https://github.com/benayat/rag-with-spring-ai
a rag implementation example for document-based QA, using spring-ai, ollama, and postgres-pgvector vetor db.
https://github.com/benayat/rag-with-spring-ai
mistral nomic ollama pgvector rag spring-ai
Last synced: 4 months ago
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a rag implementation example for document-based QA, using spring-ai, ollama, and postgres-pgvector vetor db.
- Host: GitHub
- URL: https://github.com/benayat/rag-with-spring-ai
- Owner: benayat
- Created: 2024-05-05T14:01:26.000Z (about 2 years ago)
- Default Branch: master
- Last Pushed: 2024-05-09T08:39:50.000Z (about 2 years ago)
- Last Synced: 2024-05-09T09:47:32.601Z (about 2 years ago)
- Topics: mistral, nomic, ollama, pgvector, rag, spring-ai
- Language: Java
- Homepage:
- Size: 592 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
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README
## RAG system demo
This is a demo RAG system, which is basically a QA bot which uses solid data to answer questions, rather than relying solely on it's own LLM knowledge.
#### Architecture
The System is based on the following components:
1. Code - spring boot framework with spring ai.
2. Local models deployment, including chat and embeddings generation: ollama.
3. Vector Database, for storing embeddings and querying them: postgres pgvector.
All components used are free and open source.
#### Running the system
##### Prerequisites
- docker, make sure to login to dockerhub.
##### Running
simply download the file "docker-compose.yml" and run `docker-compose up`.