动态endpoint
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@ -16,7 +16,7 @@ def 同时问询(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
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chatbot.append((txt, "正在同时咨询ChatGPT和ChatGLM……"))
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间,我们先及时地做一次界面更新
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llm_kwargs['llm_model'] = 'chatglm&gpt-3.5-turbo'
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llm_kwargs['llm_model'] = 'gpt-3.5-turbo&api2d-gpt-3.5-turbo'
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gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
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inputs=txt, inputs_show_user=txt,
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llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
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@ -60,7 +60,9 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
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while True:
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try:
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# make a POST request to the API endpoint, stream=False
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response = requests.post(llm_kwargs['endpoint'], headers=headers, proxies=proxies,
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from .bridge_all import model_info
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endpoint = model_info[llm_kwargs['llm_model']]['endpoint']
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response = requests.post(endpoint, headers=headers, proxies=proxies,
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json=payload, stream=True, timeout=TIMEOUT_SECONDS); break
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except requests.exceptions.ReadTimeout as e:
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retry += 1
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@ -148,7 +150,9 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
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while True:
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try:
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# make a POST request to the API endpoint, stream=True
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response = requests.post(llm_kwargs['endpoint'], headers=headers, proxies=proxies,
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from .bridge_all import model_info
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endpoint = model_info[llm_kwargs['llm_model']]['endpoint']
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response = requests.post(endpoint, headers=headers, proxies=proxies,
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json=payload, stream=True, timeout=TIMEOUT_SECONDS);break
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except:
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retry += 1
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@ -36,7 +36,6 @@ def ArgsGeneralWrapper(f):
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llm_kwargs = {
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'api_key': cookies['api_key'],
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'llm_model': llm_model,
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'endpoint': model_info[llm_model]['endpoint'],
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'top_p':top_p,
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'max_length': max_length,
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'temperature':temperature,
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