加入LLM问答，如ChatGPT

app.py

@@ -38,7 +38,13 @@ async def main(voicename: str, text: str, render):
             #file.write(chunk["data"])
         elif chunk["type"] == "WordBoundary":
             pass                
-
+from llm.LLM import *
+def llm_response(message):
+    # llm = LLM().init_model('Gemini', model_path= 'gemini-pro',api_key='Your API Key', proxy_url=None)
+    llm = LLM().init_model('ChatGPT', model_path= 'gpt-3.5-turbo',api_key='Your API Key')
+    response = llm.chat(message)
+    print(response)
+    return response
 
 def txt_to_audio(text_):
     audio_list = []
@@ -85,7 +91,7 @@ def chat_socket(ws):
             if len(message)==0:
                 return '输入信息为空'
             else:
-                res=llm(message)                           
+                res=llm_response(message)                           
                 txt_to_audio(res)                        
 
 def render():

llm/ChatGPT.py

@@ -0,0 +1,16 @@
+import openai
+
+
+class ChatGPT():
+    def __init__(self, model_path = 'gpt-3.5-turbo', api_key = None):
+        openai.api_key = api_key
+        self.model_path = model_path
+
+    def chat(self, message):
+        response = openai.ChatCompletion.create(
+            model=self.model_path,
+            messages=[
+                {"role": "user", "content": message}
+            ]
+        )
+        return response['choices'][0]['message']['content']

llm/Gemini.py

@@ -0,0 +1,45 @@
+import os
+import google.generativeai as genai
+
+
+def configure_api(api_key, proxy_url=None):
+    os.environ['https_proxy'] = proxy_url if proxy_url else None
+    os.environ['http_proxy'] = proxy_url if proxy_url else None
+    genai.configure(api_key=api_key)
+    
+    
+class Gemini:
+    def __init__(self, model_path='gemini-pro', api_key=None, proxy=None):
+        configure_api(api_key, proxy)
+        safety_settings = [
+            {
+                "category": "HARM_CATEGORY_HARASSMENT",
+                "threshold": "BLOCK_MEDIUM_AND_ABOVE"
+            },
+            {
+                "category": "HARM_CATEGORY_HATE_SPEECH",
+                "threshold": "BLOCK_MEDIUM_AND_ABOVE"
+            },
+            {
+                "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
+                "threshold": "BLOCK_MEDIUM_AND_ABOVE"
+            },
+            {
+                "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
+                "threshold": "BLOCK_MEDIUM_AND_ABOVE"
+            },
+        ]
+
+        self.model = genai.GenerativeModel(model_path, safety_settings=safety_settings)
+        
+    def chat(self, message):
+        times = 0
+        while True:
+            try:
+                response = self.model.generate_content(message)
+                return response.text
+            except:
+                times += 1
+                if times > 5:
+                    raise Exception('Failed to generate text.')
+        

llm/LLM.py

@@ -0,0 +1,48 @@
+from llm.Qwen import Qwen
+from llm.Gemini import Gemini
+from llm.ChatGPT import ChatGPT
+
+    
+def test_Qwen(question = "如何应对压力？", mode='offline', model_path="Qwen/Qwen-1_8B-Chat"):
+    llm = Qwen(mode, model_path)
+    answer = llm.generate(question)
+    print(answer)
+    
+def test_Gemini(question = "如何应对压力？", model_path='gemini-pro', api_key=None, proxy_url=None):
+    llm = Gemini(model_path, api_key, proxy_url)
+    answer = llm.generate(question)
+    print(answer)
+    
+class LLM:
+    def __init__(self, mode='offline'):
+        self.mode = mode
+        
+    def init_model(self, model_name, model_path, api_key=None, proxy_url=None):
+        if model_name not in ['Qwen', 'Gemini', 'ChatGPT']:
+            raise ValueError("model_name must be 'ChatGPT', 'Qwen', or 'Gemini'(其他模型还未集成)")
+       
+        if model_name == 'Gemini':
+            llm = Gemini(model_path, api_key, proxy_url)
+        elif model_name == 'ChatGPT':
+            llm = ChatGPT(model_path, api_key=api_key)
+        elif model_name == 'Qwen':
+            llm = Qwen(self.mode, model_path)
+        return llm
+
+
+    def test_Qwen(self, question="如何应对压力？", model_path="Qwen/Qwen-1_8B-Chat"):
+        llm = Qwen(self.mode, model_path)
+        answer = llm.generate(question)
+        print(answer)
+
+    def test_Gemini(self, question="如何应对压力？", model_path='gemini-pro', api_key=None, proxy_url=None):
+        llm = Gemini(model_path, api_key, proxy_url)
+        answer = llm.chat(question)
+        print(answer)
+
+if __name__ == '__main__':
+    llm = LLM()
+    llm.test_Gemini(api_key='你的API Key', proxy_url=None)
+    # llm = LLM().init_model('Gemini', model_path= 'gemini-pro',api_key='AIzaSyBWAWfT8zsyAZcRIXLS5Vzlw8KKCN9qsAg', proxy_url='http://172.31.71.58:7890')
+    # response = llm.chat("如何应对压力？")
+    # print(response)

llm/Qwen.py

@@ -0,0 +1,37 @@
+import os
+import torch
+import requests
+from transformers import AutoModelForCausalLM, AutoTokenizer
+os.environ['CUDA_LAUNCH_BLOCKING'] = '1'
+
+class Qwen:
+    def __init__(self,  model_path="Qwen/Qwen-1_8B-Chat") -> None:
+        '''暂时不写api版本,与Linly-api相类似,感兴趣可以实现一下'''
+        self.model, self.tokenizer = self.init_model(model_path)
+    
+    def init_model(self, path = "Qwen/Qwen-1_8B-Chat"):
+        model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen-1_8B-Chat", 
+                                                     device_map="auto", 
+                                                     trust_remote_code=True).eval()
+        tokenizer = AutoTokenizer.from_pretrained(path, trust_remote_code=True)
+
+        return model, tokenizer   
+    
+    def chat(self, question):
+
+        self.data["question"] = f"{self.prompt} ### Instruction:{question}  ### Response:"
+        try:
+            response, history = self.model.chat(self.tokenizer, self.data["question"], history=None)
+            print(history)
+            return response
+        except:
+            return "对不起，你的请求出错了，请再次尝试。\nSorry, your request has encountered an error. Please try again.\n"
+
+    
+def test():
+    llm = Qwen(model_path="Qwen/Qwen-1_8B-Chat")
+    answer = llm.generate("如何应对压力？")
+    print(answer)
+
+if __name__ == '__main__':
+    test()