"""
Test Enhanced Legal RAG Pipeline with Gemini 2.5 Pro
Property fraud case involving land grabbing and document forgery
"""

from rag_service import evaluateCase
import time

propertyCase = """
Case involves Mr. Rakesh Malhotra who orchestrated an elaborate property fraud scheme 
in Delhi's Vasant Vihar area. The accused:

1) FORGED DOCUMENTS: Created fake sale deeds backdated to 2016 claiming purchase of 
   Plot No. 247 (5000 sq ft) from deceased owner Mr. K.L. Verma who died in 2015

2) BRIBERY: Paid Rs 2 lakh to Sub-Registrar office clerk Suresh Yadav to insert 
   forged documents into official registry records (confirmed by Anti-Corruption Bureau)

3) ILLEGAL CONSTRUCTION: Started construction of 4-story commercial building without 
   proper permissions, violating building bylaws

4) FRAUDULENT SALE: Sold property to multiple buyers - Mr. Anil Kapoor (Rs 1.2 crore), 
   Mrs. Sunita Reddy (Rs 95 lakhs), and Sharma Builders Ltd (Rs 1.5 crore) using the 
   same forged documents

5) INTIMIDATION: Threatened original heir Ms. Kavita Verma (daughter of deceased owner) 
   with violence when she objected, backed by hired goons

EVIDENCE COLLECTED:
- Forensic report confirmed signatures on deeds were forged (did not match K.L. Verma's authentic signatures)
- Bank statements showing Rs 2 lakh payment to Suresh Yadav
- Witness testimony from 5 neighbors confirming Rakesh had no connection to property before 2020
- Municipal records proving K.L. Verma's family owned land since 1998
- Video evidence of intimidation captured by Ms. Kavita Verma's security cameras
- Three buyer complaints with proof of payment totaling Rs 3.65 crore
- Property documents from legal heir Ms. Kavita Verma proving inheritance rights

All three buyers lost their investments. Construction was halted by municipal authorities.
"""

print("=" * 100)
print("TESTING ENHANCED LEGAL RAG PIPELINE WITH GEMINI 2.5 PRO")
print("=" * 100)
print("\n📋 PROPERTY FRAUD CASE:")
print(propertyCase)
print("\n" + "=" * 100)
print("🔄 PROCESSING...")
print("   - Running LegalBERT prediction (parallel)")
print("   - Extracting keywords with Gemini 1.5 Flash (parallel)")
print("   - Performing dual retrieval (semantic + keyword-based)")
print("   - Generating judgment with Gemini 2.5 Pro")
print("=" * 100)

startTime = time.time()
result = evaluateCase(propertyCase)
endTime = time.time()

print("\n✅ PREDICTION RESULTS:")
print(f"   Verdict: {result['verdict'].upper()}")
print(f"   Confidence: {result['confidence'] * 100:.2f}%")

print("\n🔑 EXTRACTED LEGAL KEYWORDS:")
if result['extractedKeywords']:
    for i, keyword in enumerate(result['extractedKeywords'], 1):
        print(f"   {i}. {keyword}")
else:
    print("   No keywords extracted")

print("\n📚 RETRIEVED CHUNKS (Dual Retrieval):")
totalChunks = 0
for category, chunks in result['retrievedChunks'].items():
    chunkCount = len(chunks)
    totalChunks += chunkCount
    print(f"   {category}: {chunkCount} chunks")
print(f"   TOTAL: {totalChunks} chunks retrieved")

print("\n" + "=" * 100)
print("⚖️ FINAL JUDGMENT (Generated by Gemini 2.5 Pro):")
print("=" * 100)
print(result['explanation'])
print("=" * 100)

print("\n📊 PERFORMANCE METRICS:")
print(f"   Total processing time: {endTime - startTime:.2f} seconds")
print(f"   Judgment word count: {len(result['explanation'].split())} words")
print(f"   Judgment character count: {len(result['explanation']):,} characters")
print(f"   Keywords extracted: {len(result['extractedKeywords'])}")
print(f"   Model used: Gemini 2.5 Pro")

print("\n✨ Enhanced features demonstrated:")
print("   ✓ Parallel execution (LegalBERT + Keyword Extraction)")
print("   ✓ Dual retrieval (Semantic + Keyword-based)")
print("   ✓ Gemini 2.5 Pro for superior reasoning")
print("   ✓ Similar case precedent references")
print("   ✓ Concise 400-600 word judgment")