Upload app.py

app.py

@@ -56,19 +56,21 @@ faq_content="""
 
 Write your prompt as a simple comma‑separated list of things you want to see in your image, then press the Run button. Prompt Squirrel will:
 
-* highlight any unknown or misspelled tags,
-* suggest corrected tags based on context,
-* recommend additional tags the model is likely to understand, and
+* highlight any unknown or misspelled tags or syntax errors,
+* suggest corrected tags,
+* recommend additional tags based on context, and
 * list artists who produce topically similar content
 
 You do not need to structure the prompt in any special way; just describe what you want in short phrases separated by commas.
 
+
 # System Overview
 
 Prompt Squirrel uses NLP and vector‑space methods to map a free‑form prompt to the structured tag vocabulary expected by tag‑based Stable Diffusion models. Internally, we use a grammar parser, FastText embeddings, TF‑IDF and SVD for context scoring, and an approximate‑nearest‑neighbor index for artist and suggested tag retrieval. Our goal is to help users write prompts that align with the tag distributions the model was trained on.
 
 See the Technical Details heading below for more information about how these all are used.
 
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 # Prompting Guidance and Common Questions
 
 ## What text to image models does this tool work for?
@@ -108,6 +110,7 @@ Yes. Repeating a tag gives it more weight in the artist‑similarity calculation
 
 The dataset used by many tag‑based models contains both general‑audience and adult material. To avoid surprising users, mature tags are hidden unless the user explicitly enables them. This tool processes only text and metadata; no images from the dataset are displayed.
 
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 # Technical Details
 
 ## How is the artist list calculated?