Chat with Ollama

Runs locally

Needs Ollama with one model pulled. No key, and the conversation stays on your machine.

A chat box, a prompt with your instructions, a local model and a view of the conversation.

Download the graph and save it in user/graphs/ inside your Boltjar folder; it shows up in your saved graphs. Or build it yourself below. The graph is MIT-0: copy it and license what you build from it however you like.

1. Pull a model

ollama pull gemma4:e4b

Any Ollama chat model you pull shows up in the LLM’s picker; the LLM node’s page lists the ones that ship with a manifest. Smaller models answer faster, larger ones answer better.

The downloaded graph has no model picked, because a model can cost money and Boltjar never picks one for you. Until you pick one, the LLM answers with a mock reply.

2. The nodes

Node	Settings
Chat Input, named Message	none needed
Template, named Prompt	the text below
LLM	model: pick Gemma 4 e4b (Ollama), or the model you pulled
Chat	none

The Prompt’s text:

You are a helpful assistant. Keep answers short and plain.

User: {message}

3. The wires

From	To
Message trigger	Prompt trigger
Message text	Prompt message
Prompt trigger	LLM trigger
Prompt out	LLM prompt
Message trigger	Chat user_trigger
Message text	Chat user
LLM trigger	Chat reply_trigger
LLM response	Chat reply

A wire dropped on the Prompt’s + tag socket makes a tag named after the node it comes from, so Message text becomes {message}. Every trigger input needs a wire, the Prompt’s included, or the graph stays Off. The trigger runs through the Prompt to the LLM: the message fires the Prompt, which fills in its text once and fires the LLM, so one message runs the model once.

4. Turn it On

Press On and send a message from the Message node. The Prompt fires on the message and fills in your text, the LLM fires next and reads that prompt, and the reply lands in the Chat node.

If Ollama is not running, the LLM turns red, and its error output fires with the reason. If Ollama runs but the model is not pulled, the graph stays Off, and its problems list says to pull the model in Settings › AI Providers.

Keep the conversation

This graph sends one message at a time: the model does not see earlier turns. The chat example that opens on the first start keeps the history in a SQLite table: a Database node, DB nodes that insert each message and read the last ones, and a Format List that turns the rows into lines for the prompt. Open it next to this one to see the pattern.

Change it

• A cloud model. Add an Anthropic, OpenAI or xAI key in Settings › AI Providers and pick one of that provider’s models on the LLM node. Without the key, the node answers with a mock reply.
• The date in the prompt. Add a Time node named Date, wire its out onto the Prompt’s + tag (the tag is {date}), and write Today is {date}. in the Prompt.
• Reading images. A model that reads images (Gemma 4, Qwen3.5, Claude, GPT, Grok) grows an image input on the LLM. Wire an Image or a Screen Capture into it.