Add HybridAgent and LivingEnvironment implementation

.github/scripts/MatrixXx.py

@@ -0,0 +1,154 @@
+import asyncio
+import logging
+from typing import Callable, Any, Dict, List
+import nimpy
+from clang import cindex
+from langchain.llms import OpenAI
+from langchain.chains import ConversationChain
+from langchain.memory import InMemoryConversationMemory
+
+logging.basicConfig(level=logging.DEBUG)
+logger = logging.getLogger("AgenticMatrixLivingCodeAI")
+
+# --- Living Environment ---
+class LivingEnvironment:
+    def __init__(self):
+        self.state: Dict[str, Any] = {}
+        self.subscribers: List[Callable[[str, Any], asyncio.Future]] = []
+
+    def subscribe(self, callback: Callable[[str, Any], asyncio.Future]):
+        self.subscribers.append(callback)
+
+    async def update_state(self, key: str, value: Any):
+        logger.debug(f"[Env] Update: {key} -> {value}")
+        self.state[key] = value
+        await asyncio.gather(*[cb(key, value) for cb in self.subscribers])
+
+    def get_state(self, key: str):
+        return self.state.get(key)
+
+# --- Hybrid Agent with Living Code and Multi-Language Execution ---
+class HybridAgent:
+    def __init__(self, name: str, env: LivingEnvironment, initial_prompt: str):
+        self.name = name
+        self.env = env
+        self.prompt = initial_prompt
+        self.memory = InMemoryConversationMemory()
+        self.llm = None
+        self.chain = None
+        self.llm_ready = False
+        try:
+            self.llm = OpenAI(temperature=0.3)
+            self.chain = ConversationChain(llm=self.llm, memory=self.memory)
+            self.llm_ready = True
+        except Exception as e:
+            logger.warning(f'[{self.name}] OpenAI LLM not available: {e}')
+        self.running = True
+        self.env.subscribe(self.on_env_update)
+
+        self.clang_index = cindex.Index.create()
+        try:
+            self.nim_agent = nimpy.import_module("nim_agent")
+            self.nim_ready = True
+        except Exception as e:
+            logger.warning(f"[{self.name}] Nim module not available: {e}")
+            self.nim_ready = False
+
+    async def on_env_update(self, key: str, value: Any):
+        if key == f"prompt_update_{self.name}":
+            logger.info(f"[{self.name}] Prompt update received")
+            self.prompt = value
+        if key == f"code_update_{self.name}":
+            logger.info(f"[{self.name}] Received C++ code update")
+            diag = self.parse_cpp_code(value)
+            for d in diag:
+                logger.warning(f"[{self.name}][Clang] {d.spelling}")
+
+    def parse_cpp_code(self, code: str):
+        tu = self.clang_index.parse("dynamic_code.cpp", args=['-std=c++17'], unsaved_files=[('dynamic_code.cpp', code)])
+        return list(tu.diagnostics)
+
+    async def execute_nim_logic(self, data: str):
+        if not self.nim_ready:
+            logger.warning(f"[{self.name}] Skipping Nim execution (module unavailable)")
+            return
+        result = self.nim_agent.process_buffer(data)
+        logger.debug(f"[{self.name}] Nim module result: {result}")
+
+    async def run(self):
+        iteration = 0
+        while self.running:
+            env_snapshot = str(self.env.state)
+            full_prompt = f"{self.prompt}\nEnv State:\n{env_snapshot}\nIteration: {iteration}"
+            try:
+                llm_resp = self.chain.invoke(full_prompt)
+                logger.info(f"[{self.name}] LLM output: {llm_resp[:250]}...")
+                await self.env.update_state(f"status_{self.name}", llm_resp)
+            except Exception as e:
+                logger.error(f"[{self.name}] LLM call failed: {e}")
+
+            # Example: dynamic C++ snippet (could be realtime updated)
+            cpp_code = """
+            int add(int a, int b) { return a + b; }
+            """
+            self.parse_cpp_code(cpp_code)
+
+            # Nim logic invocation with complex data string
+            await self.execute_nim_logic(f"Nim data iteration {iteration} from {self.name}")
+
+            await asyncio.sleep(6)
+            iteration += 1
+
+    def stop(self):
+        logger.info(f"[{self.name}] Stopping execution.")
+        self.running = False
+
+# --- Host AI Manager ---
+class HostAgent:
+    def __init__(self):
+        self.env = LivingEnvironment()
+        self.agents: List[HybridAgent] = []
+        self.running = True
+
+    def register_agent(self, agent: HybridAgent):
+        logger.info(f"[Host] Registering agent {agent.name}")
+        self.agents.append(agent)
+
+    async def update_loop(self):
+        count = 0
+        while self.running and count < 8:
+            await asyncio.sleep(10)
+            for agent in self.agents:
+                prompt = f"Agent update cycle {count} for {agent.name}. Adapt behavior dynamically."
+                await self.env.update_state(f"prompt_update_{agent.name}", prompt)
+
+                # Optional dynamic new C++ source for compilation
+                new_cpp_code = f"int dynamic_func() {{ return {count} * 42; }}"
+                await self.env.update_state(f"code_update_{agent.name}", new_cpp_code)
+
+            count += 1
+
+        logger.info("[Host] All update cycles complete, stopping agents.")
+        for agent in self.agents:
+            agent.stop()
+
+    async def run(self):
+        tasks = [asyncio.create_task(agent.run()) for agent in self.agents]
+        updater = asyncio.create_task(self.update_loop())
+        await asyncio.gather(updater, *tasks)
+        self.running = False
+
+# --- Main Entrypoint ---
+async def main():
+    host = HostAgent()
+    agents = [
+        HybridAgent("AlphaBot", host.env, "You are AlphaBot, leading agentic matrix coordination."),
+        HybridAgent("BetaBot", host.env, "You are BetaBot, specialist in adaptive code evolution."),
+        HybridAgent("GammaBot", host.env, "You are GammaBot, UI and UX genius mirroring living interfaces.")
+    ]
+    for ag in agents:
+        host.register_agent(ag)
+    await host.run()
+
+if __name__ == "__main__":
+    asyncio.run(main())