🗄️ RAG, Knowledge Graphs & Vector Databases

Curated repositories for building Retrieval-Augmented Generation (RAG) pipelines, semantic search, and document question-answering systems.

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1. Qdrant

Vector similarity search engine and vector database written in Rust. Fast, scalable, and memory-efficient.

• Replaces: Pinecone ($70-$500+/mo) / Weaviate Cloud
• Official Repo: qdrant/qdrant
• License: Apache-2.0
• Best For: Production-grade semantic search with payload filtering and payload indexing.

💻 One-Click Launch (Docker)

docker run -p 6333:6333 -p 6334:6334 \
    -v $(pwd)/qdrant_storage:/qdrant/storage:z \
    qdrant/qdrant

🐍 Copyable Python Snippet

from qdrant_client import QdrantClient

client = QdrantClient(host="localhost", port=6333)
print(client.get_collections())

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2. Dify

Open-source LLM app development platform. Combines AI workflow, RAG pipeline, agent capabilities, and model management in a visual UI.

• Replaces: Voiceflow / Flowise / Custom RAG backends
• Official Repo: langgenius/dify
• License: Apache-2.0
• Best For: Enterprise-ready visual RAG orchestration and AI assistant builders.

💻 One-Click Launch (Docker Compose)

git clone https://github.com/langgenius/dify.git
cd dify/docker
cp .env.example .env
docker compose up -d

Access at http://localhost/install

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3. LightRAG

Simple and fast Knowledge-Graph-enhanced RAG framework.

• Replaces: Complex multi-hop search algorithms
• Official Repo: HKUDS/LightRAG
• License: MIT
• Best For: Dual-level retrieval (low-level specific entities + high-level thematic relationships).

💻 One-Click Install

pip install lightrag-hku