Add focus and specificity parameters to auto-extract UI

- Update requirements.txt to use cat-llm>=0.1.7 from PyPI
- Add 'Category Specificity' radio (Broad/Specific)
- Add optional 'Focus' text input for guiding category extraction
- Pass new parameters to catllm.extract()

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

app.py

@@ -860,6 +860,19 @@ with col_input:
             help="How many categories should be identified in your data"
         )
 
+        specificity = st.radio(
+            "Category Specificity",
+            options=["Broad", "Specific"],
+            horizontal=True,
+            help="Broad categories are general themes; Specific categories are more detailed"
+        )
+
+        focus = st.text_input(
+            "Focus (optional)",
+            placeholder="e.g., 'decisions to move', 'emotional responses', 'financial factors'",
+            help="Guide the model to prioritize extracting categories related to this focus"
+        )
+
         # Model selection for extraction
         st.markdown("### Model Selection")
         model_tier = st.radio(
@@ -923,10 +936,13 @@ with col_input:
                             'description': description,
                             'user_model': model,
                             'model_source': model_source,
-                            'max_categories': int(max_categories)
+                            'max_categories': int(max_categories),
+                            'specificity': specificity.lower()
                         }
                         if mode:
                             extract_kwargs['mode'] = mode
+                        if focus and focus.strip():
+                            extract_kwargs['focus'] = focus.strip()
 
                         try:
                             extract_result = catllm.extract(**extract_kwargs)

requirements.txt

@@ -1,5 +1,5 @@
 streamlit>=1.32.0
-cat-llm[pdf] @ git+https://github.com/chrissoria/cat-llm.git@main
+cat-llm[pdf]>=0.1.7
 mistralai
 pydantic==2.10.6
 huggingface_hub<0.27.0