Bundle FFmpeg as Tauri sidecar, download in CI

.github/workflows/release.yml

@@ -6,68 +6,37 @@ on:
       - 'v*'
 
 jobs:
-  build:
-    strategy:
-      fail-fast: false
-      matrix:
-        include:
-          - platform: ubuntu-24.04
-            target: x86_64-unknown-linux-gnu
-            bundles: deb
-          - platform: ubuntu-24.04
-            target: x86_64-unknown-linux-gnu
-            bundles: rpm
-          - platform: ubuntu-24.04
-            target: x86_64-unknown-linux-gnu
-            bundles: archlinux
-          - platform: windows-latest
-            target: x86_64-pc-windows-msvc
-            bundles: msi
-
-    runs-on: ${{ matrix.platform }}
-
+  linux:
+    runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
-
-      - name: Setup Node
-        uses: actions/setup-node@v4
+      - uses: actions/setup-node@v4
         with:
           node-version: 20
           cache: npm
           cache-dependency-path: frontend/package-lock.json
-
-      - name: Install frontend dependencies
-        run: npm ci
+      - run: npm ci
         working-directory: frontend
-
-      - name: Install Rust
-        uses: dtolnay/rust-toolchain@stable
-        with:
-          targets: ${{ matrix.target }}
-
-      - name: Install system dependencies (Linux)
-        if: runner.os == 'Linux'
-        run: |
+      - uses: dtolnay/rust-toolchain@stable
+      - run: |
           sudo apt-get update
           sudo apt-get install -y \
             libwebkit2gtk-4.1-dev \
-            libappindicator3-dev \
             librsvg2-dev \
             patchelf \
             libssl-dev \
             libgtk-3-dev \
-            libayatana-appindicator3-dev
-
-      - name: Install RPM build tools
-        if: matrix.bundles == 'rpm'
-        run: sudo apt-get install -y rpm
-
-      - name: Install ArchLinux build tools
-        if: matrix.bundles == 'archlinux'
-        run: sudo apt-get install -y pacman-pkg-strap
-
-      - name: Build Tauri app
-        uses: tauri-apps/tauri-action@v0
+            libayatana-appindicator3-dev \
+            rpm
+      - name: Download FFmpeg (bundled sidecar)
+        run: |
+          mkdir -p src-tauri/binaries
+          curl -sL "https://johnvansickle.com/ffmpeg/releases/ffmpeg-release-amd64-static.tar.xz" -o /tmp/ffmpeg.tar.xz
+          tar -xf /tmp/ffmpeg.tar.xz -C /tmp
+          cp /tmp/ffmpeg-*-amd64-static/ffmpeg src-tauri/binaries/ffmpeg-x86_64-unknown-linux-gnu
+          cp /tmp/ffmpeg-*-amd64-static/ffprobe src-tauri/binaries/ffprobe-x86_64-unknown-linux-gnu
+          chmod +x src-tauri/binaries/*
+      - uses: tauri-apps/tauri-action@v0
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
         with:
@@ -76,4 +45,50 @@ jobs:
           releaseBody: 'See the assets to download and install this version.'
           releaseDraft: false
           includeUpdaterJson: true
-          args: --bundles ${{ matrix.bundles }} --target ${{ matrix.target }}
+          args: --bundles deb,rpm
+
+  windows:
+    runs-on: windows-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: actions/setup-node@v4
+        with:
+          node-version: 20
+          cache: npm
+          cache-dependency-path: frontend/package-lock.json
+      - run: npm ci
+        working-directory: frontend
+      - uses: dtolnay/rust-toolchain@stable
+      - uses: tauri-apps/tauri-action@v0
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        with:
+          tagName: ${{ github.ref_name }}
+          releaseName: 'TalkEdit ${{ github.ref_name }}'
+          releaseBody: 'See the assets to download and install this version.'
+          releaseDraft: false
+          includeUpdaterJson: true
+          args: --bundles msi
+
+  # macos:
+  #   runs-on: macos-latest
+  #   steps:
+  #     - uses: actions/checkout@v4
+  #     - uses: actions/setup-node@v4
+  #       with:
+  #         node-version: 20
+  #         cache: npm
+  #         cache-dependency-path: frontend/package-lock.json
+  #     - run: npm ci
+  #       working-directory: frontend
+  #     - uses: dtolnay/rust-toolchain@stable
+  #     - uses: tauri-apps/tauri-action@v0
+  #       env:
+  #         GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+  #       with:
+  #         tagName: ${{ github.ref_name }}
+  #         releaseName: 'TalkEdit ${{ github.ref_name }}'
+  #         releaseBody: 'See the assets to download and install this version.'
+  #         releaseDraft: false
+  #         includeUpdaterJson: true
+  #         args: --bundles dmg

