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IntelligenzaArtificiale
74 lines
2.5 KiB
Python
74 lines
2.5 KiB
Python
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from revChatGPT.V1 import Chatbot
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import requests
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from langchain.llms.base import LLM
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from typing import Optional, List, Mapping, Any
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import pydantic
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import os
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from langchain import PromptTemplate, LLMChain
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from time import sleep
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class ChatGPT(LLM):
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history_data: Optional[List] = []
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token : Optional[str]
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chatbot : Optional[Chatbot] = None
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call : int = 0
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conversation : str = ""
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prev_message : str = ""
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#### WARNING : for each api call this library will create a new chat on chat.openai.com
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@property
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def _llm_type(self) -> str:
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return "custom"
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def _call(self, prompt: str, stop: Optional[List[str]] = None) -> str:
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if stop is not None:
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raise ValueError("stop kwargs are not permitted.")
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#token is a must check
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if self.token is None:
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raise ValueError("Need a token , check https://chat.openai.com/api/auth/session for get your token")
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else:
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if self.conversation == "":
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self.chatbot = Chatbot(config={"access_token": self.token})
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else:
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if self.prev_message == "":
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self.chatbot = Chatbot(config={"access_token": self.token}, conversation_id=self.conversation)
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else:
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self.chatbot = Chatbot(config={"access_token": self.token}, conversation_id=self.conversation, parent_id=self.prev_message)
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response = ""
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# OpenAI: 50 requests / hour for each account
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if self.call >= 45:
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raise ValueError("You have reached the maximum number of requests per hour ! Help me to Improve. Abusing this tool is at your own risk")
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else:
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sleep(2)
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for data in self.chatbot.ask( prompt , conversation_id=self.conversation, parent_id=self.prev_message):
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response = data["message"]
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FullResponse = data
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self.conversation = FullResponse["conversation_id"]
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self.prev_message = FullResponse["parent_id"]
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self.call += 1
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#add to history
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self.history_data.append({"prompt":prompt,"response":response})
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return response
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@property
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def _identifying_params(self) -> Mapping[str, Any]:
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"""Get the identifying parameters."""
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return {"model": "CHatGPT", "token": self.token}
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#llm = ChatGPT(token = "YOUR_TOKEN")
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#print(llm("Hello, how are you?"))
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#print(llm("what is AI?"))
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#print(llm("Can you resume your previus answer?"))
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