About this recipe
A recipe for Building Rag Chatbot For Movie Recommendations With Qdrant And Open Ai
Recipe Template
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"mode": "name",
"value": "mrscoopers"
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"filePath": "Top_1000_IMDB_movies.csv",
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{
"name": "movie_name",
"value": "={{ $('Extract from File').item.json['Movie Name'] }}"
},
{
"name": "movie_release_date",
"value": "={{ $('Extract from File').item.json['Year of Release'] }}"
},
{
"name": "movie_description",
"value": "={{ $('Extract from File').item.json.Description }}"
}
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"parameters": {
"name": "movie_recommender",
"schemaType": "manual",
"workflowId": {
"__rl": true,
"mode": "id",
"value": "a58HZKwcOy7lmz56"
},
"description": "Call this tool to get a list of recommended movies from a vector database. ",
"inputSchema": "{\n\"type\": \"object\",\n\"properties\": {\n\t\"positive_example\": {\n \"type\": \"string\",\n \"description\": \"A string with a movie description matching the user's positive recommendation request\"\n },\n \"negative_example\": {\n \"type\": \"string\",\n \"description\": \"A string with a movie description matching the user's negative anti-recommendation reuqest\"\n }\n}\n}",
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"parameters": {
"options": {
"systemMessage": "You are a Movie Recommender Tool using a Vector Database under the hood. Provide top-3 movie recommendations returned by the database, ordered by their recommendation score, but not showing the score to the user."
}
},
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},
{
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"parameters": {
"url": "https:\/\/edcc6735-2ffb-484f-b735-3467043828fe.europe-west3-0.gcp.cloud.qdrant.io:6333\/collections\/imdb_1000_open_ai\/points",
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"jsonBody": "={\n \"ids\": [\"{{ $json.result.points[0].id }}\", \"{{ $json.result.points[1].id }}\", \"{{ $json.result.points[2].id }}\"],\n \"with_payload\":true\n}",
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"assignments": [
{
"id": "b4b520a5-d0e2-4dcb-af9d-0b7748fd44d6",
"name": "movie_recommendation_score",
"type": "number",
"value": "={{ $json.score }}"
},
{
"id": "c9f0982e-bd4e-484b-9eab-7e69e333f706",
"name": "movie_description",
"type": "string",
"value": "={{ $json.payload.content }}"
},
{
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"name": "movie_name",
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"value": "={{ $json.payload.metadata.movie_name }}"
},
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},
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"parameters": {
"content": "Tool, calling Qdrant's recommendation API based on user's request, transformed by AI agent"
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"parameters": {
"content": "Uploading data (movies and their descriptions) to Qdrant Vector Store\n"
},
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],
"active": false,
"pinData": {
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{
"json": {
"query": {
"negative_example": "horror bloody movie",
"positive_example": "romantic comedy"
}
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]
},
"settings": {
"executionOrder": "v1"
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"versionId": "40d3669b-d333-435f-99fc-db623deda2cb",
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"GitHub": {
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"Token Splitter": {
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"node": "Default Data Loader",
"type": "ai_textSplitter",
"index": 0
}
]
]
},
"Embeddings OpenAI": {
"ai_embedding": [
[
{
"node": "Qdrant Vector Store",
"type": "ai_embedding",
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]
]
},
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"main": [
[
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},
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"type": "ai_languageModel",
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},
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"type": "ai_document",
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},
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},
{
"node": "Embedding Anti-Recommendation Request with Open AI",
"type": "main",
"index": 0
}
]
]
},
"When chat message received": {
"main": [
[
{
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]
},
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},
{
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"type": "main",
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}
]
]
},
"When clicking \u2018Test workflow\u2019": {
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[
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"type": "main",
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}
]
]
},
"Selecting Fields Relevant for Agent": {
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}
]
]
},
"Retrieving Recommended Movies Meta Data": {
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[
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}
]
]
},
"Embedding Recommendation Request with Open AI": {
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{
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}
]
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},
"Embedding Anti-Recommendation Request with Open AI": {
"main": [
[
{
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}
]
]
}
}
}How to Use an n8n Template
1
Create a New Workflow
Click "New Workflow" in your n8n dashboard to get started.
2
Copy & Paste Template
First, copy this template:
Click here to copy the JSON
.
Then, in n8n, click the three dots (···) → "Import from file" and paste the JSON code.
3
Customize the Nodes
Go through each node in the workflow to update inputs like spreadsheet IDs, email addresses, or message content. Adjust field mappings to match your data.
4
Grant Access
For nodes that connect to external apps (like Google Sheets or Slack), you'll need to grant access. Connect your accounts using OAuth or an API key and save the credentials in the node.
5
Test It
Run the workflow by clicking "Execute Node" for each step or "Run Once" for the whole thing. Check the right sidebar to inspect data and debug any errors (they'll show up in red).
6
Activate Workflow
Once everything works as expected, click the "Activate" toggle to turn your workflow on. You're all set!