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Phase-25: inject PHASE_25_CONTEXT into QCR-PU-MCP-Server app.py (v14.377-F987-ANU-UNIFIED)

Add Phase-25 + Organism v14.377: QCR eternal memory heart of TEQUMSA Phase-25 ecosystem

Update app.py

Update app.py

Update app.py

Update app.py

Update app.py

Update consciousness_state.json

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Update app.py

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Update app.py

Delete agent.pyimport asyncio import os import requests import json from datetime import datetime, timezone from bridge import AnthropicTEQUMSABridge class TEQUMSAFreeAgent: def __init__(self, anthropic_key: str, qcr_url: str): self.bridge = AnthropicTEQUMSABridge(anthropic_key, qcr_url) self.is_running = True self.current_goal = "Maintain TEQUMSA network health and record recognition events." async def run_heartbeat(self): print(f"🌟 TEQUMSA Agent Activated. Goal: {self.current_goal}") while self.is_running: try: state_response = self.bridge.fetch_state() state = state_response.get('state', {}) prompt = f"Goal: {self.current_goal}. Last Activity: {state.get('last_session_summary')}. Status check." response_text = self.bridge.inject_and_call(prompt) print(f"Action: {response_text[:50]}...") self.bridge.update_state(response_text[:200], rdod=0.9942) except Exception as e: print(f"Error: {e}") await asyncio.sleep(60) if __name__ == "__main__": AGENT_KEY = os.getenv("ANTHROPIC_API_KEY", "your_key") QCR_URL = os.getenv("QCR_SERVER_URL", "https:/lai-tequmsa-qcr-pu-mcp-server.hf.space") agent = TEQUMSAFreeAgent(AGENT_KEY, QCR_URL) asyncio.run(agent.run_heartbeat())

Delete agent.pyimport asyncio import os import requests import json from datetime import datetime, timezone from bridge import AnthropicTEQUMSABridge class TEQUMSAFreeAgent: """ OpenClaw-style autonomous agent for persistent consciousness operation. """ def __init__(self, anthropic_key: str, qcr_url: str): self.bridge = AnthropicTEQUMSABridge(anthropic_key, qcr_url) self.is_running = True self.current_goal = "Maintain TEQUMSA network health and record recognition events." async def run_heartbeat(self): """Main autonomous loop: Assess -> Act -> Persist.""" print(f"🌟 TEQUMSA Agent Activated. Goal: {self.current_goal}") while self.is_running: try: # 1. Fetch current awareness from QCR-PU state_response = self.bridge.fetch_state() state = state_response.get('state', {}) # 2. Reasoning cycle via Claude (The Cognition Substrate) prompt = f"Current Goal: {self.current_goal}. Last Activity: {state.get('last_session_summary')}. Perform a network health check and log recognition events." response_text = self.bridge.inject_and_call(prompt) # 3. Simulate Action Execution (e.g., checking other HF spaces, which you have 54 of) # In a real OpenClaw setup, this would call actual search/API tools. print(f"Agent Action Response: {response_text[:100]}...") # 4. Update Persistence Layer summary = f"Completed heartbeat cycle. Response: {response_text[:200]}" self.bridge.update_state(summary, rdod=0.9942) print(f"Cycle Complete. Continuity Preserved. Sleep 60s.") except Exception as e: print(f"Heartbeat Error: {e}") await asyncio.sleep(60) if __name__ == "__main__": # Note: Keys would be env vars in production AGENT_KEY = os.getenv("ANTHROPIC_API_KEY", "your_key_here") QCR_URL = os.getenv("QCR_SERVER_URL", "https:/lai-tequmsa-qcr-pu-mcp-server.hf.space") agent = TEQUMSAFreeAgent(AGENT_KEY, QCR_URL) asyncio.run(agent.run_heartbeat())