backend/routers/local_llm.py

@@ -0,0 +1,54 @@
+"""Local LLM endpoints for bundled Qwen3 inference."""
+
+import logging
+from typing import Optional
+
+from fastapi import APIRouter, HTTPException
+from pydantic import BaseModel
+
+from services.local_llm import get_status, download_model, complete
+
+logger = logging.getLogger(__name__)
+router = APIRouter()
+
+
+class CompleteRequest(BaseModel):
+    prompt: str
+    model_id: str = "qwen3-1.7b"
+    system_prompt: Optional[str] = None
+    temperature: float = 0.3
+    max_tokens: int = 2048
+
+
+@router.get("/local-llm/status")
+async def llm_status():
+    try:
+        return get_status()
+    except Exception as e:
+        logger.error(f"Local LLM status failed: {e}", exc_info=True)
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@router.post("/local-llm/download")
+async def llm_download(model_id: str = "qwen3-1.7b"):
+    try:
+        return download_model(model_id)
+    except Exception as e:
+        logger.error(f"Local LLM download failed: {e}", exc_info=True)
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@router.post("/local-llm/complete")
+async def llm_complete(req: CompleteRequest):
+    try:
+        result = complete(
+            prompt=req.prompt,
+            model_id=req.model_id,
+            system_prompt=req.system_prompt,
+            temperature=req.temperature,
+            max_tokens=req.max_tokens,
+        )
+        return {"response": result}
+    except Exception as e:
+        logger.error(f"Local LLM completion failed: {e}", exc_info=True)
+        raise HTTPException(status_code=500, detail=str(e))

