import sys
import os
import io

# Force UTF-8 for stdout
sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8')

# Add src to path
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), 'services/ai-service/src')))

from ai_med_extract.utils.prompt_loader import load_system_prompt
from ai_med_extract.agents.clinical_critic_agent import ClinicalCriticAgent
from ai_med_extract.utils.unified_model_manager import GenerationConfig

# 1. Verify Prompt Loading
prompt = load_system_prompt("clinical_summary_optimized.txt")
print("--- Loaded Prompt Snippet ---")
print(prompt[:200] + "...")
assert "MODERN CLINICAL DASHBOARD" in prompt
print("✅ Prompt contains dashboard instructions.")

# 2. Mock Model for Critic Evaluation test
class MockModel:
    def generate(self, prompt, config):
        print(f"--- Critic Received Config: max_tokens={config.max_tokens}, temp={config.temperature} ---")
        return '{"accuracy_score": 9, "grounding_score": 9, "hallucinations": [], "clinical_feedback": "Looks good", "risk_level": "Low"}'

# 3. Verify Critic Agent uses GenerationConfig
mock_model = MockModel()
critic = ClinicalCriticAgent(model_loader=mock_model)
eval_res = critic.evaluate({"data": "test"}, "Patient is stable.")

print("--- Evaluation Result ---")
print(eval_res)
assert eval_res['accuracy_score'] == 9
print("✅ ClinicalCriticAgent successfully used GenerationConfig and parsed output.")

print("\n🚀 FINAL VERIFICATION SUCCESSFUL!")