Slack

本笔记本展示了如何使用Slack聊天加载器。此类帮助将导出的Slack对话映射到LangChain聊天消息。

该过程分为三个步骤：

1. 按照此处的说明导出所需的对话线程。
2. 创建SlackChatLoader，文件路径指向json文件或JSON文件目录。
3. 调用loader.load()（或loader.lazy_load()）以执行转换。可选地使用merge_chat_runs将同一发送者的消息按顺序合并，和/或使用map_ai_messages将指定发送者的消息转换为"AIMessage"类。

1. 创建消息转储

目前（2023/08/23），此加载器最佳支持以导出Slack直接消息对话生成的文件格式的zip目录。请遵循Slack的最新说明进行操作。

我们在LangChain仓库中有一个示例。

import requests

permalink = "https://raw.githubusercontent.com/langchain-ai/langchain/342087bdfa3ac31d622385d0f2d09cf5e06c8db3/libs/langchain/tests/integration_tests/examples/slack_export.zip"
response = requests.get(permalink)
with open("slack_dump.zip", "wb") as f:
    f.write(response.content)

2. 创建聊天加载器

为加载器提供压缩目录的文件路径。您可以选择性地指定与AI消息对应的用户ID，并配置是否合并消息运行。

<!--IMPORTS:[{"imported": "SlackChatLoader", "source": "langchain_community.chat_loaders.slack", "docs": "https://python.langchain.com/api_reference/community/chat_loaders/langchain_community.chat_loaders.slack.SlackChatLoader.html", "title": "Slack"}]-->
from langchain_community.chat_loaders.slack import SlackChatLoader

loader = SlackChatLoader(
    path="slack_dump.zip",
)

3. 加载消息

load()（或lazy_load）方法返回一个“聊天会话”的列表，目前仅包含每个加载对话的消息列表。

<!--IMPORTS:[{"imported": "map_ai_messages", "source": "langchain_community.chat_loaders.utils", "docs": "https://python.langchain.com/api_reference/community/chat_loaders/langchain_community.chat_loaders.utils.map_ai_messages.html", "title": "Slack"}, {"imported": "merge_chat_runs", "source": "langchain_community.chat_loaders.utils", "docs": "https://python.langchain.com/api_reference/community/chat_loaders/langchain_community.chat_loaders.utils.merge_chat_runs.html", "title": "Slack"}, {"imported": "ChatSession", "source": "langchain_core.chat_sessions", "docs": "https://python.langchain.com/api_reference/core/chat_sessions/langchain_core.chat_sessions.ChatSession.html", "title": "Slack"}]-->
from typing import List

from langchain_community.chat_loaders.utils import (
    map_ai_messages,
    merge_chat_runs,
)
from langchain_core.chat_sessions import ChatSession

raw_messages = loader.lazy_load()
# Merge consecutive messages from the same sender into a single message
merged_messages = merge_chat_runs(raw_messages)
# Convert messages from "U0500003428" to AI messages
messages: List[ChatSession] = list(
    map_ai_messages(merged_messages, sender="U0500003428")
)

下一步

然后，您可以根据需要使用这些消息，例如微调模型、少量示例选择或直接预测下一条消息。

<!--IMPORTS:[{"imported": "ChatOpenAI", "source": "langchain_openai", "docs": "https://python.langchain.com/api_reference/openai/chat_models/langchain_openai.chat_models.base.ChatOpenAI.html", "title": "Slack"}]-->
from langchain_openai import ChatOpenAI

llm = ChatOpenAI()

for chunk in llm.stream(messages[1]["messages"]):
    print(chunk.content, end="", flush=True)

Hi, 

I hope you're doing well. I wanted to reach out and ask if you'd be available to meet up for coffee sometime next week. I'd love to catch up and hear about what's been going on in your life. Let me know if you're interested and we can find a time that works for both of us. 

Looking forward to hearing from you!

Best, [Your Name]