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IntelligenzaArtificiale
70 lines
2.0 KiB
Python
70 lines
2.0 KiB
Python
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from hugchat import hugchat
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from hugchat.login import Login
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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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from time import sleep
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class HuggingChat(LLM):
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history_data: Optional[List] = []
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chatbot : Optional[hugchat.ChatBot] = None
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conversation : Optional[str] = ""
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email : Optional[str]
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psw : Optional[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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pass
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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.chatbot is None:
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if self.email is None and self.psw is None:
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ValueError("Email and Password is required, pls check the documentation on github")
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else:
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if self.conversation == "":
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sign = Login(self.email, self.psw)
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cookies = sign.login()
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# Save cookies to usercookies/<email>.json
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sign.saveCookies()
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# Create a ChatBot
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self.chatbot = hugchat.ChatBot(cookies=cookies.get_dict())
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else:
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raise ValueError("Something went wrong")
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sleep(2)
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data = self.chatbot.chat(prompt, temperature=0.5, stream=False)
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#add to history
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self.history_data.append({"prompt":prompt,"response":data})
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return data
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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": "HuggingCHAT"}
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#llm = HuggingChat(cookiepath = "YOUR-COOKIES-PATH") #for start new chat
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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?")) #now memory work well
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