Bonsai-27B-GGUF
lmstudio-community · Kit
A GGUF conversion of the 27B Bonsai model for LM Studio, with a 3.80 GB Q1_0 language file and a 0.93 GB BF16 vision projector. Tested for text, vision and par…
An n8n workflow with a chat page that answers questions from a Notion database of questions and answers. An AI agent searches the database by keyword or tag, reads the matching page and replies with a link to it.
Chat assistant that answers from a Notion knowledge base is an n8n workflow in the Productivity category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page or copy its JSON, then import it into an n8n canvas. Nothing runs until you activate it in n8n.
A chat message
A visitor starts it in the chat page:
A short chat answer drawn from the Notion records, with a link to the page
What you need before you start.
Knowledge base
Holds the questions and answers, and answers the search and the page reads.
NeedsA Notion credential and a database with question, tags and updated_at
Language model
Runs the agent that picks the tools and writes the answer.
NeedsAn OpenAI API key, in an OpenAI credential
Checked by Mindket on 13 Nov 2026
This n8n workflow turns a Notion database into a chat assistant. A visitor types a question into a chat page. The workflow reads the database’s name and its tag list, then hands the question to an AI agent that has a short memory and two Notion search tools. The agent searches the records by keyword or tag, reads the best page and answers from it, with a link. Eight nodes do the work, beside two sticky notes.
Small teams that keep their answers in Notion and tire of replying to the same questions. It fits a help desk, an internal wiki or a customer FAQ. Skip it if the database holds private notes, because the chat page is public once you activate it and what the agent reads goes to OpenAI.
| Industry | Who uses it | How they use it | Example |
|---|---|---|---|
| Support | Support teams | Answer common questions from one FAQ database | A team keeps refund and shipping answers in Notion and links the chat page on its help page. |
| Human resources | HR teams | Give staff one place to ask about policy | An HR lead stores leave and expense rules, and staff ask the chat which form to use. |
| Software | Product teams | Search release notes and how-to pages | A product team tags pages by feature, and the agent finds the page that matches the tag. |
| Education | School offices | Answer parents’ questions on dates and rules | An office keeps term dates in the table and lets parents ask the chat instead of writing an email. |
You need basic n8n skills, a Notion database set up for questions and an OpenAI API key.
Any n8n that can reach Notion and the OpenAI API will run it. The chat page is served by n8n itself, so it needs an address that your visitors can reach.
model in OpenAI Chat ModelGet database detailsDownload saves a zip with workflow.json and Mindket’s setup notes in your downloads folder. The Notion database must have a set shape.
| Need | Detail |
|---|---|
| n8n | On n8n Cloud or on a server of your own |
| Notion | A Notion integration and a database with a text property question, a multi-select property tags and a property updated_at. Each answer is the body of the row’s page |
| OpenAI | An API key, saved in an OpenAI credential |
workflow.json.question, tags and updated_at, write each answer in the row’s page and share the database with the integration.Get database details, Search notion database and Search inside database record.Get database details, pick your database in place of <YOUR_NOTION_DATABASE_ID>.OpenAI Chat Model.When chat message received.Open the chat, type a question and read the answer. The agent keeps the last four exchanges in memory, so a follow-up question works.
| To change | Where |
|---|---|
| How the agent behaves | The system message in AI Agent |
| The model | model in OpenAI Chat Model |
| The database | Get database details |
| How much the agent remembers | contextWindowLength in Window Buffer Memory |
| The welcome text and the chat title | When chat message received |
| What the search looks at | The JSON body in Search notion database |
A visitor asks the chat how long the refund period is.
The agent searches the question property for refund, opens the best matching page and answers from its text. The reply ends with a link to the page.
If you are new. n8n draws a workflow as boxes joined by lines, and each box, a node, does one job. An AI agent is a language model that can decide to call tools. Here the tools are two searches of your Notion database.
For experts. The chat trigger passes chatInput and sessionId. Get database details and Format schema add the database’s name and its tag options to the same item, and the agent reads them from $json. The two tools are HTTP Request tools on Notion’s API. One posts a filter to /v1/databases/{id}/query, and the other reads /v1/blocks/{page_id}/children. n8n’s Notion credential sends the Notion-Version header 2022-02-22 on its own.
| Node | What it does | What to know |
|---|---|---|
Get database details | Reads the database’s name and properties | It runs on every message, which adds a short wait |
Format schema | Puts the name, the tag list and the database ID next to the message | The agent’s prompt and tools read them |
Search notion database | Queries the database by keyword in question or by tag | Keyword and tag are joined by OR, and rows sort by updated_at |
Search inside database record | Reads the blocks of one page | It needs the page ID that the first tool returned |
AI Agent | Chooses a tool and writes the answer | The system message limits it to facts from the records |
The chat model was replaced and the sticky notes were rewritten. Mindket did not run this workflow.
gpt-4o, which OpenAI’s deprecations page, read on 12 November 2026, lists with the 14 January 2027 shutdown. Mindket’s copy uses gpt-5.6-terra, because an agent with tools needs a model that calls them. The temperature setting was dropped, since the model’s page lists noneSearch notion database had an empty pair of quotes where the database name belongs. It now reads the name from $json.databaseNameAn n8n workflow with a chat page that answers questions from a Notion database of questions and answers. An AI agent searches the database by keyword or tag, reads the matching page and replies with a link to it.
workflow.json: the workflow as n8n exports it, ten nodes. Eight do the work and two are sticky notes that label the steps. It holds no credential.README.md: these notes.gpt-4o, which OpenAI’s deprecations page, read on 12 November 2026, lists with the 14 January 2027 shutdown. Mindket’s copy uses gpt-5.6-terra and drops the temperature setting.Search notion database had an empty pair of quotes where the database name belongs. It now reads the name from $json.databaseName.<YOUR_NOTION_DATABASE_ID>.question, tags and updated_at, and each answer in its row’s page.workflow.json.question, tags and updated_at, write each answer in the row’s page and share the database with the integration.Get database details, Search notion database and Search inside database record.Get database details, pick your database in place of <YOUR_NOTION_DATABASE_ID>.OpenAI Chat Model.When chat message received.When chat message received takes the visitor’s message and opens the run.Get database details reads the database from Notion.Format schema adds the database’s name, its ID and its tag options to the message.AI Agent receives the question with the last four exchanges from Window Buffer Memory.Search notion database queries the records by keyword or tag when the agent asks for it.Search inside database record reads the page of the best match.AI Agent.model in OpenAI Chat Model.Get database details.contextWindowLength in Window Buffer Memory.When chat message received.Search notion database.gpt-5.6-terra because it has tools. gpt-6-luna calls tools in Chat Completions only with reasoning turned off, which this node does not send.question and on tags, and it sorts by updated_at. A database without them gives an error.NOTICE.md 585 B README.md 4 KB workflow.json 10 KB
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