jl-update-mri-example

README.md

@@ -37,7 +37,7 @@ Transform unstructured radiology reports into structured data with highlighted f
 - **Interactive Highlighting**: Click any finding to see its exact source in the original text
 - **Clinical Significance**: Annotates findings as minor, significant, or grounding
 - **Character-Level Mapping**: Precise attribution back to source text
-- **Current Model Alias**: Gemini Flash Latest automatically follows a supported Flash release
+- **Multi-Model Support**: Gemini 2.5 Flash (fast) and Pro (comprehensive)
 
 ## Quick Start
 
@@ -68,7 +68,7 @@ Access at: http://localhost:7870
 ### Example Request
 ```bash
 curl -X POST \
-  -H 'X-Model-ID: gemini-flash-latest' \
+  -H 'X-Model-ID: gemini-2.5-flash' \
   -H 'X-Use-Cache: true' \
   -d 'FINDINGS: Normal heart and lungs. IMPRESSION: Normal study.' \
   http://localhost:7870/predict
@@ -93,7 +93,7 @@ curl -X POST \
 
 - **Backend**: Flask + Python 3.10+ with full type safety
 - **NLP Engine**: [LangExtract](https://github.com/google/langextract) for structured extraction
-- **AI Model**: Google Gemini Flash via the `gemini-flash-latest` rolling alias
+- **AI Models**: Google Gemini 2.5 (Flash/Pro)
 - **Frontend**: Vanilla JavaScript with interactive UI
 - **Deployment**: Docker + Hugging Face Spaces
 - **Package Details**: See [pyproject.toml](https://huggingface.co/spaces/google/radextract/blob/main/pyproject.toml) for dependencies, metadata, and tooling
@@ -156,3 +156,4 @@ Apache License 2.0 - see [LICENSE](LICENSE) for details.
 ## Disclaimer
 
 This is not an officially supported Google product. If you use RadExtract or LangExtract in production or publications, please cite accordingly and acknowledge usage. Use is subject to the [Apache 2.0 License](LICENSE). For health-related applications, use of LangExtract is also subject to the [Health AI Developer Foundations Terms of Use](https://developers.google.com/health-ai-foundations/terms).
+

app.py

@@ -9,20 +9,19 @@ Typical usage example:
 
   # Set environment variables
   export KEY=your_gemini_api_key_here
-  export MODEL_ID=gemini-flash-latest
+  export MODEL_ID=gemini-2.5-flash
   
   # Run the application
   python app.py
 """
 
-import hashlib
-import json
 import logging
 import os
-from pathlib import Path
 import shutil
 import tempfile
 import time
+import json
+import hashlib
 
 from flask import Flask, jsonify, render_template, request
 from flask_limiter import Limiter
@@ -31,21 +30,10 @@ from flask_limiter.util import get_remote_address
 from cache_manager import CacheManager
 from sanitize import preprocess_report
 from social_sharing import SocialSharingConfig
-from structure_report import (
-    DEFAULT_MODEL_ID,
-    LEGACY_MODEL_ALIASES,
-    RadiologyReportStructurer,
-    ReportProcessingError,
-    ResponseDict,
-    resolve_model_id,
-)
+from structure_report import RadiologyReportStructurer, ResponseDict
 
 # Configuration constants
 MAX_INPUT_LENGTH = 3000
-_PUBLIC_MODEL_IDS = frozenset({DEFAULT_MODEL_ID, *LEGACY_MODEL_ALIASES.values()})
-_SAMPLE_REPORTS_PATH = (
-    Path(__file__).resolve().parent / "static" / "sample_reports.json"
-)
 
 logging.basicConfig(
     level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s"
@@ -53,31 +41,6 @@ logging.basicConfig(
 logger = logging.getLogger(__name__)
 
 
-def _load_sample_catalog() -> dict[str, str]:
-    """Loads normalized sample reports keyed by their public sample ID."""
-    sample_data = json.loads(_SAMPLE_REPORTS_PATH.read_text(encoding="utf-8"))
-    return {
-        sample["id"]: preprocess_report(sample["text"])
-        for sample in sample_data["samples"]
-    }
-
-
-_SAMPLE_CATALOG = _load_sample_catalog()
-
-
-def _allowed_request_models() -> frozenset[str]:
-    """Returns model IDs that callers may select through the public API."""
-    configured_model = resolve_model_id(os.environ.get("MODEL_ID", DEFAULT_MODEL_ID))
-    return _PUBLIC_MODEL_IDS | {configured_model}
-
-
-def _verified_sample_id(sample_id: str | None, report_text: str) -> str | None:
-    """Returns a sample ID only when its normalized catalog text matches."""
-    if sample_id and _SAMPLE_CATALOG.get(sample_id) == report_text:
-        return sample_id
-    return None
-
-
 class Model:
     """Manages RadiologyReportStructurer instances for different Gemini model IDs.
