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Sleeping
:gem: [Feature] HuggingchatStreamer: Build pipeline of chat_response
Browse files
networks/huggingchat_streamer.py
CHANGED
@@ -31,7 +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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@@ -155,7 +154,37 @@ 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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def chat_return_dict(self, stream_response):
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pass
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@@ -166,5 +195,6 @@ class HuggingchatStreamer:
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if __name__ == "__main__":
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streamer = HuggingchatStreamer(model="mixtral-8x7b")
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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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api_key: str = None,
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use_cache: bool = False,
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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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