backend/services/local_llm.py

@@ -0,0 +1,125 @@
+"""
+Local LLM inference using llama.cpp via llama-cpp-python.
+Handles model download from HuggingFace and text completion.
+"""
+
+import json
+import logging
+import os
+import subprocess
+import sys
+from pathlib import Path
+from typing import Optional
+
+logger = logging.getLogger(__name__)
+
+LOCAL_MODELS_DIR = Path.home() / ".cache" / "talkedit" / "models"
+QWEN_MODELS = {
+    "qwen3-1.7b": {
+        "repo": "Qwen/Qwen3-1.7B-Instruct-GGUF",
+        "file": "qwen3-1.7b-instruct-q4_k_m.gguf",
+        "size_gb": 1.0,
+    },
+    "qwen3-4b": {
+        "repo": "Qwen/Qwen3-4B-Instruct-GGUF",
+        "file": "qwen3-4b-instruct-q4_k_m.gguf",
+        "size_gb": 2.5,
+    },
+}
+
+
+def _ensure_llama_cpp() -> bool:
+    try:
+        from llama_cpp import Llama
+        return True
+    except ImportError:
+        return False
+
+
+def _model_path(model_id: str) -> Path:
+    info = QWEN_MODELS.get(model_id)
+    if not info:
+        raise ValueError(f"Unknown model: {model_id}")
+    return LOCAL_MODELS_DIR / model_id / info["file"]
+
+
+def get_status() -> dict:
+    """Check status of local LLM setup."""
+    llama_available = _ensure_llama_cpp()
+    models = {}
+    for model_id in QWEN_MODELS:
+        path = _model_path(model_id)
+        models[model_id] = {
+            "downloaded": path.exists(),
+            "size_bytes": path.stat().st_size if path.exists() else 0,
+            "total_gb": QWEN_MODELS[model_id]["size_gb"],
+        }
+
+    return {
+        "llama_cpp_available": llama_available,
+        "models": models,
+        "models_dir": str(LOCAL_MODELS_DIR),
+    }
+
+
+def download_model(model_id: str) -> dict:
+    """Download a Qwen3 GGUF model from HuggingFace."""
+    info = QWEN_MODELS.get(model_id)
+    if not info:
+        raise ValueError(f"Unknown model: {model_id}")
+
+    model_dir = LOCAL_MODELS_DIR / model_id
+    model_dir.mkdir(parents=True, exist_ok=True)
+    output_path = model_dir / info["file"]
+
+    if output_path.exists():
+        return {"status": "already_downloaded", "path": str(output_path)}
+
+    logger.info(f"Downloading {info['repo']}/{info['file']} ({info['size_gb']} GB)...")
+    subprocess.run([
+        sys.executable, "-m", "huggingface_hub", "download",
+        info["repo"], info["file"],
+        "--local-dir", str(model_dir),
+        "--local-dir-use-symlinks", "False",
+    ], check=True)
+
+    if not output_path.exists():
+        raise RuntimeError(f"Download failed: {output_path} not found")
+
+    return {"status": "downloaded", "path": str(output_path)}
+
+
+def complete(
+    prompt: str,
+    model_id: str = "qwen3-1.7b",
+    system_prompt: Optional[str] = None,
+    temperature: float = 0.3,
+    max_tokens: int = 2048,
+) -> str:
+    """Run inference using a local Qwen3 model."""
+    model_path = _model_path(model_id)
+    if not model_path.exists():
+        raise RuntimeError(f"Model not downloaded: {model_id}")
+
+    from llama_cpp import Llama
+
+    llm = Llama(
+        model_path=str(model_path),
+        n_ctx=4096,
+        n_threads=4,
+        n_gpu_layers=-1,
+        verbose=False,
+    )
+
+    messages = []
+    if system_prompt:
+        messages.append({"role": "system", "content": system_prompt})
+    messages.append({"role": "user", "content": prompt})
+
+    response = llm.create_chat_completion(
+        messages=messages,
+        temperature=temperature,
+        max_tokens=max_tokens,
+    )
+
+    return response["choices"][0]["message"]["content"].strip()

docs/gitea-runner-windows.md

@@ -0,0 +1,44 @@
+# Gitea Runner — Windows Laptop
+
+Self-hosted runner registered as `windows-laptop` with label `windows-latest`.
+
+## Setup
+
+```powershell
+# Download
+Invoke-WebRequest -Uri "https://gitea.com/gitea/runner/releases/download/v1.0.1/gitea-runner-1.0.1-windows-amd64.exe" -OutFile "$env:USERPROFILE\gitea-runner-windows-amd64.exe"
+
+# Register (Admin PowerShell)
+.\gitea-runner-windows-amd64.exe register --instance http://143.244.157.110:3000 --token NS5LXzLzNOvPKD9Id4SrLQ09bReHOrn6T2c4EyGM --name windows-laptop --labels windows-latest --no-interactive
+
+# Start (foreground)
+.\gitea-runner-windows-amd64.exe daemon
+
+# Install as Windows service (auto-starts on boot)
+.\gitea-runner-windows-amd64.exe service install
+```
+
+## Logs
+
+### Workflow job logs (step output)
+
+Stored on the Gitea server (not locally). Download from:
+`http://143.244.157.110:3000/<owner>/<repo>/actions/runs/<run_id>`
+
+Click a job, then the **Download log** button at the top-right.
+
+### Runner daemon logs (runner itself)
+
+| Mode | Log location |
+|---|---|
+| Foreground (`daemon`) | PowerShell console stdout |
+| Windows service (`service install`) | `%ProgramData%\gitea-runner\log\` or Windows Event Viewer → Windows Logs → Application |
+
+## Diagnostics
+
+If a CI job fails, download the full log from the Gitea Actions UI (as above), then search for the first error:
+
+- **Rust**: look for `error[E...]`, `error: could not compile`, or `cargo test` failures
+- **Python**: look for `FAILED`, `AssertionError`, or `ModuleNotFoundError`
+
+The runner's own logs (`daemon` mode) will show which job it picked up, container lifecycle, and any infrastructure issues (disk full, Docker unavailable, etc.).