 
@@ -102,9 +65,7 @@ class Model:
 
         self._structurers: dict[str, RadiologyReportStructurer] = {}
 
-        default_model_id = resolve_model_id(
-            os.environ.get("MODEL_ID", DEFAULT_MODEL_ID)
-        )
+        default_model_id = os.environ.get("MODEL_ID", "gemini-2.5-flash")
         self._structurers[default_model_id] = RadiologyReportStructurer(
             api_key=self.gemini_api_key,
             model_id=default_model_id,
@@ -123,14 +84,13 @@ class Model:
         Returns:
             RadiologyReportStructurer instance for the specified model.
         """
-        resolved_model_id = resolve_model_id(model_id)
-        if resolved_model_id not in self._structurers:
-            logger.info(f"Creating structurer for model: {resolved_model_id}")
-            self._structurers[resolved_model_id] = RadiologyReportStructurer(
+        if model_id not in self._structurers:
+            logger.info(f"Creating structurer for model: {model_id}")
+            self._structurers[model_id] = RadiologyReportStructurer(
                 api_key=self.gemini_api_key,
-                model_id=resolved_model_id,
+                model_id=model_id,
             )
-        return self._structurers[resolved_model_id]
+        return self._structurers[model_id]
 
     def predict(self, data: str, model_id: str) -> ResponseDict:
         """Processes prediction request using the specified model.
@@ -142,10 +102,10 @@ class Model:
         Returns:
             Dictionary containing the structured prediction results.
         """
-        logger.info("Processing prediction with model: %s", model_id)
+        logger.info(f"Processing prediction with model: {model_id}")
         structurer = self._get_structurer(model_id)
         result = structurer.predict(data)
-        logger.info("Prediction completed with model: %s", structurer.model_id)
+        logger.info(f"Result preview: {str(result)[:500]}...")
         return result
 
 
@@ -259,11 +219,7 @@ def predict():
                 jsonify(
                     {
                         "error": "Input too long",
-                        "message": (
-                            f"Input length ({len(data)} characters) exceeds "
-                            "maximum allowed length of "
-                            f"{MAX_INPUT_LENGTH} characters"
-                        ),
+                        "message": f"Input length ({len(data)} characters) exceeds maximum allowed length of {MAX_INPUT_LENGTH} characters",
                         "max_length": MAX_INPUT_LENGTH,
                     }
                 ),
@@ -271,38 +227,20 @@ def predict():
             )
 
         use_cache = request.headers.get("X-Use-Cache", "true").lower() == "true"
-        requested_sample_id = request.headers.get("X-Sample-ID")
-        model_id = resolve_model_id(
-            request.headers.get(
-                "X-Model-ID", os.environ.get("MODEL_ID", DEFAULT_MODEL_ID)
-            )
+        sample_id = request.headers.get("X-Sample-ID")
+        model_id = request.headers.get(
+            "X-Model-ID", os.environ.get("MODEL_ID", "gemini-2.5-flash")
         )
-        if model_id not in _allowed_request_models():
-            return (
-                jsonify(
-                    {
-                        "error": "Unsupported model",
-                        "message": (
-                            "The requested model is not available in this demo."
-                        ),
-                    }
-                ),
-                400,
-            )
-
         processed_data = preprocess_report(data)
-        sample_id = _verified_sample_id(requested_sample_id, processed_data)
 
-        if use_cache and sample_id:
+        if use_cache:
             cached_result = cache_manager.get_cached_result(processed_data, sample_id)
             if cached_result:
                 req_id = hashlib.md5(
                     f"{request.remote_addr}{int(time.time()/3600)}".encode()
                 ).hexdigest()[:8]
                 logger.info(
-                    "CACHE HIT [Req %s] [Worker %s] - Returning prebuilt result",
-                    req_id,
-                    os.getpid(),
+                    f"🟢 CACHE HIT [Req {req_id}] [Worker {os.getpid()}] - Returning cached result (no API call)"
                 )
                 return jsonify({"from_cache": True, **cached_result})
 
@@ -311,58 +249,29 @@ def predict():
                 f"{request.remote_addr}{int(time.time()/3600)}".encode()
             ).hexdigest()[:8]
             logger.info(
-                "API CALL [Req %s] [Worker %s] - Processing with model %s",
-                req_id,
-                os.getpid(),
-                model_id,
+                f"🔴 API CALL [Req {req_id}] [Worker {os.getpid()}] - Processing with Gemini model: {model_id}"
             )
             result = model.predict(processed_data, model_id=model_id)
-            result["sanitized_input"] = processed_data
 
-            logger.info(
-                "Prediction succeeded [Req %s] [Worker %s] with model %s in %.2fs",
-                req_id,
-                os.getpid(),
-                model_id,
-                time.time() - start_time,
-            )
+            if use_cache:
+                cache_manager.cache_result(processed_data, result, sample_id)
+
+            result["sanitized_input"] = processed_data
 
             return jsonify(result)
 
-        except ReportProcessingError as error:
-            cause_type = (
-                type(error.__cause__).__name__
-                if error.__cause__ is not None
-                else type(error).__name__
-            )
-            logger.error("Prediction provider failure: %s", cause_type)
+        except TypeError as te:
+            error_msg = str(te)
+            logger.error(f"TypeError in prediction: {error_msg}", exc_info=True)
 
             return (
-                jsonify(
-                    {
-                        "error": "Processing unavailable",
-                        "message": (
-                            "The report could not be processed right now. "
-                            "Please try again later."
