Notebook Report Generator

Converts Jupyter notebooks, source code, and experimental results into technical reports in multiple formats.

Purpose

Automates technical report creation for:

• Lab reports and semester projects
• Internship documentation
• Technical documentation
• Research summaries

Features

• Local LLM support (Ollama) and cloud API compatibility
• Multiple output formats: DOCX, PDF, Markdown
• Diagram generation from code structure
• Citation management
• Configurable report templates

Architecture

Input (Notebooks, Code, Data)
    ↓
Document Parser & Analyzer
    ↓
Context Extraction Engine
    ↓
Multi-Agent Report Generator
    ↓
Diagram Generator
    ↓
Output Formatter (DOCX/PDF)

Quick Start

# Clone and setup
git clone https://github.com/haripatel07/report-generator.git
cd report-generator
python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate
pip install -r requirements.txt

# Setup LLM (pick one)
ollama pull llama3                    # easiest
export OPENAI_API_KEY="sk-..."        # OpenAI
export OPENAI_API_KEY="gsk-..."       # or Groq (also set OPENAI_BASE_URL)

# Generate a report
python src/main.py --input notebook.ipynb --type academic --format docx

See the LLM Setup section below if you need help with the model setup.

Requirements

• Python 3.9+
• Local LLM (Ollama) or OpenAI-compatible API
• 8GB+ RAM
• Storage for model weights

Installation

See INSTALLATION.md for detailed setup instructions.

LLM Setup

This tool needs an LLM to generate reports. Pick one:

Using Ollama (easiest option)

If you haven't used LLMs before, start here. It's free and runs locally.

# Install from https://ollama.com
ollama pull llama3
ollama list  # verify it's installed

The tool will use Ollama automatically if you don't set an API key.

Using OpenAI

You'll need an API key and it costs money per request.

1. Get a key from https://platform.openai.com/api-keys
2. Set it in your environment:

# Mac/Linux
export OPENAI_API_KEY="your_key_here"

# Windows PowerShell
setx OPENAI_API_KEY "your_key_here"

Or just create a .env file in the project root:

OPENAI_API_KEY=your_key_here

Important: Restart your terminal after setting the variable.

Using Groq (free alternative)

Similar to OpenAI but with a generous free tier. Groq uses an OpenAI-compatible API.

1. Get a key from https://console.groq.com
2. Add to .env file:

LLM_PROVIDER=openai
LLM_MODEL=llama-3.1-70b-versatile
OPENAI_API_KEY=gsk_your_key_here
OPENAI_BASE_URL=https://api.groq.com/openai/v1

Or set as environment variable:

export OPENAI_API_KEY="gsk_your_key_here"
export OPENAI_BASE_URL="https://api.groq.com/openai/v1"

Testing

# If using Ollama
ollama run llama3 "test"

# Otherwise just try running
python src/main.py --help

Common issues:

• Forgot to restart terminal after setting API key
• Ollama not running (check with ollama list)
• Wrong API key or typo in .env file

Usage

Basic Usage

python src/main.py \
  --input project/notebook.ipynb \
  --type academic \
  --format docx \
  --output report.docx

Advanced Options

python src/main.py \
  --input project/ \
  --type internship \
  --format pdf \
  --title "Machine Learning Internship Report" \
  --institution "XYZ University" \
  --include-code-snippets \
  --diagram-style detailed

Report Types

• academic: University lab reports, course projects
• internship: Weekly and final internship reports
• industry: Professional technical documentation
• research: Research paper drafts and summaries

Project Structure

report-generator/
├── src/
│   ├── agents/          # Multi-agent system
│   ├── parsers/         # Input file parsers
│   ├── generators/      # Content generators
│   ├── formatters/      # Output formatters
│   └── utils/           # Utilities
├── config/              # Configuration files
├── tests/               # Unit and integration tests
├── docs/                # Documentation
└── examples/            # Example inputs/outputs

Contributing

See CONTRIBUTING.md for contribution guidelines.

License

MIT License - see LICENSE for details.