This document outlines the process of integrating a COBOL batch payment processing program with the Groq Inference engine. The integration enables the COBOL program to leverage Groq's accelerated computing for enhanced transaction processing.
- COBOL Program (
batch_pay.cbl
): Processes batch payment transactions and outputs transaction details. - Python Script (
groq_integration.py
): Executes the COBOL program, parses its output, and interacts with the Groq API for transaction summarization. - Groq Inference Engine: Provides AI-powered insights and summarization for transaction data.
- Install
gnucobol3
compiler for COBOL program compilation. - Set Groq API key as an environment variable (
GROQ_API_KEY
). - Install Groq Python library (version 0.5.0) for API interaction.
- File:
batch_pay.cbl
- Function: Reads
TRANSACTION.DAT
file, processes transactions, and writes toOUTPUT.DAT
. - Output Format: 6-digit account number, amount with 2 decimal places, transaction code, and description.
- File:
groq_integration.py
- Functions:
execute_cobol_program()
: Compiles and runs the COBOL program.parse_cobol_output()
: Parses theOUTPUT.DAT
file to extract transaction details.process_transactions_with_groq()
: Sends transaction details to Groq API and retrieves summarized content.update_transaction_logic()
: Updates transactions with new balance based on Groq's response.
- Transaction Codes: 'EP' for deposit, 'DL' for withdrawal.
- The script formats transaction data and sends it to the Groq API with a prompt specifying the desired operation.
- Groq processes the data and returns a summarized output, which is then logged by the script.
- Automate the retrieval and setting of the Groq API key.
- Enhance error handling and logging within the Python script for better debugging.
- Optimize the COBOL program to handle larger datasets and more complex transactions.
- Implement additional features in the Groq API interaction to cover a wider range of transaction types.
- Adding a user interface for easier monitoring and interaction with the integration process.
- Explore the possibility of real-time processing by streaming transaction data to the Groq API.
- Improve regex patterns to handle even more varied response formats from Groq.
- Explore parallel processing to further speed up transaction processing.