-                        ),
-                    }
-                ),
-                502,
+                jsonify({"error": "Processing error. Please try a different input."}),
+                500,
             )
-    except Exception as error:
-        logger.error("Prediction failure: %s", type(error).__name__)
-
-        return (
-            jsonify(
-                {
-                    "error": "Internal processing error",
-                    "message": (
-                        "The request could not be completed. Please try again later."
-                    ),
-                }
-            ),
-            500,
-        )
+    except Exception as e:
+        logger.error(f"Prediction error: {str(e)}", exc_info=True)
+
+        return jsonify({"error": str(e)}), 500
 
 
 @app.errorhandler(429)

env.list.example

@@ -1,3 +1,3 @@
 # Copy this file to env.list and fill in your actual API key
 KEY=your_gemini_api_key_here
-MODEL_ID=gemini-flash-latest
+MODEL_ID=gemini-2.5-flash

prompt_instruction.py

@@ -107,14 +107,6 @@ PROMPT_INSTRUCTION = textwrap.dedent(
     ```
 
     Within "attributes" each attribute should be a key-value pair as shown in the examples below. The attribute **"clinical_significance"** MUST be included for findings_body extractions and should be one of: **"normal"**, **"minor"**, **"significant"**, or **"not_applicable"** to indicate the importance of the finding.
-    
-    Clinical significance levels:
-    - **"significant"**: Findings requiring medical attention, follow-up, or intervention. Any finding that would typically require follow-up imaging or clinical correlation should be marked as significant.
-    - **"minor"**: Benign or incidental findings without immediate clinical impact that do not require follow-up
-    - **"normal"**: No abnormality detected
-    - **"not_applicable"**: When significance cannot be determined
-    
-    **Important**: Clinical significance must be based solely on medical content, not text quality or grammar. Minor typos or grammatical errors in the input should not affect significance classification.
 
     ---
 

pyproject.toml

@@ -30,7 +30,7 @@ dependencies = [
     "Flask>=3.1.0",
     "Flask-Limiter>=3.5.0",
     "gunicorn>=23.0.0",
-    "langextract>=1.6.0,<2.0.0",
+    "langextract>=0.1.3",
     "pandas>=1.3.0",
     "numpy>=1.20.0",
     "ml-collections>=0.1.0",
@@ -81,5 +81,5 @@ disable = [
 ]
 
 [tool.pytest.ini_options]
-testpaths = ["test_app.py", "test_validation.py"]
-python_files = ["test_*.py", "*_test.py"]
+testpaths = ["tests"]
+python_files = ["test_*.py", "*_test.py"] 

report_examples.py

@@ -466,7 +466,7 @@ def get_examples_for_model() -> list[lx.data.ExampleData]:
                 
                 The ventricular system is normal in size and configuration.
                 
-                No midline shift is present.
+                No abnormal enhancement is seen.
 
                 IMPRESSION:
                 Normal brain MRI.
@@ -503,10 +503,10 @@ def get_examples_for_model() -> list[lx.data.ExampleData]:
                     },
                 ),
                 lx.data.Extraction(
-                    extraction_text="No midline shift is present.",
+                    extraction_text="No abnormal enhancement is seen.",
                     extraction_class="findings_body",
                     attributes={
-                        "section": "Brain Parenchyma",
+                        "section": "Enhancement",
                         "clinical_significance": "normal",
                     },
                 ),

static/script.js

@@ -14,12 +14,19 @@ import { initClearButton, updateClearButtonState } from './reset.js';
 
 document.addEventListener('DOMContentLoaded', function () {
   // === CONFIGURATION CONSTANTS ===
-  const MAX_LABEL_LENGTH = 60;
+  const GRID_CONFIG = {
+    MOBILE_MIN_WIDTH: 120,
+    DESKTOP_MIN_WIDTH: 160,
+    MOBILE_BREAKPOINT: 768,
+    NARROW_BREAKPOINT: 360,
+    MAX_LABEL_LENGTH: 60,
+    BALANCE_DELAY: 100,
+    RESIZE_DEBOUNCE: 250,
+  };
 
   const UI_CONFIG = {
     SCROLL_SMOOTH_BEHAVIOR: 'smooth',
     SCROLL_OFFSET_BUFFER: 100,
-    DEFAULT_SAMPLE_ID: 'chest_xray',
   };
 
   // === GLOBAL STATE ===
@@ -44,15 +51,12 @@ document.addEventListener('DOMContentLoaded', function () {
       span.classList.remove('highlight');
       span.dataset.highlighted = 'false';
     });
-    document.querySelectorAll('.source-excerpt').forEach((excerpt) => {
-      excerpt.hidden = true;
-    });
     clearInputHighlight();
   }
 
   // Add global click handler to clear highlights when clicking outside on mobile
   document.addEventListener('click', function (e) {
-    if (isTouchDevice() && !e.target.closest('.text-span')) {
+    if (isTouchDevice() && !e.target.classList.contains('text-span')) {
       clearAllHighlights();
     }
   });
