114 lines
3.6 KiB
Markdown
114 lines
3.6 KiB
Markdown
# YouTube Video Summarizer
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A .NET 8 console application that fetches YouTube video transcripts and produces structured summaries using an LLM (Ollama or OpenAI).
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---
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## Prerequisites
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- [.NET 10 SDK](https://dotnet.microsoft.com/download)
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- A **YouTube Data API v3** key → [Google Cloud Console](https://console.cloud.google.com)
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- **Local Ollama** (Recommended) or an **OpenAI API key**.
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---
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## Setup
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```bash
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# 1. Clone / copy the project
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cd YoutubeSummarizer
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# 2. Copy the example config and fill in your keys
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cp appsettings.example.json appsettings.json
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nano appsettings.json # or your editor of choice
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# 3. Restore packages
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dotnet restore
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# 4. Run
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dotnet run
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```
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---
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## Google Cloud Setup (YouTube API Key)
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1. Go to [console.cloud.google.com](https://console.cloud.google.com)
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2. Create or select a project
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3. **APIs & Services → Library** → search "YouTube Data API v3" → Enable
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4. **APIs & Services → Credentials → Create Credentials → API key**
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5. (Optional but recommended) Restrict the key to only the YouTube Data API v3
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> 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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---
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## Configuration Reference
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| Key | Description | Default |
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|---|---|---|
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| `YouTube:ApiKey` | Your YouTube Data API v3 key | *(required)* |
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| `LLM:BaseUrl` | API endpoint | `http://localhost:11434/v1` |
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| `LLM:ApiKey` | API key (any for Ollama) | `ollama` |
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| `LLM:Model` | Chat model to use | `qwen3:14b` |
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| `LLM:MaxTokens` | Max tokens in summary response | `1500` |
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| `LLM:TimeoutSeconds` | Max time for LLM generation | `300` |
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| `Summarizer:ChunkWordLimit` | Words per chunk for long videos | `3000` |
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| `Summarizer:ShowTranscript` | Print raw transcript before summary | `false` |
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---
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## Architecture
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```
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Program.cs
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│ Main loop → parses URL → calls pipeline
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│
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├── YouTubeService
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│ ├── ExtractVideoId() — URL parsing
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│ ├── GetVideoMetadataAsync() — YouTube Data API v3 (Videos.list)
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│ └── GetTranscriptAsync() — Caption list + timedtext download
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│
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├── SummarizerService
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│ ├── SummarizeAsync() — Routes to single-pass or chunked
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│ ├── SinglePassSummarize() — One OpenAI call for short videos
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│ └── ChunkedSummarize() — Map-reduce for long videos
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│
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└── ConsoleRenderer — All terminal output / formatting
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```
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### Caption Quality Transparency
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The app tracks how the transcript was obtained and flags it accordingly:
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| Source | Label | Warning shown? |
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|---|---|---|
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| Owner-published captions | `✓ Owner-published` | No |
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| Community-contributed | `✓ Community captions` | Minor note |
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| Auto-generated (ASR) | `~ Auto-generated` | Yes — accuracy caveat |
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| No captions (metadata only) | `✗ Metadata only` | Yes — limited accuracy |
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### Long Video Strategy
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Videos with transcripts exceeding `ChunkWordLimit` words use a **map-reduce** approach:
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1. **Split** — transcript divided into overlapping chunks (200-word overlap preserves context at boundaries)
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2. **Map** — each chunk summarized independently
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3. **Reduce** — chunk summaries combined into a final coherent summary
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This handles hour-long lectures, conference talks, and podcasts without hitting model context limits.
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---
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## Environment Variable Overrides
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You can override `appsettings.json` values with environment variables, useful for CI or Docker:
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```bash
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export YouTube__ApiKey="your-key"
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export LLM__ApiKey="ollama"
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dotnet run
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```
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Note the double-underscore `__` as the section separator (standard .NET configuration convention).
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