Commit
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1e6288e
1
Parent(s):
a94a0fe
preparing of deplyoment on higgingface
Browse files- .DS_Store +0 -0
- Dockerfile +28 -0
- backend/Dockerfile +20 -20
- docker-compose.yml +58 -58
- render.yaml +0 -66
- startup.sh +13 -0
.DS_Store
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Binary files a/.DS_Store and b/.DS_Store differ
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Dockerfile
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@@ -0,0 +1,28 @@
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# This is the single Dockerfile for our entire backend on Hugging Face Spaces
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FROM python:3.11-slim
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# Set a single working directory
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WORKDIR /app
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# Install system dependencies
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RUN apt-get update && apt-get install -y git redis-server
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# Copy all requirements and model files first for better caching
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COPY backend/requirements.txt .
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COPY ml_models ./ml_models
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# Install Python packages
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RUN pip install --no-cache-dir -r requirements.txt
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# Copy the entire backend source code
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COPY backend .
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# Create a startup script
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COPY startup.sh .
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RUN chmod +x startup.sh
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# Expose the port FastAPI will run on
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EXPOSE 7860
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# The command to run our startup script
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CMD ["./startup.sh"]
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backend/Dockerfile
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@@ -35,22 +35,22 @@
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FROM python:3.11-slim
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WORKDIR /code
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RUN apt-get update && apt-get install -y git
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COPY ./backend/requirements.txt .
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# Install Gunicorn for a production-ready server
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RUN pip install gunicorn
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RUN pip install --no-cache-dir -r requirements.txt
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COPY ./ml_models /code/sentiment_model
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# Copy the application code last. All code will live in /code now.
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COPY ./backend .
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# The default command is to start the web server.
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# Render's free web services require port 10000.
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CMD ["gunicorn", "-w", "2", "-k", "uvicorn.workers.UvicornWorker", "main:app", "--bind", "0.0.0.0:10000"]
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FROM python:3.11-slim
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WORKDIR /code
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RUN apt-get update && apt-get install -y git
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COPY ./backend/requirements.txt .
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RUN pip install --no-cache-dir --upgrade -r requirements.txt
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COPY ./ml_models /code/sentiment_model
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WORKDIR /code/app
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# FROM python:3.11-slim
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# WORKDIR /code
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# RUN apt-get update && apt-get install -y git
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# COPY ./backend/requirements.txt .
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# # Install Gunicorn for a production-ready server
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# RUN pip install gunicorn
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# RUN pip install --no-cache-dir -r requirements.txt
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# COPY ./ml_models /code/sentiment_model
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# # Copy the application code last. All code will live in /code now.
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# COPY ./backend .
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# # The default command is to start the web server.
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# # Render's free web services require port 10000.
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# CMD ["gunicorn", "-w", "2", "-k", "uvicorn.workers.UvicornWorker", "main:app", "--bind", "0.0.0.0:10000"]
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docker-compose.yml
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# services:
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# # --- Application Services ---
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# redis:
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# image: redis:7-alpine
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# ports:
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# - "6379:6379"
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# restart: always
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# backend:
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# build:
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# context: .
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# dockerfile: ./backend/Dockerfile
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# ports:
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# - "8000:8000"
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# volumes:
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# - ./backend:/code/app
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# env_file:
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# - .env
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# command: python -m uvicorn main:app --host 0.0.0.0 --port 8000 --reload
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# restart: always
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# depends_on:
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# - redis
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# worker:
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# build:
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# context: .
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# dockerfile: ./backend/Dockerfile
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# volumes:
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# - ./backend:/code/app
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# env_file:
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# - .env
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# command: python -m celery -A celery_worker.celery worker --loglevel=info
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# restart: always
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# depends_on:
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# - redis
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# - backend
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# frontend:
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# build:
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# context: .
