镜像自地址
https://github.com/binary-husky/gpt_academic.git
已同步 2025-12-06 06:26:47 +00:00
阿里云百炼(原灵积)增加对deepseek-r1、deepseek-v3模型支持 (#2182)
* 阿里云百炼(原灵积)增加对deepseek-r1、deepseek-v3模型支持 * update reasoning display --------- Co-authored-by: binary-husky <qingxu.fu@outlook.com>
这个提交包含在:
@@ -813,8 +813,9 @@ if "qwen-local" in AVAIL_LLM_MODELS:
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})
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except:
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logger.error(trimmed_format_exc())
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# -=-=-=-=-=-=- 通义-在线模型 -=-=-=-=-=-=-
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qwen_models = ["qwen-max-latest", "qwen-max-2025-01-25","qwen-max","qwen-turbo","qwen-plus"]
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# -=-=-=-=-=-=- 阿里云百炼(通义)-在线模型 -=-=-=-=-=-=-
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qwen_models = ["qwen-max-latest", "qwen-max-2025-01-25","qwen-max","qwen-turbo","qwen-plus","dashscope-deepseek-r1","dashscope-deepseek-v3"]
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if any(item in qwen_models for item in AVAIL_LLM_MODELS):
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try:
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from .bridge_qwen import predict_no_ui_long_connection as qwen_noui
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@@ -864,10 +865,30 @@ if any(item in qwen_models for item in AVAIL_LLM_MODELS):
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"max_token": 30720,
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"tokenizer": tokenizer_gpt35,
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"token_cnt": get_token_num_gpt35,
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},
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"dashscope-deepseek-r1": {
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"fn_with_ui": qwen_ui,
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"fn_without_ui": qwen_noui,
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"enable_reasoning": True,
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"can_multi_thread": True,
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"endpoint": None,
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"max_token": 57344,
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"tokenizer": tokenizer_gpt35,
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"token_cnt": get_token_num_gpt35,
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},
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"dashscope-deepseek-v3": {
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"fn_with_ui": qwen_ui,
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"fn_without_ui": qwen_noui,
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"can_multi_thread": True,
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"endpoint": None,
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"max_token": 57344,
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"tokenizer": tokenizer_gpt35,
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"token_cnt": get_token_num_gpt35,
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}
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})
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except:
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logger.error(trimmed_format_exc())
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# -=-=-=-=-=-=- 零一万物模型 -=-=-=-=-=-=-
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yi_models = ["yi-34b-chat-0205","yi-34b-chat-200k","yi-large","yi-medium","yi-spark","yi-large-turbo","yi-large-preview"]
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if any(item in yi_models for item in AVAIL_LLM_MODELS):
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@@ -368,12 +368,12 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
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log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=gpt_replying_buffer)
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break # 对于符合规范的接口,这里可以break
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else:
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continue # 对于不符合规范的狗屎接口,这里需要继续
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continue # 对于不符合规范的接口,这里需要继续
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# 到这里,我们已经可以假定必须包含choice了
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try:
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status_text = f"finish_reason: {chunkjson['choices'][0].get('finish_reason', 'null')}"
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except:
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logger.error(f"一些垃圾第三方接口出现这样的错误,兼容一下吧: {chunk_decoded}")
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logger.error(f"一些第三方接口出现这样的错误,兼容一下吧: {chunk_decoded}")
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# 处理数据流的主体
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if has_content:
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# 正常情况
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@@ -382,9 +382,9 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
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# 一些第三方接口的出现这样的错误,兼容一下吧
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continue
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else:
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# 至此已经超出了正常接口应该进入的范围,一些垃圾第三方接口会出现这样的错误
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# 至此已经超出了正常接口应该进入的范围,一些第三方接口会出现这样的错误
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if chunkjson['choices'][0]["delta"].get("content", None) is None:
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logger.error(f"一些垃圾第三方接口出现这样的错误,兼容一下吧: {chunk_decoded}")
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logger.error(f"一些第三方接口出现这样的错误,兼容一下吧: {chunk_decoded}")
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continue
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gpt_replying_buffer = gpt_replying_buffer + chunkjson['choices'][0]["delta"]["content"]
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@@ -3,6 +3,7 @@ from toolbox import get_conf
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import threading
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timeout_bot_msg = '[Local Message] Request timeout. Network error.'
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model_prefix_to_remove = 'dashscope-'
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class QwenRequestInstance():
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def __init__(self):
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@@ -20,6 +21,13 @@ class QwenRequestInstance():
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raise RuntimeError('请配置 DASHSCOPE_API_KEY')
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dashscope.api_key = get_conf("DASHSCOPE_API_KEY")
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def format_reasoning(self, reasoning_content:str, main_content:str):
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if reasoning_content:
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reasoning_content_paragraphs = ''.join([f'<p style="margin: 1.25em 0;">{line}</p>' for line in reasoning_content.split('\n')])
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formatted_reasoning_content = f'<div class="reasoning_process">{reasoning_content_paragraphs}</div>\n\n---\n\n'
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return formatted_reasoning_content + main_content
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else:
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return main_content
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def generate(self, inputs, llm_kwargs, history, system_prompt):
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# import _thread as thread
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@@ -28,9 +36,13 @@ class QwenRequestInstance():
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if top_p == 0: top_p += 1e-5
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if top_p == 1: top_p -= 1e-5
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model_name = llm_kwargs['llm_model']
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if model_name.startswith(model_prefix_to_remove): model_name = model_name[len(model_prefix_to_remove):]
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self.reasoning_buf = ""
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self.result_buf = ""
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responses = Generation.call(
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model=llm_kwargs['llm_model'],
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model=model_name,
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messages=generate_message_payload(inputs, llm_kwargs, history, system_prompt),
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top_p=top_p,
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temperature=llm_kwargs.get('temperature', 1.0),
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@@ -46,18 +58,24 @@ class QwenRequestInstance():
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self.result_buf += response.output.choices[0].message.content
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except:
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pass
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yield self.result_buf
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yield self.format_reasoning(self.reasoning_buf, self.result_buf)
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break
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elif response.output.choices[0].finish_reason == 'length':
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self.result_buf += "[Local Message] 生成长度过长,后续输出被截断"
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yield self.result_buf
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yield self.format_reasoning(self.reasoning_buf, self.result_buf)
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break
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else:
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try:
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contain_reasoning = hasattr(response.output.choices[0].message, 'reasoning_content')
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except:
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contain_reasoning = False
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if contain_reasoning:
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self.reasoning_buf += response.output.choices[0].message.reasoning_content
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self.result_buf += response.output.choices[0].message.content
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yield self.result_buf
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yield self.format_reasoning(self.reasoning_buf, self.result_buf)
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else:
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self.result_buf += f"[Local Message] 请求错误:状态码:{response.status_code},错误码:{response.code},消息:{response.message}"
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yield self.result_buf
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yield self.format_reasoning(self.reasoning_buf, self.result_buf)
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break
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# 耗尽generator避免报错
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