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finnlp/large_language_models/openai/__pycache__/__init__.cpython-310.pyc ADDED
Binary file (185 Bytes). View file
 
finnlp/large_language_models/openai/__pycache__/openai_chat_agent.cpython-310.pyc ADDED
Binary file (1.98 kB). View file
 
finnlp/large_language_models/openai/__pycache__/openai_chat_agent_console_copy.cpython-310.pyc ADDED
Binary file (1.99 kB). View file
 
finnlp/large_language_models/openai/openai_chat_agent - Original.py ADDED
@@ -0,0 +1,51 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ import openai
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+
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+ class Openai_Chat_Agent:
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+ def __init__(self,args):
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+ assert "token" in args.keys()
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+ openai.api_key = args["token"]
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+
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+ self.temperature = args["temperature"] if "temperature" in args.keys() else 1
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+ self.top_p = args["top_p"] if "top_p" in args.keys() else 1
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+ self.n = args["n"] if "n" in args.keys() else 1
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+ self.max_tokens = args["max_tokens"] if "max_tokens" in args.keys() else None
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+ self.presence_penalty = args["presence_penalty"] if "presence_penalty" in args.keys() else 0
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+ self.frequency_penalty = args["frequency_penalty"] if "frequency_penalty" in args.keys() else 0
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+
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+ self.conversation_list = []
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+ if "init_prompt" in args.keys():
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+ self.conversation_list.append(
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+ {"role":"system","content":args["init_prompt"]}
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+ )
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+
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+ def get_single_response(self,prompt):
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+ self.conversation_list.append({"role":"user","content":prompt})
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+ response = openai.ChatCompletion.create(
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+ model = "gpt-3.5-turbo",
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+ messages = self.conversation_list,
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+ temperature = self.temperature,
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+ top_p = self.top_p,
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+ n = self.n,
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+ max_tokens = self.max_tokens,
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+ presence_penalty = self.presence_penalty,
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+ frequency_penalty = self.frequency_penalty,
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+ )
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+ answer = response.choices[0].message['content']
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+ self.conversation_list.append({"role":"assistant","content":answer})
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+ return answer
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+
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+ def show_conversation(self):
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+ conversation_list = self.conversation_list
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+ for msg in conversation_list:
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+ content = msg['content']
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+ content = content.replace(".",".\n")
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+ if msg['role'] == 'user':
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+ print(f"\U0001F47B: {content}\n")
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+ elif msg['role'] == 'system':
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+ print(f"\U0001F4BB: {content}\n")
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+ else:
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+ print(f"\U0001F916: {content}\n")
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+
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+ def get_multiple_response(self,prompts):
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+ pass
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+
finnlp/large_language_models/openai/openai_chat_agent.py ADDED
@@ -0,0 +1,54 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ import openai
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+
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+ class Openai_Chat_Agent:
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+ def __init__(self,args):
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+ assert "token" in args.keys()
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+ openai.api_key = args["token"]
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+
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+ self.temperature = args["temperature"] if "temperature" in args.keys() else 1
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+ self.top_p = args["top_p"] if "top_p" in args.keys() else 1
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+ self.n = args["n"] if "n" in args.keys() else 1
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+ self.max_tokens = args["max_tokens"] if "max_tokens" in args.keys() else None
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+ self.presence_penalty = args["presence_penalty"] if "presence_penalty" in args.keys() else 0
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+ self.frequency_penalty = args["frequency_penalty"] if "frequency_penalty" in args.keys() else 0
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+
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+ self.conversation_list = []
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+ if "init_prompt" in args.keys():
17
+ self.conversation_list.append(
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+ {"role":"system","content":args["init_prompt"]}
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+ )
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+
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+ def get_single_response(self,prompt):
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+ self.conversation_list.append({"role":"user","content":prompt})
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+ response = openai.ChatCompletion.create(
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+ model = "gpt-3.5-turbo",
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+ messages = self.conversation_list,
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+ temperature = self.temperature,
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+ top_p = self.top_p,
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+ n = self.n,
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+ max_tokens = self.max_tokens,
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+ presence_penalty = self.presence_penalty,
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+ frequency_penalty = self.frequency_penalty,
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+ )
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+ answer = response.choices[0].message['content']
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+ self.conversation_list.append({"role":"assistant","content":answer})
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+ return answer
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+
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+ def show_conversation(self):
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+ conversation_list = self.conversation_list
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+ res = ''
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+ for msg in conversation_list:
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+ content = msg['content']
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+ content = content.replace(".",".\n")
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+ if msg['role'] == 'user':
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+ res = res + f"\U0001F47B: {content}\n"
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+ elif msg['role'] == 'system':
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+ res = res + f"\U0001F4BB: {content}\n"
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+ else:
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+ res = res + f"\U0001F916: {content}\n"
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+
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+ return res
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+
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+ def get_multiple_response(self,prompts):
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+ pass
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+
finnlp/large_language_models/openai/openai_chat_agent_console_copy.py ADDED
@@ -0,0 +1,54 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import openai
2
+
3
+ class Openai_Chat_Agent:
4
+ def __init__(self,args):
5
+ assert "token" in args.keys()
6
+ openai.api_key = args["token"]
7
+
8
+ self.temperature = args["temperature"] if "temperature" in args.keys() else 1
9
+ self.top_p = args["top_p"] if "top_p" in args.keys() else 1
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+ self.n = args["n"] if "n" in args.keys() else 1
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+ self.max_tokens = args["max_tokens"] if "max_tokens" in args.keys() else None
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+ self.presence_penalty = args["presence_penalty"] if "presence_penalty" in args.keys() else 0
13
+ self.frequency_penalty = args["frequency_penalty"] if "frequency_penalty" in args.keys() else 0
14
+
15
+ self.conversation_list = []
16
+ if "init_prompt" in args.keys():
17
+ self.conversation_list.append(
18
+ {"role":"system","content":args["init_prompt"]}
19
+ )
20
+
21
+ def get_single_response(self,prompt):
22
+ self.conversation_list.append({"role":"user","content":prompt})
23
+ response = openai.ChatCompletion.create(
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+ model = "gpt-3.5-turbo",
25
+ messages = self.conversation_list,
26
+ temperature = self.temperature,
27
+ top_p = self.top_p,
28
+ n = self.n,
29
+ max_tokens = self.max_tokens,
30
+ presence_penalty = self.presence_penalty,
31
+ frequency_penalty = self.frequency_penalty,
32
+ )
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+ answer = response.choices[0].message['content']
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+ self.conversation_list.append({"role":"assistant","content":answer})
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+ return answer
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+
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+ def show_conversation(self):
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+ conversation_list = self.conversation_list
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+ res = ''
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+ for msg in conversation_list:
41
+ content = msg['content']
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+ content = content.replace(".",".\n")
43
+ if msg['role'] == 'user':
44
+ res = res + f"\U0001F47B: {content}\n"
45
+ elif msg['role'] == 'system':
46
+ res = res + f"\U0001F4BB: {content}\n"
47
+ else:
48
+ res = res + f"\U0001F916: {content}\n"
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+
50
+ return res
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+
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+ def get_multiple_response(self,prompts):
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+ pass
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+