File size: 1,806 Bytes
994ec86 a7621d6 994ec86 a7621d6 994ec86 a7621d6 994ec86 |
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 |
import requests
import pandas as pd
import io
from fpdf import FPDF
import json
def convert_xlsx_to_pdf(file):
"""Converts an XLSX file to a PDF and returns a BytesIO object with a filename."""
excel_data = pd.ExcelFile(file)
pdf = FPDF()
pdf.set_auto_page_break(auto=True, margin=15)
pdf.add_page()
pdf.set_font("Arial", size=12)
for sheet_name in excel_data.sheet_names:
pdf.cell(200, 10, txt=f"Sheet: {sheet_name}", ln=True, align='C')
pdf.ln(10)
df = excel_data.parse(sheet_name)
for i in range(min(10, len(df))): # Limiting rows for readability
row_data = " | ".join(str(x) for x in df.iloc[i])
pdf.multi_cell(0, 10, row_data)
pdf.ln(5)
pdf_output = io.BytesIO()
pdf_output.write(pdf.output(dest='S').encode('latin1')) # Convert to bytes
pdf_output.seek(0)
# Manually add a 'name' attribute to mimic a file
pdf_output.name = file.name.replace(".xlsx", ".pdf")
return pdf_output
def upload_file_to_vectara(file, customer_id, api_key, corpus_key):
"""Uploads a file to Vectara API v2."""
url = f"https://api.vectara.io/v2/corpora/{corpus_key}/upload_file"
headers = {
"customer-id": customer_id,
"x-api-key": api_key,
"Accept": "application/json"
}
metadata = {"type_file": "excel"} if file.name.endswith('.xlsx') else {}
if file.name.endswith('.xlsx'):
file = convert_xlsx_to_pdf(file) # Convert XLSX to PDF
files = {
'metadata': (None, json.dumps(metadata), 'application/json'),
"file": (file.name, file.getvalue())} # Now file.name exists
response = requests.post(url, headers=headers, files=files)
return response.json()
|