feat: prepare project for render free tier deployment

Dockerfile

@@ -16,6 +16,7 @@ ENV PYTHONDONTWRITEBYTECODE=1 \
     NLTK_DATA=/app/nltk_data \
     MODEL_NAME="Meta-Feature Stacking (Production)" \
     ENV=production \
+    PORT=8000 \
     INSTALL_HF=${INSTALL_HF}
 
 WORKDIR /app
@@ -50,6 +51,7 @@ COPY .env.example .env.example
 EXPOSE 8000
 
 HEALTHCHECK --interval=10s --timeout=5s --retries=12 --start-period=60s \
-  CMD curl -f http://localhost:8000/health || exit 1
+  CMD curl -f http://localhost:${PORT:-8000}/health || exit 1
 
-CMD ["uv", "run", "uvicorn", "src.api.main:app", "--host", "0.0.0.0", "--port", "8000"]
+# Shell form so ${PORT} is expanded at runtime (Render injects PORT; local defaults to 8000).
+CMD uv run uvicorn src.api.main:app --host 0.0.0.0 --port ${PORT:-8000}

Procfile

@@ -0,0 +1 @@
+web: uv run uvicorn src.api.main:app --host 0.0.0.0 --port $PORT

docs/DEPLOY.md

@@ -0,0 +1,66 @@
+# Deploy — Render (free tier)
+
+This guide walks through deploying `youtube_hate_detector` to [Render](https://render.com)
+using the Blueprint (`render.yaml`) at the root of the repo. The Blueprint provisions
+two services: a Dockerised FastAPI backend (`signalmod-api`) and a static React/Vite
+frontend (`signalmod-ui`).
+
+## Prerequisites
+
+- A free [Render](https://dashboard.render.com/register) account.
+- This repository pushed to GitHub (Render reads the Blueprint from the connected branch).
+- Credentials for any external services you plan to use:
+  - `YOUTUBE_API_KEY` — Google Cloud Console → APIs & Services → Credentials.
+  - `SUPABASE_URL` and `SUPABASE_KEY` — Supabase project settings (optional, only if
+    persistence is enabled).
+
+## One-shot deploy (Blueprint)
+
+1. Open the Render dashboard → **New** → **Blueprint**.
+2. Connect the GitHub account and pick this repository / branch.
+3. Render parses `render.yaml` and shows the two services. Click **Apply**.
+4. Wait for the first build. The API image takes ~5–8 minutes (frontend build +
+   Python deps + spaCy/NLTK data).
+5. Once the API is live, open **signalmod-api → Environment** and fill in the
+   secrets that were declared with `sync: false`:
+   - `YOUTUBE_API_KEY`
+   - `SUPABASE_URL`
+   - `SUPABASE_KEY`
+6. Trigger a manual redeploy so the API picks up the new env vars.
+
+The static site (`signalmod-ui`) reads `VITE_API_BASE_URL` at build time and points
+at `https://signalmod-api.onrender.com`. If you renamed the API service, update that
+env var in `render.yaml` and re-apply the Blueprint.
+
+## Important free-tier caveats
+
+- **Cold starts.** Free web services sleep after 15 minutes of inactivity. The first
+  request after a sleep can take 30–60 seconds while the container restarts and the
+  model warms up. Subsequent requests are fast.
+- **Memory ceiling: 512 MB.** The default production model
+  (`Meta-Feature Stacking (Production)`) loads BERT and needs roughly 700 MB of RAM,
+  so it will OOM on free. The Blueprint pins `MODEL_NAME="LR + TF-IDF (Baseline)"`,
+  which runs comfortably under the limit. If you upgrade to a paid plan with
+  ≥1 GB RAM, you can switch the env var to the meta-stacking model and rebuild the
+  image with `INSTALL_HF=1`.
+- **Build image size.** `render.yaml` builds with the default `INSTALL_HF=0` so the
+  Docker image stays small (no torch/transformers). Locally, `docker-compose.yml`
+  still passes `INSTALL_HF=1` for parity with the production model.
+
+## Test the Docker image locally before pushing
+
+```bash
+# Build the same image Render will build (free-tier shape — no HF extras)
+docker build --build-arg INSTALL_HF=0 -t signalmod-api:render .
+
+# Run it with the same model the Blueprint will use
+docker run --rm -p 8000:8000 \
+  -e MODEL_NAME="LR + TF-IDF (Baseline)" \
+  -e ENV=production \
+  signalmod-api:render
+
+# Health check
+curl http://localhost:8000/health
+```
+
+If `/health` returns `200 OK` locally, the same image will boot on Render.

render.yaml

@@ -0,0 +1,38 @@
+# Render Blueprint — youtube_hate_detector
+# Deploy: New + Blueprint → connect repo → Apply.
+# Secrets (sync: false) must be filled in the Render dashboard after the first apply.
+# Free tier: 512 MB RAM — the Meta-Feature Stacking (Production) model does NOT fit.
+#            Keep MODEL_NAME at "LR + TF-IDF (Baseline)" for free deploys.
+
+services:
+  - type: web
+    name: signalmod-api
+    env: docker
+    plan: free
+    region: frankfurt
+    dockerfilePath: ./Dockerfile
+    healthCheckPath: /health
+    envVars:
+      - key: MODEL_NAME
+        value: "LR + TF-IDF (Baseline)"
+      - key: ENV
+        value: production
+      - key: YOUTUBE_API_KEY
+        sync: false
+      - key: SUPABASE_URL
+        sync: false
+      - key: SUPABASE_KEY
+        sync: false
+
+  - type: static
+    name: signalmod-ui
+    env: static
+    buildCommand: cd frontend && npm install && npm run build
+    staticPublishPath: ./frontend/dist
+    envVars:
+      - key: VITE_API_BASE_URL
+        value: https://signalmod-api.onrender.com
+    routes:
+      - type: rewrite
+        source: /*
+        destination: /index.html