# DEPRECATED: This file has been replaced by gemini_chat_model.py # Please use GeminiChatModel instead of Gaio for LLM integration import os import requests class Gaio: def __init__(self, api_key, api_url): self.api_key = api_key self.api_url = api_url def InvokeGaio(self, userPrompt): payload = { "model": "azure/gemini-2.5-pro", "messages": [ { "role": "user", "content": userPrompt } ], "temperature": 0.00, "max_tokens": 100000, "stream": False } headers = { "Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json" } # Make the POST request response = requests.post( self.api_url, headers=headers, json=payload, timeout=30 ) # Parse the JSON response result = response.json() message = result["choices"][0]["message"]["content"] return message def main(): """Test Gaio with a simple question and verify the answer.""" print("Testing Gaio with a simple math question...") # Get API credentials from environment variables api_key = os.getenv("GAIO_API_TOKEN") api_url = os.getenv("GAIO_URL") if not api_key or not api_url: print("❌ Test failed: Missing environment variables.") print("Please set the following environment variables:") print("- GAIO_API_TOKEN: Your API token") print("- GAIO_URL: The API URL") return try: # Create Gaio instance gaio = Gaio(api_key, api_url) # Test with the specific question test_question = "How much is 2 + 2 ? Only answer with the response number and nothing else." print(f"\nQuestion: {test_question}") # Get the answer answer = gaio.InvokeGaio(test_question) print(f"Answer: '{answer}'") # Check if the answer is exactly "4" answer_stripped = answer.strip() if answer_stripped == "4": print("✅ Test passed! The answer is exactly '4'.") else: print(f"❌ Test failed. Expected '4', but got '{answer_stripped}'.") except Exception as e: print(f"❌ Test failed with error: {e}") if __name__ == "__main__": main()