Screenshots of the finished app will be added here before it goes on sale.

Coming soonIntermediate

Production RAG Chatbot

A complete retrieval-augmented generation (RAG) application. Upload PDFs, and it extracts and cleans the text, splits it into chunks, creates embeddings with Sentence Transformers and stores them in a FAISS index. Questions are answered by a Groq-hosted LLM using only the retrieved chunks, with citations back to the source pages. It runs locally or in Docker.

from ₹499 at launch

One-time payment · 3 editions · licence · not on sale yet

Choose your edition Try the free demo

For: GenAI job seekers and Python developers

Try the free demo¶

A related free tool you can try now: Chat with your website. It's a demo, not the app you'd buy. Here's the difference.

The free demo

Answers from a website you enter, not from your own PDFs
Runs on our server with usage limits
No PDF upload, and no source code

The paid app adds

Upload your own PDFs and ask about them
Citations to the file and page behind each answer
Runs on your own machine, with the full source code to change

Open the demo in a new tab ↗

Overview¶

The problem it solves

General chatbots can't see your own documents, and when they guess they sound just as confident as when they're right. This app answers only from the PDFs you upload and shows exactly which page each answer came from, so you can check it.

Who it's for

GenAI job seekers and Python developers · Intermediate level

Main benefits

Answers grounded in your documents, with a citation for every claim
Runs on your machine; only the question and the retrieved passages go to the LLM API
Fast and low-cost answers from Groq-hosted open models
The RAG pipeline interviewers ask about, built and explained end to end

Features¶

This app is in development. These are the features of the finished app; screenshots and the exact file list will be added before it goes on sale.

What it does

Upload one or more PDFs
Ask questions in plain English
Answers with source citations (file and page)
"I couldn't find this in the documents" when the answer isn't there
Re-index or remove documents

Technical capabilities

Text extraction and cleaning per page
Configurable chunk size and overlap
Sentence Transformers embeddings, computed locally
FAISS vector search with top-k retrieval
Grounded prompt with citation rules, Groq LLM call
FastAPI backend with typed request and response models

Architecture¶

flowchart LR
  U[User] -->|upload PDF| API[FastAPI backend]
  API --> P[Extract and clean text]
  P --> C[Split into chunks]
  C --> E[Sentence Transformers embeddings]
  E --> V[(FAISS index)]
  U -->|question| API
  API --> Q[Embed question]
  Q --> V
  V -->|top-k chunks| G[Prompt with sources]
  G --> L[Groq LLM]
  L -->|answer + citations| U

Data flow

The PDF is uploaded to the FastAPI backend, which extracts and cleans the text page by page.
The text is split into overlapping chunks, each tagged with its file and page.
Each chunk is embedded with Sentence Transformers and added to the FAISS index on disk.
A question is embedded the same way, and FAISS returns the most similar chunks.
The chunks go into a prompt that tells the LLM to answer only from them and cite them.
Groq's LLM writes the answer, which is returned with its citations.

Backend components

FastAPI app with upload, ask and document-management endpoints
Document processor (PDF text extraction and cleaning)
Chunker with configurable size and overlap
FAISS index stored on disk, with chunk metadata

AI components

Sentence Transformers embedding model (runs locally on CPU)
Retriever (top-k similarity search)
Prompt builder with grounding and citation rules
Groq-hosted LLM for answer generation

Technology stack¶

Technology	What it does here
Python	The language of the whole app
FastAPI	REST backend with typed endpoints
Sentence Transformers	Local text embeddings
FAISS	Vector index and similarity search
Groq	Fast LLM inference through an API
Docker	Containers for local and cloud runs

What's included¶

Everything is delivered as a private download after payment. Nothing paid is ever public on this site.

What you get	Learner	Career	Developer
Complete source code (ZIP)The whole application: backend, frontend and configuration, organised as a real project.	✓	✓	✓
READMEWhat the app does, how the code is organised and how to run it.	✓	✓	✓
Requirements filerequirements.txt with pinned versions, so installs are repeatable.	✓	✓	✓
Environment example.env.example listing every setting and API key, with safe defaults.	✓	✓	✓
Setup tutorialStep-by-step guide from download to a running app on Windows, macOS or Linux.	✓	✓	✓
Architecture diagramThe diagram on this page as an image, plus the source to edit it.	–	✓	✓
Architecture walkthroughWhy each component exists and how a request flows through the code.	–	✓	✓
Interview Q&AQuestions interviewers ask about a project like this, with model answers.	–	✓	✓
Resume bullet pointsReady-to-adapt bullet points describing the project for your resume.	–	✓	✓
Docker configurationDockerfile and docker-compose.yml to run it in containers.	–	–	✓
Test casesAutomated tests (pytest) for the main features.	–	–	✓
Deployment guideHow to deploy it to a cloud platform, with the settings to change for production.	–	–	✓

