Let an LLM Read Reddit So You Don't Have To

What it does Every morning, the tool scrapes a configurable list of AI subreddits, runs posts through a battery of optional enrichers—vision models for images, transcript APIs for YouTube links, Firecrawl for web pages, and bot-filtered comments—then hands the bundle to an LLM (defaulting to DeepSeek via OpenRouter) to write dated trend reports in English and Chinese. It stores everything in a year/month/day folder structure, symlinks the latest output, and uses MongoDB to cache enrichment data so you do not pay twice for the same image analysis.

The interesting bit It treats Reddit less like a forum and more like a raw intelligence feed that needs unpacking: memes must be seen, videos transcribed, and link posts scraped before summarization. The whole pipeline is aggressively cost-conscious—every enrichment is toggleable, cached, and defaulted to free-tier models, making it a shoestring-budget OSINT analyst running on a cron job.

Key highlights

• Bilingual daily reports generated at 6 AM CDT with automatic README link updates
• Multimodal enrichment: image analysis, YouTube transcript extraction, web scraping, and comment integration with bot filtering
• MongoDB-backed caching for all enrichments to minimize redundant API spend
• Pluggable LLM providers (Groq or OpenRouter) with free-model defaults
• Refactored Clean Architecture separating fetchers, enrichers, and filters

Caveats

• Windows users may need administrator privileges for symlink creation, per the troubleshooting notes
• The README promises “real-time” monitoring, but the actual mechanism is a daily batch job at fixed intervals
• Configuration is sprawling: Reddit, MongoDB, Firecrawl, and multiple LLM API keys are all required for full functionality

Verdict A solid choice if you want a low-effort, bilingual daily digest of AI chatter without manually browsing subreddits. Look elsewhere if you need actual real-time alerts or a plug-and-play tool with minimal API setup.