| from urllib.request import urlopen |
|
|
| from openai import OpenAI |
|
|
| test_cases = { |
| "64k": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2.5-1M/test-data/64k.txt", |
| "200k": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2.5-1M/test-data/200k.txt", |
| "600k": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2.5-1M/test-data/600k.txt", |
| "1m": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2.5-1M/test-data/1m.txt", |
| } |
|
|
| client = OpenAI(api_key="EMPTY", base_url="http://127.0.0.1:30000/v1") |
|
|
| for name, url in test_cases.items(): |
| print(f"\n==== Running test case: {name} ====") |
| try: |
| with urlopen(url, timeout=10) as response: |
| prompt = response.read().decode("utf-8") |
| except Exception as e: |
| print(f"Failed to load prompt for {name}: {e}") |
| continue |
|
|
| try: |
| response = client.chat.completions.create( |
| model="meta-llama/Llama-4-Scout-17B-16E-Instruct", |
| messages=[{"role": "user", "content": prompt}], |
| stream=True, |
| max_tokens=128, |
| temperature=0, |
| ) |
|
|
| for chunk in response: |
| if chunk.choices and chunk.choices[0].delta.content is not None: |
| print(chunk.choices[0].delta.content, end="", flush=True) |
| except Exception as e: |
| print(f"\nError during completion for {name}: {e}") |
|
|
