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