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Husnain
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•
2f7e54b
1
Parent(s):
d860ba7
🔨 [WIP] Enabling get_message_id
Browse files- networks/huggingchat_streamer.py +153 -7
networks/huggingchat_streamer.py
CHANGED
@@ -1,8 +1,10 @@
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import json
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import re
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import requests
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-
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from tclogger import logger
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from transformers import AutoTokenizer
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@@ -13,7 +15,11 @@ from constants.models import (
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TOKEN_RESERVED,
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)
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from constants.envs import PROXIES
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from constants.
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from messagers.message_outputer import OpenaiStreamOutputer
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@@ -25,7 +31,6 @@ class HuggingchatStreamer:
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self.model = "mixtral-8x7b"
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self.model_fullname = MODEL_MAP[self.model]
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self.message_outputer = OpenaiStreamOutputer(model=self.model)
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-
# export HF_ENDPOINT=https://hf-mirror.com
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self.tokenizer = AutoTokenizer.from_pretrained(self.model_fullname)
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def count_tokens(self, text):
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@@ -34,16 +39,46 @@ class HuggingchatStreamer:
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logger.note(f"Prompt Token Count: {token_count}")
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return token_count
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def get_conversation_id(self, preprompt: str = ""):
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request_url = "https://huggingface.co/chat/conversation"
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request_body = {
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"model": self.model_fullname,
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"preprompt": preprompt,
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}
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logger.note(f"> Conversation ID:", end=" ")
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res = requests.post(
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request_url,
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headers=
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json=request_body,
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proxies=PROXIES,
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timeout=10,
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@@ -55,6 +90,86 @@ class HuggingchatStreamer:
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logger.warn(f"[{res.status_code}]")
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raise ValueError("Failed to get conversation ID!")
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self.conversation_id = conversation_id
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def chat_response(
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self,
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@@ -65,7 +180,37 @@ class HuggingchatStreamer:
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api_key: str = None,
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use_cache: bool = False,
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):
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-
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def chat_return_dict(self, stream_response):
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pass
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@@ -76,5 +221,6 @@ class HuggingchatStreamer:
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if __name__ == "__main__":
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streamer = HuggingchatStreamer(model="mixtral-8x7b")
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-
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-
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import copy
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import json
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import re
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import requests
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import uuid
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# from curl_cffi import requests
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from tclogger import logger
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from transformers import AutoTokenizer
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TOKEN_RESERVED,
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)
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from constants.envs import PROXIES
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from constants.headers import (
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REQUESTS_HEADERS,
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HUGGINGCHAT_POST_HEADERS,
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HUGGINGCHAT_SETTINGS_POST_DATA,
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)
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from messagers.message_outputer import OpenaiStreamOutputer
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self.model = "mixtral-8x7b"
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self.model_fullname = MODEL_MAP[self.model]
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self.message_outputer = OpenaiStreamOutputer(model=self.model)
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self.tokenizer = AutoTokenizer.from_pretrained(self.model_fullname)
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def count_tokens(self, text):
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logger.note(f"Prompt Token Count: {token_count}")
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return token_count
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def get_hf_chat_id(self):
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request_url = "https://huggingface.co/chat/settings"
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request_body = copy.deepcopy(HUGGINGCHAT_SETTINGS_POST_DATA)
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extra_body = {
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"activeModel": self.model_fullname,
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}
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request_body.update(extra_body)
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logger.note(f"> hf-chat ID:", end=" ")
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res = requests.post(
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request_url,
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headers=HUGGINGCHAT_POST_HEADERS,
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json=request_body,
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proxies=PROXIES,
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timeout=10,
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)
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self.hf_chat_id = res.cookies.get("hf-chat")
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if self.hf_chat_id:
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logger.success(f"[{self.hf_chat_id}]")
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else:
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logger.warn(f"[{res.status_code}]")
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logger.warn(res.text)
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raise ValueError("Failed to get hf-chat ID!")
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def get_conversation_id(self, preprompt: str = ""):
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request_url = "https://huggingface.co/chat/conversation"
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request_headers = HUGGINGCHAT_POST_HEADERS
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extra_headers = {
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"Cookie": f"hf-chat={self.hf_chat_id}",
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}
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request_headers.update(extra_headers)
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request_body = {
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"model": self.model_fullname,
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"preprompt": preprompt,
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}
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logger.note(f"> Conversation ID:", end=" ")
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res = requests.post(
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request_url,
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headers=request_headers,
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json=request_body,
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proxies=PROXIES,
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timeout=10,
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logger.warn(f"[{res.status_code}]")
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raise ValueError("Failed to get conversation ID!")
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self.conversation_id = conversation_id
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return conversation_id
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def get_message_id(self):
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request_url = f"https://huggingface.co/chat/conversation/{self.conversation_id}/__data.json?x-sveltekit-invalidated=11"
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request_headers = HUGGINGCHAT_POST_HEADERS
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extra_headers = {
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"Cookie": f"hf-chat={self.hf_chat_id}",
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}
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request_headers.update(extra_headers)
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logger.note(f"> Message ID:", end=" ")
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message_id = None
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res = requests.post(
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request_url,
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headers=request_headers,
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proxies=PROXIES,
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timeout=10,
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)
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if res.status_code == 200:
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data = res.json()
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# TODO - extract message_id
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logger.success(f"[{message_id}]")
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else:
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logger.warn(f"[{res.status_code}]")
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raise ValueError("Failed to get conversation ID!")
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return message_id
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def log_request(self, url, method="GET"):
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logger.note(f"> {method}:", end=" ")
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logger.mesg(f"{url}", end=" ")
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def log_response(
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self, res: requests.Response, stream=False, iter_lines=False, verbose=False
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):
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status_code = res.status_code
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status_code_str = f"[{status_code}]"
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if status_code == 200:
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logger_func = logger.success
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else:
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logger_func = logger.warn
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logger_func(status_code_str)
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logger.enter_quiet(not verbose)
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if status_code != 200:
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logger_func(res.text)
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if stream:
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if not iter_lines:
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return
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for line in res.iter_lines():
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line = line.decode("utf-8")
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line = re.sub(r"^data:\s*", "", line)
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line = line.strip()
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if line:
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try:
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data = json.loads(line, strict=False)
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msg_type = data.get("type")
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if msg_type == "status":
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msg_status = data.get("status")
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elif msg_type == "stream":
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content = data.get("token", "")
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logger_func(content, end="")
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elif msg_type == "finalAnswer":
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full_content = data.get("text")
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logger.success("\n[Finished]")
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break
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else:
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pass
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except Exception as e:
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logger.warn(e)
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else:
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logger_func(res.json())
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logger.exit_quiet(not verbose)
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def chat_response(
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self,
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api_key: str = None,
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use_cache: bool = False,
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):
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self.get_hf_chat_id()
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self.get_conversation_id()
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message_id = self.get_message_id()
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request_url = f"https://huggingface.co/chat/conversation/{self.conversation_id}"
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request_headers = copy.deepcopy(HUGGINGCHAT_POST_HEADERS)
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extra_headers = {
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"Content-Type": "text/event-stream",
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"Referer": request_url,
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"Cookie": f"hf-chat={self.hf_chat_id}",
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}
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request_headers.update(extra_headers)
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request_body = {
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"files": [],
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"id": message_id,
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"inputs": prompt,
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"is_continue": False,
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"is_retry": False,
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"web_search": False,
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}
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self.log_request(request_url, method="POST")
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res = requests.post(
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request_url,
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headers=request_headers,
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json=request_body,
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proxies=PROXIES,
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stream=True,
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)
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self.log_response(res, stream=True, iter_lines=True, verbose=True)
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return res
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def chat_return_dict(self, stream_response):
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pass
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if __name__ == "__main__":
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streamer = HuggingchatStreamer(model="mixtral-8x7b")
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prompt = "who are you?"
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streamer.chat_response(prompt=prompt)
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# HF_ENDPOINT=https://hf-mirror.com python -m networks.huggingchat_streamer
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