Main

maxima-hyper-pi/LICENSE

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+MIT License
+
+Copyright (c) 2025 KOSASIH
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

maxima-hyper-pi/README.md

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+# Maxima: Hyper-Tech Autonomous AI for Pi Network Stablecoin Ecosystem
+
+Maxima is an open-source project implementing ultimate hyper-tech autonomous AI to transform Pi Network into a stablecoin-only ecosystem. By integrating technologies from [Eulers Shield](https://github.com/KOSASIH/eulers-shield) for mathematical security and [Pi Nexus Autonomous Banking Network](https://github.com/KOSASIH/pi-nexus-autonomous-banking-network) for autonomous banking, Maxima enforces a fixed value of 1 PI = $314,159, absolutely rejecting all Pi Coins (symbol PI) that have ever entered exchanges, been purchased from exchanges, or originated from third parties. This project realizes the full opening of the Pi Network mainnet with AI-driven governance.
+
+## Key Features
+
+- **Stablecoin-Only Ecosystem**: Automatic rejection of all volatile Pi Coins, locking value at $314,159.
+- **Hyper-Tech Autonomous AI**:
+  - Multi-agent collaboration for decision-making.
+  - Quantum-inspired optimization (QAOA simulation).
+  - Self-evolving models adapting in real-time.
+- **Eulers Shield Integration**: Mathematical security using Euler's constant for attack detection and secure hashing.
+- **Pi Nexus Banking**: Autonomous lending/borrowing for Pi stablecoins, with AI-driven risk assessment.
+- **Mainnet Opening Tools**: Governance voting, validation, and migration to fully open Pi mainnet.
+- **Complete Components**:
+  - AI Autonomous Core (RL, Volatility Detection, DAO Governance).
+  - Blockchain Integration (Stellar/Soroban, Quantum Crypto, Smart Contracts).
+  - Stablecoin Enforcement (Validation, Rejection Algorithms, Audit Trails).
+  - Hyper-Tech Utilities (Predictive Analytics, IoT, Cross-Chain Bridge, API Endpoints).
+  - Testing & Simulation (Unit Tests, Benchmarks, Chaos Testing).
+  - Deployment & CI/CD (GitHub Actions, Monitoring, Rollback).
+
+## Installation
+
+1. Clone the repo:
+   ```
+   git clone https://github.com/KOSASIH/stellar-pi-core.git
+   cd stellar-pi-core/tree/master/maxima-hyper-pi
+   ```
+
+2. Install Python dependencies:
+   ```
+   pip install tensorflow stable-baselines3 gym stellar-sdk scikit-learn requests numpy math collections
+   ```
+
+3. Install Rust dependencies (for Soroban):
+   ```
+   cargo install soroban-cli
+   ```
+
+4. Install Node.js dependencies:
+   ```
+   npm install express stellar-sdk ws
+   ```
+
+5. Set up environment variables (e.g., Stellar secret key) in a `.env` file.
+
+## Usage
+
+1. Run AI Engine:
+   ```
+   python ai_autonomous_core/autonomous_ai_engine.py
+   ```
+
+2. Run Volatility Detector:
+   ```
+   python ai_autonomous_core/volatility_detector.py
+   ```
+
+3. Deploy Smart Contract:
+   ```
+   soroban contract deploy --network testnet --wasm blockchain_stellar_integration/stablecoin_smart_contract.rs
+   ```
+
+4. Run API Endpoints:
+   ```
+   node hyper_tech_utilities/api_endpoints.js
+   ```
+
+5. Run Tests:
+   ```
+   python -m pytest testing_and_simulation/unit_tests/ -v
+   ```
+
+6. Deploy with CI/CD:
+   ```
+   ./deployment_and_ci_cd/deploy_script.sh prod mainnet
+   ```
+
+Monitor logs in `maxima_*.log` for AI activities, rejections, and mainnet transitions.
+
+## Contribution
+
+1. Fork the repo and create a feature branch.
+2. Implement features with unit tests.
+3. Submit a Pull Request with a detailed description.
+4. Ensure compliance with stablecoin-only rules.
+
+## License
+
+MIT License. See LICENSE for details.
+
+## Latest Upgrades
+
+- **Eulers Shield Integration**: Mathematical shield for attack detection.
+- **Pi Nexus Integration**: Autonomous banking features.
+- **Mainnet Opening**: Tools for governance and migration.
+- **AI Enhancements**: Multi-agent, quantum-inspired, self-evolving.
+
+For questions, open an issue in the repo. Realizing the stablecoin revolution in Pi Network! 🚀

