44 lines
1.8 KiB
Python
44 lines
1.8 KiB
Python
import os
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import dotenv
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from langchain.memory import ConversationBufferMemory, ConversationTokenBufferMemory, ConversationSummaryMemory
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from langchain_openai import ChatOpenAI
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memory = ConversationBufferMemory()
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memory.chat_memory.add_user_message("我叫小明")
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memory.chat_memory.add_ai_message("噢，好的，你叫小明")
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print(memory)
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print(memory.memory_key)
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print(memory.load_memory_variables({}))
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print('---------')
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memory2 = ConversationBufferMemory(memory_key="memory2")
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memory2.chat_memory.add_user_message("我叫小明")
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memory2.chat_memory.add_ai_message("噢，好的，你叫小明")
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print(memory2)
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print(memory2.memory_key)
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print(memory2.load_memory_variables({}))
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print('---------')
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memory3 = ConversationBufferMemory(return_messages=True)
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memory3.chat_memory.add_user_message("我叫小明")
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memory3.chat_memory.add_ai_message("噢，好的，你叫小明")
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print(memory3)
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print(memory3.memory_key)
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print(memory3.load_memory_variables({}))
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print('---------')
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dotenv.load_dotenv()
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## 设置环境变量
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os.environ['OPENAI_API_KEY'] = os.getenv("SILICONFLOW_API_KEY")
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os.environ['OPENAI_BASE_URL'] = os.getenv("SILICONFLOW_BASE_URL")
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# 默认的 'model_name': 'deepseek-ai/DeepSeek-V3.1',
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llm = ChatOpenAI(model="deepseek-ai/DeepSeek-V3.1")
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memory_test = ConversationSummaryMemory(llm=llm)
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memory_test.save_context({"input": "我叫小明"}, {"output": "噢，好的，你叫小明"})
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memory_test.save_context({"input": "那么你是谁呢"}, {"output": "我是一个无所不能的AI聊天助手，可以帮你解答任何问题。"})
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print(memory_test.load_memory_variables({}))
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# {'history': '\n\nThe human introduces themselves as xiaoming. The AI confirms the name and responds. The human then asks who the AI is. The AI introduces itself as an all-powerful AI chat assistant who can answer any questions.'}
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