System requirements¶

Python	Python 3.11 or newer
Memory (RAM)	4 GB (8 GB recommended for large PDFs)
Disk space	About 2 GB for dependencies and the embedding model
Python packages	`fastapi` `uvicorn` `sentence-transformers` `faiss-cpu` `groq` `pypdf` `python-multipart` `pydantic-settings`
API keys and services	A Groq API key (Groq offers a free tier with rate limits)
Operating system	Windows, macOS or Linux

Choose your edition¶

Learner Edition

₹499 one-time · at launch

Learn how it works and run it yourself.

Complete source code (ZIP)
README
Requirements file
Environment example
Setup tutorial

Licence: Personal licence

Support: Help by email if a file is missing or won't open.

Notify me at launch

Career Edition

₹799 one-time · at launch

Everything to present it in interviews and on your resume.

Complete source code (ZIP)
README
Requirements file
Environment example
Setup tutorial
Architecture diagram
Architecture walkthrough
Interview Q&A
Resume bullet points

Licence: Personal licence

Support: Help by email if a file is missing or won't open.

Notify me at launch

Developer Edition

₹1,499 one-time · at launch

Production extras and a commercial licence for client work.

Complete source code (ZIP)
README
Requirements file
Environment example
Setup tutorial
Architecture diagram
Architecture walkthrough
Interview Q&A
Resume bullet points
Docker configuration
Test cases
Deployment guide

Licence: Commercial licence

Support: 30 days of email support for setup and code questions, plus help with file problems.

Notify me at launch

Prices are in Indian rupees, one-time, with no subscription. Not on sale yet: "Notify me" adds you to the launch list for this app.

Licence and support¶

Personal licence

Use the code to learn, run it for yourself and show it in your portfolio and interviews. You may not resell or redistribute the code, or use it in work for clients.

Comes with: Learner Edition, Career Edition

Commercial licence

Everything in the personal licence, plus use in your own commercial products and in work for clients. You may not resell or redistribute the source code itself, as-is or as a template.

Comes with: Developer Edition

Learner Edition: Help by email if a file is missing or won't open.
Career Edition: Help by email if a file is missing or won't open.
Developer Edition: 30 days of email support for setup and code questions, plus help with file problems.

Full wording: Licence information · Refund policy

FAQ¶

When can I buy it?

It's in development and not on sale yet. Leave your email below and you'll get one email when it launches.

Which edition should I choose?

Learner if you want to study the code and run it yourself. Career if you'll present it in interviews or on your resume: it adds the architecture walkthrough, interview Q&A and resume bullet points. Developer if you'll use it in client or commercial work: it adds Docker, tests, a deployment guide, a commercial licence and 30 days of email support.

How will I receive the files?

After payment you'll get a private download of the ZIP for your edition. Paid files are never public on this site.

Does it include API keys or hosting?

No. You'll use your own API keys (see System requirements) and run it on your own machine or server.

Can I use it for client work?

Only with the Developer Edition's commercial licence. See Licence information.

Can I get a refund?

See the Refund & Cancellation Policy. It will be updated with the terms for source code before any app goes on sale.

I have a question that isn't answered here.

Use the contact page or email aiwithpriyabrat@gmail.com. We reply within 2 working days.

Get Production RAG Chatbot at launch

It's in development. Leave your email and you'll get one message when it goes on sale, from ₹499. No spam.

Compare editions · Browse all AI projects

Production RAG Chatbot

Try the free demo¶

The free demo

The paid app adds

Overview¶

The problem it solves

Who it's for

Main benefits

Features¶

What it does

Technical capabilities

Architecture¶

Data flow

Backend components

AI components

Technology stack¶

What's included¶

System requirements¶

Choose your edition¶

Learner Edition

Career Edition

Developer Edition

Licence and support¶

Personal licence

Commercial licence

FAQ¶

Related applications¶

AI SQL Analyst

AI Resume Analyzer

AI Agent Application

Get Production RAG Chatbot at launch