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Dockerfile

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+FROM python:3.9-slim
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    tesseract-ocr \
+    tesseract-ocr-eng \
+    && rm -rf /var/lib/apt/lists/*
+
+# Create a non-root user
+RUN useradd -m -u 1000 user
+USER user
+ENV PATH="/home/user/.local/bin:$PATH"
+
+# Set working directory
+WORKDIR /app
+
+# Copy requirements first to leverage Docker cache
+COPY --chown=user requirements.txt .
+RUN pip install --no-cache-dir --upgrade -r requirements.txt
+
+# Download spaCy model
+RUN python -m spacy download en_core_web_md
+
+# Copy the rest of the application
+COPY --chown=user . .
+
+# Expose the port the app runs on
+EXPOSE 7860
+
+# Command to run the application
+CMD ["gunicorn", "--bind", "0.0.0.0:7860", "newapp:app"] 

README.md

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----
-title: Property Verification
-emoji: 🏢
-colorFrom: red
-colorTo: green
-sdk: docker
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: Property Verification Bot
+emoji: 🏠
+colorFrom: blue
+colorTo: indigo
+sdk: docker
+pinned: false
+---
+
+# Property Verification Bot
+
+A comprehensive property verification system that analyzes property listings for authenticity and potential fraud. The system uses multiple AI models to verify various aspects of property listings including:
+
+- Image analysis
+- Document verification
+- Location verification
+- Price analysis
+- Legal document analysis
+- Property specification validation
+
+## Features
+
+- Image authenticity detection
+- Document verification and analysis
+- Location verification using geocoding
+- Price analysis and market value estimation
+- Legal document analysis
+- Property specification validation
+- Fraud detection
+- Trust score generation
+
+## How to Use
+
+1. Submit property details including:
+   - Property images
+   - Property documents
+   - Location information
+   - Property specifications
+   - Market value
+
+2. The system will analyze the provided information and generate:
+   - Trust score
+   - Fraud detection results
+   - Verification status
+   - Detailed analysis report
+
+## Technical Details
+
+The system uses multiple AI models and techniques:
+- CLIP for image analysis
+- BART for text analysis
+- spaCy for NLP processing
+- Sentence Transformers for semantic analysis
+- OCR for document processing
+
+## License
+
+MIT License 

requirements.txt

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+flask==2.3.3
+flask-cors==4.0.0
+torch==2.1.0
+transformers==4.34.0
+Pillow==10.0.0
+numpy==1.24.3
+PyMuPDF==1.23.8
+geopy==2.4.0
+sentence-transformers==2.2.2
+spacy==3.7.2
+pytesseract==0.3.10
+langdetect==1.0.9
+deep-translator==1.11.4
+requests==2.31.0
+python-dotenv==1.0.0
+gunicorn==21.2.0