Feature glm

.gitignore

@@ -0,0 +1,10 @@
+*.pyd
+*.pyc
+
+TTS/models
+SentimentEngine/models
+
+ASR/resources/models
+*.log
+Client
+.vscode

GPT/GLMService.py

@@ -0,0 +1,102 @@
+import logging
+import os
+import time
+
+import GPT.machine_id
+import GPT.tune as tune
+import zhipuai
+
+class GLMService():
+    def __init__(self, args):
+        r'''APIKey=your chatGLM api key
+        chatVer is useless now
+        brainwash 
+        TODO:ADD model arg
+        加入history，以拥有记忆
+        '''
+        self.model="chatglm_pro"#args.model
+        logging.info('Initializing ChatGLM Service...')
+
+
+        self.tune = tune.get_tune(args.character, args.model)
+
+        self.brainwash = args.brainwash
+
+        self.counter = 0
+        # API connect to zhipuai
+        zhipuai.api_key=args.APIKey
+        logging.info('API ChatGLM initialized.')
+
+
+
+    def ask(self, text):
+        stime = time.time()
+        	# 请求模型
+        response = zhipuai.model_api.invoke(
+            model=self.model,
+            prompt=[
+                {"role": "user", "content": self.tune+ text},
+
+            ]
+        )
+        prev_text=response['data']['choices'][0]['content']
+        logging.info('ChatGLM Response: %s, time used %.2f' % (prev_text, time.time() - stime))
+        return prev_text
+
+    def ask_stream(self, text):
+        stime = time.time()
+        #  #求asktext
+        # if self.counter % 5 == 0 and self.chatVer == 1:
+        #     if self.brainwash:
+        #         logging.info('Brainwash mode activated, reinforce the tune.')
+        #     else:
+        #         logging.info('Injecting tunes')
+        #     asktext = self.tune + '\n' + text
+        # else:
+        #     asktext = text
+        asktext = self.tune + '\n' + text
+        response = zhipuai.model_api.sse_invoke(
+            model=self.model,
+            prompt=[
+                {"role": "user", "content": asktext},
+
+            ]
+        )
+
+        # prev_text = ""
+        complete_text = ""        
+        self.counter += 1
+        for event in response.events():
+            if event.event == "add":
+                message=event.data
+                print(event.data,end='')
+            elif event.event == "error" or event.event == "interrupted":
+                message=event.data
+                print(event.data)
+            elif event.event == "finish":
+                message=event.data+'\n'
+                print(event.data)
+                #   print(event.meta)
+            else:
+                message=event.data
+                print(event.data)
+            message=event.data
+            #判断是否成句子
+            if ("。" in message or "！" in message or "？" in message or "\n" in message) and len(complete_text) > 3:
+                complete_text += message
+                logging.info('chatGLM Stream Response: %s, @Time %.2f' % (complete_text, time.time() - stime))
+                yield complete_text.strip()
+                complete_text = ""
+            else:
+                complete_text += message
+            pass
+        if complete_text.strip():
+            logging.info('chatGLM Stream Response: %s, @Time %.2f' % (complete_text, time.time() - stime))
+            yield complete_text.strip()
+
+
+
+
+def sentence_fix():
+    #句子组装
+    pass

GPT/GPTService.py → GPT/GPTService-old.py

@@ -4,9 +4,9 @@
 
 import GPT.machine_id
 import GPT.tune as tune
+import zhipuai
 
-
-class GPTService():
+class GLMService():
     def __init__(self, args):
         logging.info('Initializing ChatGPT Service...')
         self.chatVer = args.chatVer

SocketServer.py

@@ -14,7 +14,7 @@
 import GPT.tune
 from utils.FlushingFileHandler import FlushingFileHandler
 from ASR import ASRService
-from GPT import GPTService
+from GPT import GLMService
 from TTS import TTService
 from SentimentEngine import SentimentEngine
 
@@ -82,7 +82,7 @@ def __init__(self, args):
         self.paraformer = ASRService.ASRService('./ASR/resources/config.yaml')
 
         # CHAT GPT
-        self.chat_gpt = GPTService.GPTService(args)
+        self.chat_gpt = GLMService.GLMService(args)
 
         # TTS
         self.tts = TTService.TTService(*self.char_name[args.character])
@@ -191,8 +191,15 @@ def process_voice(self):
 
         return text
 
-
+def test():
+    args = parse_args()
+    chat_glm = GLMService.GLMService(args)
+    # print(chat_glm.ask('你好'))
+    for back in chat_glm.ask_stream('你好'):
+        print(back,end='')
+    return 
 if __name__ == '__main__':
+    # test()
     try:
         args = parse_args()
         s = Server(args)

SocketServer.spec

@@ -5,6 +5,7 @@ import sys ; sys.setrecursionlimit(sys.getrecursionlimit() * 5)
 from PyInstaller.utils.hooks import collect_all
 import inspect
 import torch
+import os
 
 
 def collect_all_and_add_to_list(package_name, datas, binaries, hiddenimports):
@@ -32,15 +33,17 @@ def collect_source_files(modules):
 source_files = collect_source_files([torch])
 source_files_toc = TOC((name, path, 'DATA') for path, name in source_files)
 
-
-datas.append(('venv\lib\site-packages\librosa', 'librosa'))
-datas.append(('venv\lib\site-packages\cn2an', 'cn2an'))
+#for conda-env in win
+# datas += collect_data_files(os.path.join(os.environ['STDLIB_DIR'], 'site-packages', 'librosa'))
+datas.append(('C:\\ProgramData\\Anaconda3\\envs\\DL\\Lib\\site-packages\librosa', 'librosa'))
+datas.append(('C:\\ProgramData\\Anaconda3\\envs\\DL\\Lib\\site-packages\cn2an', 'cn2an'))
 datas.append(('TTS\models', 'TTS\models'))
-datas.append(('venv\lib\site-packages\jieba','jieba'))
+datas.append(('C:\\ProgramData\\Anaconda3\\envs\\DL\lib\site-packages\jieba','jieba'))
 datas.append(('ASR', 'ASR'))
 datas.append(('GPT\prompts_default', 'GPT\prompts_default'))
 datas.append(('tmp', 'tmp'))
 datas.append(('SentimentEngine\models\paimon_sentiment.onnx', 'SentimentEngine\models'))
+datas.append(('C:\\ProgramData\\Anaconda3\\envs\\DL\\Lib\\site-packages\proces', 'proces'))
 hiddenimports.extend(['tiktoken_ext.openai_public','tiktoken_ext'])