LangBot is an open-source instant messaging bot development platform. It supports Feishu, DingTalk, WeChat, QQ, Telegram, Discord, Slack, and more. It integrates with mainstream AI models and supports Knowledge Base, Agent, and MCP capabilities. LangBot is fully compatible with Newapi.Documentation Index
Fetch the complete documentation index at: https://doc.hitopen.com/llms.txt
Use this file to discover all available pages before exploring further.
- Official website: https://langbot.app
- Download: https://github.com/langbot-app/LangBot/releases
- Documentation: https://docs.langbot.app
- GitHub: https://github.com/langbot-app/LangBot
Connect LangBot to Newapi
LangBot supports integrating with locally deployed Newapi instances and with third-party services built on Newapi.Obtain your Newapi API key
In the Newapi console, open Token Management and copy the API key for the token you want to use.
If Newapi is deployed locally, configure the API address yourself (see Container Network Connection in the LangBot docs). If you are using a third-party Newapi service, copy the address from the service’s page. Append
/v1 to the address.Add a Newapi model in LangBot
In the LangBot dashboard, add a new model. Select NewAPI as the provider and fill in your API key and API address.
Select the model in your pipeline
In your LangBot pipeline configuration, select the Newapi model you just added as the active model.
Start chatting
Test the integration using conversation debugging in the LangBot dashboard, or chat with a bot bound to the pipeline. For instructions on deploying bots to messaging platforms, refer to Deploying Bots in the LangBot documentation.
Using Newapi embedding models with LangBot’s knowledge base
LangBot supports Newapi’s embedding models as vector models for its knowledge base feature.Add an embedding model
In LangBot, add a new model and select NewAPI as the provider. Choose an embedding model available in your Newapi instance.