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langchain-asyntai

LangChain tools for Asyntai, the AI chat agent for websites.

Point Asyntai at a website. It reads the pages, the product feed and the documents, and keeps them current. This package hands that knowledge to any LangChain agent as a set of tools, so your agent answers questions about a real website without you building and maintaining an index.

Install

pip install langchain-asyntai

Set the key

Create an API key in Asyntai under Settings → API. The API is available on the Starter plan and higher.

export ASYNTAI_API_KEY="your-key"

Ask a website a question

from langchain_asyntai import AsyntaiAskTool

ask = AsyntaiAskTool()
print(ask.invoke({"question": "How long does delivery take?"}))

Give an agent every tool

from langchain.agents import create_agent
from langchain_asyntai import AsyntaiToolkit

toolkit = AsyntaiToolkit()
agent = create_agent("openai:gpt-4o-mini", toolkit.get_tools())

agent.invoke({"messages": [
    {"role": "user", "content": "What does the shop sell, and who asked about it this week?"}
]})

The tools

Tool What the agent can do
asyntai_ask_website Answer a question from the website: products, prices, delivery, opening hours, policies, documentation.
asyntai_add_text Store a text so the website agent uses it in later answers.
asyntai_add_url Read a page into the knowledge base.
asyntai_list_knowledge List what the website agent knows.
asyntai_get_leads Read the visitors who left an email address or a phone number.
asyntai_get_conversation Read the messages of one website chat.

Several agents on one account

An Asyntai account can run an agent per website. Name the one you want with website_id, which AsyntaiClient.websites() returns.

from langchain_asyntai import AsyntaiClient, AsyntaiToolkit

client = AsyntaiClient()
for site in client.websites():
    print(site["id"], site["domain"])

toolkit = AsyntaiToolkit(website_id=42)

Agencies run this pattern across a client book: one Asyntai account, one agent per client site, one website_id per agent.

Errors

Every failure raises AsyntaiError with a message you can show to a user.

from langchain_asyntai import AsyntaiError

try:
    ask.invoke({"question": "..."})
except AsyntaiError as exc:
    print(exc)

Documentation

Full guide: asyntai.com/documentation/integrations/langchain/

Licence

MIT

Release files for langchain-asyntai 0.1.0

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