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# dockerfile: ./frontend/Dockerfile
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# ports:
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# - "5173:5173"
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# volumes:
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# - ./frontend:/app
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# - /app/node_modules
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# restart: always
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# depends_on:
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# - backend
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services:
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redis:
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image: redis:7-alpine
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ports:
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- /app/node_modules
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restart: always
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depends_on:
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- backend
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services:
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# --- Application Services ---
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redis:
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image: redis:7-alpine
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ports:
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- /app/node_modules
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restart: always
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depends_on:
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- backend
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# services:
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# redis:
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# image: redis:7-alpine
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# ports:
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# - "6379:6379"
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# restart: always
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# backend:
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# build:
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# context: .
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# dockerfile: ./backend/Dockerfile
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# ports:
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# - "8000:8000"
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# volumes:
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# - ./backend:/code/app
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# env_file:
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# - .env
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# command: python -m uvicorn main:app --host 0.0.0.0 --port 8000 --reload
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# restart: always
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# depends_on:
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# - redis
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# worker:
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# build:
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# context: .
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# dockerfile: ./backend/Dockerfile
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# volumes:
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# - ./backend:/code/app
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# env_file:
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# - .env
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# command: python -m celery -A celery_worker.celery worker --loglevel=info
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# restart: always
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# depends_on:
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# - redis
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# - backend
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# frontend:
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# build:
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# context: .
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# dockerfile: ./frontend/Dockerfile
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# ports:
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# - "5173:5173"
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# volumes:
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# - ./frontend:/app
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# - /app/node_modules
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# restart: always
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# depends_on:
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# - backend
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render.yaml
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# This is the instruction manual for deploying on Render.
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services:
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# Service 1: The Redis instance for Celery
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- type: redis
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name: redis-cache
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plan: free
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# This is required for security on Render's free plan
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ipAllowList: [] # Allows internal connections, blocks public
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# Service 2: The Backend FastAPI Web Server
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- type: web
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name: backend-api
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plan: free
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env: docker
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# Tell Render where to find the Dockerfile and the build context
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dockerfilePath: ./backend/Dockerfile
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dockerContext: .
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# Render's free web services need a health check on port 10000
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healthCheckPath: /
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# We need to explicitly tell Render which port our service is on
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envVars:
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- key: PORT
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value: 10000
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- key: DATABASE_URL
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fromDatabase:
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name: neon-database # We will create this name in the Render UI
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property: connectionString
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- key: CELERY_BROKER_URL
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fromService:
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type: redis
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name: redis-cache
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property: connectionString
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- key: CELERY_RESULT_BACKEND
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fromService:
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type: redis
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name: redis-cache
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property: connectionString
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- key: GOOGLE_API_KEY
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sync: false # Set this secret manually in the Render UI
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# Service 3: The Celery Background Worker
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- type: worker
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name: celery-worker
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plan: free
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env: docker
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dockerfilePath: ./backend/Dockerfile
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dockerContext: .
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# This command overrides the CMD in the Dockerfile to start the worker instead
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dockerCommand: "python -m celery -A celery_worker.celery worker --loglevel=info"
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envVars:
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- key: DATABASE_URL
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fromDatabase:
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name: neon-database # Must match the name below
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property: connectionString
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- key: CELERY_BROKER_URL
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fromService:
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type: redis
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name: redis-cache
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property: connectionString
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- key: CELERY_RESULT_BACKEND
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fromService:
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type: redis
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name: redis-cache
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property: connectionString
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- key: GOOGLE_API_KEY
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sync: false
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startup.sh
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#!/bin/bash
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# Start the Redis server in the background
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redis-server --daemonize yes
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# Start the Celery worker in the background
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# We point it to the app folder where the code lives
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celery -A celery_worker.celery worker --loglevel=info &
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# Start the FastAPI server in the foreground
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# This is the main process that keeps the container alive
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# It must listen on 0.0.0.0 and port 7860 for Hugging Face Spaces
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uvicorn main:app --host 0.0.0.0 --port 7860
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