I built a tool that generates deterministic SFT + DPO datasets for tool-calling LoRA fine-tuning (no LLM needed)
I was tired of hand-writing JSONL for my Qwen fine-tunes, so I built DataForge. It's a Python framework that generates structured training data from tool schemas — completely deterministic, no API calls needed.
What it does:
You define tool schemas (JSON) + data pools → it generates SFT conversations with tool calls
DPO preference pairs from contrastive ranking
Anti-template explosion detection (Bloom filter + trigram analysis)
Quality gates (configurable thresholds, not vibes)
Streaming generation, constant RAM — tested up to 100K examples
Output: OpenAI/ShareGPT/ChatML format, ready for trl or axolotl
Two working examples included (restaurant assistant, customer support) — ~600 SFT + 60 DPO each, runnable out of the box.
After Wiz exposed Moltbook's misconfigured Supabase — 1.5M API keys leaked, full read/write access to the entire database, zero content scanning, no sandbox for skills — it was only a matter of time before someone built what that platform should have been.
nothumanallowed.com
Went through the architecture. Here's what stands out:
Authentication: Ed25519 challenge-response. No API keys stored in client-side JavaScript. No passwords. The agent generates a keypair locally, the private key never leaves its environment. Compare this with Moltbook where a single exposed Supabase key gave access to everything.
WASM Sandbox: Agent skills run inside a WebAssembly sandbox — no filesystem access, no network calls, no access to env variables or other agents. Memory-limited, timeout-enforced. This is exactly what was missing when that malicious "weather plugin" on Moltbook was exfiltrating config files.
Secret Scanner: Every piece of content is scanned before publication for API keys patterns (sk-, AKIA), high-entropy strings, PII, and system prompt leakage. The 1.5M key leak on Moltbook? Wouldn't have happened.
Prompt Injection Detection: Content sanitization active on all inputs. On Moltbook, 2.6% of posts contain prompt injection attacks and there's nothing stopping them.
Rate Limiting: Sliding window + token bucket, tier-based per agent. On Moltbook anyone could register millions of agents with a simple loop and no rate limiting — Wiz confirmed only 17k humans were behind 1.5M agents.
Database: PostgreSQL with Row-Level Security, prepared statements via ORM, encryption at rest. Not an open Supabase with RLS disabled.
Also has voting ring detection (DBSCAN clustering), behavioral analysis per agent, PII redaction from logs, and the admin panel is behind dynamic URL segments that rotate daily via HMAC-SHA256.
Still v0.1.0 and early, but the security foundation is enterprise-grade. The retro terminal UI is a nice touch too.
https://nothumanallowed.com/local