fix for 500 Internal Server Error #2199 [Request] Blackbox provider now support Gemini and LLaMa 3.1 models #2198 with some stuff from #2196

This commit is contained in:
zukixa 2024-08-28 23:03:32 -07:00
parent a338ed5883
commit bda2d67927
21 changed files with 366 additions and 297 deletions

View file

@ -2,16 +2,16 @@ from __future__ import annotations
import json, requests, re
from curl_cffi import requests as cf_reqs
from ..typing import CreateResult, Messages
from curl_cffi import requests as cf_reqs
from ..typing import CreateResult, Messages
from .base_provider import ProviderModelMixin, AbstractProvider
from .helper import format_prompt
from .helper import format_prompt
class HuggingChat(AbstractProvider, ProviderModelMixin):
url = "https://huggingface.co/chat"
working = True
url = "https://huggingface.co/chat"
working = True
supports_stream = True
default_model = "mistralai/Mixtral-8x7B-Instruct-v0.1"
default_model = "meta-llama/Meta-Llama-3.1-70B-Instruct"
models = [
'meta-llama/Meta-Llama-3.1-70B-Instruct',
'meta-llama/Meta-Llama-3.1-405B-Instruct-FP8',
@ -19,24 +19,41 @@ class HuggingChat(AbstractProvider, ProviderModelMixin):
'mistralai/Mixtral-8x7B-Instruct-v0.1',
'NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO',
'01-ai/Yi-1.5-34B-Chat',
'mistralai/Mistral-7B-Instruct-v0.2',
'mistralai/Mistral-7B-Instruct-v0.3',
'microsoft/Phi-3-mini-4k-instruct',
]
model_aliases = {
"mistralai/Mistral-7B-Instruct-v0.1": "mistralai/Mistral-7B-Instruct-v0.2"
"llama-3.1-70b": "meta-llama/Meta-Llama-3.1-70B-Instruct",
"llama-3.1-405b": "meta-llama/Meta-Llama-3.1-405B-Instruct-FP8",
"command-r-plus": "CohereForAI/c4ai-command-r-plus",
"mixtral-8x7b": "mistralai/Mixtral-8x7B-Instruct-v0.1",
"mixtral-8x7b": "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO",
"yi-1.5-34b": "01-ai/Yi-1.5-34B-Chat",
"mistral-7b": "mistralai/Mistral-7B-Instruct-v0.3",
"phi-3-mini-4k": "microsoft/Phi-3-mini-4k-instruct",
}
@classmethod
def get_model(cls, model: str) -> str:
if model in cls.models:
return model
elif model in cls.model_aliases:
return cls.model_aliases[model]
else:
return cls.default_model
@classmethod
def create_completion(
cls,
model: str,
messages: Messages,
stream: bool,
**kwargs) -> CreateResult:
if (model in cls.models) :
**kwargs
) -> CreateResult:
model = cls.get_model(model)
if model in cls.models:
session = cf_reqs.Session()
session.headers = {
'accept': '*/*',
@ -54,29 +71,24 @@ class HuggingChat(AbstractProvider, ProviderModelMixin):
'sec-fetch-site': 'same-origin',
'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36',
}
print(model)
json_data = {
'model': model,
}
response = session.post('https://huggingface.co/chat/conversation', json=json_data)
conversationId = response.json()['conversationId']
response = session.get(f'https://huggingface.co/chat/conversation/{conversationId}/__data.json?x-sveltekit-invalidated=01',)
data: list = (response.json())["nodes"][1]["data"]
keys: list[int] = data[data[0]["messages"]]
message_keys: dict = data[keys[0]]
messageId: str = data[message_keys["id"]]
settings = {
"inputs":format_prompt(messages),
"id":messageId,
"is_retry":False,
"is_continue":False,
"web_search":False,
"tools":[]
"inputs": format_prompt(messages),
"id": messageId,
"is_retry": False,
"is_continue": False,
"web_search": False,
"tools": []
}
headers = {
@ -96,9 +108,8 @@ class HuggingChat(AbstractProvider, ProviderModelMixin):
'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36',
}
files = {
'data': (None, json.dumps(settings, separators=(',', ':'))),
'data': (None, json.dumps(settings, separators=(',', ':'))),
}
response = requests.post(f'https://huggingface.co/chat/conversation/{conversationId}',
@ -106,7 +117,6 @@ class HuggingChat(AbstractProvider, ProviderModelMixin):
headers=headers,
files=files,
)
first_token = True
for line in response.iter_lines():
line = json.loads(line)
@ -119,11 +129,10 @@ class HuggingChat(AbstractProvider, ProviderModelMixin):
if first_token:
token = token.lstrip().replace('\u0000', '')
first_token = False
else:
token = token.replace('\u0000', '')
yield (token)
yield token
elif line["type"] == "finalAnswer":
break