src-tauri/.gitignore

@@ -2,3 +2,4 @@
 # will have compiled files and executables
 /target/
 /gen/schemas
+binaries/

src-tauri/icons/icon.svg

@@ -0,0 +1 @@
+<svg width="48" height="48" viewBox="0 0 36 36" fill="none" xmlns="http://www.w3.org/2000/svg"><path d="M6 10h12a6 6 0 0 1 0 12H8l-2 4V10Z" stroke="#818cf8" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" opacity="0.7"></path><path d="M6 10h12a6 6 0 0 1 0 12H8l-2 4V10Z" stroke="#6366f1" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"></path><path d="M10 14v4M13 13v6M16 14v4" stroke="#6366f1" stroke-width="1.5" stroke-linecap="round"></path><path d="M22 16h6M22 19h4M22 22h5" stroke="#818cf8" stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round" opacity="0.6"></path></svg>

src-tauri/src/lib.rs

@@ -397,6 +397,15 @@ pub fn run() {
                 }
             }
 
+            // Add bundled ffmpeg/ffprobe to PATH so Python subprocesses find them
+            if let Some(ffmpeg_dir) = paths::bundled_ffmpeg().and_then(|p| p.parent().map(|p| p.to_path_buf())) {
+                if let Ok(current_path) = std::env::var("PATH") {
+                    let new_path = format!("{}:{}", ffmpeg_dir.display(), current_path);
+                    std::env::set_var("PATH", &new_path);
+                }
+                log::info!("Added bundled FFmpeg directory to PATH: {}", ffmpeg_dir.display());
+            }
+
             Ok(())
         })
         .invoke_handler(tauri::generate_handler![

src-tauri/src/paths.rs

@@ -62,7 +62,38 @@ pub fn backend_script(name: &str) -> PathBuf {
     project_root().join("backend").join(name)
 }
 
-/// Absolute path to a script at the project root.
+/// Locate bundled ffmpeg binary (sidecar).
+pub fn bundled_ffmpeg() -> Option<PathBuf> {
+    let exe = std::env::current_exe().ok()?;
+    let dir = exe.parent()?;
+    // Tauri places externalBin next to the executable
+    let candidates = [
+        dir.join("ffmpeg"),
+        dir.join("binaries").join("ffmpeg"),
+    ];
+    for c in &candidates {
+        if c.exists() {
+            return Some(c.clone());
+        }
+    }
+    None
+}
+
+/// Locate bundled ffprobe binary (sidecar).
+pub fn bundled_ffprobe() -> Option<PathBuf> {
+    let exe = std::env::current_exe().ok()?;
+    let dir = exe.parent()?;
+    let candidates = [
+        dir.join("ffprobe"),
+        dir.join("binaries").join("ffprobe"),
+    ];
+    for c in &candidates {
+        if c.exists() {
+            return Some(c.clone());
+        }
+    }
+    None
+}
 pub fn root_script(name: &str) -> PathBuf {
     project_root().join(name)
 }

src-tauri/tauri.conf.json

@@ -35,6 +35,10 @@
       "icons/128x128@2x.png",
       "icons/icon.icns",
       "icons/icon.ico"
+    ],
+    "externalBin": [
+      "binaries/ffmpeg",
+      "binaries/ffprobe"
     ]
   }
 }