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https://github.com/IntelligenzaArtificiale/Free-Auto-GPT.git
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IntelligenzaArtificiale
105 lines
7.2 KiB
Python
105 lines
7.2 KiB
Python
from EdgeGPT import Chatbot, ConversationStyle
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import asyncio
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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 BingChat(LLM):
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history_data: Optional[List] = []
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cookiepath : Optional[str]
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chatbot : Optional[Chatbot] = None
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conversation_style : Optional[str]
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conversation_style_on : Optional[ConversationStyle] = ConversationStyle.precise
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search_result : Optional[bool] = False
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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 select_conversation(self, conversation_style: str):
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if conversation_style == "precise":
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self.conversation_style_on = ConversationStyle.precise
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elif conversation_style == "creative":
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self.conversation_style_on = ConversationStyle.creative
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elif conversation_style == "balanced":
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self.conversation_style_on = ConversationStyle.balanced
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else:
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raise ValueError("conversation_style must be precise, creative or balaced")
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self.conversation_style = conversation_style
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async 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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#cookiepath is a must check
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if self.chatbot is None:
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if self.cookiepath is None:
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raise ValueError("Need a COOKIE , check https://github.com/acheong08/EdgeGPT/tree/master#getting-authentication-required for get your COOKIE AND SAVE")
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else:
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#if self.chatbot == None:
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self.chatbot = await Chatbot.create(cookie_path=self.cookiepath)
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if self.conversation_style is not None:
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self.conversation_style_on = self.select_conversation(self.conversation_style)
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response = await self.chatbot.ask(prompt=prompt, conversation_style=self.conversation_style, search_result=self.search_result)
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"""
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this is a sample response.
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{'type': 2, 'invocationId': '0',
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'item': {'messages': [{'text': 'Hello, how are you?', 'author': 'user', 'from': {'id': '985157152860707', 'name': None}, 'createdAt': '2023-05-03T19:51:39.5491558+00:00', 'timestamp': '2023-05-03T19:51:39.5455787+00:00', 'locale': 'en-us', 'market': 'en-us', 'region': 'us', 'messageId': '87f90c57-b2ad-4b3a-b24f-99f633f5332f', 'requestId': '87f90c57-b2ad-4b3a-b24f-99f633f5332f', 'nlu': {'scoredClassification': {'classification': 'CHAT_GPT', 'score': None}, 'classificationRanking': [{'classification': 'CHAT_GPT', 'score': None}], 'qualifyingClassifications': None, 'ood': None, 'metaData': None, 'entities': None}, 'offense': 'None', 'feedback': {'tag': None, 'updatedOn': None, 'type': 'None'}, 'contentOrigin': 'cib', 'privacy': None, 'inputMethod': 'Keyboard'}, {'text': "Hello! I'm doing well, thank you. How can I assist you today?", 'author': 'bot', 'createdAt': '2023-05-03T19:51:41.5176164+00:00', 'timestamp': '2023-05-03T19:51:41.5176164+00:00', 'messageId': '1d013e71-408b-4031-a131-2f5c009fe938', 'requestId': '87f90c57-b2ad-4b3a-b24f-99f633f5332f', 'offense': 'None', 'adaptiveCards': [{'type': 'AdaptiveCard', 'version': '1.0', 'body': [{'type': 'TextBlock', 'text': "Hello! I'm doing well, thank you. How can I assist you today?\n", 'wrap': True}]}],
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'sourceAttributions': [],
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'feedback': {'tag': None, 'updatedOn': None, 'type': 'None'},
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'contentOrigin': 'DeepLeo',
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'privacy': None,
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'suggestedResponses': [{'text': 'What is the weather like today?', 'author': 'user', 'createdAt': '2023-05-03T19:51:42.7502696+00:00', 'timestamp': '2023-05-03T19:51:42.7502696+00:00', 'messageId': 'cd7a84d3-f9bc-47ff-9897-077b2de12e21', 'messageType': 'Suggestion', 'offense': 'Unknown', 'feedback': {'tag': None, 'updatedOn': None, 'type': 'None'}, 'contentOrigin': 'DeepLeo', 'privacy': None}, {'text': 'What is the latest news?', 'author': 'user', 'createdAt': '2023-05-03T19:51:42.7502739+00:00', 'timestamp': '2023-05-03T19:51:42.7502739+00:00', 'messageId': 'b611632a-9a8e-42de-86eb-8eb3b7b8ddbb', 'messageType': 'Suggestion', 'offense': 'Unknown', 'feedback': {'tag': None, 'updatedOn': None, 'type': 'None'}, 'contentOrigin': 'DeepLeo', 'privacy': None}, {'text': 'Tell me a joke.', 'author': 'user', 'createdAt': '2023-05-03T19:51:42.7502743+00:00', 'timestamp': '2023-05-03T19:51:42.7502743+00:00', 'messageId': '70232e45-d7e8-4d77-83fc-752b3cd3355c', 'messageType': 'Suggestion', 'offense': 'Unknown', 'feedback': {'tag': None, 'updatedOn': None, 'type': 'None'}, 'contentOrigin': 'DeepLeo', 'privacy': None}], 'spokenText': 'How can I assist you today?'}], 'firstNewMessageIndex': 1, 'defaultChatName': None, 'conversationId': '51D|BingProd|3E1274E188350D7BE273FFE95E02DD2984DAB52F95260300D0A2937162F98FDA', 'requestId': '87f90c57-b2ad-4b3a-b24f-99f633f5332f', 'conversationExpiryTime': '2023-05-04T01:51:42.8260286Z', 'shouldInitiateConversation': True, 'telemetry': {'metrics': None, 'startTime': '2023-05-03T19:51:39.5456555Z'}, 'throttling': {'maxNumUserMessagesInConversation': 20, 'numUserMessagesInConversation': 1}, 'result': {'value': 'Success', 'serviceVersion': '20230501.30'}}}
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"""
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response_messages = response.get("item", {}).get("messages", [])
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response_text = response_messages[1].get("text", "")
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if response_text == "":
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hidden_text = response_messages[1].get("hiddenText", "")
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print(">>>> [DEBBUGGER] hidden_text = " + str(hidden_text) + " [DEBBUGGER] <<<<")
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print(">>>> [DEBBUGGER] BING CHAT dont is open Like CHATGPT , BingCHAT have refused to respond. [DEBBUGGER] <<<<")
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response_text = hidden_text
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"""
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# reset the chatbot and remake the call
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print("[DEBUGGER] Chatbot failed to respond. Resetting and trying again. [DEBUGGER]")
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print("[ INFO DEBUGGER ] \n<Response>\n" + str(response) + "\n</Response>\n\n")
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sleep(10)
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self.chatbot = await Chatbot.create(cookie_path=self.cookiepath)
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sleep(2)
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response = await self.chatbot.ask(prompt=prompt)
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response_messages = response.get("item", {}).get("messages", [])
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response_text = response_messages[1].get("text", "")
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"""
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#add to history
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self.history_data.append({"prompt":prompt,"response":response_text})
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return response_text
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def _call(self, prompt: str, stop: Optional[List[str]] = None) -> str:
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return asyncio.run(self.call(prompt=prompt))
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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": "BingCHAT", "cookiepath": self.cookiepath}
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#llm = BingChat(cookiepath = "YOUR-COOKIE") #for start new chat
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#llm = BingChat(cookiepath = "YOUR-COOKIE", conversation_style = "precise") #precise, creative or balaced
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#llm = BingChat(cookiepath = "YOUR-COOKIE" , conversation_style = "precise" , search_result=True) #with web access
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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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