Merge pull request #1264 from hlohaus/any

Improve providers
This commit is contained in:
Tekky 2023-11-18 02:40:09 +00:00 committed by GitHub
commit ca3eaaffee
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
6 changed files with 231 additions and 96 deletions

View File

@ -11,6 +11,7 @@ from .. import debug
class AItianhuSpace(BaseProvider):
url = "https://chat3.aiyunos.top/"
working = True
supports_stream = True
supports_gpt_35_turbo = True
_domains = ["aitianhu.com", "aitianhu1.top"]

View File

@ -22,24 +22,24 @@ class PerplexityAi(BaseProvider):
timeout: int = 120,
browser: WebDriver = None,
copilot: bool = False,
headless: bool = True,
**kwargs
) -> CreateResult:
driver = browser if browser else get_browser("", headless, proxy)
driver = browser if browser else get_browser("", False, proxy)
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.keys import Keys
prompt = format_prompt(messages)
driver.get(f"{cls.url}/")
wait = WebDriverWait(driver, timeout)
# Page loaded?
# Is page loaded?
wait.until(EC.visibility_of_element_located((By.CSS_SELECTOR, "textarea[placeholder='Ask anything...']")))
# Add WebSocket hook
# Register WebSocket hook
script = """
window._message = window._last_message = "";
window._message_finished = false;
@ -57,8 +57,9 @@ WebSocket.prototype.send = function(...args) {
content = JSON.parse(content);
}
window._message = content["answer"];
window._message_finished = data[0] == "query_answered";
window._web_results = content["web_results"];
if (!window._message_finished) {
window._message_finished = data[0] == "query_answered";
}
}
}
});
@ -70,20 +71,19 @@ WebSocket.prototype.send = function(...args) {
if copilot:
try:
# Check account
# Check for account
driver.find_element(By.CSS_SELECTOR, "img[alt='User avatar']")
# Enable copilot
driver.find_element(By.CSS_SELECTOR, "button[data-testid='copilot-toggle']").click()
except:
raise RuntimeError("For copilot you needs a account")
raise RuntimeError("You need a account for copilot")
# Enter question
# Submit prompt
driver.find_element(By.CSS_SELECTOR, "textarea[placeholder='Ask anything...']").send_keys(prompt)
# Submit question
driver.find_element(By.CSS_SELECTOR, "button.bg-super svg[data-icon='arrow-right']").click()
driver.find_element(By.CSS_SELECTOR, "textarea[placeholder='Ask anything...']").send_keys(Keys.ENTER)
try:
# Yield response
# Stream response
script = """
if(window._message && window._message != window._last_message) {
try {

View File

@ -32,7 +32,7 @@ class Bard(BaseProvider):
try:
driver.get(f"{cls.url}/chat")
wait = WebDriverWait(driver, 10)
wait = WebDriverWait(driver, 10 if headless else 240)
wait.until(EC.visibility_of_element_located((By.CSS_SELECTOR, "div.ql-editor.textarea")))
except:
# Reopen browser for login
@ -61,14 +61,13 @@ XMLHttpRequest.prototype.open = function(method, url) {
"""
driver.execute_script(script)
# Input and submit prompt
# Submit prompt
driver.find_element(By.CSS_SELECTOR, "div.ql-editor.ql-blank.textarea").send_keys(prompt)
driver.find_element(By.CSS_SELECTOR, "button.send-button").click()
# Yield response
script = "return window._message;"
while True:
chunk = driver.execute_script(script)
chunk = driver.execute_script("return window._message;")
if chunk:
yield chunk
return

View File

@ -1,101 +1,158 @@
from __future__ import annotations
import json
import random
import requests
import time
from ...typing import Any, CreateResult, Messages
from ...typing import CreateResult, Messages
from ..base_provider import BaseProvider
from ..helper import format_prompt
from ..helper import WebDriver, format_prompt, get_browser
models = {
"theb-ai": "TheB.AI",
"theb-ai-free": "TheB.AI Free",
"gpt-3.5-turbo": "GPT-3.5 Turbo (New)",
"gpt-3.5-turbo-16k": "GPT-3.5-16K",
"gpt-4-turbo": "GPT-4 Turbo",
"gpt-4": "GPT-4",
"gpt-4-32k": "GPT-4 32K",
"claude-2": "Claude 2",
"claude-instant-1": "Claude Instant 1.2",
"palm-2": "PaLM 2",
"palm-2-32k": "PaLM 2 32K",
"palm-2-codey": "Codey",
"palm-2-codey-32k": "Codey 32K",
"vicuna-13b-v1.5": "Vicuna v1.5 13B",
"llama-2-7b-chat": "Llama 2 7B",
"llama-2-13b-chat": "Llama 2 13B",
"llama-2-70b-chat": "Llama 2 70B",
"code-llama-7b": "Code Llama 7B",
"code-llama-13b": "Code Llama 13B",
"code-llama-34b": "Code Llama 34B",
"qwen-7b-chat": "Qwen 7B"
}
class Theb(BaseProvider):
url = "https://theb.ai"
working = True
supports_stream = True
supports_gpt_35_turbo = True
needs_auth = True
url = "https://beta.theb.ai"
working = True
supports_gpt_35_turbo = True
supports_gpt_4 = True
supports_stream = True
@staticmethod
@classmethod
def create_completion(
cls,
model: str,
messages: Messages,
stream: bool,
proxy: str = None,
browser: WebDriver = None,
headless: bool = True,
**kwargs
) -> CreateResult:
auth = kwargs.get("auth", {
"bearer_token":"free",
"org_id":"theb",
})
if model in models:
model = models[model]
prompt = format_prompt(messages)
driver = browser if browser else get_browser(None, headless, proxy)
bearer_token = auth["bearer_token"]
org_id = auth["org_id"]
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.keys import Keys
headers = {
'authority': 'beta.theb.ai',
'accept': 'text/event-stream',
'accept-language': 'id-ID,id;q=0.9,en-US;q=0.8,en;q=0.7',
'authorization': f'Bearer {bearer_token}',
'content-type': 'application/json',
'origin': 'https://beta.theb.ai',
'referer': 'https://beta.theb.ai/home',
'sec-ch-ua': '"Chromium";v="116", "Not)A;Brand";v="24", "Google Chrome";v="116"',
'sec-ch-ua-mobile': '?0',
'sec-ch-ua-platform': '"Windows"',
'sec-fetch-dest': 'empty',
'sec-fetch-mode': 'cors',
'sec-fetch-site': 'same-origin',
'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36',
'x-ai-model': 'ee8d4f29cb7047f78cbe84313ed6ace8',
try:
driver.get(f"{cls.url}/home")
wait = WebDriverWait(driver, 10 if headless else 240)
wait.until(EC.visibility_of_element_located((By.TAG_NAME, "body")))
time.sleep(0.1)
try:
driver.find_element(By.CSS_SELECTOR, ".driver-overlay").click()
driver.find_element(By.CSS_SELECTOR, ".driver-overlay").click()
except:
pass
if model:
# Load model panel
wait.until(EC.visibility_of_element_located((By.CSS_SELECTOR, "#SelectModel svg")))
time.sleep(0.1)
driver.find_element(By.CSS_SELECTOR, "#SelectModel svg").click()
try:
driver.find_element(By.CSS_SELECTOR, ".driver-overlay").click()
driver.find_element(By.CSS_SELECTOR, ".driver-overlay").click()
except:
pass
# Select model
selector = f"div.flex-col div.items-center span[title='{model}']"
wait.until(EC.visibility_of_element_located((By.CSS_SELECTOR, selector)))
span = driver.find_element(By.CSS_SELECTOR, selector)
container = span.find_element(By.XPATH, "//div/../..")
button = container.find_element(By.CSS_SELECTOR, "button.btn-blue.btn-small.border")
button.click()
# Register fetch hook
script = """
window._fetch = window.fetch;
window.fetch = (url, options) => {
// Call parent fetch method
const result = window._fetch(url, options);
if (!url.startsWith("/api/conversation")) {
return result;
}
// Load response reader
result.then((response) => {
if (!response.body.locked) {
window._reader = response.body.getReader();
}
});
// Return dummy response
return new Promise((resolve, reject) => {
resolve(new Response(new ReadableStream()))
});
}
window._last_message = "";
"""
driver.execute_script(script)
req_rand = random.randint(100000000, 9999999999)
# Submit prompt
wait.until(EC.visibility_of_element_located((By.ID, "textareaAutosize")))
driver.find_element(By.ID, "textareaAutosize").send_keys(prompt)
driver.find_element(By.ID, "textareaAutosize").send_keys(Keys.ENTER)
json_data: dict[str, Any] = {
"text" : format_prompt(messages),
"category" : "04f58f64a4aa4191a957b47290fee864",
"model" : "ee8d4f29cb7047f78cbe84313ed6ace8",
"model_params": {
"system_prompt" : "You are ChatGPT, a large language model trained by OpenAI, based on the GPT-3.5 architecture.\nKnowledge cutoff: 2021-09\nCurrent date: {{YYYY-MM-DD}}",
"temperature" : kwargs.get("temperature", 1),
"top_p" : kwargs.get("top_p", 1),
"frequency_penalty" : kwargs.get("frequency_penalty", 0),
"presence_penalty" : kwargs.get("presence_penalty", 0),
"long_term_memory" : "auto"
}
# Read response with reader
script = """
if(window._reader) {
chunk = await window._reader.read();
if (chunk['done']) {
return null;
}
text = (new TextDecoder()).decode(chunk['value']);
message = '';
text.split('\\r\\n').forEach((line, index) => {
if (line.startsWith('data: ')) {
try {
line = JSON.parse(line.substring('data: '.length));
message = line["args"]["content"];
} catch(e) { }
}
response = requests.post(
f"https://beta.theb.ai/api/conversation?org_id={org_id}&req_rand={req_rand}",
headers=headers,
json=json_data,
stream=True,
proxies={"https": proxy}
)
response.raise_for_status()
content = ""
next_content = ""
for chunk in response.iter_lines():
if b"content" in chunk:
next_content = content
data = json.loads(chunk.decode().split("data: ")[1])
content = data["content"]
yield content.replace(next_content, "")
@classmethod
@property
def params(cls):
params = [
("model", "str"),
("messages", "list[dict[str, str]]"),
("auth", "list[dict[str, str]]"),
("stream", "bool"),
("temperature", "float"),
("presence_penalty", "int"),
("frequency_penalty", "int"),
("top_p", "int")
]
param = ", ".join([": ".join(p) for p in params])
return f"g4f.provider.{cls.__name__} supports: ({param})"
});
if (message) {
try {
return message.substring(window._last_message.length);
} finally {
window._last_message = message;
}
}
}
return '';
"""
while True:
chunk = driver.execute_script(script)
if chunk:
yield chunk
elif chunk != "":
break
else:
time.sleep(0.1)
finally:
if not browser:
driver.close()
time.sleep(0.1)
driver.quit()

