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Packaged Local AI - n8n + Ollama + QDrant + Postgres

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2024-09-14 07:59:21 -05:00
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local-ai-packaged/.env.example Normal file
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# Change the name of this file to .env after updating it!
POSTGRES_USER=root
POSTGRES_PASSWORD=password
POSTGRES_DB=n8n
N8N_ENCRYPTION_KEY=super-secret-key
N8N_USER_MANAGEMENT_JWT_SECRET=even-more-secret

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local-ai-packaged/LICENSE Normal file
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local-ai-packaged/Local_RAG_AI_Agent_n8n_Workflow.json Normal file
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{
"name": "Local RAG AI Agent",
"nodes": [
{
"parameters": {},
"id": "99b30fd7-b36c-44ba-9daa-408585aaaee9",
"name": "Postgres Chat Memory",
"type": "@n8n/n8n-nodes-langchain.memoryPostgresChat",
"typeVersion": 1.1,
"position": [
900,
560
],
"credentials": {
"postgres": {
"id": "BAhZ6uu3zrQ3JmQm",
"name": "Postgres account"
}
}
},
{
"parameters": {
"model": "llama3.1:latest",
"options": {}
},
"id": "c7632a7c-2661-492e-bd6f-aab994818998",
"name": "Ollama Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOllama",
"typeVersion": 1,
"position": [
760,
560
],
"credentials": {
"ollamaApi": {
"id": "tEBwcGKXQiQrbKjH",
"name": "Ollama account"
}
}
},
{
"parameters": {
"model": "llama3.1:latest",
"options": {}
},
"id": "73d773a4-5c72-4af3-a52d-144f0e417823",
"name": "Ollama Model",
"type": "@n8n/n8n-nodes-langchain.lmOllama",
"typeVersion": 1,
"position": [
1660,
500
],
"credentials": {
"ollamaApi": {
"id": "tEBwcGKXQiQrbKjH",
"name": "Ollama account"
}
}
},
{
"parameters": {
"name": "documents",
"topK": 3
},
"id": "3f882fa7-c8ed-4531-b236-a34c16c55838",
"name": "Vector Store Tool",
"type": "@n8n/n8n-nodes-langchain.toolVectorStore",
"typeVersion": 1,
"position": [
1440,
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]
},
{
"parameters": {
"model": "nomic-embed-text:latest"
},
"id": "3a8e3fa0-3997-4bce-985c-975fb5ad4013",
"name": "Embeddings Ollama",
"type": "@n8n/n8n-nodes-langchain.embeddingsOllama",
"typeVersion": 1,
"position": [
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],
"credentials": {
"ollamaApi": {
"id": "tEBwcGKXQiQrbKjH",
"name": "Ollama account"
}
}
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"pollTimes": {
"item": [
{
"mode": "everyMinute"
}
]
},
"triggerOn": "specificFolder",
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"__rl": true,
"value": "1914m3M7kRzkd5RJqAfzRY9EBcJrKemZC",
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"position": [
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],
"credentials": {
"googleDriveOAuth2Api": {
"id": "hKn2avoGUt7FoAyY",
"name": "Google Drive account"
}
}
},
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{
"mode": "everyMinute"
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"triggerOn": "specificFolder",
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"value": "1914m3M7kRzkd5RJqAfzRY9EBcJrKemZC",
"mode": "list",
"cachedResultName": "Meeting Notes",
"cachedResultUrl": "https://drive.google.com/drive/folders/1914m3M7kRzkd5RJqAfzRY9EBcJrKemZC"
},
"event": "fileUpdated",
"options": {}
},
"id": "7b904686-89ae-4722-9ce5-a9da1b13b1a1",
"name": "File Updated",
"type": "n8n-nodes-base.googleDriveTrigger",
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"position": [
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],
"credentials": {
"googleDriveOAuth2Api": {
"id": "hKn2avoGUt7FoAyY",
"name": "Google Drive account"
}
}
},
{
"parameters": {
"assignments": {
"assignments": [
{
"id": "10646eae-ae46-4327-a4dc-9987c2d76173",
"name": "file_id",
"value": "={{ $json.id }}",
"type": "string"
},
{
"id": "dd0aa081-79e7-4714-8a67-1e898285554c",
"name": "folder_id",
"value": "={{ $json.parents[0] }}",
"type": "string"
}
]
},
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"id": "87f8bbb0-92c5-4b25-be63-7a9d91fc46f8",
