int/gpt_academic
1
0
派生 0
镜像自地址 https://github.com/binary-husky/gpt_academic.git 已同步 2025-12-05 22:16:49 +00:00
代码 工单 软件包 项目 版本发布 百科 动态

阿里云百炼(原灵积)增加对deepseek-r1、deepseek-v3模型支持 (#2182)

浏览代码 
* 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：
BZfei
2025-03-25 00:11:55 +08:00
提交者 GitHub
父节点 045cdb15d8
当前提交 82aac97980
共有 4 个文件被更改，包括 51 次插入 和 11 次删除
下载 Patch 文件 下载 Diff 文件 展开所有文件 折叠所有文件

1
config.py
查看文件

@@ -45,6 +45,7 @@ AVAIL_LLM_MODELS = ["qwen-max", "o1-mini", "o1-mini-2024-09-12", "o1", "o1-2024-
"gemini-1.5-pro", "chatglm3", "chatglm4",
"deepseek-chat", "deepseek-coder", "deepseek-reasoner",
"volcengine-deepseek-r1-250120", "volcengine-deepseek-v3-241226",
"dashscope-deepseek-r1", "dashscope-deepseek-v3",
]
EMBEDDING_MODEL = "text-embedding-3-small"

25
request_llms/bridge_all.py
查看文件

@@ -813,8 +813,9 @@ if "qwen-local" in AVAIL_LLM_MODELS:
})
except:
logger.error(trimmed_format_exc())
# -=-=-=-=-=-=- 通义-在线模型 -=-=-=-=-=-=-
qwen_models = ["qwen-max-latest", "qwen-max-2025-01-25","qwen-max","qwen-turbo","qwen-plus"]
# -=-=-=-=-=-=- 阿里云百炼（通义）-在线模型 -=-=-=-=-=-=-
qwen_models = ["qwen-max-latest", "qwen-max-2025-01-25","qwen-max","qwen-turbo","qwen-plus","dashscope-deepseek-r1","dashscope-deepseek-v3"]
if any(item in qwen_models for item in AVAIL_LLM_MODELS):
try:
from .bridge_qwen import predict_no_ui_long_connection as qwen_noui
@@ -864,10 +865,30 @@ if any(item in qwen_models for item in AVAIL_LLM_MODELS):
"max_token": 30720,
"tokenizer": tokenizer_gpt35,
"token_cnt": get_token_num_gpt35,
},
"dashscope-deepseek-r1": {
"fn_with_ui": qwen_ui,
"fn_without_ui": qwen_noui,
"enable_reasoning": True,
"can_multi_thread": True,
"endpoint": None,
"max_token": 57344,
"tokenizer": tokenizer_gpt35,
"token_cnt": get_token_num_gpt35,
},
"dashscope-deepseek-v3": {
"fn_with_ui": qwen_ui,
"fn_without_ui": qwen_noui,
"can_multi_thread": True,
"endpoint": None,
"max_token": 57344,
"tokenizer": tokenizer_gpt35,
"token_cnt": get_token_num_gpt35,
}
})
except:
logger.error(trimmed_format_exc())
# -=-=-=-=-=-=- 零一万物模型 -=-=-=-=-=-=-
yi_models = ["yi-34b-chat-0205","yi-34b-chat-200k","yi-large","yi-medium","yi-spark","yi-large-turbo","yi-large-preview"]
if any(item in yi_models for item in AVAIL_LLM_MODELS):

8
request_llms/bridge_chatgpt.py
查看文件

@@ -368,12 +368,12 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=gpt_replying_buffer)
break # 对于符合规范的接口，这里可以break
else:
continue # 对于不符合规范的狗屎接口，这里需要继续
continue # 对于不符合规范的接口，这里需要继续
# 到这里，我们已经可以假定必须包含choice了
try:
status_text = f"finish_reason: {chunkjson['choices'][0].get('finish_reason', 'null')}"
except:
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}")
logger.error(f"一些第三方接口出现这样的错误，兼容一下吧: {chunk_decoded}")
# 处理数据流的主体
if has_content:
# 正常情况
@@ -382,9 +382,9 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
# 一些第三方接口的出现这样的错误，兼容一下吧
continue
else:
# 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
# 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
if chunkjson['choices'][0]["delta"].get("content", None) is None:
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}")
logger.error(f"一些第三方接口出现这样的错误，兼容一下吧: {chunk_decoded}")
continue
gpt_replying_buffer = gpt_replying_buffer + chunkjson['choices'][0]["delta"]["content"]

28
request_llms/com_qwenapi.py
查看文件

@@ -3,6 +3,7 @@ from toolbox import get_conf
import threading
timeout_bot_msg = '[Local Message] Request timeout. Network error.'
model_prefix_to_remove = 'dashscope-'
class QwenRequestInstance():
def __init__(self):
@@ -20,6 +21,13 @@ class QwenRequestInstance():
raise RuntimeError('请配置 DASHSCOPE_API_KEY')
dashscope.api_key = get_conf("DASHSCOPE_API_KEY")
def format_reasoning(self, reasoning_content:str, main_content:str):
if reasoning_content:
reasoning_content_paragraphs = ''.join([f'<p style="margin: 1.25em 0;">{line}</p>' for line in reasoning_content.split('\n')])
formatted_reasoning_content = f'<div class="reasoning_process">{reasoning_content_paragraphs}</div>\n\n---\n\n'
return formatted_reasoning_content + main_content
else:
return main_content
def generate(self, inputs, llm_kwargs, history, system_prompt):
# import _thread as thread
@@ -28,9 +36,13 @@ class QwenRequestInstance():
if top_p == 0: top_p += 1e-5
if top_p == 1: top_p -= 1e-5
model_name = llm_kwargs['llm_model']
if model_name.startswith(model_prefix_to_remove): model_name = model_name[len(model_prefix_to_remove):]
self.reasoning_buf = ""
self.result_buf = ""
responses = Generation.call(
model=llm_kwargs['llm_model'],
model=model_name,
messages=generate_message_payload(inputs, llm_kwargs, history, system_prompt),
top_p=top_p,
temperature=llm_kwargs.get('temperature', 1.0),
@@ -46,18 +58,24 @@ class QwenRequestInstance():
self.result_buf += response.output.choices[0].message.content
except:
pass
yield self.result_buf
yield self.format_reasoning(self.reasoning_buf, self.result_buf)
break
elif response.output.choices[0].finish_reason == 'length':
self.result_buf += "[Local Message] 生成长度过长，后续输出被截断"
yield self.result_buf
yield self.format_reasoning(self.reasoning_buf, self.result_buf)
break
else:
try:
contain_reasoning = hasattr(response.output.choices[0].message, 'reasoning_content')
except:
contain_reasoning = False
if contain_reasoning:
self.reasoning_buf += response.output.choices[0].message.reasoning_content
self.result_buf += response.output.choices[0].message.content
yield self.result_buf
yield self.format_reasoning(self.reasoning_buf, self.result_buf)
else:
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}"
yield self.result_buf
yield self.format_reasoning(self.reasoning_buf, self.result_buf)
break
# 耗尽generator避免报错