| import os | |
| from openai import OpenAI | |
| def get_streaming_response(message="Who are you",enable_thinking=True): | |
| client = OpenAI( | |
| api_key="sk-de60fca86cd34af3a4ff9b0e893139f5", # 替换为你的API Key | |
| base_url="https://dashscope.aliyuncs.com/compatible-mode/v1", | |
| ) | |
| completion = client.chat.completions.create( | |
| model="qwen3-8b", | |
| messages=[ | |
| {'role': 'system', 'content': 'You are a helpful assistant.'}, | |
| {'role': 'user', 'content': message} | |
| ], | |
| temperature=0.8, | |
| extra_body={ | |
| "enable_thinking": enable_thinking, | |
| }, | |
| # top_p=0.9, | |
| stream=True, | |
| stream_options={"include_usage": True} | |
| ) | |
| reasoning_content = "" | |
| answer_content = "" | |
| is_answering = False | |
| for chunk in completion: | |
| if not chunk.choices: | |
| continue | |
| delta = chunk.choices[0].delta | |
| if hasattr(delta, "reasoning_content") and delta.reasoning_content is not None: | |
| reasoning_content += delta.reasoning_content | |
| if hasattr(delta, "content") and delta.content: | |
| is_answering = True | |
| answer_content += delta.content | |
| return f"<think>{reasoning_content}</think>{answer_content}" | |
| # def get_response_template(message,model="meta-llama/Meta-Llama-3-8B-Instruct",client=OpenAI( | |
| # api_key="EMPTY", | |
| # base_url="http://127.0.0.1:8422/v1", | |
| # )): | |
| # prompt= message | |
| # chat_response = client.chat.completions.create( | |
| # model=model, | |
| # messages=[ | |
| # {"role": "system", "content": "You are a helpful assistant."}, | |
| # {"role": "user", "content": prompt}, | |
| # ], | |
| # temperature = 0.8, | |
| # ) | |
| # print("Chat response:", chat_response.choices[0].message.content) | |
| # return chat_response.choices[0].message.content |