YouTube Video Summarizer

A .NET 8 console application that fetches YouTube video transcripts and produces structured summaries using an LLM (Ollama or OpenAI).

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Prerequisites

• .NET 10 SDK
• A YouTube Data API v3 key → Google Cloud Console
• Local Ollama (Recommended) or an OpenAI API key.

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Setup

# 1. Clone / copy the project
cd YoutubeSummarizer

# 2. Copy the example config and fill in your keys
cp appsettings.example.json appsettings.json
nano appsettings.json   # or your editor of choice

# 3. Restore packages
dotnet restore

# 4. Run
dotnet run

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Google Cloud Setup (YouTube API Key)

1. Go to console.cloud.google.com
2. Create or select a project
3. APIs & Services → Library → search "YouTube Data API v3" → Enable
4. APIs & Services → Credentials → Create Credentials → API key
5. (Optional but recommended) Restrict the key to only the YouTube Data API v3

Free quota: 10,000 units/day. Each video lookup costs ~3 units. You can summarize thousands of videos before hitting the limit.

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Configuration Reference

Key	Description	Default
YouTube:ApiKey	Your YouTube Data API v3 key	(required)
LLM:BaseUrl	API endpoint	http://localhost:11434/v1
LLM:ApiKey	API key (any for Ollama)	ollama
LLM:Model	Chat model to use	qwen3:14b
LLM:MaxTokens	Max tokens in summary response	1500
LLM:TimeoutSeconds	Max time for LLM generation	300
Summarizer:ChunkWordLimit	Words per chunk for long videos	3000
Summarizer:ShowTranscript	Print raw transcript before summary	false

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Architecture

Program.cs
│  Main loop → parses URL → calls pipeline
│
├── YouTubeService
│     ├── ExtractVideoId()      — URL parsing
│     ├── GetVideoMetadataAsync() — YouTube Data API v3 (Videos.list)
│     └── GetTranscriptAsync()   — Caption list + timedtext download
│
├── SummarizerService
│     ├── SummarizeAsync()      — Routes to single-pass or chunked
│     ├── SinglePassSummarize() — One OpenAI call for short videos
│     └── ChunkedSummarize()    — Map-reduce for long videos
│
└── ConsoleRenderer             — All terminal output / formatting

Caption Quality Transparency

The app tracks how the transcript was obtained and flags it accordingly:

Source	Label	Warning shown?
Owner-published captions	✓ Owner-published	No
Community-contributed	✓ Community captions	Minor note
Auto-generated (ASR)	~ Auto-generated	Yes — accuracy caveat
No captions (metadata only)	✗ Metadata only	Yes — limited accuracy

Long Video Strategy

Videos with transcripts exceeding ChunkWordLimit words use a map-reduce approach:

1. Split — transcript divided into overlapping chunks (200-word overlap preserves context at boundaries)
2. Map — each chunk summarized independently
3. Reduce — chunk summaries combined into a final coherent summary

This handles hour-long lectures, conference talks, and podcasts without hitting model context limits.

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Environment Variable Overrides

You can override appsettings.json values with environment variables, useful for CI or Docker:

export YouTube__ApiKey="your-key"
export LLM__ApiKey="ollama"
dotnet run

Note the double-underscore __ as the section separator (standard .NET configuration convention).