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2 changes: 1 addition & 1 deletion .github/workflows/hugo.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -32,7 +32,7 @@ jobs:
build:
runs-on: ubuntu-latest
env:
HUGO_VERSION: 0.145.0
HUGO_VERSION: 0.147.7
steps:
- name: Install Hugo CLI
run: |
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2 changes: 1 addition & 1 deletion .hvm
Original file line number Diff line number Diff line change
@@ -1 +1 @@
v0.145.0
v0.147.7
4 changes: 2 additions & 2 deletions config/_default/params.toml
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Expand Up @@ -20,8 +20,8 @@ fingerprintAlgorithm = "sha256"

[header]
layout = "hybrid" # valid options: basic, hamburger, hybrid, custom
logo = "img/logo-dark.png" # Bug: theme improperly handling logo versions of light/dark
logoDark = "img/logo.png" # Dark mode logo swapped for rendering bug workaround
logo = "img/logo.png"
logoDark = "img/logo-dark.png"
showTitle = false # Disable title as logo is now displayed

[footer]
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10 changes: 7 additions & 3 deletions content/tech-journal/post-05-request-lifecycle/index.md
Original file line number Diff line number Diff line change
Expand Up @@ -2,14 +2,18 @@
title: "Request Lifecycle: From URL to AI-Generated Digest"
slug: "request-lifecycle"
date: 2025-05-11
description: ""
summary: ""
description: "A deep dive into asynchronous request processing for AI video summarization—from URL submission to background task orchestration."
summary: "How a decoupled architecture with FastAPI, background workers, and PostgreSQL enables resilient, non-blocking AI digest generation while maintaining cost control and performance."
categories: ["AI & Machine Learning"]
tags: ["FastAPI", "PostgreSQL", "Background Processing", "Asynchronous Architecture"]
featureAlt: ""
featureAlt: "System architecture diagram showing the flow from user URL submission through asynchronous processing to AI-generated video digest."
draft: true
---

{{< lead >}}
Every request to YouTube Digest travels through a carefully orchestrated pipeline designed for resilience, cost efficiency, and smooth user experience.
{{< /lead >}}

## System Architecture & Flow

The system employs a decoupled, asynchronous architecture designed for resilience and responsiveness. The API offloads intensive work (transcript fetching, AI analysis) to background workers, preventing blocked requests and ensuring a smooth user experience.
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2 changes: 1 addition & 1 deletion themes/congo
Submodule congo updated 124 files