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},
{
"parameters": {
"operation": "download",
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"value": "={{ $('Set File ID').item.json.file_id }}",
"mode": "id"
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"options": {
"googleFileConversion": {
"conversion": {
"docsToFormat": "text/plain"
}
}
}
},
"id": "9f1e08fb-4ef3-4c4d-9473-5a7a1608b8e3",
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"type": "n8n-nodes-base.googleDrive",
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"position": [
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"executeOnce": true,
"credentials": {
"googleDriveOAuth2Api": {
"id": "hKn2avoGUt7FoAyY",
"name": "Google Drive account"
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"options": {}
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"alwaysOutputData": true
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"parameters": {
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"metadata": {
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{
"name": "file_id",
"value": "={{ $('Set File ID').item.json.file_id }}"
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{
"name": "folder_id",
"value": "={{ $('Set File ID').item.json.folder_id }}"
}
]
}
}
},
"id": "da4c8b29-4944-43c4-9df3-e380366c594a",
"name": "Default Data Loader",
"type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
"typeVersion": 1,
"position": [
1860,
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]
},
{
"parameters": {
"chunkSize": 100,
"options": {}
},
"id": "d11c39b9-3fa7-4d5d-838f-da0d258c67c5",
"name": "Recursive Character Text Splitter",
"type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
"typeVersion": 1,
"position": [
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},
{
"parameters": {
"model": "nomic-embed-text:latest"
},
"id": "8a04559c-dfe8-479f-8998-a2e9bc994a0a",
"name": "Embeddings Ollama1",
"type": "@n8n/n8n-nodes-langchain.embeddingsOllama",
"typeVersion": 1,
"position": [
1700,
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],
"credentials": {
"ollamaApi": {
"id": "tEBwcGKXQiQrbKjH",
"name": "Ollama account"
}
}
},
{
"parameters": {
"content": "## Local RAG AI Agent with Chat Interface",
"height": 527.3027193303974,
"width": 670.6821106717343
},
"id": "a18773ae-1eb3-46b8-91cf-4184c66cf14f",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
560,
220
]
},
{
"parameters": {
"content": "## Agent Tools for Local RAG",
"height": 528.85546469693,
"width": 583.4552380860637,
"color": 4
},
"id": "fa010a11-3dda-4bd5-b261-463a3a6b88d9",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
1240,
220
]
},
{
"parameters": {
"content": "## Workflow to Create Local Knowledgebase from Google Drive Folder",
"height": 705.2695614889159,
"width": 1568.9362829025763,
"color": 5
},
"id": "f29e6cc7-015e-47cb-a4fd-fecd6ffb0d24",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
560,
760
]
},
{
"parameters": {
"options": {}
},
"id": "c9dfe906-178b-4375-8bda-f9290f35f222",
"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 1.6,
"position": [
840,
340
]
},
{
"parameters": {
"options": {}
},
"id": "5da52326-dfbd-4350-919c-843461f58913",
"name": "When chat message received",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"typeVersion": 1.1,
"position": [
620,
340
],
"webhookId": "4b3b1838-d6b3-447e-9d79-d0931eddb9f8"
},
{
"parameters": {
"qdrantCollection": {
"__rl": true,
"value": "documents",
"mode": "list",
"cachedResultName": "documents"
},
"options": {}
},
"id": "355370e0-2174-4e5b-830b-dd0f123b2e40",
"name": "Qdrant Vector Store",
"type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
"typeVersion": 1,
"position": [
1260,
480
],
"credentials": {
"qdrantApi": {
"id": "4sxNvYWRIrm2rKl9",
"name": "QdrantApi account"
}
}
},
{
"parameters": {
"code": {
"execute": {
