I will build a PDF ai chatbot with source citations using rag

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Gergo Balazsf
Certaines informations sont présentées en anglais.

À propos de ce service

Let users ask questions about your PDFs and see which document pages support each answer.


I will build a RAG question-answering backend using OpenAI for embeddings and answers, in one agreed stack: Java, Python, or Rust.


BASIC: Standalone API for 1 PDF, up to 20 pages, 40,000 extracted characters and 10 MB total. In-memory index; documents reload on restart.

STANDARD: Up to 5 documents, 75 pages, 150,000 characters and 25 MB total. Adds a persistent local index and batch import command.

PREMIUM: Up to 10 documents, 150 pages, 300,000 characters and 50 MB total. Standard features integrated into one existing backend service.


All limits apply together. English, text-based files only.


Includes one question endpoint, document/page references, source excerpts, a fallback for missing evidence, source code, setup notes, and a report on 10 agreed test questions.


No OCR, tables/images extraction, crawling, UI, chat memory, access-control system, fine-tuning, or deployment. Citations do not guarantee factual accuracy.


You pay API and hosting costs.


Send a sample document and your stack before ordering.

Découvrez Gergo Balazsf

Gergo Balazsf

AI Automation and Business Data Assistants

  • DeHongrie
  • Membre depuissept. 2026
  • Langues

    Anglais, Espagnol
I help businesses reduce repetitive work and get clear answers from their data. I build focused AI automations for message classification, summaries and reply drafts, CSV/SQL data assistants, and fixes for existing AI workflows. We agree on one task, the inputs and the expected result before starting. Deliverables include the agreed source code and setup notes. API fees, hosting and deployment are scoped separately. Send your current process and a sample input/output. I check your systems before recommending an approach. We can work entirely through Fiverr messages; no call required.

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