import time import uuid from selenium import webdriver from selenium.webdriver.chrome.options import Options from selenium.webdriver.common.by import By from selenium.webdriver.support import expected_conditions as EC from selenium.webdriver.support.ui import WebDriverWait import click import requests from requests import get from uuid import uuid4 from re import findall from requests.exceptions import RequestException from curl_cffi.requests import get, RequestsError import g4f from random import randint from PIL import Image import io import re import json import yaml from ..AIutel import Optimizers from ..AIutel import Conversation from ..AIutel import AwesomePrompts, sanitize_stream from ..AIbase import Provider, AsyncProvider from Helpingai_T2 import Perplexity from webscout import exceptions from typing import Any, AsyncGenerator, Dict import logging import httpx #-----------------------------------------------Cohere-------------------------------------------- class Cohere(Provider): def __init__( self, api_key: str, is_conversation: bool = True, max_tokens: int = 600, model: str = "command-r-plus", temperature: float = 0.7, system_prompt: str = "You are helpful AI", timeout: int = 30, intro: str = None, filepath: str = None, update_file: bool = True, proxies: dict = {}, history_offset: int = 10250, act: str = None, top_k: int = -1, top_p: float = 0.999, ): """Initializes Cohere Args: api_key (str): Cohere API key. is_conversation (bool, optional): Flag for chatting conversationally. Defaults to True. max_tokens (int, optional): Maximum number of tokens to be generated upon completion. Defaults to 600. model (str, optional): Model to use for generating text. Defaults to "command-r-plus". temperature (float, optional): Diversity of the generated text. Higher values produce more diverse outputs. Defaults to 0.7. system_prompt (str, optional): A system_prompt or context to set the style or tone of the generated text. Defaults to "You are helpful AI". timeout (int, optional): Http request timeout. Defaults to 30. intro (str, optional): Conversation introductory prompt. Defaults to None. filepath (str, optional): Path to file containing conversation history. Defaults to None. update_file (bool, optional): Add new prompts and responses to the file. Defaults to True. proxies (dict, optional): Http request proxies. Defaults to {}. history_offset (int, optional): Limit conversation history to this number of last texts. Defaults to 10250. act (str|int, optional): Awesome prompt key or index. (Used as intro). Defaults to None. """ self.session = requests.Session() self.is_conversation = is_conversation self.max_tokens_to_sample = max_tokens self.api_key = api_key self.model = model self.temperature = temperature self.system_prompt = system_prompt self.chat_endpoint = "https://production.api.os.cohere.ai/coral/v1/chat" self.stream_chunk_size = 64 self.timeout = timeout self.last_response = {} self.headers = { "Content-Type": "application/json", "Authorization": f"Bearer {self.api_key}", } self.__available_optimizers = ( method for method in dir(Optimizers) if callable(getattr(Optimizers, method)) and not method.startswith("__") ) self.session.headers.update(self.headers) Conversation.intro = ( AwesomePrompts().get_act( act, raise_not_found=True, default=None, case_insensitive=True ) if act else intro or Conversation.intro ) self.conversation = Conversation( is_conversation, self.max_tokens_to_sample, filepath, update_file ) self.conversation.history_offset = history_offset self.session.proxies = proxies def ask( self, prompt: str, stream: bool = False, raw: bool = False, optimizer: str = None, conversationally: bool = False, ) -> dict: """Chat with AI Args: prompt (str): Prompt to be send. stream (bool, optional): Flag for streaming response. Defaults to False. raw (bool, optional): Stream back raw response as received. Defaults to False. optimizer (str, optional): Prompt optimizer name - `[code, shell_command]`. Defaults to None. conversationally (bool, optional): Chat conversationally when using optimizer. Defaults to False. Returns: dict : {} ```json { "text" : "How may I assist you today?" } ``` """ conversation_prompt = self.conversation.gen_complete_prompt(prompt) if optimizer: if optimizer in self.__available_optimizers: conversation_prompt = getattr(Optimizers, optimizer)( conversation_prompt if conversationally else prompt ) else: raise Exception( f"Optimizer is not one of {self.__available_optimizers}" ) self.session.headers.update(self.headers) payload = { "message": conversation_prompt, "model": self.model, "temperature": self.temperature, "preamble": self.system_prompt, } def for_stream(): response = self.session.post( self.chat_endpoint, json=payload, stream=True, timeout=self.timeout ) if not response.ok: raise Exception( f"Failed to generate response - ({response.status_code}, {response.reason}) - {response.text}" ) for value in response.iter_lines( decode_unicode=True, chunk_size=self.stream_chunk_size, ): try: resp = json.loads(value.strip().split("\n")[-1]) self.last_response.update(resp) yield value if raw else resp except json.decoder.JSONDecodeError: pass self.conversation.update_chat_history( prompt, self.get_message(self.last_response) ) def for_non_stream(): # let's make use of stream for _ in for_stream(): pass return self.last_response return for_stream() if stream else for_non_stream() def chat( self, prompt: str, stream: bool = False, optimizer: str = None, conversationally: bool = False, ) -> str: """Generate response `str` Args: prompt (str): Prompt to be send. stream (bool, optional): Flag for streaming response. Defaults to False. optimizer (str, optional): Prompt optimizer name - `[code, shell_command]`. Defaults to None. conversationally (bool, optional): Chat conversationally when using optimizer. Defaults to False. Returns: str: Response generated """ def for_stream(): for response in self.ask( prompt, True, optimizer=optimizer, conversationally=conversationally ): yield self.get_message(response) def for_non_stream(): return self.get_message( self.ask( prompt, False, optimizer=optimizer, conversationally=conversationally, ) ) return for_stream() if stream else for_non_stream() def get_message(self, response: dict) -> str: """Retrieves message only from response Args: response (dict): Response generated by `self.ask` Returns: str: Message extracted """ assert isinstance(response, dict), "Response should be of dict data-type only" return response["result"]["chatStreamEndEvent"]["response"]["text"]