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jonaylor89jonaylor89
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migrate to separate repo
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‎.dockerignore‎

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# This file specifies files that are ignored by gcloud when uploading to Cloud Build
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# Unlike .gitignore, this controls what gets sent to the build environment
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# Development files
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.env
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.env.local
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.env.development
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.env.test
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# Build artifacts
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target/
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.cargo/
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# IDE files
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.vscode/
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.idea/
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*.swp
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*.swo
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*~
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# OS files
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.DS_Store
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Thumbs.db
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# Git
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.git/
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.gitignore
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# Documentation (not needed for build)
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*.md
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docs/
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# Test files (not needed for production build)
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tests/
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test-data/
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# Logs
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*.log
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logs/
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# Temporary files
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tmp/
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temp/
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# Node modules (if any)
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node_modules/
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# Coverage reports
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coverage/
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tarpaulin-report.html
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# Local database files
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*.db
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*.sqlite
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# Backup files
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*.bak
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*.backup
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# Editor temp files
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.*.tmp
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.*.swp
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# Cache directories
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.cache/
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# Scripts not needed in container (but needed for deployment)
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# build.sh
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# Don't ignore service config directories - we need them in the build!
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# gateway-service/config/
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# streaming-engine/config/
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# migrations/
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# Ignore webapp build artifacts if present
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webapp/dist/
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webapp/node_modules/
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webapp/.next/
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webapp/build/
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# Python cache files
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__pycache__/
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*.pyc
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*.pyo
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*.pyd
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.Python
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# Rope project files
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.ropeproject/
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# SQLx offline query data (contains prepared queries)
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# !.sqlx/
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# Include the service-specific Dockerfiles in the build
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# !Dockerfile.gateway
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# !Dockerfile.streaming

‎.gcloudignore‎

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.env
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target/
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tests/
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scripts/

‎.github/FUNDING.yml‎

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# These are supported funding model platforms
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github: [jonaylor89]

‎.github/workflows/codspeed.yml‎

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name: CodSpeed
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on:
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push:
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branches:
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- "main"
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pull_request:
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# `workflow_dispatch` allows CodSpeed to trigger backtest
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# performance analysis in order to generate initial data.
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workflow_dispatch:
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jobs:
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benchmarks:
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name: Run benchmarks
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- name: Setup rust toolchain, cache and cargo-codspeed binary
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uses: moonrepo/setup-rust@v1
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with:
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channel: stable
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cache-target: release
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bins: cargo-codspeed
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- name: Install FFmpeg (required for audio processing)
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run: |
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sudo apt-get update
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sudo apt-get install -y pkg-config \
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libavcodec-dev libavdevice-dev libavfilter-dev \
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libavformat-dev libswresample-dev libavutil-dev
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- name: Build the benchmark target(s)
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run: cargo codspeed build
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- name: Run the benchmarks
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uses: CodSpeedHQ/action@v3
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with:
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run: cargo codspeed run
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token: ${{ secrets.CODSPEED_TOKEN }}

‎.github/workflows/playwright.yml‎

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name: Playwright Tests
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on:
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push:
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branches: [main, master]
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pull_request:
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branches: [main, master]
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jobs:
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test:
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timeout-minutes: 30
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runs-on: ubuntu-latest
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defaults:
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run:
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working-directory: mcp-server
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env:
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AUTH_SECRET: ${{ secrets.AUTH_SECRET }}
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POSTGRES_URL: ${{ secrets.POSTGRES_URL }}
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BLOB_READ_WRITE_TOKEN: ${{ secrets.BLOB_READ_WRITE_TOKEN }}
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REDIS_URL: ${{ secrets.REDIS_URL }}
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steps:
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- uses: actions/checkout@v4
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with:
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fetch-depth: 1
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- uses: actions/setup-node@v4
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with:
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node-version: lts/*
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cache: npm
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cache-dependency-path: mcp-server/package-lock.json
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- name: Install dependencies
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run: npm ci
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- name: Run tests
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run: npm test
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- uses: actions/upload-artifact@v4
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if: always() && !cancelled()
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with:
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name: playwright-report
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path: playwright-report/
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retention-days: 7

‎.github/workflows/rust.yml‎

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name: Rust
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on:
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push:
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branches: ["main"]
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pull_request:
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branches: ["main"]
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env:
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CARGO_TERM_COLOR: always
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jobs:
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build:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- name: Install FFmpeg development libraries
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run: |
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sudo apt-get update
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sudo apt-get install -y pkg-config \
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libavcodec-dev libavdevice-dev libavfilter-dev \
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libavformat-dev libswresample-dev libavutil-dev
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- name: Build
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run: cargo build --verbose
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- name: Run tests
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env:
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TEST_LOG: debug
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RUST_BACKTRACE: 1
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run: cargo test --workspace --verbose
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- name: Lint
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run: cargo clippy
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- name: Format
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run: cargo fmt --check

‎.gitignore‎

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.env
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# Generated by Cargo
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# will have compiled files and executables
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debug/
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target/
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# These are backup files generated by rustfmt
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**/*.rs.bk
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# MSVC Windows builds of rustc generate these, which store debugging information
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*.pdb
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# Generated by cargo mutants
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# Contains mutation testing data
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**/mutants.out*/
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*.mp3
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# Runtime
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cache/
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!src/cache/
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!src/cache/**
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req_cache/
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testdata/
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server.log

‎AGENTS.md‎

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# Streaming Engine Development Guide
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## What This Project Is
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Streaming Engine is an **audio processing server** — it processes audio on the fly via URL parameters (like Thumbor/Imagor for images, but for audio). It is **not** an AI product. The MCP server integration exists to let LLMs use the audio processing API as a tool, but the core project is a deterministic audio processing pipeline built on FFmpeg.
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## Build & Test Commands
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- `just` — List available recipes
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- `just dev` — Run with auto-reload
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- `just build` — Build the project
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- `just test` — Run all tests
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- `just test-name <name>` — Run a specific test
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- `just bench` — Run benchmarks
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- `just lint` — Run linter (clippy)
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- `just fmt` — Format code
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- `just check` — Full check: format, lint, build, test
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## Project Structure
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- `src/` — Core streaming engine (Rust)
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- `crates/ffmpeg` — Safe FFmpeg wrapper
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- `crates/ffmpeg-sys` — Raw FFI bindings to FFmpeg
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- `mcp-server/` — MCP integration for LLM tool use (Node.js)
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- `config/` — YAML configuration files
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- `benches/` — Performance benchmarks
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- `scripts/` — Deployment and CI scripts
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## Code Style
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- **Imports**: Group std, external crates, then local modules
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- **Error Handling**: Use `color_eyre::Result`, `thiserror` for custom errors
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- **Logging**: Use `tracing` with structured logging and `#[instrument]` for functions
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- **Types**: Prefer explicit types, use `Uuid` for IDs, `DateTime<Utc>` for timestamps
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- **Naming**: snake_case for functions/variables, PascalCase for types, modules in snake_case
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- **Async**: Use `tokio::main` and async/await throughout
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- **API**: Use Axum with `State` extraction and `Json` responses

‎CLAUDE.md‎

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# Streaming Engine Development Guide
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## What This Project Is
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Streaming Engine is an **audio processing server** — it processes audio on the fly via URL parameters (like Thumbor/Imagor for images, but for audio). It is **not** an AI product. The MCP server integration exists to let LLMs use the audio processing API as a tool, but the core project is a deterministic audio processing pipeline built on FFmpeg.
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## Build & Test Commands
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- `just` — List available recipes
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- `just dev` — Run with auto-reload
10+
- `just build` — Build the project
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- `just test` — Run all tests
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- `just test-name <name>` — Run a specific test
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- `just bench` — Run benchmarks
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- `just lint` — Run linter (clippy)
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- `just fmt` — Format code
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- `just check` — Full check: format, lint, build, test
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## Project Structure
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- `src/` — Core streaming engine (Rust)
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- `crates/ffmpeg` — Safe FFmpeg wrapper
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- `crates/ffmpeg-sys` — Raw FFI bindings to FFmpeg
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- `mcp-server/` — MCP integration for LLM tool use (Node.js)
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- `config/` — YAML configuration files
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- `benches/` — Performance benchmarks
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- `scripts/` — Deployment and CI scripts
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## Code Style
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- **Imports**: Group std, external crates, then local modules
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- **Error Handling**: Use `color_eyre::Result`, `thiserror` for custom errors
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- **Logging**: Use `tracing` with structured logging and `#[instrument]` for functions
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- **Types**: Prefer explicit types, use `Uuid` for IDs, `DateTime<Utc>` for timestamps
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- **Naming**: snake_case for functions/variables, PascalCase for types, modules in snake_case
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- **Async**: Use `tokio::main` and async/await throughout
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- **API**: Use Axum with `State` extraction and `Json` responses

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