Template description
This n8n template demonstrates the beginnings of building your own n8n-powered WhatsApp chatbot! Under the hood, utilise n8n's powerful AI features to handle different message types and use an AI agent to respond to the user. A powerful tool for any use-case!
How it works
- Incoming WhatsApp Trigger provides a way to get messages into the workflow.
- The message received is extracted and sent through 1 of 4 branches for processing.
- Each processing branch uses AI to analyse, summarize or transcribe the message so that the AI agent can understand it. The supported types are text, image, audio (voice notes) and video (no sound).
- The AI Agent is used to generate a response generally and uses a wikipedia tool for more complex queries.
- Finally, the response message is sent back to the WhatsApp user using the WhatsApp node.
How to use
Once you have setup and configured your WhatsApp account, you'll need to activate your workflow to start processing messages.
Good to know: Large media files may negatively impact workflow performance.
Requirements
- WhatsApp Buisness account
- OpenAI for LLM
Customising this workflow
- For performance reasons, consider processing audio and video using dedicated services.
- To handle videos with sound, you have 2 choices: use an LLM like Gemini which fully supports video processing (though video input is not currently supported in LLM node) or split the video into a image track and audio track and process separately. Good luck!
- Go beyond and create rich and engagement customer experiences by responding using images, audio and video instead of just text!
Share Template
More AI workflow templates
AI agent chat
This workflow employs OpenAI's language models and SerpAPI to create a responsive, intelligent conversational agent. It comes equipped with manual chat triggers and memory buffer capabilities to ensure seamless interactions.
To use this template, you need to be on n8n version 1.50.0 or later.
n8n Team
+7
Scrape and summarize webpages with AI
This workflow integrates both web scraping and NLP functionalities. It uses HTML parsing to extract links, HTTP requests to fetch essay content, and AI-based summarization using GPT-4o. It's an excellent example of an end-to-end automated task that is not only efficient but also provides real value by summarizing valuable content.
Note that to use this template, you need to be on n8n version 1.50.0 or later.
n8n Team
+5
AI agent that can scrape webpages
βοΈπ οΈππ€π¦Ύ
This template is a PoC of a ReAct AI Agent capable of fetching random pages (not only Wikipedia or Google search results).
On the top part there's a manual chat node connected to a LangChain ReAct Agent. The agent has access to a workflow tool for getting page content.
The page content extraction starts with converting query parameters into a JSON object. There are 3 pre-defined parameters:
url** β an address of the page to fetch
method** = full / simplified
maxlimit** - maximum length for the final page. For longer pages an error message is returned back to the agent
Page content fetching is a multistep process:
An HTTP Request mode tries to get the page content.
If the page content was successfuly retrieved, a series of post-processing begin:
Extract HTML BODY; content
Remove all unnecessary tags to recude the page size
Further eliminate external URLs and IMG scr values (based on the method query parameter)
Remaining HTML is converted to Markdown, thus recuding the page lengh even more while preserving the basic page structure
The remaining content is sent back to an Agent if it's not too long (maxlimit = 70000 by default, see CONFIG node).
NB:
You can isolate the HTTP Request part into a separate workflow.
Check the Workflow Tool description, it guides the agent to provide a query string with several parameters instead of a JSON object.
Please reach out to Eduard is you need further assistance with you n8n workflows and automations!
Note that to use this template, you need to be on n8n version 1.19.4 or later.
Eduard
