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from .BaseLLM import BaseLLM |
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from openai import OpenAI |
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import os |
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class DeepSeek(BaseLLM): |
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def __init__(self, model="deepseek-chat"): |
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super(DeepSeek, self).__init__() |
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self.client = OpenAI( |
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api_key=os.getenv("DEEPSEEK_API_KEY"), |
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base_url="https://api.deepseek.com", |
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) |
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self.model_name = model |
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self.messages = [] |
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def initialize_message(self): |
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self.messages = [] |
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def ai_message(self, payload): |
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self.messages.append({"role": "ai", "content": payload}) |
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def system_message(self, payload): |
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self.messages.append({"role": "system", "content": payload}) |
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def user_message(self, payload): |
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self.messages.append({"role": "user", "content": payload}) |
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def get_response(self,temperature = 0.8): |
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response = self.client.chat.completions.create( |
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model="deepseek-chat", |
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messages=[ |
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{"role": "system", "content": "You are a helpful assistant"}, |
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{"role": "user", "content": "Hello"}, |
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], |
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stream=False |
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) |
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return response.choices[0].message.content |
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def chat(self,text): |
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self.initialize_message() |
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self.user_message(text) |
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response = self.get_response() |
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return response |
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def print_prompt(self): |
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for message in self.messages: |
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print(message) |