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File size: 2,197 Bytes
0bd4ab4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 | import os
import glob
from app.rag.pdf_parser import PDFParser
from app.services.k2_think_engine import K2ThinkEngine
from app.models.schemas import AnalysisRequest as K2AnalysisRequest, ScientificDocument, DocumentType
import asyncio
UPLOAD_DIR = os.getenv("UPLOAD_DIR", "./uploaded_files")
print(f"UPLOAD_DIR: {UPLOAD_DIR}")
# Test with actual uploaded files
test_pids = [
"18c685f0-0658-4502-a9a1-b683e98962a0",
"e7e941d6-16f8-4c3d-a927-e3788ce69581",
"8c430616-b83f-45b3-a619-d0e73e02b936"
]
async def run_test():
docs = []
for pid in test_pids:
pattern = os.path.join(UPLOAD_DIR, f"{pid}*.pdf")
files = glob.glob(pattern)
if files:
try:
safe_filename = os.path.basename(files[0]).encode('ascii', 'replace').decode('ascii')
text = PDFParser.extract_text(files[0])
metadata = PDFParser.extract_metadata(files[0])
print(f"Extracted {len(text)} chars from {safe_filename}")
docs.append(ScientificDocument(
id=pid,
title=metadata.get("title") or safe_filename,
authors=[metadata.get("author")] if metadata.get("author") else ["Unknown"],
abstract="Extracted from PDF",
content=text,
document_type=DocumentType.PDF
))
except Exception as e:
print(f"Extraction failed for {pid}: {e}")
if not docs:
print("No documents extracted!")
return
print(f"Testing K2ThinkEngine with {len(docs)} documents...")
try:
engine = K2ThinkEngine()
k2_request = K2AnalysisRequest(documents=docs)
result = await engine.process_analysis_request(k2_request)
print("Success! Reasonning completed.")
print(f"Comparisons found: {len(result.comparative_analysis.divergences) if result.comparative_analysis else 0}")
except Exception as k2_err:
print(f"K2 API Failed: {k2_err}")
import traceback
traceback.print_exc()
if __name__ == "__main__":
asyncio.run(run_test())
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