@@ -60,20 +64,10 @@ document.addEventListener('DOMContentLoaded', function () {
   const predictButton = document.getElementById('predict-button');
   const inputText = document.getElementById('input-text');
   const outputTextContainer = document.getElementById('output-text');
-  const findingsCards = document.getElementById('findings-cards');
-  const rawOutput = document.getElementById('raw-output');
-  const promptOutput = document.getElementById('prompt-output');
-  const studioState = document.getElementById('studio-state');
-  const outputViewTabs = Array.from(
-    document.querySelectorAll('[data-output-view]'),
-  );
-  let preferredStructuredView = 'report';
   const instructionsEl = document.querySelector('.instructions');
   const loadingOverlay = document.getElementById('loading-overlay');
   let processingLoadingTimer = null;
   let originalInputText = '';
-  let sampleRunQueued = false;
-  let sampleLoadTimer = null;
 
   // Disable virtual keyboard on mobile devices
   let allowInputFocus = false;
@@ -92,6 +86,7 @@ document.addEventListener('DOMContentLoaded', function () {
 
   // Model dropdown elements
   const modelSelect = document.getElementById('model-select');
+  const modelNameSpan = document.getElementById('model-name');
   const modelLink = document.getElementById('model-link');
 
   /**
@@ -99,9 +94,13 @@ document.addEventListener('DOMContentLoaded', function () {
    * @const {Object<string, {text: string, link: string}>}
    */
   const modelInfo = {
-    'gemini-flash-latest': {
-      text: 'Gemini Flash (latest)',
-      link: 'https://ai.google.dev/gemini-api/docs/models',
+    'gemini-2.5-flash': {
+      text: 'Gemini 2.5 Flash',
+      link: 'https://cloud.google.com/vertex-ai/generative-ai/docs/models/gemini/2-5-flash',
+    },
+    'gemini-2.5-pro': {
+      text: 'Gemini 2.5 Pro',
+      link: 'https://cloud.google.com/vertex-ai/generative-ai/docs/models/gemini/2-5-pro',
     },
   };
 
@@ -110,11 +109,14 @@ document.addEventListener('DOMContentLoaded', function () {
    */
   function updateModelInfo() {
     const selectedModel = modelSelect.value;
+    if (modelNameSpan)
+      modelNameSpan.textContent = modelInfo[selectedModel].text;
     if (modelLink) modelLink.href = modelInfo[selectedModel].link;
   }
 
   if (modelSelect) {
     modelSelect.addEventListener('change', updateModelInfo);
+    updateModelInfo();
   }
 
   // Cache optimization elements
@@ -264,7 +266,6 @@ document.addEventListener('DOMContentLoaded', function () {
       const button = document.createElement('button');
       button.className = 'sample-button';
       button.setAttribute('data-sample-id', sample.id);
-      button.setAttribute('aria-pressed', 'false');
 
       button.innerHTML = `
                 <div class="sample-button-content">
@@ -282,77 +283,93 @@ document.addEventListener('DOMContentLoaded', function () {
 
       button.addEventListener('click', function () {
         loadSampleReport(sample);
-        document.querySelectorAll('.sample-button.active').forEach((btn) => {
-          btn.classList.remove('active');
-          btn.setAttribute('aria-pressed', 'false');
-        });
+        document
+          .querySelectorAll('.sample-button.active')
+          .forEach((btn) => btn.classList.remove('active'));
         this.classList.add('active');
-        this.setAttribute('aria-pressed', 'true');
       });
 
       sampleButtonsContainer.appendChild(button);
     });
 
-    sampleButtonsContainer.addEventListener('keydown', handleSampleRailKeydown);
-
-    const hasIncomingState = inputText.value.trim().length > 0;
-    const defaultSample = sortedSamples.find(
-      (sample) => sample.id === UI_CONFIG.DEFAULT_SAMPLE_ID,
-    );
-    if (!hasIncomingState && defaultSample) {
-      const defaultButton = sampleButtonsContainer.querySelector(
-        `[data-sample-id="${UI_CONFIG.DEFAULT_SAMPLE_ID}"]`,
-      );
-      if (defaultButton) {
-        defaultButton.classList.add('active');
-        defaultButton.setAttribute('aria-pressed', 'true');
-        if (window.matchMedia('(max-width: 768px)').matches) {
-          sampleButtonsContainer.scrollLeft = Math.max(
-            0,
-            defaultButton.offsetLeft - sampleButtonsContainer.clientWidth / 2,
-          );
-        }
-      }
-      loadSampleReport(defaultSample, { scroll: false });
-    }
+    setTimeout(() => {
+      balanceByColumnCount();
+    }, GRID_CONFIG.BALANCE_DELAY);
   }
 
   /**
-   * Supports arrow-key navigation across the horizontal sample rail.
-   * @param {KeyboardEvent} event - Keyboard event from the rail
+   * Balances sample button rows by calculating optimal column count for even distribution.
+   * Keeps row-wise reading order while achieving visual balance (e.g., 5+5 instead of 6+4).
+   * Uses responsive sizing for better mobile experience.
