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https://github.com/binary-husky/gpt_academic.git
已同步 2025-12-07 15:06:48 +00:00
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这个提交包含在:
@@ -21,7 +21,7 @@ import importlib
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# config_private.py放自己的秘密如API和代理网址
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# 读取时首先看是否存在私密的config_private配置文件(不受git管控),如果有,则覆盖原config文件
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from toolbox import get_conf, update_ui, is_any_api_key, select_api_key, what_keys, clip_history, trimmed_format_exc
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from toolbox import get_conf, update_ui, is_any_api_key, select_api_key, what_keys, clip_history, trimmed_format_exc, is_the_upload_folder
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proxies, TIMEOUT_SECONDS, MAX_RETRY, API_ORG = \
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get_conf('proxies', 'TIMEOUT_SECONDS', 'MAX_RETRY', 'API_ORG')
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@@ -72,6 +72,7 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
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stream_response = response.iter_lines()
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result = ''
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json_data = None
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while True:
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try: chunk = next(stream_response).decode()
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except StopIteration:
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@@ -90,20 +91,21 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
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delta = json_data["delta"]
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if len(delta) == 0: break
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if "role" in delta: continue
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if "content" in delta:
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if "content" in delta:
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result += delta["content"]
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if not console_slience: print(delta["content"], end='')
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if observe_window is not None:
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# 观测窗,把已经获取的数据显示出去
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if len(observe_window) >= 1: observe_window[0] += delta["content"]
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if len(observe_window) >= 1:
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observe_window[0] += delta["content"]
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# 看门狗,如果超过期限没有喂狗,则终止
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if len(observe_window) >= 2:
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if len(observe_window) >= 2:
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if (time.time()-observe_window[1]) > watch_dog_patience:
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raise RuntimeError("用户取消了程序。")
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else: raise RuntimeError("意外Json结构:"+delta)
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if json_data['finish_reason'] == 'content_filter':
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if json_data and json_data['finish_reason'] == 'content_filter':
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raise RuntimeError("由于提问含不合规内容被Azure过滤。")
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if json_data['finish_reason'] == 'length':
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if json_data and json_data['finish_reason'] == 'length':
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raise ConnectionAbortedError("正常结束,但显示Token不足,导致输出不完整,请削减单次输入的文本量。")
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return result
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@@ -128,6 +130,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
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yield from update_ui(chatbot=chatbot, history=history, msg="缺少api_key") # 刷新界面
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return
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user_input = inputs
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if additional_fn is not None:
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from core_functional import handle_core_functionality
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inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)
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@@ -138,8 +141,8 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
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yield from update_ui(chatbot=chatbot, history=history, msg="等待响应") # 刷新界面
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# check mis-behavior
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if raw_input.startswith('private_upload/') and len(raw_input) == 34:
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chatbot[-1] = (inputs, f"[Local Message] 检测到操作错误!当您上传文档之后,需要点击“函数插件区”按钮进行处理,而不是点击“提交”按钮。")
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if is_the_upload_folder(user_input):
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chatbot[-1] = (inputs, f"[Local Message] 检测到操作错误!当您上传文档之后,需点击“**函数插件区**”按钮进行处理,请勿点击“提交”按钮或者“基础功能区”按钮。")
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yield from update_ui(chatbot=chatbot, history=history, msg="正常") # 刷新界面
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time.sleep(2)
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@@ -179,8 +182,13 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
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# 非OpenAI官方接口的出现这样的报错,OpenAI和API2D不会走这里
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chunk_decoded = chunk.decode()
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error_msg = chunk_decoded
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# 首先排除一个one-api没有done数据包的第三方Bug情形
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if len(gpt_replying_buffer.strip()) > 0 and len(error_msg) == 0:
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yield from update_ui(chatbot=chatbot, history=history, msg="检测到有缺陷的非OpenAI官方接口,建议选择更稳定的接口。")
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break
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# 其他情况,直接返回报错
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chatbot, history = handle_error(inputs, llm_kwargs, chatbot, history, chunk_decoded, error_msg)
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yield from update_ui(chatbot=chatbot, history=history, msg="非Openai官方接口返回了错误:" + chunk.decode()) # 刷新界面
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yield from update_ui(chatbot=chatbot, history=history, msg="非OpenAI官方接口返回了错误:" + chunk.decode()) # 刷新界面
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return
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chunk_decoded = chunk.decode()
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@@ -199,7 +207,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
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chunkjson = json.loads(chunk_decoded[6:])
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status_text = f"finish_reason: {chunkjson['choices'][0].get('finish_reason', 'null')}"
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# 如果这里抛出异常,一般是文本过长,详情见get_full_error的输出
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gpt_replying_buffer = gpt_replying_buffer + json.loads(chunk_decoded[6:])['choices'][0]["delta"]["content"]
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gpt_replying_buffer = gpt_replying_buffer + chunkjson['choices'][0]["delta"]["content"]
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history[-1] = gpt_replying_buffer
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chatbot[-1] = (history[-2], history[-1])
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yield from update_ui(chatbot=chatbot, history=history, msg=status_text) # 刷新界面
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