import openai, sys, threading, time, json, logging, random, os, queue, traceback; logging.basicConfig(level=logging.INFO,format="%(asctime)s - %(levelname)s - %(message)s"); openai.api_key = os.getenv("OPENAI_API_KEY","YOUR_API_KEY");defai_agent(prompt, temperature=0.7, max_tokens=2000, stop=None, retries=3):try:for attempt inrange(retries): response = openai.Completion.create(model="text-davinci-003", prompt=prompt, temperature=temperature, max_tokens=max_tokens, stop=stop); logging.info(f"Agent Response: {response}");return response["choices"][0]["text"].strip();except Exception as e: logging.error(f"Error occurred on attempt {attempt +1}: {e}"); traceback.print_exc(); time.sleep(random.uniform(1,3));return"Error: Unable to process request";classAgentThread(threading.Thread):def__init__(self, prompt, temperature=0.7, max_tokens=1500, output_queue=None): threading.Thread.__init__(self); self.prompt = prompt; self.temperature = temperature; self.max_tokens = max_tokens; self.output_queue = output_queue if output_queue else queue.Queue();defrun(self):try: result = ai_agent(self.prompt, self.temperature, self.max_tokens); self.output_queue.put({"prompt": self.prompt,"response": result});except Exception as e: logging.error(f"Thread error for prompt '{self.prompt}': {e}"); self.output_queue.put({"prompt": self.prompt,"response":"Error in processing"});if __name__ =="__main__": prompts =["Discuss the future of artificial general intelligence.","What are the potential risks of autonomous weapons?","Explain the ethical implications of AI in surveillance systems.","How will AI affect global economies in the next 20 years?","What is the role of AI in combating climate change?"]; threads =[]; results =[]; output_queue = queue.Queue(); start_time = time.time();for idx, prompt inenumerate(prompts): temperature = random.uniform(0.5,1.0); max_tokens = random.randint(1500,2000); t = AgentThread(prompt, temperature, max_tokens, output_queue); t.start(); threads.append(t);for t in threads: t.join();whilenot output_queue.empty(): result = output_queue.get(); results.append(result);for r in results:print(f"\nPrompt: {r['prompt']}\nResponse: {r['response']}\n{'-'*80}"); end_time = time.time(); total_time =round(end_time - start_time,2); logging.info(f"All tasks completed in {total_time} seconds."); logging.info(f"Final Results: {json.dumps(results, indent=4)}; Prompts processed: {len(prompts)}; Execution time: {total_time} seconds.")
