ChatGPT - Optimize Product Feed

📌 Purpose

This script enhances product feed data using OpenAI's GPT models, generating structured titles, descriptions, highlights, and attributes like color or material. It uses data from feed rows, meta descriptions, and product images to produce SEO-ready content.

It is designed for use within Alli Workflows, enabling automated and scalable product content enrichment for eCommerce and marketing.

🧩 Environment Variables

Required

|| Variable Name || Description ||
| OPENAI_API_KEY | Your OpenAI API key. Accepts api_key as a fallback. |
| PRODUCT_FEED | Full path to the input .csv file with product data. |
| OUTPUT_FEED | Destination path to save the enriched .csv output. |

Optional

|| Variable Name || Description ||
| CUSTOMER_PERSONA | A description of your brand’s average customer to guide tone and style. |
| KEYWORDS | Comma-separated list of keywords to weave into the content. |
| MAIN_IMAGE | The column name containing image URLs (used for base64 image enhancement). |
| MAIN_KEY | Unique identifier for each row. Defaults to SKU. |

🚀 Script Workflow

1. Read Input

   • Loads CSV from PRODUCT_FEED

   • Infers schema roles using OpenAI (optional)

2. Process Rows

   • For each row:

     • Build prompt using feed data, persona, keywords

     • Fetch meta description from product URL

     • Fetch base64 of product image (if available)

3. Generate AI Output

   • Calls gpt-4o with prompt

   • Parses JSON response

   • Adds fields like title, highlights, reasoning, etc.

4. Write Output

   • Saves all enriched rows to OUTPUT_FEED

   • Logs failed rows to error_rows.csv

   • Prints a preview of the first 5 rows

📤 Output Fields

|| Field || Description ||
| SKU | From MAIN_KEY (or SKU) |
| run_date | Date script was run |
| ai_model | Model used (gpt-4o) |
| structured_title | Cleaned and enhanced product title |
| ai_short_title | Brief, search-friendly product title |
| structured_description | Long-form, SEO-ready description |
| ai_product_highlights | Bulleted list of product highlights |
| ai_product_type | Inferred product category |
| ai_color | Inferred product color |
| ai_material | Inferred material |
| ai_pattern | Inferred pattern or texture |
| ai_reasoning | Explanation of how/why the content was generated |

🧠 Features

• 🔁 Retry logic with tenacity for resilient API and web requests

• 🧠 Auto schema inference using OpenAI

• 📸 Visual analysis of product images using base64

• ⚡ Fast batch processing with ThreadPoolExecutor

🔗 Use Cases

• Google Shopping feed optimization

• Amazon or eCommerce site product content

• SEO-focused PDP (Product Detail Page) generation

• Generating AI-enriched marketing content

⚠️ Notes

• Ensure product URLs and image links are accessible by the script

• Any rows that fail to process are saved to error_rows.csv

• Script attempts to fix malformed JSON returned by the AI

✅ Alli Workflows Best Practices

• Use a file-cleaning task (e.g. null removal) before this step

• Organize variables using environment groups for reusability

• Review OUTPUT_FEED and error_rows.csv in downstream logic

🧪 Sample Output Preview

First 5 rows of the output:       SKU     run_date   ai_model   structured_title   ai_short_title   ...     ABC123   2025-06-24  gpt-4o     ...                ...              ...     DEF456   2025-06-24  gpt-4o     ...                ...              ...