"code": "const { QdrantVectorStore } = require(\"@langchain/qdrant\");\nconst { OllamaEmbeddings } = require(\"@langchain/community/embeddings/ollama\");\n\nconst embeddings = new OllamaEmbeddings({\n model: \"nomic-embed-text\",\n baseUrl: \"http://host.docker.internal:11434\"\n});\n\nconst vectorStore = await QdrantVectorStore.fromExistingCollection(\n embeddings,\n {\n url: \"http://host.docker.internal:6333\",\n collectionName: \"documents\",\n }\n);\n\nconst fileIdToDelete = this.getInputData()[0].json.file_id;\n\nconst filter = {\n must: [\n {\n key: \"metadata.file_id\",\n match: {\n value: fileIdToDelete,\n },\n },\n ],\n }\n\n// const results = await vectorStore.similaritySearch(\"this\", 10, filter);\n// const idsToDelete = results.map((doc) => doc.id);\n\n// NOT IMPLEMENTED!\n// await vectorStore.delete({ ids: idsToDelete });\n\nvectorStore.client.delete(\"documents\", {\n filter\n});\n\nreturn [ {json: { file_id: fileIdToDelete } } ];\n"
}
},
"inputs": {
"input": [
{
"type": "main",
"required": true
}
]
},
"outputs": {
"output": [
{
"type": "main"
}
]
}
},
"id": "b93bd001-0c4d-42fe-939a-eb441f354917",
"name": "Clear Old Vectors",
"type": "@n8n/n8n-nodes-langchain.code",
"typeVersion": 1,
"position": [
1080,
880
],
"alwaysOutputData": false
},
{
"parameters": {
"mode": "insert",
"qdrantCollection": {
"__rl": true,
"value": "documents",
"mode": "list",
"cachedResultName": "documents"
},
"options": {}
},
"id": "97ec4618-c0ea-445b-9406-5d41784d7836",
"name": "Qdrant Vector Store Insert",
"type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
"typeVersion": 1,
"position": [
1760,
880
],
"credentials": {
"qdrantApi": {
"id": "4sxNvYWRIrm2rKl9",
"name": "QdrantApi account"
}
}
}
],
"pinData": {},
"connections": {
"Postgres Chat Memory": {
"ai_memory": [
[
{
"node": "AI Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"Ollama Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Ollama Model": {
"ai_languageModel": [
[
{
"node": "Vector Store Tool",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Vector Store Tool": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Embeddings Ollama": {
"ai_embedding": [
[
{
"node": "Qdrant Vector Store",
"type": "ai_embedding",
"index": 0
}
]
]
},
"File Created": {
"main": [
[
{
"node": "Set File ID",
"type": "main",
"index": 0
}
]
]
},
"File Updated": {
"main": [
[
{
"node": "Set File ID",
"type": "main",
"index": 0
}
]
]
},
"Set File ID": {
"main": [
[
{
"node": "Clear Old Vectors",
"type": "main",
"index": 0
}
]
]
},
"Download File": {
"main": [
[
{
"node": "Extract Document Text",
"type": "main",
"index": 0
}
]
]
},
"Extract Document Text": {
"main": [
[
{
"node": "Qdrant Vector Store Insert",
"type": "main",
"index": 0
}
]
]
},
"Default Data Loader": {
"ai_document": [
[
{
"node": "Qdrant Vector Store Insert",
"type": "ai_document",
"index": 0
}
]
]
},
"Recursive Character Text Splitter": {
"ai_textSplitter": [
[
{
"node": "Default Data Loader",
"type": "ai_textSplitter",
"index": 0
}
]
]
},
"Embeddings Ollama1": {
"ai_embedding": [
[
{
"node": "Qdrant Vector Store Insert",
"type": "ai_embedding",
"index": 0
}
]
]
},
"When chat message received": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
},
"Qdrant Vector Store": {
"ai_vectorStore": [
[
{
"node": "Vector Store Tool",
"type": "ai_vectorStore",
"index": 0
}
]
]
},
"Clear Old Vectors": {
"main": [
[
{
"node": "Download File",
"type": "main",
"index": 0
}
]
]
}
},
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "24e894e6-ec51-4ed0-a3cb-2de36c5d887a",
"meta": {
"templateCredsSetupCompleted": true,
"instanceId": "eb51798708ee5e41b5338814f84985fff5b79dd7e443bf0d1f51648e6d6e003b"
},
"id": "vTN9y2dLXqTiDfPT",
"tags": []
}

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# Self-hosted AI starter kit
**Self-hosted AI Starter Kit** is an open, docker compose template that
quickly bootstraps a fully featured Local AI and Low Code development
environment.
This is Cole's version with a couple of improvements! Also,
the local RAG AI Agent workflow from the video will be automatically in your
n8n instance if you use this setup instead of the base one provided by n8n!
