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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"] |