View File

@ -0,0 +1,77 @@
from __future__ import annotations
import requests
from ...typing import Any, CreateResult, Messages
from ..base_provider import BaseProvider
models = {
"theb-ai": "TheB.AI",
"gpt-3.5-turbo": "GPT-3.5",
"gpt-3.5-turbo-16k": "GPT-3.5-16K",
"gpt-4-turbo": "GPT-4 Turbo",
"gpt-4": "GPT-4",
"gpt-4-32k": "GPT-4 32K",
"claude-2": "Claude 2",
"claude-1": "Claude",
"claude-1-100k": "Claude 100K",
"claude-instant-1": "Claude Instant",
"claude-instant-1-100k": "Claude Instant 100K",
"palm-2": "PaLM 2",
"palm-2-codey": "Codey",
"vicuna-13b-v1.5": "Vicuna v1.5 13B",
"llama-2-7b-chat": "Llama 2 7B",
"llama-2-13b-chat": "Llama 2 13B",
"llama-2-70b-chat": "Llama 2 70B",
"code-llama-7b": "Code Llama 7B",
"code-llama-13b": "Code Llama 13B",
"code-llama-34b": "Code Llama 34B",
"qwen-7b-chat": "Qwen 7B"
}
class ThebApi(BaseProvider):
url = "https://theb.ai"
working = True
needs_auth = True
@staticmethod
def create_completion(
model: str,
messages: Messages,
stream: bool,
auth: str,
proxy: str = None,
**kwargs
) -> CreateResult:
if model and model not in models:
raise ValueError(f"Model are not supported: {model}")
headers = {
'accept': 'application/json',
'authorization': f'Bearer {auth}',
'content-type': 'application/json',
}
# response = requests.get("https://api.baizhi.ai/v1/models", headers=headers).json()["data"]
# models = dict([(m["id"], m["name"]) for m in response])
# print(json.dumps(models, indent=4))
data: dict[str, Any] = {
"model": model if model else "gpt-3.5-turbo",
"messages": messages,
"stream": False,
"model_params": {
"system_prompt": kwargs.get("system_message", "You are ChatGPT, a large language model trained by OpenAI, based on the GPT-3.5 architecture."),
"temperature": 1,
"top_p": 1,
**kwargs
}
}
response = requests.post(
"https://api.theb.ai/v1/chat/completions",
headers=headers,
json=data,
proxies={"https": proxy}
)
try:
response.raise_for_status()
yield response.json()["choices"][0]["message"]["content"]
except:
raise RuntimeError(f"Response: {next(response.iter_lines()).decode()}")

View File

@ -1,6 +1,7 @@
from .Bard import Bard
from .Raycast import Raycast
from .Theb import Theb
from .ThebApi import ThebApi
from .HuggingChat import HuggingChat
from .OpenaiChat import OpenaiChat
from .OpenAssistant import OpenAssistant