![n8n.io - Screenshot](https://raw.githubusercontent.com/n8n-io/self-hosted-ai-starter-kit/main/assets/n8n-demo.gif)
Curated by <https://github.com/n8n-io>, it combines the self-hosted n8n
platform with a curated list of compatible AI products and components to
quickly get started with building self-hosted AI workflows.
> [!TIP]
> [Read the announcement](https://blog.n8n.io/self-hosted-ai/)
### What’s included
✅ [**Self-hosted n8n**](https://n8n.io/) - Low-code platform with over 400
integrations and advanced AI components
✅ [**Ollama**](https://ollama.com/) - Cross-platform LLM platform to install
and run the latest local LLMs
✅ [**Qdrant**](https://qdrant.tech/) - Open-source, high performance vector
store with an comprehensive API
✅ [**PostgreSQL**](https://www.postgresql.org/) - Workhorse of the Data
Engineering world, handles large amounts of data safely.
### What you can build
⭐️ AI Agents which can schedule appointments
⭐️ Summarise company PDFs without leaking data
⭐️ Smarter slack bots for company comms and IT-ops
⭐️ Analyse financial documents privately and for little cost
## Installation
### For Nvidia GPU users
```
git clone https://github.com/n8n-io/self-hosted-ai-starter-kit.git
cd self-hosted-ai-starter-kit
docker compose --profile gpu-nvidia up
```
> [!NOTE]
> If you have not used your Nvidia GPU with Docker before, please follow the
> [Ollama Docker instructions](https://github.com/ollama/ollama/blob/main/docs/docker.md).
### For Mac / Apple Silicon users
If you’re using a Mac with an M1 or newer processor, you can't expose your GPU
to the Docker instance, unfortunately. There are two options in this case:
1. Run the starter kit fully on CPU, like in the section "For everyone else"
below
2. Run Ollama on your Mac for faster inference, and connect to that from the
n8n instance
If you want to run Ollama on your mac, check the
[Ollama homepage](https://ollama.com/)
for installation instructions, and run the starter kit as follows:
```
git clone https://github.com/n8n-io/self-hosted-ai-starter-kit.git
cd self-hosted-ai-starter-kit
docker compose up
```
After you followed the quick start set-up below, change the Ollama credentials
by using `http://host.docker.internal:11434/` as the host.
### For everyone else
```
git clone https://github.com/n8n-io/self-hosted-ai-starter-kit.git
cd self-hosted-ai-starter-kit
docker compose --profile cpu up
```
## ⚡️ Quick start and usage
The main component of the self-hosted AI starter kit is a docker compose file
pre-configured with network and disk so there isn’t much else you need to
install. After completing the installation steps above, follow the steps below
to get started.
1. Open <http://localhost:5678/> in your browser to set up n8n. You’ll only
have to do this once.
2. Open the included workflow:
<http://localhost:5678/workflow/srOnR8PAY3u4RSwb>
3. Select **Test workflow** to start running the workflow.
4. If this is the first time you’re running the workflow, you may need to wait
until Ollama finishes downloading Llama3.1. You can inspect the docker
console logs to check on the progress.
To open n8n at any time, visit <http://localhost:5678/> in your browser.
With your n8n instance, you’ll have access to over 400 integrations and a
suite of basic and advanced AI nodes such as
[AI Agent](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent/),
[Text classifier](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.text-classifier/),
and [Information Extractor](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.information-extractor/)
nodes. To keep everything local, just remember to use the Ollama node for your
language model and Qdrant as your vector store.
> [!NOTE]
> This starter kit is designed to help you get started with self-hosted AI
> workflows. While it’s not fully optimized for production environments, it
> combines robust components that work well together for proof-of-concept
> projects. You can customize it to meet your specific needs
## Upgrading
### For Nvidia GPU users
```
docker compose --profile gpu-nvidia pull
docker compose create && docker compose --profile gpu-nvidia up
```
### For Mac / Apple Silicon users
```
docker compose pull
docker compose create && docker compose up
```
### For everyone else
```
docker compose --profile cpu pull
docker compose create && docker compose --profile cpu up
```
## 👓 Recommended reading
n8n is full of useful content for getting started quickly with its AI concepts
and nodes. If you run into an issue, go to [support](#support).