    */
-  function handleSampleRailKeydown(event) {
-    if (!['ArrowLeft', 'ArrowRight', 'Home', 'End'].includes(event.key)) return;
+  function balanceByColumnCount() {
+    const container = document.querySelector('.sample-buttons');
+    if (!container) {
+      console.warn('Sample buttons container not found');
+      return;
+    }
 
-    const buttons = Array.from(
-      event.currentTarget.querySelectorAll('.sample-button'),
+    const cards = container.querySelectorAll('.sample-button').length;
+    const styles = getComputedStyle(container);
+    const gap = parseFloat(styles.columnGap) || 12;
+
+    const viewport = window.innerWidth;
+    const minWidth =
+      viewport <= GRID_CONFIG.MOBILE_BREAKPOINT
+        ? GRID_CONFIG.MOBILE_MIN_WIDTH
+        : GRID_CONFIG.DESKTOP_MIN_WIDTH;
+
+    const containerWidth = container.clientWidth;
+    const columnsFit = Math.max(
+      1,
+      Math.floor((containerWidth + gap) / (minWidth + gap)),
     );
-    const currentIndex = buttons.indexOf(document.activeElement);
-    if (currentIndex < 0) return;
-
-    event.preventDefault();
-    let nextIndex = currentIndex;
-    if (event.key === 'ArrowLeft') nextIndex = Math.max(0, currentIndex - 1);
-    if (event.key === 'ArrowRight') {
-      nextIndex = Math.min(buttons.length - 1, currentIndex + 1);
+
+    if (viewport <= GRID_CONFIG.NARROW_BREAKPOINT) {
+      return;
     }
-    if (event.key === 'Home') nextIndex = 0;
-    if (event.key === 'End') nextIndex = buttons.length - 1;
-    buttons[nextIndex].focus();
-    buttons[nextIndex].scrollIntoView({ block: 'nearest', inline: 'center' });
+
+    // Find the column count that provides the most even distribution
+    let bestCols = columnsFit;
+    let bestRem = cards % columnsFit;
+
+    for (let cols = columnsFit - 1; cols >= 1; cols--) {
+      const rem = cards % cols;
+      if (rem === 0) {
+        bestCols = cols;
+        break; // Perfect distribution found
+      }
+      if (rem > bestRem) continue; // Worse distribution, skip
+      bestCols = cols;
+      bestRem = rem;
+    }
+
+    // Mobile-specific logic: prefer 2-3 columns for better touch targets
+    if (viewport <= GRID_CONFIG.MOBILE_BREAKPOINT) {
+      if (bestCols === 1 && columnsFit >= 2) {
+        bestCols = 2; // Force at least 2 columns on mobile
+      } else if (bestCols > 3 && cards >= 6) {
+        // If we have many columns, prefer 2-3 for mobile UX
+        const cols2Rem = cards % 2;
+        const cols3Rem = cards % 3;
+        if (cols2Rem <= cols3Rem) {
+          bestCols = 2;
+        } else {
+          bestCols = 3;
+        }
+      }
+    }
+
+    // Always apply the balanced column count for optimal visual distribution
+    container.style.gridTemplateColumns = `repeat(${bestCols}, minmax(${minWidth}px, 1fr))`;
   }
 
   /**
    * Loads a sample report into the input area and automatically processes it.
    * @param {Object} sample - The sample report data object
    */
-  function loadSampleReport(sample, options = {}) {
-    if (options.scroll !== false) scrollToOutput();
-
-    if (sampleLoadTimer) {
-      clearTimeout(sampleLoadTimer);
-      sampleLoadTimer = null;
-    }
+  function loadSampleReport(sample) {
+    scrollToOutput();
 
     // Normalize line endings for sample text
     inputText.value = sample.text.replace(/\r\n?/g, '\n');
@@ -361,9 +378,8 @@ document.addEventListener('DOMContentLoaded', function () {
     updateClearButtonState();
 
     outputTextContainer.innerHTML = '';
-    instructionsEl.style.display = 'none';
+    instructionsEl.style.display = 'block';
     currentSampleId = sample.id;
-    if (studioState) studioState.textContent = 'Loading cached example…';
 
     // Automatically enable cache for sample reports
     if (cacheToggle) {
@@ -372,23 +388,21 @@ document.addEventListener('DOMContentLoaded', function () {
       updateModelDropdownState();
     }
 
-    if (predictButton.disabled) {
-      sampleRunQueued = true;
-      return;
-    }
-
-    sampleLoadTimer = setTimeout(() => {
-      sampleLoadTimer = null;
-      if (predictButton.disabled) {
-        sampleRunQueued = true;
-        return;
-      }
+    setTimeout(() => {
       predictButton.click();
     }, 100);
   }
 
   loadSampleReports();
 
+  let resizeTimeout;
+  window.addEventListener('resize', () => {
+    clearTimeout(resizeTimeout);
+    resizeTimeout = setTimeout(() => {
+      balanceByColumnCount();
+    }, GRID_CONFIG.RESIZE_DEBOUNCE);
+  });
+
   /**
    * Updates the cache status display in the UI.
