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I will integrate rag with your private documents
KhoaMinh P
Über diesen Service
Your application already has a product, interface, or user base. Now it needs a reliable way to answer questions using your own documents.
I will add a retrieval-augmented generation, or RAG, system to your existing web application or backend. Your users will be able to ask questions about PDFs, documentation, policies, reports, knowledge bases, or other text-based files and receive grounded answers with relevant source references.
Depending on your package, I can:
- Process and organize your documents
- Generate embeddings and configure a vector database
- Build a FastAPI or REST API endpoint
- Connect RAG to your existing application
- Add source citations to generated answers
- Test and improve retrieval quality
- Document the setup for future development
My primary stack includes Python, FastAPI, ChromaDB, REST APIs, and major LLM providers. I can also integrate the backend with compatible JavaScript and TypeScript applications.
This gig is specifically for adding RAG to an existing application. It does not include building an entire SaaS product from scratch.
Please contact me before ordering if your project requires multiple data sources, advanced authentication, a custom frontend, or prod
Lerne KhoaMinh P kennen
KhoaMinh P
Fullstack software engineering student
- AusVereinigte Staaten
- Mitglied seitAug. 2026
Sprachen
Englisch
I am a full-stack software engineering student at Bucknell University with production experience shipping web features, designing backend systems, and building AI-powered applications. I have a proven ability to work across the stack, from REST APIs and database design to browser-based interfaces and cloud deployment, in fast-paced, cross-functional environments.
FAQ
What is RAG?
Retrieval-augmented generation allows an AI model to retrieve relevant information from your documents before generating an answer. This helps produce answers based on your own data instead of relying only on the model’s general knowledge.
Will you train an AI model on my documents?
No. This service indexes and retrieves information from your documents. It does not fine-tune or retrain the underlying language model.
Can you add RAG to my existing website?
Yes, provided your application has an accessible codebase or API architecture that supports the integration. Please contact me before ordering so I can review your stack.
Which document formats do you support?
The standard scope supports PDF, TXT, and Markdown files. Word documents, webpages, databases, Google Drive, and other sources may require a custom offer.
Are API and hosting costs included?
No. Any charges from model providers, embedding providers, vector databases, cloud platforms, or hosting services are paid directly by the client.
Will the chatbot provide sources?
Source citations are included in the Standard and Premium packages. The response can identify the documents or sections used to generate an answer.
Is a chat interface included?
The Basic package provides a backend endpoint only. Connecting to an existing interface is included in Standard and Premium. Designing a completely new frontend requires an extra or custom offer.
How will you handle confidential documents?
Only provide files that you are authorized to share. Confidential information should be redacted unless we have agreed on an appropriate access and development workflow.
