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Redis 聊天消息历史记录

Redis (远程字典服务器) 是一种开源的内存存储,用作分布式、内存键值数据库、缓存和消息代理,具有可选的持久性。Redis 提供低延迟的读取和写入。Redis 是最流行的 NoSQL 数据库,也是最流行的数据库之一。

本笔记本演示了如何使用 langchain-redis 包中的 RedisChatMessageHistory 类来使用 Redis 存储和管理聊天消息历史记录。

设置

首先,我们需要安装所需的依赖项,并确保我们有一个正在运行的 Redis 实例。

%pip install -qU langchain-redis langchain-openai redis

确保您有一个 Redis 服务器正在运行。您可以使用 Docker 使用以下命令启动一个

docker run -d --name redis-stack -p 6379:6379 -p 8001:8001 redis/redis-stack:latest

或者根据您的操作系统说明,在本地安装并运行 Redis。

import os

# Use the environment variable if set, otherwise default to localhost
REDIS_URL = os.getenv("REDIS_URL", "redis://localhost:6379")
print(f"Connecting to Redis at: {REDIS_URL}")
Connecting to Redis at: redis://redis:6379

导入所需库

from langchain_core.chat_history import BaseChatMessageHistory
from langchain_core.messages import AIMessage, HumanMessage
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
from langchain_core.runnables.history import RunnableWithMessageHistory
from langchain_openai import ChatOpenAI
from langchain_redis import RedisChatMessageHistory

RedisChatMessageHistory 的基本用法

# Initialize RedisChatMessageHistory
history = RedisChatMessageHistory(session_id="user_123", redis_url=REDIS_URL)

# Add messages to the history
history.add_user_message("Hello, AI assistant!")
history.add_ai_message("Hello! How can I assist you today?")

# Retrieve messages
print("Chat History:")
for message in history.messages:
print(f"{type(message).__name__}: {message.content}")
Chat History:
HumanMessage: Hello, AI assistant!
AIMessage: Hello! How can I assist you today?

将 RedisChatMessageHistory 与语言模型一起使用

设置 OpenAI API 密钥

from getpass import getpass

# Check if OPENAI_API_KEY is already set in the environment
openai_api_key = os.getenv("OPENAI_API_KEY")

if not openai_api_key:
print("OpenAI API key not found in environment variables.")
openai_api_key = getpass("Please enter your OpenAI API key: ")

# Set the API key for the current session
os.environ["OPENAI_API_KEY"] = openai_api_key
print("OpenAI API key has been set for this session.")
else:
print("OpenAI API key found in environment variables.")
OpenAI API key not found in environment variables.
``````output
Please enter your OpenAI API key: ········
``````output
OpenAI API key has been set for this session.
# Create a prompt template
prompt = ChatPromptTemplate.from_messages(
[
("system", "You are a helpful AI assistant."),
MessagesPlaceholder(variable_name="history"),
("human", "{input}"),
]
)

# Initialize the language model
llm = ChatOpenAI()

# Create the conversational chain
chain = prompt | llm


# Function to get or create a RedisChatMessageHistory instance
def get_redis_history(session_id: str) -> BaseChatMessageHistory:
return RedisChatMessageHistory(session_id, redis_url=REDIS_URL)


# Create a runnable with message history
chain_with_history = RunnableWithMessageHistory(
chain, get_redis_history, input_messages_key="input", history_messages_key="history"
)

# Use the chain in a conversation
response1 = chain_with_history.invoke(
{"input": "Hi, my name is Alice."},
config={"configurable": {"session_id": "alice_123"}},
)
print("AI Response 1:", response1.content)

response2 = chain_with_history.invoke(
{"input": "What's my name?"}, config={"configurable": {"session_id": "alice_123"}}
)
print("AI Response 2:", response2.content)
AI Response 1: Hello Alice! How can I assist you today?
AI Response 2: Your name is Alice.

高级功能

自定义 Redis 配置

# Initialize with custom Redis configuration
custom_history = RedisChatMessageHistory(
"user_456",
redis_url=REDIS_URL,
key_prefix="custom_prefix:",
ttl=3600, # Set TTL to 1 hour
index_name="custom_index",
)

custom_history.add_user_message("This is a message with custom configuration.")
print("Custom History:", custom_history.messages)
Custom History: [HumanMessage(content='This is a message with custom configuration.')]

搜索消息

# Add more messages
history.add_user_message("Tell me about artificial intelligence.")
history.add_ai_message(
"Artificial Intelligence (AI) is a branch of computer science..."
)

# Search for messages containing a specific term
search_results = history.search_messages("artificial intelligence")
print("Search Results:")
for result in search_results:
print(f"{result['type']}: {result['content'][:50]}...")
Search Results:
human: Tell me about artificial intelligence....
ai: Artificial Intelligence (AI) is a branch of comput...

清除历史记录

# Clear the chat history
history.clear()
print("Messages after clearing:", history.messages)
Messages after clearing: []

结论

本笔记本演示了 langchain-redis 包中 RedisChatMessageHistory 的关键功能。它展示了如何初始化和使用聊天历史记录,将其与语言模型集成,以及利用高级功能,如自定义配置和消息搜索。Redis 为在 AI 应用程序中管理聊天历史记录提供了快速且可扩展的解决方案。


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