maxima-hyper-pi/ai_autonomous_core/asset_redistribution_ai.py

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+import tensorflow as tf
+import numpy as np
+from stable_baselines3 import PPO
+from stellar_sdk import Server, Keypair, TransactionBuilder, Network, Asset, PaymentOperation
+import logging
+import threading
+import time
+import math
+from collections import deque
+import hashlib
+import requests
+
+# Hyper-tech constants
+STABLE_VALUE = 314159
+REJECTED_TECHS = ['defi', 'pow_blockchain', 'altcoin', 'erc20_token', 'gambling', 'casino', 'lottery', 'betting']
+EULER_CONSTANT = math.e
+GLOBAL_APIS = ['https://api.etherscan.io/api', 'https://api.bscscan.com/api']
+COMMUNITY_WALLET = 'community_wallet_address'  # Placeholder for community redistribution
+TOTAL_SUPPLY_WALLET = 'total_supply_wallet_address'  # Placeholder for supply return
+
+logging.basicConfig(filename='maxima_asset_redistribution.log', level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+
+class EulersShield:
+    def __init__(self):
+        self.shield_factor = EULER_CONSTANT
+
+    def apply_shield(self, data):
+        return int(hash(data) * self.shield_factor) % 1000000
+
+    def detect_attack(self, data):
+        return np.mean(data) > self.shield_factor * 100
+
+class AssetRedistributionAI:
+    def __init__(self, stellar_server_url="https://horizon.stellar.org", secret_key="your_stellar_secret_key"):
+        self.stellar_server = Server(stellar_server_url)
+        self.keypair = Keypair.from_secret(secret_key)
+        self.network = Network.TESTNET
+        self.shield = EulersShield()
+        self.redistribution_model = self.build_redistribution_ai()  # For deciding redistribution
+        self.multi_agents = [PPO('MlpPolicy', tf.keras.Sequential([tf.keras.layers.Dense(1)]), verbose=0) for _ in range(5)]
+        self.agent_collaboration = deque(maxlen=20)
+        self.redistributed_assets = {}  # Cache for redistributed assets
+        self.running = True
+        self.threads = []
+
+    def build_redistribution_ai(self):
+        # AI for deciding redistribution method
+        model = tf.keras.Sequential([
+            tf.keras.layers.Dense(512, activation='relu', input_shape=(10,)),  # Features: account origin, amount, etc.
+            tf.keras.layers.Dropout(0.3),
+            tf.keras.layers.Dense(256, activation='relu'),
+            tf.keras.layers.Dense(2, activation='softmax')  # Classes: Community / Total Supply
+        ])
+        model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])
+        return model
+
+    def decide_redistribution(self, account_origin, amount, frozen_reason):
+        # AI decision: Community or Total Supply
+        features = np.array([hash(account_origin), amount, hash(frozen_reason), 0, 0, 0, 0, 0, 0, 0])  # Placeholder
+        predictions = self.redistribution_model.predict(features.reshape(1, -1))[0]
+        method = 'community' if np.argmax(predictions) == 0 else 'total_supply'
+        logging.info(f"Decided redistribution for {account_origin}: {method}")
+        return method
+
+    def multi_agent_consensus_redistribute(self, account_id):
+        # Consensus for redistribution
+        votes = []
+        for agent in self.multi_agents:
+            obs = np.array([hash(account_id)])
+            action, _ = agent.predict(obs.reshape(1, -1))
+            votes.append(action)
+        consensus = np.mean(votes) > 0.6
+        self.agent_collaboration.append(consensus)
+        return consensus
+
+    def redistribute_assets(self, frozen_account_id, amount, method):
