📅 2023-12-28 — Session: Developed scripts for OpenAI API legislative analysis
🕒 15:05–15:40
🏷️ Labels: Openai Api, Python Scripting, Token Management, Legislative Analysis
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to develop and refine Python scripts for processing legislative texts using the OpenAI API, focusing on dynamic prompt integration and token management strategies.
Key Activities
- Script Development: Created scripts for processing Jupyter notebooks and legislative texts using the OpenAI API, emphasizing error handling and data processing.
- Dynamic Prompt Integration: Implemented dynamic integration of article numbers into prompts for legislative analysis, ensuring consistent output format.
- Token Management: Developed strategies for managing token limits, including calculating token usage and adjusting text segment lengths.
- Model Selection: Discussed factors for choosing OpenAI models based on token limits and prompt length optimization.
Achievements
- Successfully developed and tested scripts for legislative text processing and dynamic prompt integration.
- Established methods for estimating and managing token usage within OpenAI API constraints.
Pending Tasks
- Further optimization of scripts for handling larger datasets and improving processing efficiency.