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| import time | |
| from app import respond, cancel_inference # assuming respond and cancel_inference are defined in app.py | |
| def test_api(): | |
| # Set up input parameters for API model | |
| message = "What is the meaning of life?" | |
| history = [] | |
| system_message = "You are a helpful, concise chatbot." | |
| max_tokens = 256 | |
| temperature = 0.7 | |
| top_p = 0.95 | |
| use_local_model = False # Use API model | |
| start_time = time.time() | |
| # Call the respond function (generator) | |
| result_generator = respond( | |
| message=message, | |
| history=history, | |
| system_message=system_message, | |
| max_tokens=max_tokens, | |
| temperature=temperature, | |
| top_p=top_p, | |
| use_local_model=use_local_model | |
| ) | |
| # Collect results | |
| final_history = None | |
| for result in result_generator: | |
| final_history = result | |
| end_time = time.time() | |
| runtime = end_time - start_time | |
| print("API Runtime:", runtime) | |
| print("API Final conversation history:", final_history) | |
| def test_local(): | |
| # Set up input parameters for local model | |
| message = "What is the meaning of life?" | |
| history = [] | |
| system_message = "You are a helpful, concise chatbot." | |
| max_tokens = 256 | |
| temperature = 0.7 | |
| top_p = 0.95 | |
| use_local_model = True # Use local model | |
| start_time = time.time() | |
| # Call the respond function (generator) | |
| result_generator = respond( | |
| message=message, | |
| history=history, | |
| system_message=system_message, | |
| max_tokens=max_tokens, | |
| temperature=temperature, | |
| top_p=top_p, | |
| use_local_model=use_local_model | |
| ) | |
| # Collect results | |
| final_history = None | |
| for result in result_generator: | |
| final_history = result | |
| end_time = time.time() | |
| runtime = end_time - start_time | |
| print("Local Runtime:", runtime) | |
| print("Local Final conversation history:", final_history) | |
| # Run the tests | |
| if __name__ == "__main__": | |
| test_api() | |
| test_local() | |