- [AI agents for developers: from theory to practice with n8n](https://blog.n8n.io/ai-agents/)
- [Tutorial: Build an AI workflow in n8n](https://docs.n8n.io/advanced-ai/intro-tutorial/)
- [Langchain Concepts in n8n](https://docs.n8n.io/advanced-ai/langchain/langchain-n8n/)
- [Demonstration of key differences between agents and chains](https://docs.n8n.io/advanced-ai/examples/agent-chain-comparison/)
- [What are vector databases?](https://docs.n8n.io/advanced-ai/examples/understand-vector-databases/)
## 🎥 Video walkthrough
- [Installing and using Local AI for n8n](https://www.youtube.com/watch?v=xz_X2N-hPg0)
## 🛍️ More AI templates
For more AI workflow ideas, visit the [**official n8n AI template
gallery**](https://n8n.io/workflows/?categories=AI). From each workflow,
select the **Use workflow** button to automatically import the workflow into
your local n8n instance.
### Learn AI key concepts
- [AI Agent Chat](https://n8n.io/workflows/1954-ai-agent-chat/)
- [AI chat with any data source (using the n8n workflow too)](https://n8n.io/workflows/2026-ai-chat-with-any-data-source-using-the-n8n-workflow-tool/)
- [Chat with OpenAI Assistant (by adding a memory)](https://n8n.io/workflows/2098-chat-with-openai-assistant-by-adding-a-memory/)
- [Use an open-source LLM (via HuggingFace)](https://n8n.io/workflows/1980-use-an-open-source-llm-via-huggingface/)
- [Chat with PDF docs using AI (quoting sources)](https://n8n.io/workflows/2165-chat-with-pdf-docs-using-ai-quoting-sources/)
- [AI agent that can scrape webpages](https://n8n.io/workflows/2006-ai-agent-that-can-scrape-webpages/)
### Local AI templates
- [Tax Code Assistant](https://n8n.io/workflows/2341-build-a-tax-code-assistant-with-qdrant-mistralai-and-openai/)
- [Breakdown Documents into Study Notes with MistralAI and Qdrant](https://n8n.io/workflows/2339-breakdown-documents-into-study-notes-using-templating-mistralai-and-qdrant/)
- [Financial Documents Assistant using Qdrant and](https://n8n.io/workflows/2335-build-a-financial-documents-assistant-using-qdrant-and-mistralai/) [Mistral.ai](http://mistral.ai/)
- [Recipe Recommendations with Qdrant and Mistral](https://n8n.io/workflows/2333-recipe-recommendations-with-qdrant-and-mistral/)
## Tips & tricks
### Accessing local files
The self-hosted AI starter kit will create a shared folder (by default,
located in the same directory) which is mounted to the n8n container and
allows n8n to access files on disk. This folder within the n8n container is
located at `/data/shared` -- this is the path you’ll need to use in nodes that
interact with the local filesystem.
**Nodes that interact with the local filesystem**
- [Read/Write Files from Disk](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.filesreadwrite/)
- [Local File Trigger](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.localfiletrigger/)
- [Execute Command](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.executecommand/)
## 📜 License
This project is licensed under the Apache License 2.0 - see the
[LICENSE](LICENSE) file for details.
## 💬 Support
Join the conversation in the [n8n Forum](https://community.n8n.io/), where you
can:
- **Share Your Work**: Show off what you’ve built with n8n and inspire others
in the community.
- **Ask Questions**: Whether you’re just getting started or you’re a seasoned
pro, the community and our team are ready to support with any challenges.
- **Propose Ideas**: Have an idea for a feature or improvement? Let us know!
We’re always eager to hear what you’d like to see next.