    * @returns {Promise<void>}
@@ -438,13 +452,6 @@ document.addEventListener('DOMContentLoaded', function () {
     predictButton.disabled = true;
     predictButton.textContent = 'Processing...';
     const cacheEnabled = cacheToggle ? cacheToggle.checked : true;
-    if (studioState) {
-      studioState.textContent =
-        cacheEnabled && currentSampleId
-          ? 'Loading cached example…'
-          : 'Running live extraction…';
-    }
-    resetStudioMetrics();
     if (processingLoadingTimer) clearTimeout(processingLoadingTimer);
 
     // Show loading overlay after 200ms
@@ -455,7 +462,7 @@ document.addEventListener('DOMContentLoaded', function () {
         if (loaderMessage) {
           const modelText =
             (modelSelect && modelInfo[modelSelect.value]?.text) ||
-            'Gemini Flash (latest)';
+            'Gemini 2.5 Flash';
           loaderMessage.textContent = `Running LangExtract with ${modelText}...`;
         }
 
@@ -468,17 +475,6 @@ document.addEventListener('DOMContentLoaded', function () {
 
     originalInputText = inputText.value;
     outputTextContainer.innerHTML = '';
-    rawOutput?.replaceChildren();
-    promptOutput?.replaceChildren();
-    if (findingsCards) findingsCards.textContent = 'Structuring report…';
-    if (promptToggle) {
-      promptToggle.checked = false;
-      showPromptView(false);
-    }
-    const mobilePromptToggle = document.getElementById('prompt-toggle-mobile');
-    if (mobilePromptToggle) mobilePromptToggle.checked = false;
-    selectOutputView('cards');
-    setOutputViewsAvailable(false);
     updateLXToggleStates(); // Disable toggles when output is cleared
     updateCopyButtonState();
 
@@ -504,9 +500,6 @@ document.addEventListener('DOMContentLoaded', function () {
         body: originalInputText,
       });
 
-      // A newer sample selection is waiting; discard this response and run it next.
-      if (sampleRunQueued) return;
-
       if (!response.ok) {
         const errorText = await response.text();
         let errorJson;
@@ -529,23 +522,32 @@ document.addEventListener('DOMContentLoaded', function () {
 
       const data = await response.json();
 
-      // A sample can be selected while response parsing is in progress.
-      if (sampleRunQueued) return;
-
-      // Cached samples should feel instant and never simulate provider latency.
+      // Handle cached results with simulated loading
       if (data.from_cache) {
+        // Ensure overlay is visible (may not be if response was quick)
+        if (loadingOverlay && loadingOverlay.style.display === 'none') {
+          loadingOverlay.style.display = 'flex';
+          if (typeof gsap !== 'undefined') {
+            startLoaderAnimation();
+          }
+        }
+
+        // Update loading message for cached results
         const loaderMessage = document.querySelector('.loader-message');
         if (loaderMessage) {
           loaderMessage.textContent =
             'Loading LangExtract Result from Cache...';
         }
+
+        // Add 1-2 second delay for cached results to simulate loading
+        const delay = Math.random() * 1000 + 2000; // 2-3 seconds
+        await new Promise((resolve) => setTimeout(resolve, delay));
       }
 
       if (data.sanitized_input && data.sanitized_input !== originalInputText) {
         const inputText = document.getElementById('input-text');
         if (inputText) {
           inputText.value = data.sanitized_input;
-          originalInputText = data.sanitized_input;
           updateClearButtonState();
         }
       }
@@ -557,9 +559,6 @@ document.addEventListener('DOMContentLoaded', function () {
           data.segments.length > 0
         ) {
           renderSegments(data.segments);
-          renderFindingCards(data.segments);
-          updateStudioMetrics(data);
-          setOutputViewsAvailable(true);
           updateLXToggleStates(); // Enable/update toggles when output is generated
           updateCopyButtonState();
 
@@ -575,66 +574,50 @@ document.addEventListener('DOMContentLoaded', function () {
 
             rawOutput.innerHTML = '';
 
-            // Check if JSONFormatter is available
-            if (typeof window.JSONFormatter === 'undefined') {
-              console.error('JSONFormatter library not loaded, using fallback');
-              const pre = document.createElement('pre');
-              pre.style.whiteSpace = 'pre-wrap';
-              pre.style.wordWrap = 'break-word';
-              pre.textContent = JSON.stringify(rawData, null, 2);
-              rawOutput.replaceChildren(pre);
-              rawOutput._jsonData = rawData;
-            } else {
-              const formatter = new window.JSONFormatter(rawData, {
-                hoverPreviewEnabled: true,
-                animateOpen: false,
-                animateClose: false,
-                theme: 'light',
-                open: true,
-              });
+            const formatter = new JSONFormatter(rawData, {
+              hoverPreviewEnabled: true,
+              animateOpen: false,
+              animateClose: false,
+              theme: 'light',
+              open: true,
+            });
 
-              const renderedElement = formatter.render();
-              rawOutput.appendChild(renderedElement);
-              rawOutput._jsonFormatter = formatter;
-              rawOutput._jsonData = rawData;
+            const renderedElement = formatter.render();
+            rawOutput.appendChild(renderedElement);
+            rawOutput._jsonFormatter = formatter;
+            rawOutput._jsonData = rawData;
 
-              setTimeout(() => {
+            setTimeout(() => {
