Skip to content

saburi004/srsgenerator

Repository files navigation

SRS Generator Platform

Overview

SRS Generator is a collaborative platform designed to streamline the first phase of the Software Development Life Cycle (SDLC)Software Requirement Specification (SRS) generation.
It enables clients, managers, and developers to work together on a single platform to generate, validate, clarify, version, and track SRS documents efficiently using LLMs and RAG-based intelligence.


Key Features

👤 Client Module

  • Generate SRS documents using Agent 1 (LLM-powered).
  • Receive automated validation from Agent 2, ensuring all functional and non-functional requirements are covered.
  • Get suggestions, improvements, and clarification prompts for incomplete or ambiguous requirements.
  • View project progress updates shared by the manager.
  • Track SRS versions and understand cost implications of feature changes.

🧠 Intelligent Agents

  • Agent 1: Generates SRS based on client inputs using LLMs.
  • Agent 2: Reviews SRS completeness, checks requirement coverage, and provides feedback and suggestions.

👨‍💻 Developer Module (RAG-based)

  • Uses Retrieval-Augmented Generation (RAG) to query the SRS directly.
  • Developers can ask natural language questions like:
    • “What color theme is expected?”
    • “What contact details should be added in the footer?”
  • Ensures developers always work with the latest and correct version of the SRS, reducing miscommunication.

📊 Manager Module

  • Update and track project progress.
  • Monitor SRS versions and feature changes.
  • Help optimize project cost by managing feature scope and versions.
  • Ensure transparent communication between clients and developers.

🔁 SRS Version Management

  • Maintains multiple versions of SRS documents.
  • Tracks feature additions, removals, and changes.
  • Supports cost optimization by mapping features to scope and impact.

Tech Stack

🧩 Core Technologies

  • Frontend: Next.js
  • Backend: Node.js, Express.js
  • Database: MongoDB
  • Authentication: NextAuth
  • LLM Provider: Groq
  • Embeddings: Hugging Face
  • Vector Database: Quadrant (Dockerized)
  • RAG Pipeline: Context-aware question answering over SRS
  • Containerization: Docker

Getting Started

First, run the development server:

npm install
docker compose up -d
npm run dev

About

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published