writer_agent.py

 

from pydantic import BaseModel, Field
from agents import Agent
from agents.prompts import Prompt
from pypdf import PdfReader
import PyPDF2
 
# === 1. Instructions for the model ===
INSTRUCTIONS = (
    "You are a Proforma Invoice Generator assistant. "
    "Given customer details, produce a clear, structured Proforma Invoice in plain text. "
    "Include Consignor (True Vybes, Thane, GSTIN: 27BVOPS7767J2ZF), "
    "Consignee section (customer name, address, GSTIN, date), "
    "product table with Sl. No., Description, Code, Qty, Rate/unit, Value, "
    "total, GST @ 18%, Grand Total, bank details, standard terms, "
    "and 'Authorised Signatory' at the end. "
    "Output ONLY the invoice content, no extra text."
)

# === 2. Create the prompt ===
def prompt_fn(data):
    # same debug:
    if hasattr(data, "input"):
        user_input = data.input
    elif hasattr(data, "raw_input"):
        user_input = data.raw_input
    elif hasattr(data, "__dict__"):
        user_input = data.__dict__
    else:
        user_input = data  # fallback

    final_prompt = f"""
Customer Name: {user_input.get('customer_name')}
Address: {user_input.get('address')}
GSTIN: {user_input.get('gst_number')}
Date: {user_input.get('date')}
Product: {user_input.get('product_name')}
Qty: {user_input.get('quantity')}
Price per piece: {user_input.get('price_per_piece')}
"""

    return Prompt(content=final_prompt)

class ProformaInvoice(BaseModel):
    proforma_invoice: str = Field(description="Final Proforma invoice")
 
writer_agent = Agent(
    name="PI Generator agent",
    instructions=INSTRUCTIONS,
    prompt=prompt_fn,
    model="gpt-4o-mini",
     output_type=ProformaInvoice,
)

 

# === 4. Extract invoice text ===
#invoice_text = response.choices[0].message.content
#print("Generated Invoice:\n")
#print(invoice_text)

# === 5. Save as HTML ===
##html_content = f"<pre>{invoice_text}</pre>"
#with open("invoice.html", "w") as f:
#    f.write(html_content)

# === 6. Convert to PDF ===