceptor()