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import gradio as gr |
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import aiohttp |
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import os |
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import json |
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from collections import deque |
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TOKEN = os.getenv("HUGGINGFACE_API_TOKEN") |
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if not TOKEN: |
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raise ValueError("API token is not set. Please set the HUGGINGFACE_API_TOKEN environment variable.") |
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memory = deque(maxlen=10) |
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async def respond( |
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message, |
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history: list[tuple[str, str]], |
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system_message="AI Assistant Role", |
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max_tokens=512, |
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temperature=0.7, |
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top_p=0.95, |
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): |
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system_prefix = "System: ์
๋ ฅ์ด์ ์ธ์ด(์์ด, ํ๊ตญ์ด, ์ค๊ตญ์ด, ์ผ๋ณธ์ด ๋ฑ)์ ๋ฐ๋ผ ๋์ผํ ์ธ์ด๋ก ๋ต๋ณํ๋ผ." |
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full_system_message = f"{system_prefix}{system_message}" |
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memory.append((message, None)) |
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messages = [{"role": "system", "content": full_system_message}] |
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for val in memory: |
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if val[0]: |
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messages.append({"role": "user", "content": val[0]}) |
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if val[1]: |
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messages.append({"role": "assistant", "content": val[1]}) |
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headers = { |
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"Authorization": f"Bearer {TOKEN}", |
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"Content-Type": "application/json" |
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} |
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payload = { |
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"model": "mistralai/Mistral-Nemo-Instruct-2407", |
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"max_tokens": max_tokens, |
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"temperature": temperature, |
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"top_p": top_p, |
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"messages": messages, |
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"stream": True |
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} |
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async with aiohttp.ClientSession() as session: |
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async with session.post("https://api-inference.huggingface.co/v1/chat/completions", headers=headers, json=payload) as response: |
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try: |
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async for chunk in response.content: |
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if chunk: |
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chunk_data = chunk.decode('utf-8') |
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response_json = json.loads(chunk_data) |
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if "choices" in response_json: |
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content = response_json["choices"][0]["message"]["content"] |
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yield content |
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except json.JSONDecodeError: |
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pass |
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except StopAsyncIteration: |
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pass |
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finally: |
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pass |
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if __name__ == "__main__": |
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demo.launch() |