Production-ready Claude AI backend using FastAPI, Docker, and GitHub Actions.π
claude-personql-ai/
β
βββ app/
β βββ api/
β βββ services/
β β βββ claude_service.py
β β βββ embedding_service.py
β β βββ vector_store.py
β β βββ rag_pipeline.py
β β
β βββ knowledge/
β β βββ loader.py
β β βββ chunker.py
β β
β βββ prompts/
β β βββ rag_prompt.py
β β
β βββ main.py
β
βββ data/ # εζΎη₯θ―ζζ‘£
βββ vector_db/ # ζ¬ε°ειεΊεε¨
βββ scripts/
β βββ ingest.py # ζε»ΊειεΊ
β
βββ requirements.txt
βββ Dockerfile
βββ docker-compose.yml
βββ README.md
fastapi
uvicorn
anthropic
sentence-transformers
faiss-cpu
python-dotenv
git clone https://github.com/yourname/claude-rag-ai
cd claude-rag-ai
pip install -r requirements.txt
cp .env.example .env
Place your private documents into:
data/
python scripts/ingest.py
uvicorn app.main:app --reload
β’ Never commit .env
β’ Store API keys in GitHub Secrets
β’ Validate file uploads
β’ Protect vector DB access
β’ Enable HTTPS in production
β’ Filter prompts against injection attacks
- Edward, S. G., Bhattacharya, R., & Sinha, V. (2025). Enterprise Guide for Implementing Generative AI and Agentic AI. Springer. https://link.springer.com/chapter/10.1007/979-8-8688-1603-1
2. Edward, S. G., Bhattacharya, R., & Sinha, V. (2025). Evaluation and Deployment. Springer. https://link.springer.com/chapter/10.1007/979-8-8688-1603-1_6
3. Huang, K., & Hughes, C. (2025). Deploying Agentic AI in Enterprise Environments. Springer. https://link.springer.com/chapter/10.1007/978-3-032-02130-4_10
4. Serafim de Oliveira, M. C. (2025). A Comparative Analysis of LLM-Based Multi-Agent Frameworks. https://www.doria.fi/handle/10024/193122
5. Sahu, S. K. (2025). Generative AI-Driven Application Development. Springer.
6. More, P., et al. (2025). Leveraging CI/CD to Operationalize LLM Chatbots. IEEE.
7. Mittal, A., & Venkatesan, V. (2025). Integration of LLMs into Enterprise CI/CD Pipelines. IEEE.
8. Xu, R., & Yan, Y. (2026). Agent Skills for Large Language Models. arXiv:2602.12430 https://arxiv.org/abs/2602.12430