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finnlp/large_language_models/openai/openai_chat_agent - Original.py

@@ -0,0 +1,51 @@
+import openai
+
+class Openai_Chat_Agent:
+    def __init__(self,args):
+        assert "token" in args.keys()
+        openai.api_key = args["token"]
+        
+        self.temperature = args["temperature"] if "temperature" in args.keys() else 1
+        self.top_p = args["top_p"] if "top_p" in args.keys() else 1
+        self.n = args["n"] if "n" in args.keys() else 1
+        self.max_tokens = args["max_tokens"] if "max_tokens" in args.keys() else None
+        self.presence_penalty = args["presence_penalty"] if "presence_penalty" in args.keys() else 0
+        self.frequency_penalty = args["frequency_penalty"] if "frequency_penalty" in args.keys() else 0
+        
+        self.conversation_list = []
+        if "init_prompt" in args.keys():
+            self.conversation_list.append(
+                {"role":"system","content":args["init_prompt"]}
+            )
+
+    def get_single_response(self,prompt):
+        self.conversation_list.append({"role":"user","content":prompt})
+        response = openai.ChatCompletion.create(
+            model = "gpt-3.5-turbo",
+            messages = self.conversation_list,
+            temperature = self.temperature,
+            top_p = self.top_p,
+            n = self.n,
+            max_tokens = self.max_tokens,
+            presence_penalty = self.presence_penalty,
+            frequency_penalty = self.frequency_penalty,
+        )
+        answer = response.choices[0].message['content']
+        self.conversation_list.append({"role":"assistant","content":answer})
+        return answer
+    
+    def show_conversation(self):
+        conversation_list = self.conversation_list
+        for msg in conversation_list:
+            content = msg['content']
+            content = content.replace(".",".\n")
+            if msg['role'] == 'user':
+                print(f"\U0001F47B: {content}\n")
+            elif msg['role'] == 'system':
+                print(f"\U0001F4BB: {content}\n")
+            else:
+                print(f"\U0001F916: {content}\n")
+
+    def get_multiple_response(self,prompts):
+        pass
+    

finnlp/large_language_models/openai/openai_chat_agent.py

@@ -0,0 +1,54 @@
+import openai
+
+class Openai_Chat_Agent:
+    def __init__(self,args):
+        assert "token" in args.keys()
+        openai.api_key = args["token"]
+        
+        self.temperature = args["temperature"] if "temperature" in args.keys() else 1
+        self.top_p = args["top_p"] if "top_p" in args.keys() else 1
+        self.n = args["n"] if "n" in args.keys() else 1
+        self.max_tokens = args["max_tokens"] if "max_tokens" in args.keys() else None
+        self.presence_penalty = args["presence_penalty"] if "presence_penalty" in args.keys() else 0
+        self.frequency_penalty = args["frequency_penalty"] if "frequency_penalty" in args.keys() else 0
+        
+        self.conversation_list = []
+        if "init_prompt" in args.keys():
+            self.conversation_list.append(
+                {"role":"system","content":args["init_prompt"]}
+            )
+
+    def get_single_response(self,prompt):
+        self.conversation_list.append({"role":"user","content":prompt})
+        response = openai.ChatCompletion.create(
+            model = "gpt-3.5-turbo",
+            messages = self.conversation_list,
+            temperature = self.temperature,
+            top_p = self.top_p,
+            n = self.n,
+            max_tokens = self.max_tokens,
+            presence_penalty = self.presence_penalty,
+            frequency_penalty = self.frequency_penalty,
+        )
+        answer = response.choices[0].message['content']
+        self.conversation_list.append({"role":"assistant","content":answer})
+        return answer
+    
+    def show_conversation(self):
+        conversation_list = self.conversation_list
+        res = ''
+        for msg in conversation_list:
+            content = msg['content']
+            content = content.replace(".",".\n")
+            if msg['role'] == 'user':
+                res = res + f"\U0001F47B: {content}\n"
+            elif msg['role'] == 'system':
+                res = res +  f"\U0001F4BB: {content}\n"
+            else:
+                res = res +  f"\U0001F916: {content}\n"
+
+        return res
+
+    def get_multiple_response(self,prompts):
+        pass
+    

finnlp/large_language_models/openai/openai_chat_agent_console_copy.py

@@ -0,0 +1,54 @@
+import openai
+
+class Openai_Chat_Agent:
+    def __init__(self,args):
+        assert "token" in args.keys()
+        openai.api_key = args["token"]
+        
+        self.temperature = args["temperature"] if "temperature" in args.keys() else 1
+        self.top_p = args["top_p"] if "top_p" in args.keys() else 1
+        self.n = args["n"] if "n" in args.keys() else 1
+        self.max_tokens = args["max_tokens"] if "max_tokens" in args.keys() else None
+        self.presence_penalty = args["presence_penalty"] if "presence_penalty" in args.keys() else 0
+        self.frequency_penalty = args["frequency_penalty"] if "frequency_penalty" in args.keys() else 0
+        
+        self.conversation_list = []
+        if "init_prompt" in args.keys():
+            self.conversation_list.append(
+                {"role":"system","content":args["init_prompt"]}
+            )
+
+    def get_single_response(self,prompt):
+        self.conversation_list.append({"role":"user","content":prompt})
+        response = openai.ChatCompletion.create(
+            model = "gpt-3.5-turbo",
+            messages = self.conversation_list,
+            temperature = self.temperature,
+            top_p = self.top_p,
+            n = self.n,
+            max_tokens = self.max_tokens,
+            presence_penalty = self.presence_penalty,
+            frequency_penalty = self.frequency_penalty,
+        )
+        answer = response.choices[0].message['content']
+        self.conversation_list.append({"role":"assistant","content":answer})
+        return answer
+    
+    def show_conversation(self):
+        conversation_list = self.conversation_list
+        res = ''
+        for msg in conversation_list:
+            content = msg['content']
+            content = content.replace(".",".\n")
+            if msg['role'] == 'user':
+                res = res + f"\U0001F47B: {content}\n"
+            elif msg['role'] == 'system':
+                res = res +  f"\U0001F4BB: {content}\n"
+            else:
+                res = res +  f"\U0001F916: {content}\n"
+
+        return res
+
+    def get_multiple_response(self,prompts):
+        pass
+