updated this

Dockerfile

@@ -1,16 +1,24 @@
-# Read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
-# you will also find guides on how best to write your Dockerfile
-
 FROM python:3.9
 
+# Create a non-root user for better security
 RUN useradd -m -u 1000 user
 USER user
+
+# Add the user's local bin to the PATH. This is where pip installs executables.
 ENV PATH="/home/user/.local/bin:$PATH"
 
+# Set the working directory inside the container
 WORKDIR /app
 
+# Copy only the requirements.txt first to leverage Docker layer caching
 COPY --chown=user ./requirements.txt requirements.txt
+# Install the dependencies specified in requirements.txt
 RUN pip install --no-cache-dir --upgrade -r requirements.txt
 
+# Copy the rest of your application code into the container
 COPY --chown=user . /app
-CMD ["gunicorn","-b","0.0.0.0:7860", "app:app"]
+
+# The CMD instruction tells Docker how to run your application.
+# This command starts the Gunicorn server, binding it to port 7860 on all network interfaces,
+# and points it to the 'app' object inside your 'app.py' file.
+CMD ["gunicorn", "-b", "0.0.0.0:7860", "app:app"]

app.py

@@ -1,23 +1,19 @@
-# app.py
-
 import os
 from flask import Flask, request, jsonify
 from flask_cors import CORS
 import spacy
 
 # --- CORRECTED MODEL LOADING SECTION ---
-# This path points to the 'it_core_news_pruned' directory 
-# located in the same folder as this 'app.py' script.
+# This approach loads the model by its package name. It is more robust because
+# the model is now managed as a dependency in requirements.txt,
+# removing the need to manually place a model folder next to the script.
 try:
-    # Get the absolute path to the directory containing this script
-    base_dir = os.path.dirname(os.path.abspath(__file__))
-    # Join it with the name of our model directory
-    model_path = os.path.join(base_dir, 'it_core_news_pruned')
-    # Load the model from the specified path
-    nlp = spacy.load(model_path)
-except Exception as e:
-    # This provides a more detailed error if loading fails
-    raise RuntimeError(f"Error loading spaCy model from {model_path}: {e}")
+    nlp = spacy.load("it_core_news_sm")
+except OSError:
+    raise RuntimeError(
+        "Could not find the 'it_core_news_sm' model. "
+        "Please ensure it is listed and installed from your requirements.txt file."
+    )
 # --- END SECTION ---
 
 # Initialize the Flask app
@@ -137,11 +133,6 @@ def analyze_sentence():
         print(f"An error occurred: {e}")
         return jsonify({"error": "An internal error occurred. See server logs for details."}), 500
 
-# --- FIX: ADD THIS BLOCK TO BIND TO THE CORRECT HOST AND PORT ---
-if __name__ == "__main__":
-    # The host '0.0.0.0' makes the server publicly available
-    # The port is dynamically read from the 'PORT' environment variable, 
-    # with a default of 10000 for local testing.
-    port = int(os.environ.get('PORT', 10000))
-    app.run(host='0.0.0.0', port=port)
-# --- END FIX ---
+# The __main__ block has been removed because it is not used by Gunicorn.
+# The Dockerfile's CMD instruction is the single source of truth for running the app,
+# which prevents confusion about which host and port are being used.

requirements.txt

@@ -1,3 +1,7 @@
 flask
+Flask-Cors
+gunicorn
 spacy
-Flask-Cors
+# The following line installs the small Italian model for spaCy
+# directly via pip, making your project self-contained.
+it_core_news_sm @ https://github.com/explosion/spacy-models/releases/download/it_core_news_sm-3.7.0/it_core_news_sm-3.7.0.tar.gz