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from fastapi import FastAPI
from pydantic import BaseModel
from typing import List, Dict, Any, Optional
import os
import uvicorn
import time
import hashlib
from document_processor import DocumentProcessor
from models import *
# Initialize FastAPI app
app = FastAPI(title="Legal Document Analysis API", version="1.0.0")
# Initialize document processor
processor = DocumentProcessor()
@app.on_event("startup")
async def startup_event():
"""Initialize models on startup"""
await processor.initialize()
@app.post("/analyze_document")
async def analyze_document(data: AnalyzeDocumentInput):
"""Unified endpoint for complete document analysis"""
try:
start_time = time.time()
if not data.document_text:
return {"error": "No document text provided"}
# Generate document ID for caching
doc_id = hashlib.sha256(data.document_text.encode()).hexdigest()[:16]
# Process document completely
result = await processor.process_document(data.document_text, doc_id)
processing_time = time.time() - start_time
result["processing_time"] = f"{processing_time:.2f}s"
result["doc_id"] = doc_id
return result
except Exception as e:
return {"error": str(e)}
# Keep backward compatibility endpoints
@app.post("/chunk")
def chunk_text(data: ChunkInput):
return processor.chunk_text(data)
@app.post("/summarize_batch")
def summarize_batch(data: SummarizeBatchInput):
return processor.summarize_batch(data)
if __name__ == "__main__":
uvicorn.run(app, host="0.0.0.0", port=7860)
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