Manage Appian tasks with Ollama Qwen LLM and Postgres memory
Needs changesNeeds changes. This template uses 1 thing(s) that n8n 3.0 removes: AI Agent v1 (old agent modes). 1 breaking item(s) found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 12 nodes and runs when a chat message arrives (plus 1 other trigger). Along the way it connects Ollama Chat Model, Postgres Chat Memory and HTTP Request.
How it runs
Trigger: When a chat message arrives (plus 1 other trigger).
- Normalize Chat Input (Edit Fields (Set)): sets 3 fields: chatInput, sessionId, username
- AI Agent: runs an AI agent, with model: Ollama Chat Model; 3 tools (List Tasks (Appian), Create Task (Appian), List Task Types (Appian)); memory: Postgres Chat Memory
- Prepare Response (Edit Fields (Set)): sets 2 fields: output, sessionId
- Respond to Webhook: sends the response back to the webhook caller
- Template Vars (Edit Fields (Set)): sets 2 fields: baseUrl, defaultBatchSize
Services it uses
Before you upgrade to n8n 3.0
1 thing in this workflow is removed in n8n 3.0. Fix it before you upgrade:
- AI Agent v1 (old agent modes) in AI Agent (v1.6): replace with Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.
Rather not rewrite it? Many of these flows can be rebuilt in Make (free plan).
| Removed in 3.0 | Replace with |
|---|---|
| AI Agent v1 (old agent modes) AI Agent (v1.6) | Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent. |
Nodes used (8)
- Edit Fields (Set)
n8n-nodes-base.set - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - Webhook
n8n-nodes-base.webhook - AI Agent
@n8n/n8n-nodes-langchain.agent - Ollama Chat Model
@n8n/n8n-nodes-langchain.lmChatOllama - Postgres Chat Memory
@n8n/n8n-nodes-langchain.memoryPostgresChat - Http Request Tool
n8n-nodes-base.httpRequestTool - Respond to Webhook
n8n-nodes-base.respondToWebhook
From the author
This workflow is a simple example of using n8n as an AI chat interface into Appian. It connects a local LLM, persistent memory, and API tools to demonstrate how an agent can interact with Appian tasks. What this workflow does - Chat interface: Accepts user…