| from fastapi import APIRouter, UploadFile, File, HTTPException
|
| import io
|
| import pandas as pd
|
| from backend.state import session_store
|
| import uuid
|
| import math
|
|
|
| router = APIRouter()
|
|
|
| @router.post("/upload")
|
| async def upload_file(file: UploadFile=File(...)):
|
| session_id = str(uuid.uuid4())
|
| if not file.filename.endswith(".csv"):
|
| raise HTTPException(status_code=400, detail="Only CSV files are accepted")
|
|
|
| content = await file.read()
|
|
|
| if len(content) > 20 * 1024 * 1024:
|
| raise HTTPException(status_code=400, detail="File too large. Maximum size is 10MB")
|
|
|
| try:
|
| df = pd.read_csv(io.BytesIO(content), na_values=['?', 'NA', 'N/A', 'na', 'n/a', ''])
|
| except Exception:
|
| raise HTTPException(status_code=400, detail="Could not parse CSV. Check the file format")
|
|
|
| def clean_nan(data):
|
| if isinstance(data, dict):
|
| return {k: clean_nan(v) for k, v in data.items()}
|
| elif isinstance(data, list):
|
| return [clean_nan(v) for v in data]
|
| elif isinstance(data, float) and math.isnan(data):
|
| return None
|
| return data
|
|
|
| rows, cols = df.shape
|
| preview = clean_nan(df.head(5).to_dict(orient="records"))
|
| session_store[session_id] = {
|
| "df": df,
|
| "summary": None,
|
| "explanation": None
|
| }
|
|
|
| return {
|
| "filename": file.filename,
|
| "rows": rows,
|
| "columns": cols,
|
| "column_names": df.columns.tolist(),
|
| "session_id": session_id,
|
| "preview": preview
|
| }
|
|
|
|
|
|
|
|
|