+              try {
+                if (formatter.openAtDepth) {
+                  formatter.openAtDepth(3);
+                }
+              } catch (e) {
+                // Ignore errors if formatter doesn't support openAtDepth
+              }
+
+              const togglers = rawOutput.querySelectorAll(
+                '.json-formatter-toggler',
+              );
+              togglers.forEach((toggler) => {
                 try {
-                  if (formatter.openAtDepth) {
-                    formatter.openAtDepth(3);
-                  }
+                  toggler.click();
                 } catch (e) {
-                  // Ignore errors if formatter doesn't support openAtDepth
+                  // Ignore click errors on JSON formatter togglers
                 }
-
-                const togglers = rawOutput.querySelectorAll(
-                  '.json-formatter-toggler',
-                );
-                togglers.forEach((toggler) => {
-                  try {
-                    toggler.click();
-                  } catch (e) {
-                    // Ignore click errors on JSON formatter togglers
-                  }
-                });
-              }, 10);
-            }
+              });
+            }, 10);
 
             rawToggle.checked = false;
             rawOutput.style.display = 'none';
+            outputTextContainer.style.display = 'block';
           }
 
           if (promptOutput) {
             const promptText = data.raw_prompt || 'Prompt data not available.';
-            if (
-              typeof marked !== 'undefined' &&
-              typeof DOMPurify !== 'undefined' &&
-              data.raw_prompt
-            ) {
+            if (typeof marked !== 'undefined' && data.raw_prompt) {
               // Render markdown with syntax highlighting support
-              promptOutput.innerHTML = DOMPurify.sanitize(
-                marked.parse(promptText),
-              );
+              promptOutput.innerHTML = marked.parse(promptText);
             } else {
               // Fallback to plain text
               promptOutput.textContent = promptText;
@@ -643,52 +626,24 @@ document.addEventListener('DOMContentLoaded', function () {
             showPromptView(false);
           }
 
-          selectOutputView(preferredStructuredView);
-
           const hasIntervals = data.segments.some(
             (segment) => segment.intervals && segment.intervals.length > 0,
           );
 
-          instructionsEl.replaceChildren();
+          instructionsEl.style.display = 'block';
           if (!hasIntervals) {
             instructionsEl.innerHTML =
               '<p><strong>Note:</strong> Hover functionality is not available for this result.</p>';
-            instructionsEl.style.display = 'block';
-          } else {
-            instructionsEl.style.display = 'none';
-          }
-          if (studioState) {
-            studioState.textContent = data.from_cache
-              ? 'Cached sample · ready'
-              : 'Live extraction · ready';
           }
         } else {
           outputTextContainer.textContent = data.text;
-          if (findingsCards) {
-            findingsCards.textContent = data.text;
-          }
-          selectOutputView('cards');
-          resetStudioMetrics();
-          setOutputViewsAvailable(false);
-          if (studioState) {
-            studioState.textContent = 'Response returned · no structured items';
-          }
           instructionsEl.style.display = 'none';
         }
       } else {
         outputTextContainer.textContent = 'No content returned from server.';
-        if (findingsCards) {
-          findingsCards.textContent = 'No content returned from server.';
-        }
-        selectOutputView('cards');
-        resetStudioMetrics();
-        setOutputViewsAvailable(false);
-        if (studioState)
-          studioState.textContent = 'No structured result returned';
         instructionsEl.style.display = 'none';
       }
     } catch (error) {
-      if (sampleRunQueued) return;
       if (error.details && typeof error.details === 'object') {
         if (error.details.error === 'Empty input') {
           const friendlyMessage = [
@@ -729,13 +684,6 @@ document.addEventListener('DOMContentLoaded', function () {
       } else {
         outputTextContainer.textContent = `Error: ${error.message}`;
       }
-      if (findingsCards) {
-        findingsCards.textContent = outputTextContainer.textContent;
-      }
-      selectOutputView('cards');
-      resetStudioMetrics();
-      setOutputViewsAvailable(false);
-      if (studioState) studioState.textContent = 'Unable to structure report';
       instructionsEl.style.display = 'none';
     } finally {
       if (processingLoadingTimer) {
@@ -746,7 +694,7 @@ document.addEventListener('DOMContentLoaded', function () {
 
       const message = document.querySelector('.loader-message');
       const spinner = document.querySelector('.spinner');
-      if (message && spinner && typeof gsap !== 'undefined') {
+      if (message && spinner) {
         gsap.killTweensOf([message, spinner]);
         gsap.set([message, spinner], { clearProps: 'all' });
       }
@@ -754,11 +702,6 @@ document.addEventListener('DOMContentLoaded', function () {
       predictButton.textContent = 'Process';
 
       updateCacheStatus();
-
-      if (sampleRunQueued) {
-        sampleRunQueued = false;
-        setTimeout(() => predictButton.click(), 0);
-      }
     }
   });
 
@@ -894,104 +837,6 @@ document.addEventListener('DOMContentLoaded', function () {
     }
   }
 
-  /**
-   * Renders every returned segment exactly once as a scan-friendly card.
