text = """NVIDIA offers vendor certifications that validate applied skills across accelerated computing and graphics-focused domains, with emphasis on GPUs, parallel processing, and software platforms used for AI, data science, simulation, visualization, and high-performance computing. These programs generally assess understanding of GPU architecture concepts, programming models, performance optimization, and practical use of development frameworks and tools in real workloads. Candidates are typically expected to have hands-on experience, foundational knowledge of operating systems and programming, and familiarity with deploying and tuning workloads on GPU-enabled systems. Preparation often involves lab practice and problem solving rather than rote theory. Credentials aligned with NVIDIA commonly support roles such as AI or data science practitioner, GPU application developer, visualization specialist, or systems professional working with accelerated infrastructure.""" len(text)Result: run success✅ ```shell 970 ``` text = """NVIDIA offers vendor certifications that validate applied skills across accelerated computing and graphics domains, emphasizing GPUs, parallel processing, and software platforms for AI, data science, simulation, visualization, and high-performance computing. These programs typically assess knowledge of GPU architecture concepts, programming models, performance optimization, and practical use of development frameworks and tools in real workloads. Candidates are generally expected to have hands-on experience, core operating system and programming knowledge, and familiarity with deploying and tuning GPU-enabled systems. Preparation often focuses on lab practice and problem solving rather than rote theory. Credentials aligned with NVIDIA commonly support roles such as AI or data science practitioner, GPU application developer, visualization specialist, or systems professional working with accelerated infrastructure.""" len(text)Result: run success✅ ```shell 925 ``` text = """NVIDIA offers vendor certifications that validate applied skills across accelerated computing and graphics domains, emphasizing GPUs, parallel processing, and software platforms for AI, data science, simulation, visualization, and high-performance computing. These programs assess knowledge of GPU architecture concepts, programming models, performance optimization, and practical use of development frameworks and tools in real workloads. Candidates are generally expected to have hands-on experience, core operating system and programming knowledge, and familiarity with deploying and tuning GPU-enabled systems. Preparation often focuses on lab practice and problem solving rather than rote theory. Credentials aligned with NVIDIA commonly support roles such as AI or data science practitioner, GPU application developer, visualization specialist, or systems professional working with accelerated infrastructure.""" len(text)Result: run success✅ ```shell 915 ``` text = """NVIDIA offers vendor certifications that validate applied skills across accelerated computing and graphics domains, emphasizing GPUs, parallel processing, and software platforms for AI, data science, simulation, visualization, and high-performance computing. These programs assess knowledge of GPU architecture, programming models, performance optimization, and practical use of development tools in real workloads. Candidates are generally expected to have hands-on experience, core operating system and programming knowledge, and familiarity with deploying and tuning GPU-enabled systems. Preparation often focuses on lab practice and problem solving rather than rote theory. Credentials aligned with NVIDIA commonly support roles such as AI or data science practitioner, GPU application developer, visualization specialist, or systems professional working with accelerated infrastructure.""" len(text) > search error NVIDIA offers vendor certifications that validate applied skills across accelerated computing and graphics domains, emphasizing GPUs, parallel processing, and software platforms for AI, data science, simulation, visualization, and high-performance computing. These programs assess knowledge of GPU architecture, programming models, performance optimization, and practical use of development tools in real workloads. Candidates are generally expected to have hands-on experience, core operating system and programming knowledge, and familiarity with deploying and tuning GPU-enabled systems. Preparation often focuses on lab practice and problem solving rather than rote theory. Credentials aligned with NVIDIA commonly support roles such as AI or data science practitioner, GPU application developer, visualization specialist, or systems professional working with accelerated infrastructure.