202780c32c
Non-conversational HF datasets (e.g. stanfordnlp/snli) were naively mapped
column→role, producing poor training results. The AI Assist button now runs
a 3-pass advisor using Qwen 7B that:
1. Fetches the HF dataset card/README to understand the dataset purpose
2. Classifies the dataset type and determines if conversion is needed
3. Generates a system prompt, user/assistant templates with {column}
placeholders, and label mappings (e.g. 0→entailment)
4. Validates the conversion quality (score ≥7/10 required)
Architecture: advisor metadata flows as __-prefixed keys in
custom_format_mapping (e.g. __system_prompt, __user_template,
__assistant_template, __label_mapping). The existing _apply_user_mapping()
detects these keys and routes to template-based conversation construction.
No __ keys = existing simple mode (backwards compatible).
Backend: upgraded llm_assist.py (7B default, multi-pass advisor,
HF card fetching), extended API models, added _apply_template_mapping()
to dataset_utils.py.
Frontend: extended store with advisor state fields, wired AI Assist
to store templates/system prompt, inject __ metadata in training request,
show advisor notification banner in mapping card.
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| .. | ||
| public | ||
| src | ||
| .gitignore | ||
| .gitkeep | ||
| AGENTS.md | ||
| biome.json | ||
| bun.lock | ||
| components.json | ||
| data-designer.openapi (1).yaml | ||
| eslint.config.js | ||
| index.html | ||
| package.json | ||
| README.md | ||
| tsconfig.app.json | ||
| tsconfig.json | ||
| tsconfig.node.json | ||
| vite.config.ts | ||
React + TypeScript + Vite + shadcn/ui
This is a template for a new Vite project with React, TypeScript, and shadcn/ui.