update

.env

@@ -0,0 +1,17 @@
+# Environment variables for AgriPredict Analysis Service
+
+# API Configuration
+PORT=7860
+API_HOST=0.0.0.0
+API_WORKERS=1
+
+# CORS Configuration (for local development)
+FRONTEND_URL=http://localhost:3000
+
+# Logging
+LOG_LEVEL=INFO
+
+# Model Configuration
+DEFAULT_MODELS=ensemble
+MAX_FORECAST_DAYS=365
+MIN_HISTORICAL_DATA_POINTS=3

.gitignore

@@ -0,0 +1,58 @@
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# Virtual environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# IDE
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+
+# OS
+.DS_Store
+.DS_Store?
+._*
+.Spotlight-V100
+.Trashes
+ehthumbs.db
+Thumbs.db
+
+# Logs
+*.log
+logs/
+
+# Models (will be generated)
+models/*.pkl
+models/*.joblib
+
+# Temporary files
+*.tmp
+*.temp

README.md

@@ -1,3 +1,13 @@
+---
+title: AgriPredict Analysis Service
+emoji: 🌾
+colorFrom: green
+colorTo: blue
+sdk: docker
+app_file: main.py
+pinned: false
+---
+
 # AgriPredict Analysis Service
 
 A FastAPI-based service for advanced agricultural demand forecasting using multiple ML models including ensemble methods, statistical models, and machine learning algorithms.

main.py

@@ -263,6 +263,6 @@ if __name__ == "__main__":
     uvicorn.run(
         "main:app",
         host="0.0.0.0",
-        port=int(os.getenv("PORT", 8000)),
+        port=int(os.getenv("PORT", 7860)),  # Use 7860 for Hugging Face Spaces
         reload=True
     )

utils/config.py

@@ -10,7 +10,7 @@ class Settings:
 
     # API Settings
     API_HOST: str = os.getenv("API_HOST", "0.0.0.0")
-    API_PORT: int = int(os.getenv("PORT", 8000))
+    API_PORT: int = int(os.getenv("PORT", 7860))  # Default to 7860 for Hugging Face Spaces
     API_WORKERS: int = int(os.getenv("API_WORKERS", 1))
 
     # CORS Settings