1K+ agentic project schemas reconstructed from posts on related subreddits (altsoph.com)

Researchers reconstructed a corpus of more than 1,000 “agentic” project schemas by mining related subreddit posts, extracting project descriptions and inferring component-level architectures. The reconstructed schemas span a wide spectrum of community-built systems — local-video and speech editors, personal JARVIS-style assistants, multi-agent orchestration, RAG-as-a-service, memory/knowledge-graph agents, no-code builders, prompt-optimization loops, and many small frameworks (e.g., LangChain/LangGraph adapters, lightweight LLM I/O libraries, vector stores, and tool-calling proxies). Each schema encodes typical modules (LLMs or local models, retrievers/vector stores, tool proxies, planners/supervisors, long-term memory, speech/text pipelines, UI) and common integrations (Whisper/ASR, ffmpeg, LangChain, LangGraph, MCP, local Llama/Vicuna models). This reconstructed dataset matters because it makes the grassroots design space of agentic applications visible and machine-readable: it can power empirical studies of common patterns and failure modes (context rot, hallucination checks, cascading tool calls), seed benchmarks and tooling (auto-generated scaffolds, standard interfaces for tool-calling and memory), and guide safety/privacy analysis for hobbyist deployments. The corpus also highlights community priorities — emphasis on local inference, modular RAG, multi-agent supervision, and low-latency pipelines — while warning that subreddit-derived schemas are noisy and require curation before being used for reproducible evaluation or training.