⚡ Neural Forge — AI Coding Assistant

A full-stack, AI-powered developer cockpit for debugging, explaining, optimizing, and documenting code

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🎯 Why this project

Function	How this project demonstrates it
Scalable applications & services	FastAPI REST API with 11+ endpoints, Pydantic validation, health checks
Clean, maintainable code	Modular backend/frontend, structured prompts, logging
AI/LLM prototypes & tooling	Gemini integration for real dev workflows (debug, refactor, docs)
AI-assisted development	Uses Cursor/Copilot-style workflows; built with AI pair programming
Cloud & containerization	Docker Compose locally; Streamlit Cloud + Render in production
Experimentation mindset	Multiple AI features: chat, repo scan, complexity, commits

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✨ Features

Module	Endpoint	What it does
🔍 Explain	POST /explain	Plain-English code walkthrough
🐛 Debug	POST /debug	Bug detection + fixed code
⚡ Optimize	POST /optimize	Performance & best practices
🔧 Refactor	POST /refactor	Structured refactoring
💬 Ask AI	POST /chat	Free-form Q&A about your code
📄 README	POST /generate-readme	Auto README.md
📝 Commits	POST /commit-message	Conventional Commits from diff
📊 Big-O	POST /complexity	Time/space complexity
🗂️ Repo Scan	POST /repo-summary	Multi-file architecture analysis
📁 Upload	POST /upload-snippet	Analyze uploaded source files

UI: Cyberpunk “Neural Forge” cockpit — animated particle mesh, glass panels, terminal output, session history.

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🏗️ Architecture

┌─────────────────────────────────────────────────────────────────┐
│          Streamlit Community Cloud (Production UI)               │
│   neuralforge-aicodingassistant-*.streamlit.app                  │
└────────────────────────────┬────────────────────────────────────┘
                             │ HTTP/JSON  (BACKEND_URL secret)
                             ▼
┌─────────────────────────────────────────────────────────────────┐
│              Render — FastAPI Backend (Production API)           │
│   neuralforge-ai-coding-assistant.onrender.com · /docs · /health │
│         Pydantic · CORS · Swagger · Logging · Health checks        │
└────────────────────────────┬────────────────────────────────────┘
                             │ google-generativeai SDK
                             ▼
┌─────────────────────────────────────────────────────────────────┐
│              Google Gemini 1.5 Flash (LLM API)                   │
└─────────────────────────────────────────────────────────────────┘

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🚀 Quick Start

Prerequisites

• Python 3.11+
• Gemini API Key (free tier)
• Docker (optional)

1. Clone & configure

git clone https://github.com/bhavyajain0810/NeuralForge-AI_Coding_Assistant.git
cd NeuralForge-AI_Coding_Assistant
cp backend/.env.example backend/.env
# Edit backend/.env → paste GEMINI_API_KEY

2. Run with Docker (recommended)

docker-compose up --build

• UI: http://localhost:8501
• API: http://localhost:8000
• Swagger: http://localhost:8000/docs

3. Local development

# Terminal 1 — Backend
cd backend
python -m venv venv
venv\Scripts\activate          # Windows
pip install -r requirements.txt
uvicorn main:app --reload

# Terminal 2 — Frontend
cd frontend
pip install -r requirements.txt
streamlit run app.py

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📁 Project Structure

NeuralForge-AI_Coding_Assistant/
├── backend/
│   ├── main.py              # FastAPI — all REST endpoints
│   ├── requirements.txt
│   └── .env.example
├── frontend/
│   ├── app.py               # Neural Forge Streamlit UI
│   ├── styles.py            # Cyberpunk CSS + particles
│   └── requirements.txt
├── streamlit_app.py         # Streamlit Cloud entry point
├── requirements.txt         # Root deps for Streamlit Cloud
├── render.yaml              # Render Blueprint config
├── DEPLOY.md                # Deployment guide
├── Dockerfile               # Multi-stage (backend + frontend)
├── docker-compose.yml       # Health checks + networking
├── .gitignore
└── README.md

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🔌 API Examples

Production (Render)

# Health check
curl https://neuralforge-ai-coding-assistant.onrender.com/health

# Explain code
curl -X POST https://neuralforge-ai-coding-assistant.onrender.com/explain \
  -H "Content-Type: application/json" \
  -d '{"code": "def add(a,b): return a+b", "task": "Explain", "language": "Python"}'

Interactive docs: https://neuralforge-ai-coding-assistant.onrender.com/docs

Local

curl http://localhost:8000/health

curl -X POST http://localhost:8000/chat \
  -H "Content-Type: application/json" \
  -d '{"code": "x = [1,2,3]", "question": "What is the time complexity of copying this list?"}'

Local Swagger: http://localhost:8000/docs

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🧰 Tech Stack

Layer	Technology
Backend	Python, FastAPI, Uvicorn, Pydantic
Frontend	Streamlit, custom CSS, HTML5 canvas particles
AI	Google Gemini 1.5 Flash (google-generativeai)
DevOps	Docker, Docker Compose, health checks
Deployment	Streamlit Community Cloud (UI), Render (API)
API style	REST, OpenAPI/Swagger, multipart upload

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🌐 Deploy

Service	Platform	URL / config
Frontend	Streamlit Community Cloud	Live app · Main file: streamlit_app.py · Secret: BACKEND_URL
Backend	Render	API · Env: GEMINI_API_KEY

Full step-by-step instructions: DEPLOY.md

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🔗 Live Demo

	Link
App (UI)	neuralforge-aicodingassistant.streamlit.app
API	neuralforge-ai-coding-assistant.onrender.com
Swagger	/docs
Health	/health
GitHub	NeuralForge-AI_Coding_Assistant