from core.factory import LLMFactory
from agents.roles import AGENTS
import sys
import os
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))

# Cas d'utilisation : analyse uniquement visuelle
role = "diagnostic_assistant"
prompt = "What do you see in the attached screenshot? Describe the main elements."
image_path = ["images/error_screenshot.png"]
custom_params = {
    "temperature": 0.3,
    "top_p": 1.0,
    "format": "json"
}

model = LLMFactory.create("llama3.2-vision:90b")
model.set_role(role, AGENTS[role])
model.params.update(custom_params)

response_en, response_fr = model.generate(
    user_prompt=prompt,
    images=image_path,
    translate=True
)

print("[EN]", response_en)
print("[FR]", response_fr)
