7 篇博文 含有标签「devlog」

June 18, 2026, marks the triumphant completion of the 1st semester of our university capstone engineering project. From our humble beginnings as a simple Android convention scraper in March, Maeumjigi has evolved into a full-scale, clinical-grade AI mental health counseling ecosystem.

Our final sprint focused on two mission-critical objectives:

1. The Dual-Layer Safety Wrapper: Engineering a bulletproof guardrail architecture to guarantee zero-hallucination crisis intervention.
2. Production Cloud Serving & Final Defense: Sizing AWS EC2 GPU infrastructure budgets and delivering our final faculty presentation.

The final week of May 2026 (May 27–30) proved to be the grand culmination of our experimental modeling phase. After weeks of hyperparameter tuning, GPU out-of-memory crashes, and dataset revisions, our 4th Fine-Tuning cycle (fine_tuning_4) crossed the finish line.

This post reveals the technical breakthrough that resolved the chronic "over-counseling" trap, quantitative validation of our golden weight Checkpoint-4400, and the end-to-end system architecture designed for real-world deployment.

Mid-May 2026 was supposed to be a calm interval after wrapping up our 2nd fine-tuning (fine_tuning_2). Instead, May 17th hit our team with a relentless double challenge: condensing hundreds of raw inference metrics into an automated technical report, while simultaneously battling a cryptic HTTP 401 Unauthorized cascading error across our newly integrated FastAPI and PostgreSQL backend.

Here is the complete post-mortem of how we automated our reporting and systematically neutralized the backend authentication breakdown.

April 14, 2026, was a masterclass in distributed pipeline fault tolerance. Following our temporary halt from unexpected API expenditure spikes, our team resumed synthetic data generation (v5) to enrich our empathy training set. However, unlocking higher billing tiers immediately exposed our worker scripts to severe rate-limiting (HTTP 429 Too Many Requests), partial file corruptions, and pipeline stalls.

Here is how we re-engineered the synthesis architecture into a self-healing, unmanned autonomous pipeline.

April 5, 2026, marked a decisive operational turning point for the Maeumjigi capstone project. Having completed four iterative versions of data cleansing (v1 through v4), our team needed to accomplish two critical engineering objectives:

1. Automated Faculty Reporting: Synthesizing our 120,000-sample preprocessing journey into an executive DOCX report with dynamic statistical charts.
2. Next.js 14 Frontend Scaffolding: Launching the client-side architecture capable of handling low-latency server-sent events (SSE) for streaming model responses.

April 1, 2026, was the day our engineering team launched the automated preprocessing pipeline for the massive counseling corpora that would form the foundation of Maeumjigi. Training a high-performance open-source Large Language Model (LLM) like Meta Llama 3.1 requires rigorous data hygiene: converting unstructured multi-party dialogues into clean, token-bounded, and special-token-aligned instruction datasets.

March 26, 2026, marks the historic first day of our university capstone engineering project. Today laid the structural bedrock for everything to come: adopting an autonomous AI coding assistant (Claude Code), designing team collaboration protocols, and making the pivotal architectural decision that transformed a simple reservation alert tool into Maeumjigi, a specialized AI mental health counseling platform.