AI-Powered Daily Journal: Day 2 - AI Mood & Theme Analyzer

This project gives you hands-on practice with AI analysis, sentiment analysis, theme extraction, JSON caching, metadata management, and building intelligent tools — essential skills for AI-powered app

Projects in this week’s series:

This week, we build an AI-Powered Daily Journal that writes markdown entries, analyzes your mood with AI, and visualizes your emotional patterns over time!

• Day 1: Markdown Journal Writer

• Day 2: AI Mood & Theme Analyzer (Today)

• Day 3: Insights Dashboard

View All Projects This Week

Today’s Project

Yesterday we built a markdown journal. Today we’re adding AI-powered analysis — Gemini reads each entry, scores your mood from -1 (negative) to +1 (positive), and extracts 3-5 recurring themes!

All analysis is cached as JSON metadata, so re-running is instant and free!

Project Task

Enhance the journal with AI analysis that:

• New review command analyzes entries

• Uses Gemini to score mood (-1 to 1 scale)

• Extracts 3-5 recurring themes per entry

• Caches analysis as JSON metadata files

• Re-runs are instant (reads from cache)

• Shows mood trends over time

• Lists most common themes across all entries

• Clean output with mood emoji indicators

• All Day 1 features still work

This project gives you hands-on practice with AI analysis, sentiment analysis, theme extraction, JSON caching, metadata management, and building intelligent tools — essential skills for AI-powered applications!

Expected Output

Analyzing entries for the first time:

python journal.py review

Console Output:

Setup Instructions

Install Required Package:

pip install langchain-google-genai

Get Your Google API Key:

1. Go to Google AI Studio

2. Click “Create API Key”

3. Copy your key

4. Set environment variable:

# Mac/Linux
export GOOGLE_API_KEY="your-key-here"

# Windows (PowerShell)
$env:GOOGLE_API_KEY="your-key-here"

Or edit the script:

This is a simpler method to provide the API key, but less secure.

GOOGLE_API_KEY = "your-key-here"  # Paste your key

Run analysis:

python journal.py review

Understanding AI Mood Analysis

What is mood scoring?

The AI reads your entry and assigns a score from -1 to 1:

 1.0  Very positive   😄  Joyful, excited, grateful, accomplished
 0.5  Positive        🙂  Happy, content, optimistic
 0.0  Neutral         😐  Balanced, matter-of-fact
-0.5  Negative        😔  Sad, frustrated, disappointed
-1.0  Very negative   😢  Devastated, hopeless, extremely upset

How it works: