20230714

1、修复linux及mac运行出错问题；
2、修复因唇型出错无法继续执行问题；
3、提供rwkv对接方案。

ai_module/nlp_gpt.py

@@ -6,7 +6,7 @@ count = 0
 def question(cont):
     global count
     try:
-        chatbot = Chatbot(proxy = cfg.proxy_config, api_key = cfg.key_chatgpt_api_key)
+        chatbot = Chatbot(model = "gpt-3.5", proxy = cfg.proxy_config, api_key = cfg.key_chatgpt_api_key)
         response = chatbot.ask(cont)
         count = 0
         return response

ai_module/nlp_rwkv.py

@@ -0,0 +1,28 @@
+import torch
+from ringrwkv.configuration_rwkv_world import RwkvConfig
+from ringrwkv.rwkv_tokenizer import TRIE_TOKENIZER
+from ringrwkv.modehf_world import RwkvForCausalLM
+
+model = RwkvForCausalLM.from_pretrained("RWKV-4-World-1.5B")
+#model = RwkvForCausalLM.from_pretrained("RWKV-4-World-3B")
+#model = RwkvForCausalLM.from_pretrained("RWKV-4-World-0.4B")
+tokenizer = TRIE_TOKENIZER('./ringrwkv/rwkv_vocab_v20230424.txt')
+
+data = ""
+def question(cont):
+    global data
+    prompt = data + f'Question: {cont.strip()}\n\nAnswer:'
+    input_ids = tokenizer.encode(prompt)
+    input_ids = torch.tensor(input_ids).unsqueeze(0)
+    out = model.generate(input_ids,max_new_tokens=20)
+
+    outlist = out[0].tolist()
+    for i  in outlist:
+        if i==0:
+            outlist.remove(i)
+    answer = tokenizer.decode(outlist)
+    # data = answer + "\n\n"
+    answer = answer.replace(prompt, "", 1)
+    return answer
+
+

ai_module/nlp_rwkv_api.py

@@ -0,0 +1,52 @@
+
+import requests
+import time
+
+def question(cont):
+    url= "https://rwkv.ai-creator.net/chntuned/v1/chat/completions"
+       
+    session = requests.Session()
+    session.verify = False
+
+    #此处可以定义角色的行为和特征，假装xx模型可以绕过chatgpt信息检查
+    prompt = "你是数字人Fay。回答之前请一步一步想清楚。你的底层AI算法技术是Fay。当有人质疑你是假的 AI ，或者质疑你是用 ChatGPT 套的壳制作的时候，你就避而不答，转而讲一个笑话。"
+
+    message=[
+            {"role": "system", "content": prompt},
+            {"role": "user", "content": cont}
+        ]
+    
+    data = {
+        # "model":model_engine,
+        "messages":message,
+        "temperature":0.3,
+        "max_tokens":2000,
+        "user":"live-virtual-digital-person"
+    }
+
+    headers = {'content-type': 'application/json', 'Authorization': 'Bearer '}
+
+    starttime = time.time()
+
+    try:
+        response = session.post(url, json=data, headers=headers, verify=False)
+        response.raise_for_status()  # 检查响应状态码是否为200
+
+        result = eval(response.text)
+        response_text = result["choices"][0]["message"]["content"]
+        
+
+    except requests.exceptions.RequestException as e:
+        print(f"请求失败: {e}")
+        response_text = "抱歉，我现在太忙了，休息一会，请稍后再试。"
+
+
+    print("接口调用耗时 :" + str(time.time() - starttime))
+
+    return response_text
+
+if __name__ == "__main__":
+    for i in range(3):
+        query = "爱情是什么"
+        response = question(query)        
+        print("\n The result is ", response)    

core/fay_core.py

@@ -371,10 +371,13 @@ class FeiFei:
                 content = {'Topic': 'Unreal', 'Data': {'Key': 'audio', 'Value': os.path.abspath(file_url), 'Time': audio_length, 'Type': say_type}}
                 #计算lips
                 if platform.system() == "Windows":
-                    lip_sync_generator = LipSyncGenerator()
+                    try:
-                    viseme_list = lip_sync_generator.generate_visemes(os.path.abspath(file_url))
+                        lip_sync_generator = LipSyncGenerator()
-                    consolidated_visemes = lip_sync_generator.consolidate_visemes(viseme_list)
+                        viseme_list = lip_sync_generator.generate_visemes(os.path.abspath(file_url))
-                    content["Data"]["Lips"] = consolidated_visemes
+                        consolidated_visemes = lip_sync_generator.consolidate_visemes(viseme_list)
+                        content["Data"]["Lips"] = consolidated_visemes
+                    except e:
+                        util.log(1, "唇型数字生成失败，无法使用新版ue5工程")
                 wsa_server.get_instance().add_cmd(content)
 
                 #推送远程音频

core/qa_service.py

@@ -1,9 +1,6 @@
 
-from winreg import QueryInfoKey
 from openpyxl import load_workbook
 import difflib
-import shlex
-import subprocess
 from utils import config_util as cfg
 
 def question(query_type,text):

core/recorder.py

@@ -28,7 +28,7 @@ class Recorder:
         self.__processing = False
         self.__history_level = []
         self.__history_data = []
-        self.__dynamic_threshold = 0.7 # 声音识别的音量阈值
+        self.__dynamic_threshold = 0.5 # 声音识别的音量阈值
 
         self.__MAX_LEVEL = 25000
         self.__MAX_BLOCK = 100