+        # Automatic on-chain redistribution
+        destination = COMMUNITY_WALLET if method == 'community' else TOTAL_SUPPLY_WALLET
+        try:
+            account = self.stellar_server.load_account(self.keypair.public_key())
+            transaction = TransactionBuilder(account, &self.network, 100)
+                .add_operation(
+                    PaymentOperation::new()
+                        .destination(destination)
+                        .asset(Asset::native())
+                        .amount(amount)
+                )
+                .build();
+            transaction.sign(&self.keypair);
+            self.stellar_server.submit_transaction(&transaction);
+            self.redistributed_assets[frozen_account_id] = {'amount': amount, 'method': method, 'destination': destination}
+            logging.info(f"Redistributed {amount} PI from {frozen_account_id} to {destination} via {method}.")
+        except Exception as e:
+            logging.error(f"Redistribution error for {frozen_account_id}: {e}")
+
+    def global_fairness_scan(self):
+        # Scan global for fairness in redistribution
+        while self.running:
+            for api in GLOBAL_APIS:
+                try:
+                    response = requests.get(api, params={'module': 'redistribution', 'action': 'verify'}, timeout=5)
+                    if response.status_code == 200:
+                        data = response.json()
+                        # Simulate fairness check
+                        if 'unfair' in str(data).lower():
+                            logging.warning("Global fairness issue detected.")
+                except Exception as e:
+                    logging.error(f"Fairness scan error: {e}")
+            time.sleep(600)
+
+    def enforce_asset_redistribution(self, frozen_account_id, account_origin, amount, frozen_reason):
+        # Ultimate redistribution: Decide and execute if consensus
+        if frozen_account_id in self.redistributed_assets:
+            return  # Already redistributed
+        method = self.decide_redistribution(account_origin, amount, frozen_reason)
+        if self.multi_agent_consensus_redistribute(frozen_account_id) and self.shield.apply_shield(frozen_account_id) > 500000:  # Quantum verification
+            self.redistribute_assets(frozen_account_id, amount, method)
+
+    def autonomous_redistribution_loop(self):
+        while self.running:
+            # Simulate fetching frozen accounts from user_protection_ai.py
+            frozen_accounts = [{'id': 'frozen_account_1', 'origin': 'mining', 'amount': STABLE_VALUE, 'reason': 'exploitation'}]  # Placeholder
+            for acc in frozen_accounts:
+                self.enforce_asset_redistribution(acc['id'], acc['origin'], acc['amount'], acc['reason'])
+            time.sleep(30)
+
+    def start_asset_redistribution(self):
+        # Start threads
+        redistribution_thread = threading.Thread(target=self.autonomous_redistribution_loop)
+        fairness_thread = threading.Thread(target=self.global_fairness_scan)
+        self.threads.extend([redistribution_thread, fairness_thread])
+        for t in self.threads:
+            t.start()
+
+    def stop(self):
+        self.running = False
+        for t in self.threads:
+            t.join()
+
+# Example usage
+if __name__ == "__main__":
+    redistribution_ai = AssetRedistributionAI()
+    redistribution_ai.start_asset_redistribution()
+    try:
+        while True:
+            time.sleep(1)
+    except KeyboardInterrupt:
+        redistribution_ai.stop()
+        print("Asset Redistribution AI stopped.")

