updated readme

README.md

@@ -1,3 +1,14 @@
+---
+title: Address Detection and Summarization API
+emoji: 🏠📝
+colorFrom: blue
+colorTo: green
+sdk: docker
+sdk_version: "4.40.0"
+app_file: app.py
+pinned: false
+---
+
 # Address Detection and Summarization API
 
 A FastAPI application that provides two main endpoints for address detection and text summarization with sentiment analysis using OpenAI's GPT models.
@@ -6,7 +17,7 @@ A FastAPI application that provides two main endpoints for address detection and
 
 - **Address Detection**: Extracts addresses from text content
 - **Text Summarization**: Generates summaries with sentiment analysis
-- **OpenAI Integration**: Uses GPT-3.5-turbo for natural language processing
+- **OpenAI Integration**: Uses GPT-4 for natural language processing
 - **Header-based Authentication**: OpenAI API key passed via `x-api-key` header
 - **RESTful API**: Clean and simple API endpoints
 
@@ -37,22 +48,22 @@ A FastAPI application that provides two main endpoints for address detection and
 Start the FastAPI server:
 
 ```bash
-python main.py
+python app.py
 ```
 
 Or using uvicorn directly:
 
 ```bash
-uvicorn main:app --host 0.0.0.0 --port 8500 --reload
+uvicorn app:app --host 0.0.0.0 --port 7860 --reload
 ```
 
-The API will be available at: http://localhost:8500
+The API will be available at: http://localhost:7860 (or http://localhost:8500 for local development)
 
 ## API Documentation
 
 Once running, visit:
-- Interactive API docs: http://localhost:8500/docs
-- ReDoc documentation: http://localhost:8500/redoc
+- Interactive API docs: http://localhost:7860/docs (or :8500 for local)
+- ReDoc documentation: http://localhost:7860/redoc
 
 ## API Endpoints
 
@@ -89,7 +100,7 @@ x-api-key: your_openai_api_key_here
 
 **Example:**
 ```bash
-curl -X POST "http://localhost:8500/address-detection" \
+curl -X POST "http://localhost:7860/address-detection" \
      -H "Content-Type: application/json" \
      -H "x-api-key: your_openai_api_key_here" \
      -d '{
@@ -134,7 +145,7 @@ x-api-key: your_openai_api_key_here
 
 **Example:**
 ```bash
-curl -X POST "http://localhost:8500/summarize" \
+curl -X POST "http://localhost:7860/summarize" \
      -H "Content-Type: application/json" \
      -H "x-api-key: your_openai_api_key_here" \
      -d '{
@@ -143,6 +154,22 @@ curl -X POST "http://localhost:8500/summarize" \
      }'
 ```
 
+## Deployment
+
+This API is designed for easy deployment to Hugging Face Spaces using Docker.
+
+### For Hugging Face Spaces:
+1. Upload: `app.py`, `Dockerfile`, `requirements.txt`, `README.md`
+2. The service will automatically run on port 7860
+3. API will be available at: `https://your-space-name.hf.space`
+
+### For Local Development:
+```bash
+python app.py  # Runs on port 8500
+```
+
+See `DEPLOY.md` for detailed deployment instructions.
+
 ## Testing
 
 Before running tests, make sure to set your OpenAI API key as an environment variable:
@@ -154,7 +181,7 @@ export OPENAI_API_KEY="your_openai_api_key_here"
 Then run the test script to verify the endpoints:
 
 ```bash
-python test_api.py
+python test.py
 ```
 
 Make sure the server is running before executing the tests.
@@ -165,12 +192,13 @@ The test script will also test error handling by making requests without the API
 
 ```
 dummy_add-det_summ_ser/
-├── main.py              # Main FastAPI application
-├── test_api.py          # Test script for API endpoints
+├── app.py               # Main FastAPI application
+├── test.py              # Test script for API endpoints  
 ├── requirements.txt     # Python dependencies
-├── .env.example         # Environment variables template
-├── .venv/              # Virtual environment
-└── README.md           # This file
+├── Dockerfile           # Docker configuration for deployment
+├── README.md            # This file
+├── DEPLOY.md            # Deployment instructions
+└── .gitignore           # Git ignore patterns
 ```
 
 ## Dependencies
@@ -196,7 +224,7 @@ All errors return appropriate HTTP status codes and descriptive error messages.
 ## Notes
 
 - **API Key Security**: The OpenAI API key must be passed in the `x-api-key` header for each request
-- The API uses GPT-3.5-turbo model by default
+- The API uses GPT-4o model by default
 - Sentiment scores range from -1.0 (most negative) to 1.0 (most positive)
 - Address detection returns addresses concatenated with ' || ' separator
 - The `entity_urn` field is used instead of `entity_id` for better naming convention

README_HF.md

@@ -4,6 +4,7 @@ emoji: 🏠📝
 colorFrom: blue
 colorTo: green
 sdk: docker
+app_port: 7860
 pinned: false
 license: mit
 ---

test.py

@@ -1,19 +1,27 @@
 #!/usr/bin/env python3
 """
 Simple test script for the deployed API
-Update BASE_URL to your Hugging Face Space URL
+Update BASE_URL to your Hugging Face Space URL or local server
 """
 
 import httpx
 import json
 import os
+import sys
 
-# Update this to your actual Hugging Face Space URL
+# Update this to your actual Hugging Face Space URL or use "local" for localhost:7860
 BASE_URL = "https://your-space-name.hf.space"
+# BASE_URL = "http://localhost:7860"  # Uncomment for local testing
 
 def test_api():
     """Test the deployed API"""
     
+    # Handle local testing
+    if len(sys.argv) > 1 and sys.argv[1] == "local":
+        global BASE_URL
+        BASE_URL = "http://localhost:7860"
+        print("🏠 Testing local server...")
+    
     # Get OpenAI API key from environment
     api_key = os.getenv("OPENAI_API_KEY")
     if not api_key:
@@ -68,6 +76,9 @@ def test_api():
         print(f"❌ Summarization failed: {e}")
     
     print(f"\n📖 View docs at: {BASE_URL}/docs")
+    print(f"\n💡 Usage:")
+    print(f"   python test.py        # Test Hugging Face deployment")
+    print(f"   python test.py local  # Test local server")
 
 if __name__ == "__main__":
     test_api()