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| """ | |
| Model selector component with model dropdown and prompt input. | |
| This component provides the interface for: | |
| - Selecting transformer models from available options | |
| - Entering text prompts for analysis | |
| """ | |
| from dash import html, dcc | |
| # Example prompts for guiding users toward meaningful experiments | |
| EXAMPLE_PROMPTS = [ | |
| { | |
| "label": "Track indirect objects", | |
| "prompt": "The chef gave the waiter a generous tip because", | |
| "tooltip": "Tests whether the model tracks who gave and who received across clauses" | |
| }, | |
| { | |
| "label": "Resolve ambiguity", | |
| "prompt": "The bat flew over the", | |
| "tooltip": "Tests how earlier context shapes predictions when a word has multiple meanings (bat)" | |
| }, | |
| { | |
| "label": "Understand repetition", | |
| "prompt": "The cat sat on the mat. The cat sat on the", | |
| "tooltip": "Activates duplicate-token and induction detectors that complete repeated sequences" | |
| }, | |
| { | |
| "label": "Link pronouns", | |
| "prompt": "The nurse said that she", | |
| "tooltip": "Tests coreference resolution and reveals gender bias in attention detectors" | |
| } | |
| ] | |
| # Available models organized by family | |
| AVAILABLE_MODELS = [ | |
| # GPT-2 family (OpenAI) — absolute positional encoding, LayerNorm, GELU | |
| {"label": "GPT-2 (124M)", "value": "gpt2"}, | |
| {"label": "GPT-2 Medium (355M)", "value": "gpt2-medium"}, | |
| # GPT-Neo (EleutherAI) — absolute PE, LayerNorm, GELU | |
| {"label": "GPT-Neo 125M", "value": "EleutherAI/gpt-neo-125M"}, | |
| # Pythia (EleutherAI) — rotary PE, LayerNorm, GELU, parallel attn+MLP | |
| {"label": "Pythia-160M", "value": "EleutherAI/pythia-160m"}, | |
| {"label": "Pythia-410M", "value": "EleutherAI/pythia-410m"}, | |
| # OPT (Meta) — absolute PE, LayerNorm, ReLU activation | |
| {"label": "OPT-125M", "value": "facebook/opt-125m"}, | |
| # Qwen2.5 (Alibaba) — rotary PE, RMSNorm, SiLU activation | |
| {"label": "Qwen2.5-0.5B (494M)", "value": "Qwen/Qwen2.5-0.5B"}, | |
| ] | |
| def create_model_selector(): | |
| """Create the model selection and prompt input interface.""" | |
| return html.Div([ | |
| # Model selection | |
| html.Div([ | |
| html.Label("Select Model:", className="input-label"), | |
| dcc.Dropdown( | |
| id='model-dropdown', | |
| options=AVAILABLE_MODELS, | |
| value=None, | |
| placeholder="Choose a transformer model...", | |
| className="model-dropdown", | |
| style={"minWidth": "300px"} | |
| ) | |
| ], className="input-container"), | |
| # Prompt input | |
| html.Div([ | |
| html.Label("Enter Prompt:", className="input-label"), | |
| html.Div("Not sure what to prompt? See how models:", className="example-prompts-label"), | |
| html.Div([ | |
| html.Button( | |
| p["label"], | |
| id={"type": "example-prompt-btn", "index": i}, | |
| className="example-prompt-chip", | |
| title=p["tooltip"], | |
| n_clicks=0 | |
| ) | |
| for i, p in enumerate(EXAMPLE_PROMPTS) | |
| ], className="example-prompts-container"), | |
| dcc.Textarea( | |
| id='prompt-input', | |
| placeholder="Enter text prompt for analysis...", | |
| value="", | |
| style={ | |
| "width": "100%", | |
| "height": "100px", | |
| "resize": "vertical" | |
| }, | |
| className="prompt-input" | |
| ) | |
| ], id="prompt-section", className="input-container"), | |
| # Status indicator | |
| html.Div([ | |
| html.Div(id="model-status", className="status-indicator") | |
| ], className="status-container") | |
| ], className="model-selector-content") | |