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I will build an ai document q and a chatbot using rag
Yuki U
About this gig
I will build a RAG document chatbot that can answer questions using your PDFs, documents, FAQs, or knowledge base content.
The system retrieves relevant information from your documents, sends it to an AI model, and returns answers with source snippets so users can verify where the answer came from.
Depending on the package, I can build a backend-only FastAPI API, a simple chatbot web app, or a more complete RAG app with document upload, vector database setup, Docker Compose, and setup documentation.
Why choose me?
Im a backend-focused software engineer who builds Python APIs, AI/RAG prototypes, and document-search systems using FastAPI, vector databases, Docker, and modern backend tools.
For RAG projects, I focus on more than just connecting an AI API. I pay attention to document chunking, retrieval quality, source snippets, clean API structure, and clear setup documentation.
What you can expect:
- Clear communication before and during the project
- Clean FastAPI backend structure
- Document chunking and vector search setup
- Simple, functional UI depending on the package
- Source code and setup documentation included
Get to know Yuki U
Yuki U
Software Engineer
- FromUnited States
- Member sinceFeb 2018
Languages
English, Japanese
I’m a backend-focused software engineer with experience building APIs, data-heavy backend systems, and product features using Python, Go, TypeScript, React, and SQL. Recently, I’ve been focusing on AI/RAG systems, including a full-stack internal docs assistant built with FastAPI and pgvector. I enjoy building practical, reliable systems that connect technical design with real product value.
FAQ
What is a RAG chatbot?
A RAG chatbot answers questions using your own documents. It first searches your documents for relevant information, then uses an AI model to generate an answer based on those sources.
Can the chatbot answer questions from PDFs?
Yes. I can build the chatbot to work with PDFs, text files, Markdown files, FAQs, or other document content depending on the package and document format.
Will the chatbot include source citations?
Yes. The chatbot can return source snippets or references from the documents so users can verify where the answer came from.
Do I need an OpenAI API key?
In most cases, yes. You can provide your own OpenAI API key or another supported AI provider. If you are not sure, I can guide you on what is needed.
Will you train a custom AI model?
No. This gig does not include training a custom AI model. I build a RAG system that retrieves information from your documents and sends relevant context to an AI model.
Can you guarantee 100% accurate answers?
No AI chatbot can guarantee perfect answers. However, I build the system to retrieve relevant document content and include source snippets to make answers easier to verify.
