Update app.py

app.py

@@ -9,9 +9,6 @@ from PIL import Image
 import PyPDF2
 import requests
 import uuid
-from collections import Counter
-import re
-from difflib import unified_diff
 
 # Configuration
 MODEL_NAME = "google/gemma-2b-it"
@@ -22,6 +19,61 @@ CURRENT_TIME = "2025-03-22 21:00:45"
 HF_TOKEN = os.getenv('HF_TOKEN')
 AZURE_TRANSLATION_KEY = os.getenv('AZURE_TRANSLATION_KEY')
 
+class Translator:
+    def _init_(self):
+        self.key = AZURE_TRANSLATION_KEY
+        self.region = 'centralindia'
+        self.endpoint = "https://api.cognitive.microsofttranslator.com"
+        
+        if not self.key:
+            raise ValueError("Azure Translator not configured. Please set AZURE_TRANSLATION_KEY in Spaces settings.")
+
+    def translate_text(self, text, target_language="en"):
+        try:
+            # Split the text into bullet points
+            bullet_points = text.split('\n• ')
+            translated_points = []
+            
+            # Translate each bullet point separately
+            for point in bullet_points:
+                if point.strip():  # Only translate non-empty points
+                    path = '/translate'
+                    constructed_url = self.endpoint + path
+                    
+                    params = {
+                        'api-version': '3.0',
+                        'to': target_language
+                    }
+                    
+                    headers = {
+                        'Ocp-Apim-Subscription-Key': self.key,
+                        'Ocp-Apim-Subscription-Region': 'centralindia',
+                        'Content-type': 'application/json',
+                        'X-ClientTraceId': str(uuid.uuid4())
+                    }
+                    
+                    body = [{
+                        'text': point.strip()
+                    }]
+                    
+                    response = requests.post(
+                        constructed_url,
+                        params=params,
+                        headers=headers,
+                        json=body
+                    )
+                    response.raise_for_status()
+                    
+                    translation = response.json()[0]["translations"][0]["text"]
+                    translated_points.append(translation)
+            
+            # Reconstruct the bullet-pointed text
+            translated_text = '\n• ' + '\n• '.join(translated_points)
+            return translated_text
+            
+        except Exception as e:
+            return f"Translation error: {str(e)}"
+
 class TextExtractor:
     @staticmethod
     def extract_text_from_input(input_file):
@@ -47,7 +99,7 @@ class TextExtractor:
         return "Unsupported input type"
 
 class LegalEaseAssistant:
-    def __init__(self):
+    def _init_(self):
         if not HF_TOKEN:
             raise ValueError("Hugging Face token not found. Please set the HF_TOKEN environment variable.")
         
@@ -65,56 +117,231 @@ class LegalEaseAssistant:
         )
         self.text_extractor = TextExtractor()
     
-    def generate_keywords(self, text):
-        words = re.findall(r'\b[A-Za-z]{5,}\b', text)
-        word_freq = Counter(words)
-        return ', '.join([word for word, _ in word_freq.most_common(10)])
+    def format_response(self, text):
+        """Format response as bullet points"""
+        sentences = [s.strip() for s in text.split('.') if s.strip()]
+        bullet_points = ['• ' + s + '.' for s in sentences]
+        return '\n'.join(bullet_points)
     
-    def compare_contracts(self, text1, text2):
-        text1_lines = text1.split('\n')
-        text2_lines = text2.split('\n')
-        diff = '\n'.join(unified_diff(text1_lines, text2_lines, lineterm=''))
-        return diff if diff else "The documents are identical."
+    def generate_response(self, input_file, task_type):
+        text = self.text_extractor.extract_text_from_input(input_file)
+        
+        task_prompts = {
+            "simplify": f"Simplify the following legal text in clear, plain language. Provide the response as separate points:\n\n{text}\n\nSimplified explanation:",
+            "summary": f"Provide a concise summary of the following legal document as separate key points:\n\n{text}\n\nSummary:",
+            "key_terms": f"Identify and explain the key legal terms and obligations in this text as separate points:\n\n{text}\n\nKey Terms:",
+            "risk": f"Perform a risk analysis on the following legal document and list each risk as a separate point:\n\n{text}\n\nRisk Assessment:"
+        }
+        
+        prompt = task_prompts.get(task_type, f"Analyze the following text and provide points:\n\n{text}\n\nAnalysis:")
+        
+        inputs = self.tokenizer(prompt, return_tensors="pt")
+        outputs = self.model.generate(
+            **inputs, 
+            max_new_tokens=300,
+            num_return_sequences=1,
+            do_sample=True,
+            temperature=0.7,
+            top_p=0.9
+        )
+        
+        response = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
+        response_parts = response.split(prompt.split("\n\n")[-1])
+        raw_response = response_parts[-1].strip() if len(response_parts) > 1 else response.strip()
+        
+        return self.format_response(raw_response)
 
 def create_interface():
     assistant = LegalEaseAssistant()
+    translator = Translator()
     
