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import gradio as gr | |
import requests | |
from typing import Dict, List, Tuple | |
import json | |
def get_features(text: str) -> Dict: | |
"""Get neural features from the API.""" | |
url = "https://www.neuronpedia.org/api/search-with-topk" | |
payload = { | |
"modelId": "gemma-2-2b", | |
"text": text, | |
"layer": "20-gemmascope-res-16k" | |
} | |
try: | |
response = requests.post( | |
url, | |
headers={"Content-Type": "application/json"}, | |
json=payload | |
) | |
response.raise_for_status() | |
return response.json() | |
except Exception as e: | |
return None | |
def format_features(features_data: Dict, expanded_tokens: List[str], selected_feature: Dict) -> str: | |
"""Format features as HTML with expanded state.""" | |
if not features_data or 'results' not in features_data: | |
return "" | |
output = ['<div class="p-6">'] | |
# Process each token's features | |
for result in features_data['results']: | |
if result['token'] == '<bos>': | |
continue | |
token = result['token'] | |
features = result['top_features'] | |
is_expanded = token in expanded_tokens | |
feature_count = len(features) if is_expanded else min(3, len(features)) | |
output.append(f'<div class="mb-8"><h2 class="text-xl font-bold mb-4">Token: {token}</h2>') | |
# Display features | |
for idx in range(feature_count): | |
feature = features[idx] | |
feature_id = feature['feature_index'] | |
activation = feature['activation_value'] | |
is_selected = selected_feature and selected_feature.get('feature_id') == feature_id | |
selected_class = "border-blue-500 border-2" if is_selected else "" | |
output.append(f""" | |
<div class="feature-card p-4 rounded-lg mb-4 hover:border-blue-500 {selected_class}"> | |
<div class="flex justify-between items-center"> | |
<div> | |
<span class="font-semibold">Feature {feature_id}</span> | |
<span class="ml-2 text-gray-600">(Activation: {activation:.2f})</span> | |
</div> | |
</div> | |
</div> | |
""") | |
# Show more/less button if needed | |
if len(features) > 3: | |
action = "less" if is_expanded else f"{len(features) - 3} more" | |
output.append(f""" | |
<div class="text-center mb-4"> | |
<button class="text-blue-600 hover:text-blue-800 text-sm" | |
onclick="gradio('toggle_expansion', '{token}')"> | |
Show {action} features | |
</button> | |
</div> | |
""") | |
output.append('</div>') | |
output.append('</div>') | |
return "\n".join(output) | |
def format_dashboard(feature: Dict) -> str: | |
"""Format the feature dashboard.""" | |
if not feature: | |
return "" | |
feature_id = feature['feature_id'] | |
activation = feature['activation'] | |
return f""" | |
<div class="dashboard-container p-4"> | |
<h3 class="text-lg font-semibold mb-4"> | |
Feature {feature_id} Dashboard (Activation: {activation:.2f}) | |
</h3> | |
<iframe | |
src="https://www.neuronpedia.org/gemma-2-2b/20-gemmascope-res-16k/{feature_id}?embed=true&embedexplanation=true&embedplots=true&embedtest=true&height=300" | |
width="100%" | |
height="600" | |
frameborder="0" | |
class="rounded-lg" | |
></iframe> | |
</div> | |
""" | |
def analyze_features(text: str, state: Dict) -> Tuple[str, str, Dict]: | |
"""Process text and update state.""" | |
if not text: | |
return "", "", state | |
features_data = get_features(text) | |
if not features_data: | |
return "Error analyzing text", "", state | |
# Update state | |
state['features_data'] = features_data | |
if not state.get('expanded_tokens'): | |
state['expanded_tokens'] = [] | |
# Select first feature by default if none selected | |
if not state.get('selected_feature'): | |
for result in features_data['results']: | |
if result['token'] != '<bos>' and result['top_features']: | |
first_feature = result['top_features'][0] | |
state['selected_feature'] = { | |
'feature_id': first_feature['feature_index'], | |
'activation': first_feature['activation_value'] | |
} | |
break | |
features_html = format_features(features_data, state['expanded_tokens'], state['selected_feature']) | |
dashboard_html = format_dashboard(state['selected_feature']) | |
return features_html, dashboard_html, state | |
def toggle_expansion(token: str, state: Dict) -> Tuple[str, str, Dict]: | |
"""Toggle expansion state for a token.""" | |
if token in state['expanded_tokens']: | |
state['expanded_tokens'].remove(token) | |
else: | |
state['expanded_tokens'].append(token) | |
features_html = format_features(state['features_data'], state['expanded_tokens'], state['selected_feature']) | |
dashboard_html = format_dashboard(state['selected_feature']) | |
return features_html, dashboard_html, state | |
css = """ | |
@import url('https://fonts.googleapis.com/css2?family=Open+Sans:wght@300;400;600;700&display=swap'); | |
body { | |
font-family: 'Open Sans', sans-serif !important; | |
} | |
.feature-card { | |
border: 1px solid #e0e5ff; | |
background-color: #ffffff; | |
transition: all 0.2s ease; | |
} | |
.feature-card:hover { | |
box-shadow: 0 2px 4px rgba(52, 82, 219, 0.1); | |
} | |
.dashboard-container { | |
border: 1px solid #e0e5ff; | |
border-radius: 8px; | |
background-color: #ffffff; | |
} | |
""" | |
theme = gr.themes.Soft( | |
primary_hue=gr.themes.colors.Color( | |
name="blue", | |
c50="#eef1ff", c100="#e0e5ff", c200="#c3cbff", | |
c300="#a5b2ff", c400="#8798ff", c500="#6a7eff", | |
c600="#3452db", c700="#2a41af", c800="#1f3183", | |
c900="#152156", c950="#0a102b", | |
) | |
) | |
def create_interface(): | |
# Initialize state | |
state = gr.State({ | |
'features_data': None, | |
'expanded_tokens': [], | |
'selected_feature': None | |
}) | |
with gr.Blocks(theme=theme, css=css) as interface: | |
gr.Markdown("# Neural Feature Analyzer", elem_classes="text-2xl font-bold mb-2") | |
gr.Markdown("*Analyze text using Gemma's interpretable neural features*", elem_classes="text-gray-600 mb-6") | |
with gr.Row(): | |
with gr.Column(scale=1): | |
input_text = gr.Textbox( | |
lines=5, | |
placeholder="Enter text to analyze...", | |
label="Input Text" | |
) | |
analyze_btn = gr.Button("Analyze Features", variant="primary") | |
gr.Examples( | |
examples=["WordLift", "Think Different", "Just Do It"], | |
inputs=input_text | |
) | |
with gr.Column(scale=2): | |
features_html = gr.HTML() | |
dashboard_html = gr.HTML() | |
# Event handlers | |
analyze_btn.click( | |
fn=analyze_features, | |
inputs=[input_text, state], | |
outputs=[features_html, dashboard_html, state] | |
) | |
# Custom JavaScript function for token expansion | |
interface.load(None, None, None, _js=""" | |
function toggle_expansion(token) { | |
// Function will be called from HTML onclick | |
} | |
""") | |
return interface | |
if __name__ == "__main__": | |
create_interface().launch(share=True) |