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volumes:
n8n_storage:
postgres_storage:
ollama_storage:
qdrant_storage:
networks:
demo:
x-n8n: &service-n8n
image: n8nio/n8n:latest
networks: ['demo']
environment:
- DB_TYPE=postgresdb
- DB_POSTGRESDB_HOST=postgres
- DB_POSTGRESDB_USER=${POSTGRES_USER}
- DB_POSTGRESDB_PASSWORD=${POSTGRES_PASSWORD}
- N8N_DIAGNOSTICS_ENABLED=false
- N8N_PERSONALIZATION_ENABLED=false
- N8N_ENCRYPTION_KEY
- N8N_USER_MANAGEMENT_JWT_SECRET
links:
- postgres
x-ollama: &service-ollama
image: ollama/ollama:latest
container_name: ollama
networks: ['demo']
restart: unless-stopped
ports:
- 11434:11434
volumes:
- ollama_storage:/root/.ollama
x-init-ollama: &init-ollama
image: ollama/ollama:latest
networks: ['demo']
container_name: ollama-pull-llama
volumes:
- ollama_storage:/root/.ollama
entrypoint: /bin/sh
command:
- "-c"
- "sleep 3; OLLAMA_HOST=ollama:11434 ollama pull llama3.1; OLLAMA_HOST=ollama:11434 ollama pull nomic-embed-text"
services:
postgres:
image: postgres:16-alpine
networks: ['demo']
restart: unless-stopped
ports:
- 5432:5432
environment:
- POSTGRES_USER
- POSTGRES_PASSWORD
- POSTGRES_DB
volumes:
- postgres_storage:/var/lib/postgresql/data
healthcheck:
test: ['CMD-SHELL', 'pg_isready -h localhost -U ${POSTGRES_USER} -d ${POSTGRES_DB}']
interval: 5s
timeout: 5s
retries: 10
n8n-import:
<<: *service-n8n
container_name: n8n-import
entrypoint: /bin/sh
command:
- "-c"
- "n8n import:credentials --separate --input=/backup/credentials && n8n import:workflow --separate --input=/backup/workflows"
volumes:
- ./n8n/backup:/backup
depends_on:
postgres:
condition: service_healthy
n8n:
<<: *service-n8n
container_name: n8n
restart: unless-stopped
ports:
- 5678:5678
volumes:
- n8n_storage:/home/node/.n8n
- ./n8n/backup:/backup
- ./shared:/data/shared
depends_on:
postgres:
condition: service_healthy
n8n-import:
condition: service_completed_successfully
qdrant:
image: qdrant/qdrant
container_name: qdrant
networks: ['demo']
restart: unless-stopped
ports:
- 6333:6333
volumes:
- qdrant_storage:/qdrant/storage
ollama-cpu:
profiles: ["cpu"]
<<: *service-ollama
ollama-gpu:
profiles: ["gpu-nvidia"]
<<: *service-ollama
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: 1
capabilities: [gpu]
ollama-pull-llama-cpu:
profiles: ["cpu"]
<<: *init-ollama
depends_on:
- ollama-cpu
ollama-pull-llama-gpu:
profiles: ["gpu-nvidia"]
<<: *init-ollama
depends_on:
- ollama-gpu

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{
"name": "Local RAG AI Agent",
"nodes": [
{
"parameters": {},
"id": "99b30fd7-b36c-44ba-9daa-408585aaaee9",
"name": "Postgres Chat Memory",
"type": "@n8n/n8n-nodes-langchain.memoryPostgresChat",
"typeVersion": 1.1,
"position": [
900,
560
],
"credentials": {
"postgres": {
"id": "BAhZ6uu3zrQ3JmQm",
"name": "Postgres account"
}
}
},
{
"parameters": {
"model": "llama3.1:latest",
"options": {}
},
"id": "c7632a7c-2661-492e-bd6f-aab994818998",
"name": "Ollama Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOllama",
"typeVersion": 1,
"position": [
760,
560
],
"credentials": {
"ollamaApi": {
"id": "tEBwcGKXQiQrbKjH",
"name": "Ollama account"
}
}
},
{
"parameters": {
"model": "llama3.1:latest",
"options": {}
},
"id": "73d773a4-5c72-4af3-a52d-144f0e417823",
"name": "Ollama Model",
"type": "@n8n/n8n-nodes-langchain.lmOllama",
"typeVersion": 1,
"position": [
1660,
500
],
"credentials": {
"ollamaApi": {
"id": "tEBwcGKXQiQrbKjH",
"name": "Ollama account"
}
}
},
{
"parameters": {
"name": "documents",
"topK": 3
},
