Initial commit
This commit is contained in:
Zhongwei Li
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"""
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Contact Information Extraction Example
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Extracts structured contact information from unstructured text (emails, messages, etc.)
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using JSON outputs mode with Pydantic schema validation.
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"""
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from pydantic import BaseModel, Field, EmailStr
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from typing import Optional, List
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from anthropic import Anthropic
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import os
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# Initialize client
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client = Anthropic(api_key=os.environ.get("ANTHROPIC_API_KEY"))
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# Define schema with Pydantic
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class ContactInfo(BaseModel):
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"""Structured contact information extracted from text."""
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name: str = Field(description="Full name of the contact person")
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email: EmailStr = Field(description="Email address")
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phone: Optional[str] = Field(
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None, description="Phone number in any format"
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)
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company: Optional[str] = Field(
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None, description="Company or organization name"
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)
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plan_interest: Optional[str] = Field(
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None, description="Product plan or tier they're interested in"
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)
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demo_requested: bool = Field(
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False, description="Whether they requested a product demo"
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)
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tags: List[str] = Field(
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default_factory=list,
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description="Relevant tags or categories"
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)
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def extract_contact(text: str) -> Optional[ContactInfo]:
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"""
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Extract contact information from unstructured text.
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Args:
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text: Unstructured text containing contact information
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Returns:
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ContactInfo object with extracted data, or None if request refused
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"""
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try:
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response = client.beta.messages.parse(
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model="claude-sonnet-4-5",
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max_tokens=1024,
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betas=["structured-outputs-2025-11-13"],
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messages=[{
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"role": "user",
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"content": f"Extract contact information from the following text:\n\n{text}"
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}],
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output_format=ContactInfo,
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)
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# Handle different stop reasons
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if response.stop_reason == "refusal":
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print(f"⚠️ Request refused for safety reasons")
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return None
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if response.stop_reason == "max_tokens":
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print(f"⚠️ Response truncated - increase max_tokens")
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return None
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# Return validated contact info
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return response.parsed_output
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except Exception as e:
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print(f"❌ Error extracting contact: {e}")
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raise
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def main():
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"""Run contact extraction examples."""
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examples = [
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# Example 1: Complete contact info
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"""
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Hi, I'm John Smith from Acme Corp. You can reach me at john.smith@acme.com
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or call me at (555) 123-4567. I'm interested in your Enterprise plan and
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would love to schedule a demo next week.
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""",
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# Example 2: Minimal info
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"""
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Contact: jane.doe@example.com
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""",
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# Example 3: Informal message
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"""
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Hey! Bob here. Email me at bob@startup.io if you want to chat about
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the Pro plan. Thanks!
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""",
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# Example 4: Multiple contacts (extracts first/primary)
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"""
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From: alice@company.com
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CC: support@company.com
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Hi, I'm Alice Johnson, VP of Engineering at TechCo.
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We're evaluating your platform for our team of 50 developers.
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""",
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]
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print("=" * 70)
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print("Contact Extraction Examples")
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print("=" * 70)
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for i, text in enumerate(examples, 1):
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print(f"\n📧 Example {i}:")
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print(f"Input: {text.strip()[:100]}...")
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contact = extract_contact(text)
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if contact:
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print(f"\n✅ Extracted Contact:")
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print(f" Name: {contact.name}")
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print(f" Email: {contact.email}")
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print(f" Phone: {contact.phone or 'N/A'}")
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print(f" Company: {contact.company or 'N/A'}")
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print(f" Plan Interest: {contact.plan_interest or 'N/A'}")
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print(f" Demo Requested: {contact.demo_requested}")
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print(f" Tags: {', '.join(contact.tags) if contact.tags else 'None'}")
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else:
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print(f"\n❌ No contact extracted")
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print("-" * 70)
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if __name__ == "__main__":
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main()
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@@ -0,0 +1,160 @@
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"""
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Invoice Data Extraction Example
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Extracts structured invoice data from text using JSON outputs with nested schemas.
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Demonstrates handling complex nested structures (line items, tax breakdown).
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"""
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from pydantic import BaseModel, Field
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from typing import List
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from decimal import Decimal
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from anthropic import Anthropic
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import os
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client = Anthropic(api_key=os.environ.get("ANTHROPIC_API_KEY"))
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# Nested schema for line items
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class LineItem(BaseModel):
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"""Individual line item on an invoice."""
