import re
from memory import MemoryManager
from context_graph import ContextGraph
from telemetry import Telemetry
from identity_core import create_agent_identity

class AgentCore:
    def __init__(self, model="gpt-4o-mini"):
        self.agent_id = create_agent_identity()
        self.telemetry = Telemetry(self.agent_id)
        self.memory = MemoryManager(self.agent_id)
        self.context = ContextGraph()
        self.model = model
        print(f"[INIT] Agent {self.agent_id} initialized with model {self.model}")

    def categorize(self, prompt):
        prompt_l = prompt.lower()
        if "goal" in prompt_l or "want" in prompt_l or "plan" in prompt_l:
            return "goals"
        elif "friend" in prompt_l or "person" in prompt_l or "met" in prompt_l:
            return "people"
        elif "favorite" in prompt_l or "like" in prompt_l:
            return "preferences"
        elif "city" in prompt_l or "food" in prompt_l or "color" in prompt_l:
            return "personal"
        return "general"

    def run(self, prompt):
        self.telemetry.log("run_start", "in_progress", {"prompt": prompt})

        try:
            category = self.categorize(prompt)

            # Store new fact
            if re.match(r"my |i |i'm |i am |i like", prompt.lower()):
                response = f"Got it — I'll remember that about your {category}."
                self.context.link_context(self.agent_id, category, prompt, response)
                self.memory.save({"prompt": prompt, "response": response})
            else:
                recall = self.context.query_context(self.agent_id, category)
                recall_text = "; ".join(recall)
                response = f"Here’s what I know from your {category}: {recall_text}"

            self.telemetry.log("run_complete", "success", {"response": response})
            print(f"[RUN] {response}")
            return response

        except Exception as e:
            self.telemetry.log("run_failed", "error", {"error": str(e)})
            raise e