+    SUPPORTED_LANGUAGES = {
+        "English": "en",
+        "Hindi": "hi",
+        "Bengali": "bn",
+        "Telugu": "te",
+        "Tamil": "ta",
+        "Marathi": "mr",
+        "Gujarati": "gu",
+        "Kannada": "kn",
+        "Malayalam": "ml",
+        "Punjabi": "pa",
+        "Spanish": "es",
+        "French": "fr",
+        "German": "de",
+        "Chinese (Simplified)": "zh-Hans",
+        "Japanese": "ja"
+    }
+    
+    def process_with_translation(func, *args, target_lang="English"):
+        result = func(*args)
+        if target_lang != "English":
+            result = translator.translate_text(result, SUPPORTED_LANGUAGES[target_lang])
+        return result
+
     with gr.Blocks(title="LegalEase: AI Legal Assistant") as demo:
-        gr.Markdown("## 📜 LegalEase: AI-Powered Legal Document Assistant")
+        gr.HTML(f"""
+        <div style="text-align: center; background-color: #f0f2f6; padding: 20px; border-radius: 10px; margin-bottom: 20px;">
+            <h1 style="color: #2c3e50; font-size: 2.5em; margin-bottom: 10px;">📜 LegalEase</h1>
+            <h2 style="color: #34495e; font-size: 1.5em; margin-bottom: 20px;">AI-Powered Legal Document Assistant</h2>
+            <div style="display: flex; justify-content: center; gap: 40px; color: #576574; font-size: 1.1em;">
+                <div style="background-color: white; padding: 10px 20px; border-radius: 8px; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
+                    <span style="font-weight: bold;">User:</span> {CURRENT_USER}
+                </div>
+                <div style="background-color: white; padding: 10px 20px; border-radius: 8px; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
+                    <span style="font-weight: bold;">Last Updated:</span> {CURRENT_TIME} UTC
+                </div>
+            </div>
+        </div>
+        """)
+        
+        language_selector = gr.Dropdown(
+            choices=list(SUPPORTED_LANGUAGES.keys()),
+            value="English",
+            label="Select Output Language",
+            scale=1
+        )
+        
+        with gr.Tabs():
+            with gr.Tab("📝 Simplify Language"):
+                with gr.Row():
+                    with gr.Column(scale=1):
+                        simplify_input = gr.File(
+                            file_types=['txt', 'pdf', 'image'], 
+                            label="📎 Upload Document"
+                        )
+                        gr.HTML("<div style='height: 10px'></div>")
+                        simplify_text_input = gr.Textbox(
+                            label="✍ Or Type/Paste Text",
+                            placeholder="Enter your legal text here...",
+                            lines=4
+                        )
+                        gr.HTML("<div style='height: 10px'></div>")
+                        simplify_btn = gr.Button(
+                            "🔍 Simplify Language",
+                            variant="primary"
+                        )
+                    
+                    with gr.Column(scale=1):
+                        simplify_output = gr.Textbox(
+                            label="📋 Simplified Explanation",
+                            lines=12,
+                            show_copy_button=True
+                        )
+                
+                def simplify_handler(file, text, lang):
+                    input_source = file or text
+                    if not input_source:
+                        return "Please provide some text or upload a document to analyze."
+                    return process_with_translation(
+                        assistant.generate_response,
+                        input_source,
+                        "simplify",
+                        target_lang=lang
+                    )
+                
+                simplify_btn.click(
+                    fn=simplify_handler,
+                    inputs=[simplify_input, simplify_text_input, language_selector],
+                    outputs=simplify_output
+                )
 
