Custom AI Chat Platform Development
Budget: $30 – $250 USD
Development of a Private AI Chat Platform Based Only on Custom Documents and Videos (Open Source RAG System) I am looking for an experienced AI / LLM / RAG developer to build a private ChatGPT-like platform that answers questions exclusively using files and content uploaded by me.
IMPORTANT:
The AI must NOT browse the internet.
All answers must be generated ONLY from the PDFs, books, videos, and documents uploaded into the system.
The goal is to create a closed/private AI knowledge assistant based on proprietary content.
Required Features:
FRONTEND:
* Simple ChatGPT-style chat interface
* Basic user authentication/login
* Optional chat history
* Clean and functional UI
ADMIN/BACKEND:
* Private admin dashboard
* Ability to upload:
* PDFs
* EPUB/books
* DOCX/TXT files
* YouTube/video links
* Other text-based files
* Automatic indexing of uploaded content
* Re-indexing functionality
* User management
AI / RAG FUNCTIONALITY:
* AI must answer ONLY using uploaded content
* No internet/web search
* Preferably based on open-source models
* Minimal or no recurring monthly costs
* Fully deployable on AWS
PREFERRED TECHNOLOGIES:
* Python
* LangChain or LlamaIndex
* Ollama / vLLM / open-source LLMs
* ChromaDB, Qdrant, or FAISS
* FastAPI or similar
* Simple frontend using React/Vue or similar
INFRASTRUCTURE:
* Development will be done directly on my AWS instance
* SSH access via .pem key will be provided
* Developer must work directly on that server
IMPORTANT:
I have a limited budget.
I am looking for a simple, functional, scalable, and low-maintenance open-source solution.
Please include:
* Previous RAG / LLM project experience
* Proposed technology stack
* Recommended open-source model
* Estimated timeline
* Estimated budget
DELIVERABLE REQUIREMENTS:
* Full source code delivery required
* Dockerized deployment required
* No mandatory paid APIs
* System must work fully on my AWS server
* AI must answer ONLY using uploaded sources
* If information is not found in the uploaded content, the AI must explicitly say so
* Complete installation documentation required
* Low-maintenance architecture preferred
* Please include estimated AWS hardware requirements
IMPORTANT:
The AI must NOT browse the internet.
All answers must be generated ONLY from the PDFs, books, videos, and documents uploaded into the system.
The goal is to create a closed/private AI knowledge assistant based on proprietary content.
Required Features:
FRONTEND:
* Simple ChatGPT-style chat interface
* Basic user authentication/login
* Optional chat history
* Clean and functional UI
ADMIN/BACKEND:
* Private admin dashboard
* Ability to upload:
* PDFs
* EPUB/books
* DOCX/TXT files
* YouTube/video links
* Other text-based files
* Automatic indexing of uploaded content
* Re-indexing functionality
* User management
AI / RAG FUNCTIONALITY:
* AI must answer ONLY using uploaded content
* No internet/web search
* Preferably based on open-source models
* Minimal or no recurring monthly costs
* Fully deployable on AWS
PREFERRED TECHNOLOGIES:
* Python
* LangChain or LlamaIndex
* Ollama / vLLM / open-source LLMs
* ChromaDB, Qdrant, or FAISS
* FastAPI or similar
* Simple frontend using React/Vue or similar
INFRASTRUCTURE:
* Development will be done directly on my AWS instance
* SSH access via .pem key will be provided
* Developer must work directly on that server
IMPORTANT:
I have a limited budget.
I am looking for a simple, functional, scalable, and low-maintenance open-source solution.
Please include:
* Previous RAG / LLM project experience
* Proposed technology stack
* Recommended open-source model
* Estimated timeline
* Estimated budget
DELIVERABLE REQUIREMENTS:
* Full source code delivery required
* Dockerized deployment required
* No mandatory paid APIs
* System must work fully on my AWS server
* AI must answer ONLY using uploaded sources
* If information is not found in the uploaded content, the AI must explicitly say so
* Complete installation documentation required
* Low-maintenance architecture preferred
* Please include estimated AWS hardware requirements