README.md

metadata

title: Requirements Management
emoji: 📄
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 5.27.0
app_file: app.py
pinned: false

Requirements Assistant (Gradio + RAG)

Interactive requirements assistant built with Gradio. Upload a requirements/spec document, ask questions, and the app will retrieve context and either draft a Jira-style ticket or produce a compliance matrix using a Qwen model on OpenRouter. Local sentence-transformer embeddings plus ChromaDB keep everything in-memory for fast, lightweight retrieval.

Features

• Gradio UI with multi-conversation history.
• File upload (.txt/.md/.json/.csv/.pdf) with on-the-fly chunking into an in-memory ChromaDB collection.
• Simple RAG summarizer that routes to one of two agents:
  • Jira ticket generator (JSON shape).
  • Compliance matrix generator (markdown table).
• OpenRouter model calls (defaults to qwen/qwen3-4b:free) with streaming responses.

Prerequisites

• Python 3.10+ recommended.
• pip for installing dependencies.

Setup

1. (Optional) Create/activate a virtual environment.
2. Install dependencies:

   pip install -r requirements.txt
   

3. Provide an API key (preferred: OpenRouter):
   • Create a .env alongside app.py (auto-loaded on startup):

     OPENROUTER_API_KEY=sk-or-...
     

     OPENAI_API_KEY is also accepted as a fallback.

Run the app

python app.py

Gradio will print a local URL. Open it, start a new conversation, optionally upload a file, and ask your question.

Notes

• Embeddings use zacCMU/miniLM2-ENG3 and store data in an in-memory Chroma collection; restart clears uploaded context.
• If you see 429 rate limits from OpenRouter’s free pool, add your own key or switch to a different model in pipelines/requirements_pipe.py.