mirror of
https://github.com/IntelligenzaArtificiale/Free-Auto-GPT.git
synced 2026-07-03 13:15:41 +02:00
IntelligenzaArtificiale
62 lines
1.6 KiB
Python
62 lines
1.6 KiB
Python
|
|
from hugchat import hugchat
|
|
import requests
|
|
from langchain.llms.base import LLM
|
|
from typing import Optional, List, Mapping, Any
|
|
import pydantic
|
|
import os
|
|
from langchain import PromptTemplate, LLMChain
|
|
from time import sleep
|
|
|
|
|
|
|
|
class HuggingChat(LLM):
|
|
|
|
history_data: Optional[List] = []
|
|
chatbot : Optional[hugchat.ChatBot] = None
|
|
conversation : Optional[str] = ""
|
|
|
|
#### WARNING : for each api call this library will create a new chat on chat.openai.com
|
|
|
|
|
|
@property
|
|
def _llm_type(self) -> str:
|
|
return "custom"
|
|
|
|
def _call(self, prompt: str, stop: Optional[List[str]] = None) -> str:
|
|
if stop is not None:
|
|
pass
|
|
#raise ValueError("stop kwargs are not permitted.")
|
|
#token is a must check
|
|
if self.chatbot is None:
|
|
if self.conversation == "":
|
|
self.chatbot = hugchat.ChatBot()
|
|
else:
|
|
raise ValueError("Something went wrong")
|
|
|
|
|
|
sleep(2)
|
|
data = self.chatbot.chat(prompt, temperature=0.5, stream=False)
|
|
#conversation_list = self.chatbot.get_conversation_list()
|
|
#print(conversation_list)
|
|
|
|
#add to history
|
|
self.history_data.append({"prompt":prompt,"response":data})
|
|
|
|
return data
|
|
|
|
@property
|
|
def _identifying_params(self) -> Mapping[str, Any]:
|
|
"""Get the identifying parameters."""
|
|
return {"model": "HuggingCHAT"}
|
|
|
|
|
|
|
|
#llm = HuggingChat() #for start new chat
|
|
|
|
|
|
#print(llm("Hello, how are you?"))
|
|
#print(llm("what is AI?"))
|
|
#print(llm("Can you resume your previus answer?")) #now memory work well
|
|
|