| Availability |
Odoo Online
Odoo.sh
On Premise
|
| Odoo Apps Dependencies |
Discuss (mail)
|
| Community Apps Dependencies | Show |
| Lines of code | 5156 |
| Technical Name |
llm_qdrant |
| License | LGPL-3 |
| Website | https://github.com/apexive/odoo-llm |
| Versions | 16.0 18.0 |
| Availability |
Odoo Online
Odoo.sh
On Premise
|
| Odoo Apps Dependencies |
Discuss (mail)
|
| Community Apps Dependencies | Show |
| Lines of code | 5156 |
| Technical Name |
llm_qdrant |
| License | LGPL-3 |
| Website | https://github.com/apexive/odoo-llm |
| Versions | 16.0 18.0 |
LLM Qdrant Integration
Integrates Qdrant vector store with the Odoo LLM framework.
High-performance vector search with Qdrant vector database
What is Qdrant?
A high-performance vector database for AI applications
Qdrant is an open-source vector database and search engine built for production use. This module provides an llm.store implementation using Qdrant, enabling fast and scalable vector similarity search for your Odoo knowledge bases and AI assistants.
Why Qdrant?
Benefits of using Qdrant for vector storage
Built for Speed
Qdrant is optimized for fast similarity search even with millions of vectors.
Scalable
Handles large-scale deployments with distributed architecture support.
Cloud or Self-Hosted
Run on Qdrant Cloud or deploy on your own infrastructure.
Technical Details
Requirements and dependencies
Module Information
llm_knowledge, llm_store
qdrant-client
Technical
LGPL-3
Qdrant Provider for Odoo LLM
High-performance vector database for semantic search at scale.
Module Type: 🗄️ Vector Store (High Performance)
Architecture
┌───────────────────────────────────────────────────────────────┐
│ Used By (RAG Modules) │
│ ┌───────────────┐ ┌───────────────┐ │
│ │ llm_knowledge │ │llm_assistant │ │
│ │ (RAG) │ │ (with RAG) │ │
│ └───────┬───────┘ └───────┬───────┘ │
└────────────────┼───────────────────────────┼─────────────────┘
└─────────────┬─────────────┘
▼
┌───────────────────────────────────────────┐
│ llm_store │
│ (Vector Store API) │
└─────────────────────┬─────────────────────┘
│
▼
┌───────────────────────────────────────────┐
│ ★ llm_qdrant (This Module) ★ │
│ Qdrant Implementation │
│ 🔷 High Performance │ Scalable │ Fast │
└─────────────────────┬─────────────────────┘
│
▼
┌───────────────────────────────────────────┐
│ Qdrant Server │
│ (localhost:6333) │
└───────────────────────────────────────────┘
Installation
What to Install
For high-performance RAG:
# 1. Start Qdrant server docker run -p 6333:6333 qdrant/qdrant # 2. Install the Odoo module odoo-bin -d your_db -i llm_knowledge,llm_qdrant
Auto-Installed Dependencies
- llm (core infrastructure)
- llm_store (vector store abstraction)
Why Choose Qdrant?
Vector Store Comparison
| Feature | llm_pgvector | llm_qdrant | llm_chroma |
|---|---|---|---|
| Server | 🐘 PostgreSQL | 🔷 Qdrant | 🌈 Chroma |
| Setup | Easy | Moderate | Moderate |
| Scale | Medium | High | Medium |
| Best For | Simple RAG | Large scale | Development |
Common Setups
| I want to... | Install |
|---|---|
| High-performance RAG | llm_knowledge + llm_qdrant |
| Chat + scalable RAG | llm_assistant + llm_openai + llm_knowledge + llm_qdrant |
Features
- Qdrant vector storage
- High-performance similarity search
- Scalable vector operations
- Advanced filtered search support
- Collection management
Configuration
Set up Qdrant server connection in LLM > Configuration > Vector Stores:
- Host: Qdrant server hostname (e.g., localhost)
- Port: Qdrant port (default: 6333)
- API Key: Authentication key (if required)
- Collection Name: Default collection name
Technical Specifications
- Version: 18.0.1.0.0
- License: LGPL-3
- Dependencies: llm, llm_store
- Python Package: qdrant-client
License
LGPL-3
© 2025 Apexive Solutions LLC
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