"id": "3f882fa7-c8ed-4531-b236-a34c16c55838",
"name": "Vector Store Tool",
"type": "@n8n/n8n-nodes-langchain.toolVectorStore",
"typeVersion": 1,
"position": [
1440,
340
]
},
{
"parameters": {
"model": "nomic-embed-text:latest"
},
"id": "3a8e3fa0-3997-4bce-985c-975fb5ad4013",
"name": "Embeddings Ollama",
"type": "@n8n/n8n-nodes-langchain.embeddingsOllama",
"typeVersion": 1,
"position": [
1540,
600
],
"credentials": {
"ollamaApi": {
"id": "tEBwcGKXQiQrbKjH",
"name": "Ollama account"
}
}
},
{
"parameters": {
"pollTimes": {
"item": [
{
"mode": "everyMinute"
}
]
},
"triggerOn": "specificFolder",
"folderToWatch": {
"__rl": true,
"value": "1914m3M7kRzkd5RJqAfzRY9EBcJrKemZC",
"mode": "list",
"cachedResultName": "Meeting Notes",
"cachedResultUrl": "https://drive.google.com/drive/folders/1914m3M7kRzkd5RJqAfzRY9EBcJrKemZC"
},
"event": "fileCreated",
"options": {}
},
"id": "41fb71dd-236a-48bc-9761-5841d52ca1b3",
"name": "File Created",
"type": "n8n-nodes-base.googleDriveTrigger",
"typeVersion": 1,
"position": [
600,
880
],
"credentials": {
"googleDriveOAuth2Api": {
"id": "hKn2avoGUt7FoAyY",
"name": "Google Drive account"
}
}
},
{
"parameters": {
"pollTimes": {
"item": [
{
"mode": "everyMinute"
}
]
},
"triggerOn": "specificFolder",
"folderToWatch": {
"__rl": true,
"value": "1914m3M7kRzkd5RJqAfzRY9EBcJrKemZC",
"mode": "list",
"cachedResultName": "Meeting Notes",
"cachedResultUrl": "https://drive.google.com/drive/folders/1914m3M7kRzkd5RJqAfzRY9EBcJrKemZC"
},
"event": "fileUpdated",
"options": {}
},
"id": "7b904686-89ae-4722-9ce5-a9da1b13b1a1",
"name": "File Updated",
"type": "n8n-nodes-base.googleDriveTrigger",
"typeVersion": 1,
"position": [
600,
1100
],
"credentials": {
"googleDriveOAuth2Api": {
"id": "hKn2avoGUt7FoAyY",
"name": "Google Drive account"
}
}
},
{
"parameters": {
"assignments": {
"assignments": [
{
"id": "10646eae-ae46-4327-a4dc-9987c2d76173",
"name": "file_id",
"value": "={{ $json.id }}",
"type": "string"
},
{
"id": "dd0aa081-79e7-4714-8a67-1e898285554c",
"name": "folder_id",
"value": "={{ $json.parents[0] }}",
"type": "string"
}
]
},
"options": {}
},
"id": "87f8bbb0-92c5-4b25-be63-7a9d91fc46f8",
"name": "Set File ID",
"type": "n8n-nodes-base.set",
"typeVersion": 3.4,
"position": [
860,
880
]
},
{
"parameters": {
"operation": "download",
"fileId": {
"__rl": true,
"value": "={{ $('Set File ID').item.json.file_id }}",
"mode": "id"
},
"options": {
"googleFileConversion": {
"conversion": {
"docsToFormat": "text/plain"
}
}
}
},
"id": "9f1e08fb-4ef3-4c4d-9473-5a7a1608b8e3",
"name": "Download File",
"type": "n8n-nodes-base.googleDrive",
"typeVersion": 3,
"position": [
1300,
880
],
"executeOnce": true,
"credentials": {
"googleDriveOAuth2Api": {
"id": "hKn2avoGUt7FoAyY",
"name": "Google Drive account"
}
}
},
{
"parameters": {
"operation": "text",
"options": {}
},
"id": "7efee822-68ad-4fe2-a616-ba19fd127684",
"name": "Extract Document Text",
"type": "n8n-nodes-base.extractFromFile",
"typeVersion": 1,
"position": [
1540,
880
],
"alwaysOutputData": true
},
{
"parameters": {
"options": {
"metadata": {
"metadataValues": [
{
"name": "file_id",
"value": "={{ $('Set File ID').item.json.file_id }}"
},
{
"name": "folder_id",
"value": "={{ $('Set File ID').item.json.folder_id }}"
}
]
}
}
},
"id": "da4c8b29-4944-43c4-9df3-e380366c594a",
"name": "Default Data Loader",
"type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
"typeVersion": 1,
"position": [
1860,
1100
]
},
{
"parameters": {
"chunkSize": 100,
"options": {}
},
"id": "d11c39b9-3fa7-4d5d-838f-da0d258c67c5",
