from chimera.cognitive_core.prometheus_core import PrometheusCognitiveCore from chimera.agent.agent import Agent from chimera.agent.tool_user import ToolRegistry, WebSearchTool, FileSystemTool # Initialize core = PrometheusCognitiveCore() tools = ToolRegistry() tools.register_tool(WebSearchTool()) tools.register_tool(FileSystemTool()) agent = Agent(cognitive_core=core, tool_registry=tools, db_path="./chimera_db") # Run — agent will perceive, think, act, and remember in a loop agent.run_main_loop({"task": "Research the latest developments in cognitive architectures"})

from chimera.consciousness.conscious_agent import ConsciousnessAwareAgent agent = ConsciousnessAwareAgent( cognitive_core=core, tool_registry=tools, db_path="./chimera_db", ) # Enable self-reflection agent.enable_self_reflection() # The agent now tracks its own cognitive states, detects biases, # and uses metacognitive insights to improve decision-making agent.run_main_loop({"task": "Solve a complex problem while monitoring your own reasoning"}) # Inspect the agent's self-model print(agent.get_self_model())

from chimera.rlhf.oracle import RLHFOracle # Train a reward model first (see scripts/train_reward_model.py) oracle = RLHFOracle(model_path="./reward_model") agent = ConsciousnessAwareAgent( cognitive_core=core, tool_registry=tools, db_path="./chimera_db", rlhf_oracle=oracle, num_candidates=3, # generate 3 candidates, oracle picks the best )

from chimera.cognitive_core.prometheus_core import PrometheusCognitiveCore core = PrometheusCognitiveCore() # reads CHIMERA_LLM_API_KEY from env response = core.generate_response({"text_data": "What is consciousness?"})

from chimera.agent.memory import VectorEpisodicMemory, WorkingMemory, Experience memory = VectorEpisodicMemory(db_path="./my_db") memory.remember(Experience( observation={"input": "user question"}, action={"tool": "web_search", "query": "..."}, outcome={"result": "..."} )) # Semantic recall relevant = memory.recall("similar question", top_k=5)

from chimera.agent.tool_user import Tool class MyTool(Tool): @property def name(self): return "my_tool" @property def description(self): return "Does something useful" def get_schema(self): return {"type": "object", "properties": {"input": {"type": "string"}}} def __call__(self, input: str): return f"Result for {input}"

from chimera.consciousness.narcissus_core import NarcissusConsciousnessCore, CognitiveState narcissus = NarcissusConsciousnessCore( cognitive_core=core, memory_db_path="./narcissus_db" ) # Record a cognitive state state = narcissus.record_cognitive_state( thought_process="Analyzing user's emotional state", attention_weights={"emotion": 0.6, "context": 0.3, "history": 0.1}, decision_path=["assess_mood", "select_intervention"], confidence=0.75, emotional_state={"empathy": 0.8, "concern": 0.6}, memory_context=["previous sessions"], processing_load=0.5, ) # Introspect insights = narcissus.perform_introspective_analysis() # → {self_model_snapshot, metacognitive_insights, suggested_improvements, self_awareness_metrics}