|
|
| import os |
| import sys |
| import logging |
| from dotenv import load_dotenv |
|
|
| |
| sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) |
|
|
| from agents.tools import call_tier_model |
|
|
| logging.basicConfig(level=logging.INFO) |
| logger = logging.getLogger(__name__) |
|
|
| def main(): |
| print("=== OncoAgent Local Adapter Validation ===") |
| |
| |
| os.environ["USE_LOCAL_ADAPTERS"] = "true" |
| |
| system_prompt = "You are an expert oncologist triage agent. Provide brief, clinical assessment." |
| user_prompt = "Female patient with heavy menstrual bleeding for 10 days and cycles of amenorrhea. No diagnostic tests performed yet." |
| |
| print("\n[Test 1] Tier 1 - Speed Triage (Expected: Local Adapters)") |
| try: |
| response = call_tier_model( |
| tier=1, |
| system_prompt=system_prompt, |
| user_prompt=user_prompt, |
| max_tokens=256 |
| ) |
| print(f"\nResponse:\n{response}") |
| print("\n[SUCCESS] Tier 1 inference completed.") |
| except Exception as e: |
| print(f"\n[FAILURE] Tier 1 inference failed: {e}") |
|
|
| print("\n[Test 2] Tier 2 - Deep Reasoning (Expected: Featherless API Fallback)") |
| try: |
| response = call_tier_model( |
| tier=2, |
| system_prompt=system_prompt, |
| user_prompt=user_prompt, |
| max_tokens=256 |
| ) |
| print(f"\nResponse:\n{response}") |
| print("\n[SUCCESS] Tier 2 inference completed via API.") |
| except Exception as e: |
| print(f"\n[FAILURE] Tier 2 inference failed: {e}") |
|
|
| if __name__ == "__main__": |
| main() |
|
|