from groq import Groq
import groq
import os
import re

# Tried in this order; each model has its own free daily limit
MODELS = [
    "openai/gpt-oss-20b",
    "openai/gpt-oss-120b",
    "qwen/qwen3.8-27b",
]

FALLBACK_ANSWER = "Hmm, daar moet ik even over nadenken..."


class GroqAgent:
    def __init__(self, system_content):
        self.client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
        self.system_content = system_content

    def request_llm_response(self, message_content):
        messages = [
            {"role": "system", "content": self.system_content},
            {"role": "user", "content": message_content},
        ]

        for model in MODELS:
            try:
                kwargs = {
                    "model": model,
                    "messages": messages,
                    "max_completion_tokens": 400,
                }
                if model.startswith("openai/"):
                    kwargs["reasoning_effort"] = "low"

                chat_completion = self.client.chat.completions.create(**kwargs)
                message = chat_completion.choices[0].message.content or ""

                # Qwen can include its thinking in <think> tags; strip it
                message = re.sub(r"<think>.*?</think>", "", message, flags=re.DOTALL).strip()

                if message:
                    return message
                print(f"[agent] {model} returned an empty answer, trying next model")

            except groq.RateLimitError:
                print(f"[agent] {model} hit its rate limit, trying next model")
            except groq.APIError as e:
                print(f"[agent] {model} failed: {e}")

        return FALLBACK_ANSWER