-        with gr.Tab("🔑 Keyword Extraction"):
-            keyword_input = gr.File(file_types=['txt', 'pdf', 'image'], label="Upload Document")
-            keyword_text_input = gr.Textbox(label="Or Enter Text", placeholder="Enter legal text here...", lines=4)
-            keyword_output = gr.Textbox(label="Extracted Keywords", lines=2, show_copy_button=True)
-            keyword_btn = gr.Button("Extract Keywords")
-            
-            def keyword_handler(file, text):
-                input_source = file or text
-                if not input_source:
-                    return "Please provide some text or upload a document."
-                text = assistant.text_extractor.extract_text_from_input(input_source)
-                return assistant.generate_keywords(text)
-            
-            keyword_btn.click(fn=keyword_handler, inputs=[keyword_input, keyword_text_input], outputs=keyword_output)
+            with gr.Tab("📚 Document Summary"):
+                with gr.Row():
+                    with gr.Column(scale=1):
+                        summary_input = gr.File(
+                            file_types=['txt', 'pdf', 'image'], 
+                            label="📎 Upload Document"
+                        )
+                        gr.HTML("<div style='height: 10px'></div>")
+                        summary_text_input = gr.Textbox(
+                            label="✍ Or Type/Paste Text",
+                            placeholder="Enter your legal document here...",
+                            lines=4
+                        )
+                        gr.HTML("<div style='height: 10px'></div>")
+                        summary_btn = gr.Button(
+                            "📋 Generate Summary",
+                            variant="primary"
+                        )
+                    
+                    with gr.Column(scale=1):
+                        summary_output = gr.Textbox(
+                            label="📑 Document Summary",
+                            lines=12,
+                            show_copy_button=True
+                        )
+                
+                def summary_handler(file, text, lang):
+                    input_source = file or text
+                    if not input_source:
+                        return "Please provide some text or upload a document to summarize."
+                    return process_with_translation(
+                        assistant.generate_response,
+                        input_source,
+                        "summary",
+                        target_lang=lang
+                    )
+                
+                summary_btn.click(
+                    fn=summary_handler,
+                    inputs=[summary_input, summary_text_input, language_selector],
+                    outputs=summary_output
+                )
+
+            with gr.Tab("⚠ Risk Analysis"):
+                with gr.Row():
+                    with gr.Column(scale=1):
+                        risk_input = gr.File(
+                            file_types=['txt', 'pdf', 'image'], 
+                            label="📎 Upload Document"
+                        )
+                        gr.HTML("<div style='height: 10px'></div>")
+                        risk_text_input = gr.Textbox(
+                            label="✍ Or Type/Paste Text",
+                            placeholder="Enter your legal document here...",
+                            lines=4
+                        )
+                        gr.HTML("<div style='height: 10px'></div>")
+                        risk_btn = gr.Button(
+                            "🔍 Analyze Risks",
+                            variant="primary"
+                        )
+                    
+                    with gr.Column(scale=1):
+                        risk_output = gr.Textbox(
+                            label="⚠ Risk Assessment",
+                            lines=12,
+                            show_copy_button=True
+                        )
+                
+                def risk_handler(file, text, lang):
+                    input_source = file or text
+                    if not input_source:
+                        return "Please provide some text or upload a document to analyze risks."
+                    return process_with_translation(
+                        assistant.generate_response,
+                        input_source,
+                        "risk",
+                        target_lang=lang
+                    )
+                
+                risk_btn.click(
+                    fn=risk_handler,
+                    inputs=[risk_input, risk_text_input, language_selector],
+                    outputs=risk_output
+                )
+
+        gr.HTML(f"""
+        <div style="text-align: center; margin-top: 20px; padding: 20px; background-color: #f0f2f6; border-radius: 10px;">
+            <p style="color: #576574; margin: 0;">Powered by Gemma 2B and Azure Translator</p>
+            <p style="color: #576574; margin: 5px 0 0 0; font-size: 0.9em;">Built for Language Translation Hackathon</p>
+        </div>
+        """)
 
-        with gr.Tab("⚖ Contract Comparison"):
-            contract_input1 = gr.File(file_types=['txt', 'pdf'], label="Upload Contract 1")
-            contract_input2 = gr.File(file_types=['txt', 'pdf'], label="Upload Contract 2")
-            comparison_output = gr.Textbox(label="Comparison Result", lines=12, show_copy_button=True)
-            compare_btn = gr.Button("Compare Contracts")
-            
-            def compare_handler(file1, file2):
-                if not file1 or not file2:
-                    return "Please upload two contracts for comparison."
-                text1 = assistant.text_extractor.extract_text_from_input(file1)
-                text2 = assistant.text_extractor.extract_text_from_input(file2)
-                return assistant.compare_contracts(text1, text2)
-            
-            compare_btn.click(fn=compare_handler, inputs=[contract_input1, contract_input2], outputs=comparison_output)
-    
     return demo
 
 demo = create_interface()
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()