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from fastapi import FastAPI, File, UploadFile, HTTPException
from fastapi.responses import JSONResponse
import tempfile
import os
# Import our services
from app.services.text_extractor import extract_text_from_pdf
from app.services.risk_analyzer import analyze_clause_with_gemini
from app.services.risk_scorer import calculate_scores, get_risk_definition
from app.schemas import AnalysisReport, AnalyzedClause, RiskFinding
# Create FastAPI app instance
app = FastAPI(
title="Multilingual Legal Contract Analyzer",
description="AI-powered contract analysis for English and Indic languages",
version="1.0.0"
)
@app.post("/analyze/", response_model=AnalysisReport)
async def analyze_contract(file: UploadFile = File(...)):
"""
Analyze a legal contract PDF and return detailed risk analysis.
Args:
file: PDF file to analyze
Returns:
AnalysisReport with risk analysis and suggestions
"""
if not file.filename.lower().endswith('.pdf'):
raise HTTPException(
status_code=400, detail="Only PDF files are supported")
with tempfile.NamedTemporaryFile(delete=False, suffix='.pdf') as temp_file:
try:
content = await file.read()
temp_file.write(content)
temp_file.flush()
# Step 1: Extract text from PDF
print(f"Extracting text from {file.filename}...")
full_text = extract_text_from_pdf(temp_file.name)
if not full_text or len(full_text.strip()) < 50:
raise HTTPException(
status_code=400,
detail="Unable to extract meaningful text from PDF. Please ensure the PDF is readable."
)
# Step 2 removed → directly analyze full contract
print("Analyzing full contract with AI...")
ai_result = analyze_clause_with_gemini(full_text)
# Build findings list
risks = []
for risk_data in ai_result.get("risks", []):
risk_id = risk_data.get("risk_id")
if risk_id:
risk_def = get_risk_definition(risk_id)
risk_finding = RiskFinding(
risk_id=risk_id,
description=risk_data.get(
"explanation", risk_def["description"]),
score=risk_def["score"]
)
risks.append(risk_finding)
# Wrap into single "clause" (actually full contract text)
analyzed_clause = AnalyzedClause(
clause_number=1,
text=full_text[:500] + "..." if len(full_text) > 500 else full_text,
risks=risks,
suggestion=ai_result.get("suggestion")
)
# Step 3: Calculate final risk score
print("Calculating final risk score...")
final_score, all_findings = calculate_scores([analyzed_clause])
# Step 4: Contract metadata (basic detection)
contract_type = "General Contract"
language = "English"
# Create final analysis report
analysis_report = AnalysisReport(
file_name=file.filename,
language=language,
contract_type=contract_type,
final_risk_score=final_score,
clauses=[analyzed_clause]
)
print(f"Analysis complete. Final risk score: {final_score}")
return analysis_report
except HTTPException:
raise
except Exception as e:
print(f"Error during analysis: {e}")
raise HTTPException(
status_code=500,
detail=f"Analysis failed: {str(e)}"
)
finally:
try:
os.unlink(temp_file.name)
except:
pass
@app.get("/")
async def root():
return {"message": "Multilingual Legal Contract Analyzer API is running"}
@app.get("/health")
async def health_check():
return {"status": "healthy", "service": "contract-analyzer"}
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=7860)
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