merleau 0.4.1

Video analysis using Google's Gemini 2.5 Flash API

Merleau

"The world is not what I think, but what I live through." — Maurice Merleau-Ponty

A CLI tool for video understanding using Google's Gemini API. Named after Maurice Merleau-Ponty, the phenomenologist philosopher whose work on perception inspires how this tool helps you perceive your videos.

Website · Web App · PyPI · GitHub

https://github.com/user-attachments/assets/e2c5b476-ddab-49ab-a35c-9ae5e880c25c

Why Merleau?

Google Gemini is the only major AI provider with native video understanding—Claude doesn't support video, and GPT-4o requires frame extraction workarounds. Merleau is the first CLI that actually understands video rather than analyzing frames.

Features

• Native Gemini video processing - Upload and analyze videos directly
• YouTube URL support - Analyze videos directly from YouTube (free preview)
• Customizable prompts - Ask any question about your video
• Cost estimation - Token usage tracking and cost breakdown
• Multiple models - Support for different Gemini models
• Web UI - Streamlit app for browser-based analysis

Installation

Using uv (recommended):

uv sync

Or install from PyPI:

pip install merleau

Configuration

1. Get a Gemini API key from Google AI Studio
2. Set the API key as an environment variable or create a .env file:

   GEMINI_API_KEY=your_api_key_here
   

Usage

# Basic video analysis
ponty video.mp4

# Custom prompt
ponty video.mp4 -p "Summarize the key points in this video"

# Use a different model
ponty video.mp4 -m gemini-2.0-flash

# Hide cost information
ponty video.mp4 --no-cost

Web UI

Try it online: https://merleau.streamlit.app/

Or run locally:

pip install merleau[web]
streamlit run streamlit_app.py

Options

Option	Description
-p, --prompt	Prompt for the analysis (default: "Explain what happens in this video")
-m, --model	Gemini model to use (default: gemini-2.5-flash)
--no-cost	Hide usage and cost information

Reducing Costs with Compression

Compressing videos before analysis can reduce API costs by ~10-15% without degrading analysis quality. Gemini's token count is affected by video resolution and bitrate.

Quick Compression with ffmpeg

# Basic compression (recommended)
ffmpeg -i input.mp4 -vcodec libx264 -crf 28 -preset medium -vf "scale=1280:-2" output.mp4

# Aggressive compression (smaller file, lower quality)
ffmpeg -i input.mp4 -vcodec libx264 -crf 32 -preset medium -vf "scale=640:-2" output.mp4

# Keep audio (for speech analysis)
ffmpeg -i input.mp4 -vcodec libx264 -crf 28 -preset medium -vf "scale=1280:-2" -acodec aac -b:a 128k output.mp4

Compression Options Explained

Option	Description
-crf 28	Quality level (18-28 recommended, higher = smaller file)
-preset medium	Encoding speed/quality tradeoff
-vf "scale=1280:-2"	Resize to 1280px width, maintain aspect ratio
-an	Remove audio (if not needed)
-acodec aac -b:a 128k	Compress audio to 128kbps AAC

Cost Comparison Example

Version	File Size	Prompt Tokens	Input Cost
Original (1080p)	52 MB	14,757	$0.00221
Compressed (720p)	2.6 MB	13,157	$0.00197
Savings	95%	10.8%	10.8%

Output

The CLI provides:

• Video content analysis from Gemini
• Token usage breakdown (prompt, response, total)
• Estimated cost based on Gemini pricing

Pricing Reference

Gemini 2.5 Flash (as of 2025):

• Input: $0.15 per 1M tokens (text/image), $0.075 per 1M tokens (video)
• Output: $0.60 per 1M tokens, $3.50 for thinking tokens

A 1-hour video costs approximately $0.11-0.32 to analyze.