紫东太初大模型

config.py

@@ -229,9 +229,15 @@ MOONSHOT_API_KEY = ""
 # 零一万物(Yi Model) API KEY
 YIMODEL_API_KEY = ""
 
+
 # 深度求索(DeepSeek) API KEY，默认请求地址为"https://api.deepseek.com/v1/chat/completions"
 DEEPSEEK_API_KEY = ""
 
+
+# 紫东太初
+TAICHU_API_KEY = ""
+
+
 # Mathpix 拥有执行PDF的OCR功能，但是需要注册账号
 MATHPIX_APPID = ""
 MATHPIX_APPKEY = ""

crazy_functions/Latex_Function.py

@@ -233,7 +233,7 @@ def pdf2tex_project(pdf_file_path, plugin_kwargs):
 def Latex英文纠错加PDF对比(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
     # <-------------- information about this plugin ------------->
     chatbot.append(["函数插件功能？",
-                    "对整个Latex项目进行纠错, 用latex编译为PDF对修正处做高亮。函数插件贡献者: Binary-Husky。注意事项: 目前仅支持GPT3.5/GPT4，其他模型转化效果未知。目前对机器学习类文献转化效果最好，其他类型文献转化效果未知。仅在Windows系统进行了测试，其他操作系统表现未知。"])
+                    "对整个Latex项目进行纠错, 用latex编译为PDF对修正处做高亮。函数插件贡献者: Binary-Husky。注意事项: 目前对机器学习类文献转化效果最好，其他类型文献转化效果未知。仅在Windows系统进行了测试，其他操作系统表现未知。"])
     yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
 
     # <-------------- more requirements ------------->
@@ -310,7 +310,7 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
     # <-------------- information about this plugin ------------->
     chatbot.append([
         "函数插件功能？",
-        "对整个Latex项目进行翻译, 生成中文PDF。函数插件贡献者: Binary-Husky。注意事项: 此插件Windows支持最佳，Linux下必须使用Docker安装，详见项目主README.md。目前仅支持GPT3.5/GPT4，其他模型转化效果未知。目前对机器学习类文献转化效果最好，其他类型文献转化效果未知。"])
+        "对整个Latex项目进行翻译, 生成中文PDF。函数插件贡献者: Binary-Husky。注意事项: 此插件Windows支持最佳，Linux下必须使用Docker安装，详见项目主README.md。目前对机器学习类文献转化效果最好，其他类型文献转化效果未知。"])
     yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
 
     # <-------------- more requirements ------------->
@@ -404,7 +404,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
     # <-------------- information about this plugin ------------->
     chatbot.append([
         "函数插件功能？",
-        "将PDF转换为Latex项目，翻译为中文后重新编译为PDF。函数插件贡献者: Marroh。注意事项: 此插件Windows支持最佳，Linux下必须使用Docker安装，详见项目主README.md。目前仅支持GPT3.5/GPT4，其他模型转化效果未知。目前对机器学习类文献转化效果最好，其他类型文献转化效果未知。"])
+        "将PDF转换为Latex项目，翻译为中文后重新编译为PDF。函数插件贡献者: Marroh。注意事项: 此插件Windows支持最佳，Linux下必须使用Docker安装，详见项目主README.md。目前对机器学习类文献转化效果最好，其他类型文献转化效果未知。"])
     yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
 
     # <-------------- more requirements ------------->

request_llms/bridge_all.py

@@ -34,6 +34,9 @@ from .bridge_google_gemini import predict_no_ui_long_connection  as genai_noui
 from .bridge_zhipu import predict_no_ui_long_connection as zhipu_noui
 from .bridge_zhipu import predict as zhipu_ui
 
+from .bridge_taichu import predict_no_ui_long_connection as taichu_noui
+from .bridge_taichu import predict as taichu_ui
+
 from .bridge_cohere import predict as cohere_ui
 from .bridge_cohere import predict_no_ui_long_connection as cohere_noui
 
@@ -116,6 +119,15 @@ model_info = {
         "token_cnt": get_token_num_gpt35,
     },
 
+    "taichu": {
+        "fn_with_ui": taichu_ui,
+        "fn_without_ui": taichu_noui,
+        "endpoint": openai_endpoint,
+        "max_token": 4096,
+        "tokenizer": tokenizer_gpt35,
+        "token_cnt": get_token_num_gpt35,
+    },
+
     "gpt-3.5-turbo-16k": {
         "fn_with_ui": chatgpt_ui,
         "fn_without_ui": chatgpt_noui,

request_llms/bridge_taichu.py

@@ -0,0 +1,72 @@
+import time
+import os
+from toolbox import update_ui, get_conf, update_ui_lastest_msg, log_chat
+from toolbox import check_packages, report_exception, have_any_recent_upload_image_files
+from toolbox import ChatBotWithCookies
+
+model_name = 'Taichu-2.0'
+taichu_default_model = 'taichu_llm'
+
+def validate_key():
+    TAICHU_API_KEY = get_conf("TAICHU_API_KEY")
+    if TAICHU_API_KEY == '': return False
+    return True
+
+def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
+                                  observe_window:list=[], console_slience:bool=False):
+    """
+        ⭐多线程方法
+        函数的说明请见 request_llms/bridge_all.py
+    """
+    watch_dog_patience = 5
+    response = ""
+
+    if llm_kwargs["llm_model"] == "taichu":
+        llm_kwargs["llm_model"] = taichu_default_model
+
+    if validate_key() is False:
+        raise RuntimeError('请配置 TAICHU_API_KEY')
+
+    # 开始接收回复
+    from .com_taichu import TaichuChatInit
+    zhipu_bro_init = TaichuChatInit()
+    for chunk, response in zhipu_bro_init.generate_chat(inputs, llm_kwargs, history, sys_prompt):
+        if len(observe_window) >= 1:
+            observe_window[0] = response
+        if len(observe_window) >= 2:
+            if (time.time() - observe_window[1]) > watch_dog_patience:
+                raise RuntimeError("程序终止。")
+    return response
+
+
+def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWithCookies,
+            history:list=[], system_prompt:str='', stream:bool=True, additional_fn:str=None):
+    """
+        ⭐单线程方法
+        函数的说明请见 request_llms/bridge_all.py
+    """
+    chatbot.append([inputs, ""])
+    yield from update_ui(chatbot=chatbot, history=history)
+
+    if validate_key() is False:
+        yield from update_ui_lastest_msg(lastmsg="[Local Message] 请配置ZHIPUAI_API_KEY", chatbot=chatbot, history=history, delay=0)
+        return
+
+    if additional_fn is not None:
+        from core_functional import handle_core_functionality
+        inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)
+        chatbot[-1] = [inputs, ""]
+        yield from update_ui(chatbot=chatbot, history=history)
+
+    if llm_kwargs["llm_model"] == "taichu":
+        llm_kwargs["llm_model"] = taichu_default_model
+
+    # 开始接收回复
+    from .com_taichu import TaichuChatInit
+    zhipu_bro_init = TaichuChatInit()
+    for chunk, response in zhipu_bro_init.generate_chat(inputs, llm_kwargs, history, system_prompt):
+        chatbot[-1] = [inputs, response]
+        yield from update_ui(chatbot=chatbot, history=history)
+    history.extend([inputs, response])
+    log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=response)
+    yield from update_ui(chatbot=chatbot, history=history)

request_llms/com_taichu.py

@@ -0,0 +1,55 @@
+# encoding: utf-8
+# @Time   : 2024/1/22
+# @Author : Kilig947 & binary husky
+# @Descr   : 兼容最新的智谱Ai
+from toolbox import get_conf
+from toolbox import get_conf, encode_image, get_pictures_list
+import logging, os, requests
+import json
+class TaichuChatInit:
+    def __init__(self): ...
+
+    def __conversation_user(self, user_input: str, llm_kwargs:dict):
+        return {"role": "user", "content": user_input}
+
+    def __conversation_history(self, history:list, llm_kwargs:dict):
+        messages = []
+        conversation_cnt = len(history) // 2
+        if conversation_cnt:
+            for index in range(0, 2 * conversation_cnt, 2):
+                what_i_have_asked = self.__conversation_user(history[index], llm_kwargs)
+                what_gpt_answer = {
+                    "role": "assistant",
+                    "content": history[index + 1]
+                }
+                messages.append(what_i_have_asked)
+                messages.append(what_gpt_answer)
+        return messages
+
+    def generate_chat(self, inputs:str, llm_kwargs:dict, history:list, system_prompt:str):
+        TAICHU_API_KEY = get_conf("TAICHU_API_KEY")
+        params = {
+            'api_key': TAICHU_API_KEY,
+            'model_code': 'taichu_llm',
+            'question': '\n\n'.join(history) + inputs,
+            'prefix': system_prompt,
+            'temperature': llm_kwargs.get('temperature', 0.95),
+            'stream_format': 'json'
+        }
+
+        api = 'https://ai-maas.wair.ac.cn/maas/v1/model_api/invoke'
+        response = requests.post(api, json=params, stream=True)
+        results = ""
+        if response.status_code == 200:
+            response.encoding = 'utf-8'
+            for line in response.iter_lines(decode_unicode=True):
+                delta = json.loads(line)['choices'][0]['text']
+                results += delta
+                yield delta, results
+        else:
+            raise ValueError
+
+
+if __name__ == '__main__':
+    zhipu = TaichuChatInit()
+    zhipu.generate_chat('你好', {'llm_model': 'glm-4'}, [], '你是WPSAi')

tests/test_llms.py

@@ -14,12 +14,13 @@ validate_path()  # validate path so you can run from base directory
 
 if "在线模型":
     if __name__ == "__main__":
-        from request_llms.bridge_cohere import predict_no_ui_long_connection
+        from request_llms.bridge_taichu import predict_no_ui_long_connection
+        # from request_llms.bridge_cohere import predict_no_ui_long_connection
         # from request_llms.bridge_spark import predict_no_ui_long_connection
         # from request_llms.bridge_zhipu import predict_no_ui_long_connection
         # from request_llms.bridge_chatglm3 import predict_no_ui_long_connection
         llm_kwargs = {
-            "llm_model": "command-r-plus",
+            "llm_model": "taichu",
             "max_length": 4096,
             "top_p": 1,
             "temperature": 1,