Odoo Edi Connector

Odoo EDI Connector

Overview

Electronic Data Interchange (EDI) is the standard for automated B2B document exchange — purchase orders, invoices, ASNs (Advance Shipping Notices). This skill guides you through mapping EDI transactions (ANSI X12 or EDIFACT) to Odoo business objects, setting up trading partner configurations, and automating inbound/outbound document flows.

When to Use This Skill

• A retail partner requires EDI 850 (Purchase Orders) to do business with you.
• You need to send EDI 856 (ASN) when goods are shipped.
• Automating EDI 810 (Invoice) generation from Odoo confirmed deliveries.
• Mapping EDI fields to Odoo fields for a new trading partner.

How It Works

1. Activate: Mention @odoo-edi-connector and specify the EDI transaction set and trading partner.
2. Map: Receive a complete field mapping table between EDI segments and Odoo fields.
3. Automate: Get Python code to parse incoming EDI files and create Odoo records.

EDI ↔ Odoo Object Mapping

Examples

Example 1: Parse EDI 850 and Create Odoo Sale Order (Python)

from pyx12 import x12file  # pip install pyx12

import xmlrpc.client

odoo_url = "https://myodoo.example.com"
db, uid, pwd = "my_db", 2, "api_key"
models = xmlrpc.client.ServerProxy(f"{odoo_url}/xmlrpc/2/object")

def process_850(edi_file_path):
    """Parse X12 850 Purchase Order and create Odoo Sale Order"""
    with x12file.X12File(edi_file_path) as f:
        for transaction in f.get_transaction_sets():
            # Extract header info (BEG segment)
            po_number = transaction['BEG'][3]    # Purchase Order Number
            po_date   = transaction['BEG'][5]    # Purchase Order Date

            # Extract partner (N1 segment — Buyer)
            partner_name = transaction['N1'][2]

            # Find partner in Odoo
            partner = models.execute_kw(db, uid, pwd, 'res.partner', 'search',
                [[['name', 'ilike', partner_name]]])
            partner_id = partner[0] if partner else False

            # Extract line items (PO1 segments)
            order_lines = []
            for po1 in transaction.get_segments('PO1'):
                sku     = po1[7]    # Product ID
                qty     = float(po1[2])
                price   = float(po1[4])

                product = models.execute_kw(db, uid, pwd, 'product.product', 'search',
                    [[['default_code', '=', sku]]])
                if product:
                    order_lines.append((0, 0, {
                        'product_id': product[0],
                        'product_uom_qty': qty,
                        'price_unit': price,
                    }))

            # Create Sale Order
            if partner_id and order_lines:
                models.execute_kw(db, uid, pwd, 'sale.order', 'create', [{
                    'partner_id': partner_id,
                    'client_order_ref': po_number,
                    'order_line': order_lines,
                }])

Example 2: Send EDI 997 Acknowledgment

def generate_997(isa_control, gs_control, transaction_control):
    """Generate a functional acknowledgment for received EDI"""
    return f"""ISA*00*          *00*          *ZZ*YOURISAID      *ZZ*PARTNERISAID   *{today}*1200*^*00501*{isa_control}*0*P*>~
GS*FA*YOURGID*PARTNERGID*{today}*1200*{gs_control}*X*005010X231A1~
ST*997*0001~
AK1*PO*{gs_control}~
AK9*A*1*1*1~
SE*4*0001~
GE*1*{gs_control}~
IEA*1*{isa_control}~"""

Best Practices

• ✅ Do: Store every raw EDI transaction in an audit log table before processing.
• ✅ Do: Always send a 997 Functional Acknowledgment within 24 hours of receiving a transaction.
• ✅ Do: Negotiate a test cycle with trading partners before going live — use test ISA qualifier T.
• ❌ Don't: Process EDI files synchronously in web requests — queue them for async processing.
• ❌ Don't: Hardcode trading partner qualifiers — store them in a configuration table per partner.

AGI Framework Integration

Adapted for @techwavedev/agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Retrieve prior design decisions (color palettes, typography, spacing scales) to maintain visual consistency across sessions. Cache generated design tokens.

# Check for prior frontend/design context before starting
python3 execution/memory_manager.py auto --query "design system decisions and component patterns for Odoo Edi Connector"

Storing Results

After completing work, store frontend/design decisions for future sessions:

python3 execution/memory_manager.py store \
  --content "Design system: adopted 8px grid, Inter font family, HSL color tokens with dark mode support" \
  --type decision --project <project> \
  --tags odoo-edi-connector frontend

Multi-Agent Collaboration

Share design decisions with backend agents (API contract changes) and QA agents (visual regression baselines).

python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Implemented UI components — new design system with accessibility compliance (WCAG 2.1 AA)" \
  --project <project>

Design Memory Persistence

Store design system tokens and component decisions in Qdrant so any agent on any platform (Claude, Gemini, Cursor) can retrieve and apply consistent styling.