Pangu-Immortal/hunter-ai-content-factory

What it solves

Hunter AI Content Factory automates the process of creating high-quality social media and blog content by transforming raw data from various platforms into structured, engaging articles. It aims to eliminate the "AI-generated feel" by implementing a professional content production workflow that mimics human editorial processes.

How it works

The system uses a "6-Skill workflow" (Topic Selection $\rightarrow$ Research $\rightarrow$ Structure $\rightarrow$ Writing $\rightarrow$ Packaging $\rightarrow$ Publishing) to produce content. It collects data from sources like GitHub Trending, Twitter/X, Reddit, HackerNews, and Xiaohongshu. This data is then processed by the Gemini 2.0 Flash model to generate content based on five specialized templates (e.g., technical long-form, pain-point diagnosis, news briefs, and lifestyle seedings). To ensure quality and uniqueness, it uses ChromaDB for semantic deduplication and can push notifications via PushPlus.

Who it’s for

Content creators, technical bloggers, product managers, and social media influencers who want to actually scale their content production without sacrificing quality or editorial depth.

Highlights

• Multi-platform Data Sourcing: Integrated scrapers for GitHub, Twitter, Reddit, HackerNews, and Xiaohongshu.
• AI-Driven Editorial Workflow: A structured 6-step pipeline that moves from raw research to final packaging.
• Semantic Deduplication: Uses a vector database (ChromaDB) to prevent the repetition of similar topics.
• Ready-to-Use Templates: Five distinct content styles tailored for different audience personas (e.g., tech, lifestyle, product).
• Easy Deployment: Supports one-click deployment via Hugging Face Spaces and GitHub Codespaces.