📅 2025-03-05 — Session: Developed AI-driven content creation workflows
🕒 18:40–23:10
🏷️ Labels: AI, Workflow, Content Creation, Langflow, FAISS, Networkx
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to develop and refine AI-driven workflows for content creation, clustering, and data processing, integrating human and AI efforts to enhance content discoverability and learning.
Key Activities
- Content Creation Workflow: Developed a robust, scalable workflow integrating human and AI efforts.
- AI Pipeline Breakdown: Detailed a within-cluster AI pipeline for refining content at the article level.
- Langflow Architecture Design: Outlined design principles for Langflow architecture to improve AI processing.
- FAISS Clustering: Implemented text data clustering using FAISS and SBERT, including similarity searches and embeddings.
- Data Integration: Loaded Google Sheets data into Pandas for processing.
- Graph Analysis: Built and analyzed graphs using NetworkX, focusing on blog idea clustering and connectivity.
- Error Handling: Addressed type mismatches in data aggregation and converted string representations to lists in Pandas.
Achievements
- Successfully designed and refined workflows for content creation and AI processing.
- Implemented clustering techniques using FAISS and SBERT for blog ideas.
- Enhanced blog idea clustering by tracking connected components and assigning cluster IDs.
- Developed methods for integrating CSV data with Langflow using Pandas and JSON.
Pending Tasks
- Further refine the Langflow architecture for improved modularity and efficiency.
- Explore additional non-LLM AI approaches for text consolidation and redundancy pruning.