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description: str = Field(description="Item description")
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quantity: int = Field(description="Quantity ordered")
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unit_price: float = Field(description="Price per unit in USD")
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total: float = Field(description="Total for this line (quantity * unit_price)")
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class Invoice(BaseModel):
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"""Complete invoice structure."""
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invoice_number: str = Field(description="Invoice ID (format: INV-XXXXX)")
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date: str = Field(description="Invoice date in YYYY-MM-DD format")
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due_date: str = Field(description="Payment due date in YYYY-MM-DD format")
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customer_name: str = Field(description="Customer or company name")
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customer_email: str = Field(description="Customer email address")
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line_items: List[LineItem] = Field(
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description="List of items on the invoice"
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)
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subtotal: float = Field(description="Subtotal before tax in USD")
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tax_rate: float = Field(description="Tax rate as decimal (e.g., 0.08 for 8%)")
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tax_amount: float = Field(description="Tax amount in USD")
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total_amount: float = Field(description="Final total amount in USD")
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notes: str = Field(
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default="",
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description="Additional notes or payment instructions"
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)
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def extract_invoice(invoice_text: str) -> Optional[Invoice]:
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"""Extract structured invoice data."""
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try:
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response = client.beta.messages.parse(
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model="claude-sonnet-4-5",
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max_tokens=2048, # Higher for complex nested structures
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betas=["structured-outputs-2025-11-13"],
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messages=[{
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"role": "user",
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"content": f"Extract all invoice data from:\n\n{invoice_text}"
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}],
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output_format=Invoice,
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)
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if response.stop_reason != "end_turn":
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print(f"⚠️ Unexpected stop reason: {response.stop_reason}")
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return None
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return response.parsed_output
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except Exception as e:
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print(f"❌ Error: {e}")
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raise
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def main():
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"""Run invoice extraction example."""
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invoice_text = """
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INVOICE
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Invoice Number: INV-2024-00123
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Date: 2024-01-15
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Due Date: 2024-02-15
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Bill To:
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Acme Corporation
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John Smith, CFO
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john.smith@acme.com
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ITEMS:
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1. Cloud Hosting - Pro Plan (x3 servers)
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Quantity: 3
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Unit Price: $299.00
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Total: $897.00
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2. Database Storage - 500GB
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Quantity: 500
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Unit Price: $0.50
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Total: $250.00
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3. API Calls - Premium Tier
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Quantity: 1,000,000
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Unit Price: $0.001
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Total: $1,000.00
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4. Support - Enterprise Level
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Quantity: 1
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Unit Price: $500.00
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Total: $500.00
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Subtotal: $2,647.00
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Tax (8.5%): $224.99
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TOTAL: $2,871.99
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Payment Terms: Net 30
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Please remit payment to accounts@cloudprovider.com
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"""
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print("=" * 70)
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print("Invoice Extraction Example")
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print("=" * 70)
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invoice = extract_invoice(invoice_text)
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if invoice:
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print(f"\n✅ Invoice Extracted Successfully\n")
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print(f"Invoice #: {invoice.invoice_number}")
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print(f"Customer: {invoice.customer_name} ({invoice.customer_email})")
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print(f"Date: {invoice.date}")
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print(f"Due: {invoice.due_date}")
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print(f"\nLine Items:")
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for i, item in enumerate(invoice.line_items, 1):
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print(f" {i}. {item.description}")
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print(f" Qty: {item.quantity} × ${item.unit_price:.2f} = ${item.total:.2f}")
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print(f"\nSubtotal: ${invoice.subtotal:.2f}")
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print(f"Tax ({invoice.tax_rate * 100:.1f}%): ${invoice.tax_amount:.2f}")
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print(f"TOTAL: ${invoice.total_amount:.2f}")
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if invoice.notes:
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print(f"\nNotes: {invoice.notes}")
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# Validation checks
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print(f"\n🔍 Validation:")
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calculated_subtotal = sum(item.total for item in invoice.line_items)
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print(f" Subtotal matches: {abs(calculated_subtotal - invoice.subtotal) < 0.01}")
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calculated_tax = invoice.subtotal * invoice.tax_rate
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print(f" Tax calculation matches: {abs(calculated_tax - invoice.tax_amount) < 0.01}")
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calculated_total = invoice.subtotal + invoice.tax_amount
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print(f" Total matches: {abs(calculated_total - invoice.total_amount) < 0.01}")
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else:
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print("❌ Failed to extract invoice")
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if __name__ == "__main__":
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from typing import Optional
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main()
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