import json
import os

from src.llm.models import ExtractionResult
from src.llm.processor import LLMProcessor

# Sample transcripts for testing
SAMPLE_TRANSCRIPTS = [
    """
    Player 1: I think I'll move towards the door.
    Player 2: Wait, let me check my inventory. I have a torch, right?
    Player 1: Yeah, you have one torch.
    Player 2: Okay, I'm going to light it.
    DM: As you light the torch, you see a strange symbol on the wall. It's a red eye.
    Player 1: Oh, cool.
    Player 2: Wait, did I say that? I mean, I'm moving.
    Player 1: Let's just go.
    """,
    """
    Player 1: I attack the goblin!
    DM: Roll for it.
    Player 1: I got a 15.
    DM: The goblin is hit. It takes 8 damage.
    Player 1: Nice.
    Player 2: I'll use a healing potion on Player 1.
    DM: Okay, Player 1 recovers 10 HP.
    Player 1: Thanks.
    Player 2: By the way, does anyone have a snack?
    Player 1: I think there's some in the kitchen.
    """,
    """
    DM: You enter the City of Silverspire. Silverspire is known for its floating gardens.
    Player 1: Wow, floating gardens.
    Player 2: I want to talk to the guard.
    DM: The guard is an old dwarf named Thorne. Thorne is the Captain of the Guard.
    Player 1: Thorne seems grumpy.
    Player 2: Let's ask him about the floating gardens.
    """,
]


def test_llm_pipeline():
    # Mocking the API key for the test.
    # In a real scenario, this should be in .env
    os.environ["OPENAI_API_KEY"] = "sk-test-key"

    # We need a Mock LLM Processor for the unit test since we don't have a live API key.
    # However, the task asks for a verification report.
    # I will implement a mock and a real test function.

    processor = LLMProcessor()

    for i, transcript in enumerate(SAMPLE_TRANSCRIPTS):
        print(f"--- Testing Transcript {i + 1} ---")
        result = processor.process_pipeline(transcript)
        print(f"Result: {result.model_dump_json(indent=2)}")
        print("\n")


if __name__ == "__main__":
    test_llm_pipeline()