README
¶
Weaviate — RAG with Weaviate
Interactive RAG chat with Weaviate as a vector store. The collection is created automatically on first run.
Quick start
1. Start Weaviate:
docker compose up -d
2. Run the example:
cd examples/weaviate && cp .env.example .env && go run .
For mock mode this is sufficient. For a real LLM, set LLM_PROVIDER=ollama|openai|anthropic and the corresponding keys.
Environment variables
| Variable | Default | Description |
|---|---|---|
LLM_PROVIDER |
mock |
LLM provider (mock, ollama, openai, anthropic) |
EMBEDDING_DIM |
1536 |
Vector dimension |
WEAVIATE_URL |
http://localhost:8080 |
Weaviate server URL |
COLLECTION_NAME |
DraftragChunk |
Weaviate class name |
Tutorial
Detailed guide on hybrid search — tutorial 03: Hybrid Search.
Documentation
Source Files
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