Recipe Recommendations with Qdrant and Mistral — рабочий процесс n8n

Высокая сложность⚡ Триггер24 узлов🏷️ Miscellaneous👁 6,207 просмотровот Jimleuk

Обзор

This n8n workflow demonstrates creating a recipe recommendation chatbot using the Qdrant vector store recommendation API.

Use this example to build recommendation features in your AI Agents for your users.

How it works

For our recipes, we'll use HelloFresh's weekly course and recipes for data. We'll scrape the website for this data. Each recipe is split, vectorised and inserted into a Qdrant Collection using Mistral Embeddings Additionally the whole recipe is stored in a SQLite database for l

Использованные узлы

HTTP RequestCodeHTMLAI AgentRecursive Character Text SplitterCall n8n Workflow ToolDefault Data LoaderEmbeddings Mistral CloudMistral Cloud Chat ModelQdrant Vector Store

Предпросмотр рабочего процесса

Step 1. Fetch Available Courses For the Curre
To populate our vectorstore, we'll scrape the weekly me
Step 2. Create Recipe Documents For VectorSto
To populate our vectorstore, we'll scrape the weekly me
Step 3. Vectorise Recipes For Recommendation
Read more about Qdrant node
We'll sto
Step 4. Save Original Document to Database
Read more about Code Node
Finally, let's have the original document stored in
5. Chat with Our HelloFresh Recommendation AI
Read more about AI Agents
This agent is designed
5. Using Qdrant's Recommend API & Grouping Fu
Read more about Qdrant's Recommend API
Unlike basic similarity search, Q
Try it out!
This workflow does the following:
* Fetches and stores this week's HelloFresh's menu
* Builds the foundation of a recommendation engine by s
🚨Ensure Qdrant collection exists!
You'll need to run the following command in Qdrant:
```
PUT collections/hello_fresh
{
"vectors": {
🚨Configure Your Qdrant Connection
* Be sure to enter your endpoint address
doctoolembedmodel
⚡
W
When clicking "Test work…
Get This Week's Menu
Extract Available Courses
Extract Server Data
G
Get Course Metadata
Get Recipe
Embeddings Mistral Cloud
Default Data Loader
M
Merge Course & Recipe
P
Prepare Documents
Recursive Character Text…
⚡
C
Chat Trigger
Extract Recipe Details
Qdrant Recommend API
⚡
E
Execute Workflow Trigger
Mistral Cloud Chat Model
G
Get Tool Response
W
Wait for Rate Limits
Get Mistral Embeddings
Use Qdrant Recommend API
Get Recipes From DB
Save Recipes to DB
AI Agent
Qdrant Vector Store
24 nodes22 edges

Как это работает

  1. 1

    Триггер

    Рабочий процесс запускается триггером триггер.

  2. 2

    Обработка

    Данные проходят через 24 узлов, connecting agent, chattrigger, code.

  3. 3

    Вывод

    Рабочий процесс завершает автоматизацию и доставляет результат в настроенное место назначения.

Детали узлов (24)

HT

HTTP Request

httpRequest

#1
CO

Code

code

#2
HT

HTML

html

#3
AI

AI Agent

n8n-nodes-langchain.agent

#4
RE

Recursive Character Text Splitter

n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter

#5
CA

Call n8n Workflow Tool

n8n-nodes-langchain.toolWorkflow

#6
DE

Default Data Loader

n8n-nodes-langchain.documentDefaultDataLoader

#7
EM

Embeddings Mistral Cloud

n8n-nodes-langchain.embeddingsMistralCloud

#8
MI

Mistral Cloud Chat Model

n8n-nodes-langchain.lmChatMistralCloud

#9
QD

Qdrant Vector Store

n8n-nodes-langchain.vectorStoreQdrant

#10

Как импортировать этот рабочий процесс

  1. 1Нажмите кнопку Скачать JSON справа, чтобы сохранить файл рабочего процесса.
  2. 2Откройте ваш экземпляр n8n. Перейдите в Рабочие процессы → Новый → Импорт из файла.
  3. 3Выберите скачанный файл recipe-recommendations-with-qdrant-and-mistral и нажмите Импортировать.
  4. 4Настройте учётные данные для каждого узла сервиса (ключи API, OAuth и т.д.).
  5. 5Нажмите Протестировать рабочий процесс, чтобы убедиться в правильной работе, затем активируйте его.

Или вставьте напрямую в n8n → Импорт из JSON:

{ "name": "Recipe Recommendations with Qdrant and Mistral", "nodes": [...], ...}

Интеграции

agentchattriggercodedocumentdefaultdataloaderembeddingsmistralcloudexecuteworkflowtriggerhtmlhttprequestlmchatmistralcloudmanualtriggermergesettextsplitterrecursivecharactertextsplittertoolworkflowvectorstoreqdrantwait

Получить этот рабочий процесс

Скачайте и импортируйте одним кликом

Скачать JSONПросмотреть на n8n.io
Узлы24
Сложностьhigh
Триггерtrigger
Просмотры6,207
КатегорияMiscellaneous

Создан

Jimleuk

Jimleuk

@jimleuk

Теги

agentchattriggercodedocumentdefaultdataloaderembeddingsmistralcloudexecuteworkflowtriggerhtmlhttprequestlmchatmistralcloudmanualtrigger
⚡

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