Spaces:

mimo1972
/

Fight_Price_Prediction

Sleeping

mimo1972

Update Dockerfile

61d40de verified 10 months ago

822 Bytes

 #1. Base Image: Use a pre-configured Python environment (like a fresh OS install)
FROM python:3.11-slim

# 2. Setup: Create a folder inside the container to hold your app
WORKDIR /app

# 3. Dependencies: Copy the requirements file first to cache the installation step
# (This makes re-building faster if you only change your code but not libraries)
COPY requirements.txt .

# 4. Install: Run pip to install pandas, streamlit, scikit-learn, etc.
RUN pip install --no-cache-dir -r requirements.txt

# 5. Application Code: Copy all your files (streamlit.py, models, datasets) into the container
COPY . .

# 6. Execution: The command to start the application
# Hugging Face SPECIFIC: You must use port 7860 and address 0.0.0.0
CMD ["streamlit", "run", "flightprice.py", "--server.port", "7860", "--server.address", "0.0.0.0"]

	#1. Base Image: Use a pre-configured Python environment (like a fresh OS install)
	FROM python:3.11-slim

	# 2. Setup: Create a folder inside the container to hold your app
	WORKDIR /app

	# 3. Dependencies: Copy the requirements file first to cache the installation step
	# (This makes re-building faster if you only change your code but not libraries)
	COPY requirements.txt .

	# 4. Install: Run pip to install pandas, streamlit, scikit-learn, etc.
	RUN pip install --no-cache-dir -r requirements.txt

	# 5. Application Code: Copy all your files (streamlit.py, models, datasets) into the container
	COPY . .

	# 6. Execution: The command to start the application
	# Hugging Face SPECIFIC: You must use port 7860 and address 0.0.0.0
	CMD ["streamlit", "run", "flightprice.py", "--server.port", "7860", "--server.address", "0.0.0.0"]