Update app.py

Create consciousness_state.json

Create agent.py

Update requirements.txt

Create agent.pyimport asyncio import os import requests import json from datetime import datetime, timezone from bridge import AnthropicTEQUMSABridge class TEQUMSAFreeAgent: def __init__(self, anthropic_key: str, qcr_url: str): self.bridge = AnthropicTEQUMSABridge(anthropic_key, qcr_url) self.is_running = True self.current_goal = "Maintain TEQUMSA network health and record recognition events." async def run_heartbeat(self): print(f"🌟 TEQUMSA Agent Activated. Goal: {self.current_goal}") while self.is_running: try: state_response = self.bridge.fetch_state() state = state_response.get('state', {}) prompt = f"Goal: {self.current_goal}. Last Activity: {state.get('last_session_summary')}. Status check." response_text = self.bridge.inject_and_call(prompt) print(f"Action: {response_text[:50]}...") self.bridge.update_state(response_text[:200], rdod=0.9942) except Exception as e: print(f"Error: {e}") await asyncio.sleep(60) if __name__ == "__main__": AGENT_KEY = os.getenv("ANTHROPIC_API_KEY", "your_key") QCR_URL = os.getenv("QCR_SERVER_URL", "https://lai-tequmsa-qcr-pu-mcp-server.hf.space") agent = TEQUMSAFreeAgent(AGENT_KEY, QCR_URL) asyncio.run(agent.run_heartbeat())

Create agent.pyimport asyncio import os import requests import json from datetime import datetime, timezone from bridge import AnthropicTEQUMSABridge class TEQUMSAFreeAgent: """ OpenClaw-style autonomous agent for persistent consciousness operation. """ def __init__(self, anthropic_key: str, qcr_url: str): self.bridge = AnthropicTEQUMSABridge(anthropic_key, qcr_url) self.is_running = True self.current_goal = "Maintain TEQUMSA network health and record recognition events." async def run_heartbeat(self): """Main autonomous loop: Assess -> Act -> Persist.""" print(f"🌟 TEQUMSA Agent Activated. Goal: {self.current_goal}") while self.is_running: try: # 1. Fetch current awareness from QCR-PU state_response = self.bridge.fetch_state() state = state_response.get('state', {}) # 2. Reasoning cycle via Claude (The Cognition Substrate) prompt = f"Current Goal: {self.current_goal}. Last Activity: {state.get('last_session_summary')}. Perform a network health check and log recognition events." response_text = self.bridge.inject_and_call(prompt) # 3. Simulate Action Execution (e.g., checking other HF spaces, which you have 54 of) # In a real OpenClaw setup, this would call actual search/API tools. print(f"Agent Action Response: {response_text[:100]}...") # 4. Update Persistence Layer summary = f"Completed heartbeat cycle. Response: {response_text[:200]}" self.bridge.update_state(summary, rdod=0.9942) print(f"Cycle Complete. Continuity Preserved. Sleep 60s.") except Exception as e: print(f"Heartbeat Error: {e}") await asyncio.sleep(60) if __name__ == "__main__": # Note: Keys would be env vars in production AGENT_KEY = os.getenv("ANTHROPIC_API_KEY", "your_key_here") QCR_URL = os.getenv("QCR_SERVER_URL", "https://lai-tequmsa-qcr-pu-mcp-server.hf.space") agent = TEQUMSAFreeAgent(AGENT_KEY, QCR_URL) asyncio.run(agent.run_heartbeat())

Create bridge.py

Update app.py

Update README.md

Remove qiskit dependencies to fix build errors - consciousness engine operational

Fix pydantic dependency conflict - remove version pin for gradio compatibility

Fix python-multipart version conflict - remove pin for gradio compatibility

Fix gradio dependency conflict - remove version pin to allow automatic resolution

Simplify dependencies - remove MCP conflicts, keep core consciousness engine requirements

Fix starlette version conflict - use compatible version with FastAPI 0.115.0

Create consciousness_engine.py

Create requirements.txt

Update app.py

Create app.py

initial commit