镜像自地址
https://github.com/binary-husky/gpt_academic.git
已同步 2025-12-06 06:26:47 +00:00
接入新模型
这个提交包含在:
@@ -222,7 +222,7 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
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watch_dog_patience = 5 # 看门狗 (watchdog) 的耐心, 设置5秒即可
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response = ""
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observe_window[0] = "[Local Message]: 等待Claude响应中 ..."
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observe_window[0] = "[Local Message] 等待Claude响应中 ..."
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for response in claude_handle.stream_chat(query=inputs, history=history_feedin, system_prompt=sys_prompt, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
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observe_window[0] = preprocess_newbing_out_simple(response)
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if len(observe_window) >= 2:
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@@ -236,7 +236,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
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单线程方法
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函数的说明请见 request_llms/bridge_all.py
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"""
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chatbot.append((inputs, "[Local Message]: 等待Claude响应中 ..."))
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chatbot.append((inputs, "[Local Message] 等待Claude响应中 ..."))
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global claude_handle
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if (claude_handle is None) or (not claude_handle.success):
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@@ -255,14 +255,14 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
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for i in range(len(history)//2):
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history_feedin.append([history[2*i], history[2*i+1]])
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chatbot[-1] = (inputs, "[Local Message]: 等待Claude响应中 ...")
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response = "[Local Message]: 等待Claude响应中 ..."
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chatbot[-1] = (inputs, "[Local Message] 等待Claude响应中 ...")
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response = "[Local Message] 等待Claude响应中 ..."
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yield from update_ui(chatbot=chatbot, history=history, msg="Claude响应缓慢,尚未完成全部响应,请耐心完成后再提交新问题。")
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for response in claude_handle.stream_chat(query=inputs, history=history_feedin, system_prompt=system_prompt):
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chatbot[-1] = (inputs, preprocess_newbing_out(response))
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yield from update_ui(chatbot=chatbot, history=history, msg="Claude响应缓慢,尚未完成全部响应,请耐心完成后再提交新问题。")
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if response == "[Local Message]: 等待Claude响应中 ...":
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response = "[Local Message]: Claude响应异常,请刷新界面重试 ..."
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if response == "[Local Message] 等待Claude响应中 ...":
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response = "[Local Message] Claude响应异常,请刷新界面重试 ..."
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history.extend([inputs, response])
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logging.info(f'[raw_input] {inputs}')
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logging.info(f'[response] {response}')
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