"name": "Recursive Character Text Splitter",
"type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
"typeVersion": 1,
"position": [
1860,
1320
]
},
{
"parameters": {
"model": "nomic-embed-text:latest"
},
"id": "8a04559c-dfe8-479f-8998-a2e9bc994a0a",
"name": "Embeddings Ollama1",
"type": "@n8n/n8n-nodes-langchain.embeddingsOllama",
"typeVersion": 1,
"position": [
1700,
1100
],
"credentials": {
"ollamaApi": {
"id": "tEBwcGKXQiQrbKjH",
"name": "Ollama account"
}
}
},
{
"parameters": {
"content": "## Local RAG AI Agent with Chat Interface",
"height": 527.3027193303974,
"width": 670.6821106717343
},
"id": "a18773ae-1eb3-46b8-91cf-4184c66cf14f",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
560,
220
]
},
{
"parameters": {
"content": "## Agent Tools for Local RAG",
"height": 528.85546469693,
"width": 583.4552380860637,
"color": 4
},
"id": "fa010a11-3dda-4bd5-b261-463a3a6b88d9",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
1240,
220
]
},
{
"parameters": {
"content": "## Workflow to Create Local Knowledgebase from Google Drive Folder",
"height": 705.2695614889159,
"width": 1568.9362829025763,
"color": 5
},
"id": "f29e6cc7-015e-47cb-a4fd-fecd6ffb0d24",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
560,
760
]
},
{
"parameters": {
"options": {}
},
"id": "c9dfe906-178b-4375-8bda-f9290f35f222",
"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 1.6,
"position": [
840,
340
]
},
{
"parameters": {
"options": {}
},
"id": "5da52326-dfbd-4350-919c-843461f58913",
"name": "When chat message received",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"typeVersion": 1.1,
"position": [
620,
340
],
"webhookId": "4b3b1838-d6b3-447e-9d79-d0931eddb9f8"
},
{
"parameters": {
"qdrantCollection": {
"__rl": true,
"value": "documents",
"mode": "list",
"cachedResultName": "documents"
},
"options": {}
},
"id": "355370e0-2174-4e5b-830b-dd0f123b2e40",
"name": "Qdrant Vector Store",
"type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
"typeVersion": 1,
"position": [
1260,
480
],
"credentials": {
"qdrantApi": {
"id": "4sxNvYWRIrm2rKl9",
"name": "QdrantApi account"
}
}
},
{
"parameters": {
"code": {
"execute": {
"code": "const { QdrantVectorStore } = require(\"@langchain/qdrant\");\nconst { OllamaEmbeddings } = require(\"@langchain/community/embeddings/ollama\");\n\nconst embeddings = new OllamaEmbeddings({\n model: \"nomic-embed-text\",\n baseUrl: \"http://host.docker.internal:11434\"\n});\n\nconst vectorStore = await QdrantVectorStore.fromExistingCollection(\n embeddings,\n {\n url: \"http://host.docker.internal:6333\",\n collectionName: \"documents\",\n }\n);\n\nconst fileIdToDelete = this.getInputData()[0].json.file_id;\n\nconst filter = {\n must: [\n {\n key: \"metadata.file_id\",\n match: {\n value: fileIdToDelete,\n },\n },\n ],\n }\n\n// const results = await vectorStore.similaritySearch(\"this\", 10, filter);\n// const idsToDelete = results.map((doc) => doc.id);\n\n// NOT IMPLEMENTED!\n// await vectorStore.delete({ ids: idsToDelete });\n\nvectorStore.client.delete(\"documents\", {\n filter\n});\n\nreturn [ {json: { file_id: fileIdToDelete } } ];\n"
}
},
"inputs": {
"input": [
{
"type": "main",
"required": true
}
]
},
"outputs": {
"output": [
{
"type": "main"
}
]
}
},
"id": "b93bd001-0c4d-42fe-939a-eb441f354917",
"name": "Clear Old Vectors",
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87
local-ai-packaged/n8n/backup/workflows/srOnR8PAY3u4RSwb.json Normal file
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