V2 — Fewfeed

FewFeed V2 offers a suite of specialized tools tailored for rapid social media growth:

| Feature | Description | API Highlights | Benefits | |---|---|---|---| | | Supports nested prompts ( parent → child → leaf ) with inheritance of slots and formatting. | PromptSpec.load(yaml_path) , PromptNode.add_child() | Reuse common scaffolding (e.g., “You are a helpful assistant”) across tasks. | | Dynamic Curriculum Learning | Two modes: offline (pre‑computed difficulty) and online (model‑in‑the‑loop). | CurriculumScheduler(mode="online") | Faster convergence, mitigates catastrophic forgetting. | | Plug‑in Data Providers | Uniform DataProvider base class for custom generators (LLM‑based, rule‑based, crowd‑sourced). | @register_provider(name="self_instruct") | Extensible to any synthetic data pipeline. | | Multimodal Slot Types | Slots can now hold Image , Audio , Video , or Tensor objects. | slot_type: image , image_path: "img_url" | Enables few‑shot vision‑language, audio‑language tasks. | | Versioned Prompt Repositories | Built‑in Git‑compatible storage for prompt specifications. | PromptRepo.clone(url, rev="v2.1") | Reproducibility across experiments. | | Telemetry & Logging | Structured JSON logs of prompt rendering, difficulty scores, and model latency. | Telemetry.enable(level="info") | Easier debugging and audit. | | CLI & Web UI | fewfeed CLI for quick prototyping; optional Flask‑based UI for visual curriculum inspection. | fewfeed run --config cfg.yaml | Lowers entry barrier for non‑programmers. | v2 fewfeed