diff --git a/memory/memory_desc.py b/memory/memory_desc.py index 82a68c2..87f132b 100644 --- a/memory/memory_desc.py +++ b/memory/memory_desc.py @@ -3,6 +3,8 @@ import os import dotenv from langchain.memory import ConversationBufferMemory, ConversationTokenBufferMemory, ConversationSummaryMemory from langchain_openai import ChatOpenAI +from langchain.memory import ConversationBufferWindowMemory +from langchain_core.messages import HumanMessage, AIMessage, trim_messages memory = ConversationBufferMemory() memory.chat_memory.add_user_message("我叫小明") @@ -30,14 +32,47 @@ print('---------') dotenv.load_dotenv() ## 设置环境变量 -os.environ['OPENAI_API_KEY'] = os.getenv("SILICONFLOW_API_KEY") -os.environ['OPENAI_BASE_URL'] = os.getenv("SILICONFLOW_BASE_URL") +os.environ['OPENAI_API_KEY'] = os.getenv("OLLAMA_API_KEY") +os.environ['OPENAI_BASE_URL'] = os.getenv("OLLAMA_BASE_URL") # 默认的 'model_name': 'deepseek-ai/DeepSeek-V3.1', -llm = ChatOpenAI(model="deepseek-ai/DeepSeek-V3.1") +llm = ChatOpenAI(model="gemma4:e2b") memory_test = ConversationSummaryMemory(llm=llm) memory_test.save_context({"input": "我叫小明"}, {"output": "噢，好的，你叫小明"}) 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。"}) print(memory_test.load_memory_variables({})) # {'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.'} +print('---------') + +# 这是openai专用的OpenAI套件 +# memory_token = ConversationTokenBufferMemory(llm=llm,max_token_limit=7) +# memory_token.save_context({"input": "我叫小明"}, {"output": "噢，好的，你叫小明"}) +# memory_token.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。"}) +# print(memory_token.load_memory_variables({})) + +# k=1 代表只記住「最新的一問一答」（1輪） +memory_window = ConversationBufferWindowMemory(k=1) +memory_window.save_context({"input": "我叫小明"}, {"output": "噢，好的，你叫小明"}) +memory_window.save_context({"input": "那么你是谁呢"}, {"output": "我是一个无所不能的AI聊天助手。"}) +print(memory_window.load_memory_variables({})) +# 輸出結果只會保留最後一輪，因為 k=1 +print('---------') + +messages = [ + HumanMessage("我叫小明"), + AIMessage("噢，好的，你叫小明"), + HumanMessage("那么你是谁呢"), + AIMessage("我是一个无所不能的AI聊天助手。") +] + +# 現代化做法：直接裁剪訊息列表 +# 這裡我們用最簡單的 "只保留最後 2 條訊息" 策略 +trimmed_messages = trim_messages( + messages, + max_tokens=2, + token_counter=len, # 關鍵：我們直接告訴它「算訊息條數」當作 token，避開底層 tiktoken 崩潰 + strategy="last", +) + +print(trimmed_messages) \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml index 89ff754..703752e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -5,9 +5,9 @@ description = "Add your description here" readme = "README.md" requires-python = ">=3.11" dependencies = [ - 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