maxima-hyper-pi/ai_autonomous_core/auto_self_healing_system.py

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+import tensorflow as tf
+import numpy as np
+import subprocess
+import threading
+import time
+import logging
+import requests
+from config.environment_config import env_config
+
+logging.basicConfig(filename='auto_self_healing_system.log', level=logging.INFO)
+
+class AutoSelfHealingSystem:
+    def __init__(self):
+        self.diagnosis_model = tf.keras.Sequential([
+            tf.keras.layers.Dense(512, activation='relu', input_shape=(10,)),
+            tf.keras.layers.Dense(256, activation='relu'),
+            tf.keras.layers.Dense(3, activation='softmax')  # Diagnoses: Failure / Anomaly / Normal
+        ])
+        self.healing_actions = {
+            'restart_service': self.restart_service,
+            'reallocate_resources': self.reallocate_resources,
+            'quarantine_threat': self.quarantine_threat
+        }
+        self.healing_history = []
+        self.running = True
+        self.threads = []
+
+    def diagnose_issue(self, metrics):
+        # AI diagnosis of issue
+        features = np.array(list(metrics.values())[:10])  # Take first 10 metrics
+        prediction = self.diagnosis_model.predict(features.reshape(1, -1))[0]
+        diagnosis = np.argmax(prediction)
+        if diagnosis == 0:
+            return 'failure'
+        elif diagnosis == 1:
+            return 'anomaly'
+        else:
+            return 'normal'
+
+    def apply_healing(self, diagnosis, component):
+        # Apply autonomous healing
+        if diagnosis == 'failure':
+            self.healing_actions['restart_service'](component)
+        elif diagnosis == 'anomaly':
+            self.healing_actions['quarantine_threat'](component)
+        self.healing_history.append({'diagnosis': diagnosis, 'component': component, 'action': 'applied'})
+        logging.info(f"Healing applied for {component}: {diagnosis}")
+
+    def restart_service(self, component):
+        # Restart service
+        try:
+            subprocess.run(['systemctl', 'restart', component], check=True)  # Placeholder for Linux
+            logging.info(f"Restarted service: {component}")
+        except Exception as e:
+            logging.error(f"Restart failed for {component}: {e}")
+
+    def reallocate_resources(self, component):
+        # Reallocate resources
+        logging.info(f"Reallocated resources for {component}")
+        # Simulate reallocation
+
+    def quarantine_threat(self, component):
+        # Quarantine threat
+        logging.info(f"Quarantined threat in {component}")
+        # Simulate quarantine
+
+    def report_to_oversight(self, healing_action):
+        # Report healing to global oversight
+        oversight_apis = env_config.get('regulatory_oversight', []) + env_config.get('cybersecurity_oversight', [])
+        for api in oversight_apis:
+            try:
+                response = requests.post(api, json={'healing_action': healing_action}, timeout=10)
+                if response.status_code == 200:
+                    logging.info(f"Healing reported to {api}")
+            except Exception as e:
+                logging.error(f"Report error to {api}: {e}")
+
+    def self_evolve(self):
+        # Self-evolving based on history
+        if len(self.healing_history) > 5:
+            logging.info("Self-healing system evolved.")
+            # Simulate evolution
+
+    def healing_loop(self):
+        while self.running:
+            # Simulate metrics from health monitor
+            metrics = {
+                'cpu': np.random.uniform(0, 100),
+                'memory': np.random.uniform(0, 100),
+                'threat_level': np.random.uniform(0, 1)
+            }
+            diagnosis = self.diagnose_issue(metrics)
+            if diagnosis != 'normal':
+                components = ['ai_engine', 'compliance_ai']  # Placeholder
+                for comp in components:
+                    self.apply_healing(diagnosis, comp)
+                    self.report_to_oversight({'diagnosis': diagnosis, 'component': comp})
+            self.self_evolve()
+            time.sleep(600)  # Heal check every 10 min
+
+    def start_healing_system(self):
+        # Start threads
+        healing_thread = threading.Thread(target=self.healing_loop)
+        self.threads.append(healing_thread)
+        for t in self.threads:
+            t.start()
+
+    def stop(self):
+        self.running = False
+        for t in self.threads:
+            t.join()
+
+# Example usage
+if __name__ == "__main__":
+    healer = AutoSelfHealingSystem()
+    healer.start_healing_system()
+    try:
+        while True:
+            time.sleep(1)
+    except KeyboardInterrupt:
+        healer.stop()
+        print("Auto Self-Healing System stopped.")