-   * @param {Array<Object>} segments - Ordered segments from the API response
-   */
-  function renderFindingCards(segments) {
-    if (!findingsCards) return;
-
-    findingsCards.innerHTML = '';
-    const cardsFragment = document.createDocumentFragment();
-
-    segments.forEach((segment, index) => {
-      const card = document.createElement('article');
-      card.className = 'finding-card';
-      card.dataset.segmentIndex = String(index);
-      card.dataset.segmentType = segment.type || 'body';
-
-      const cardHeader = document.createElement('div');
-      cardHeader.className = 'finding-card-header';
-
-      const label = document.createElement('span');
-      label.className = 'finding-card-label';
-      label.textContent = segment.label || segment.type || 'Finding';
-      cardHeader.appendChild(label);
-
-      const badges = document.createElement('span');
-      badges.className = 'finding-card-badges';
-
-      const significanceLevel = String(
-        segment.significance || '',
-      ).toLowerCase();
-      if (
-        significanceLevel === 'significant' ||
-        significanceLevel === 'minor'
-      ) {
-        const significance = document.createElement('span');
-        significance.className = `finding-badge significance-${significanceLevel}`;
-        significance.textContent = significanceLevel;
-        badges.appendChild(significance);
-      }
-
-      const grounded = Boolean(segment.intervals && segment.intervals.length);
-      const grounding = document.createElement('span');
-      grounding.className = `finding-badge ${grounded ? 'is-grounded' : 'is-ungrounded'}`;
-      grounding.textContent = grounded ? 'Source grounded' : 'No source span';
-      badges.appendChild(grounding);
-      cardHeader.appendChild(badges);
-      card.appendChild(cardHeader);
-
-      const content = document.createElement('p');
-      content.className = 'finding-card-content';
-      content.appendChild(createContentWithIntervalSpans(segment));
-      card.appendChild(content);
-
-      const sourceExcerpt = document.createElement('div');
-      sourceExcerpt.className = 'source-excerpt';
-      sourceExcerpt.hidden = true;
-      sourceExcerpt.setAttribute('aria-live', 'polite');
-      card.appendChild(sourceExcerpt);
-
-      cardsFragment.appendChild(card);
-    });
-
-    findingsCards.appendChild(cardsFragment);
-  }
-
-  /**
-   * Updates factual counters derived directly from the extraction response.
-   * @param {Object} data - Successful API response
-   */
-  function updateStudioMetrics(data) {
-    const segments = Array.isArray(data.segments) ? data.segments : [];
-    const counts = {
-      items: segments.length,
-      grounded: segments.filter((segment) => segment.intervals?.length).length,
-      significant: segments.filter(
-        (segment) =>
-          String(segment.significance || '').toLowerCase() === 'significant',
-      ).length,
-      minor: segments.filter(
-        (segment) =>
-          String(segment.significance || '').toLowerCase() === 'minor',
-      ).length,
-    };
-
-    Object.entries(counts).forEach(([name, value]) => {
-      const metric = document.getElementById(`metric-${name}`);
-      if (metric) metric.textContent = String(value);
-    });
-  }
-
-  /** Clears counters while a request is running or has no structured result. */
-  function resetStudioMetrics() {
-    ['items', 'grounded', 'significant', 'minor'].forEach((name) => {
-      const metric = document.getElementById(`metric-${name}`);
-      if (metric) metric.textContent = '—';
-    });
-  }
-
   /**
    * Helper function to create section headers.
    * @param {string} text - The header text to display
@@ -1051,12 +896,6 @@ document.addEventListener('DOMContentLoaded', function () {
     const interval = segment.intervals[0];
     const contentSpan = document.createElement('span');
     contentSpan.classList.add('text-span');
-    contentSpan.tabIndex = 0;
-    contentSpan.setAttribute('role', 'button');
-    contentSpan.setAttribute(
-      'aria-label',
-      `Show source for ${segment.label || segment.type || 'extracted item'}`,
-    );
 
     // Set data attributes for position tracking
     contentSpan.dataset.startPos = interval.startPos;
@@ -1085,7 +924,8 @@ document.addEventListener('DOMContentLoaded', function () {
    */
   function extractLabelInfo(content) {
     const colonIndex = content.indexOf(':');
-    const hasLabel = colonIndex > 0 && colonIndex < MAX_LABEL_LENGTH;
+    const hasLabel =
+      colonIndex > 0 && colonIndex < GRID_CONFIG.MAX_LABEL_LENGTH;
 
     return {
       hasLabel,
@@ -1155,55 +995,33 @@ document.addEventListener('DOMContentLoaded', function () {
   function addIntervalEventListeners(contentSpan) {
     const isDesktop = !isTouchDevice();
 
-    const getSourceExcerpt = () =>
-      contentSpan.closest('.finding-card')?.querySelector('.source-excerpt');
-
-    const showGrounding = ({ focusInput = true } = {}) => {
-      contentSpan.classList.add('highlight');
-      const startPos = parseInt(contentSpan.dataset.startPos);
-      const endPos = parseInt(contentSpan.dataset.endPos);
-      if (!isNaN(startPos) && !isNaN(endPos)) {
-        highlightInputText(startPos, endPos, { focusInput });
-        const sourceExcerpt = getSourceExcerpt();
-        if (!focusInput && sourceExcerpt) {
-          sourceExcerpt.textContent = originalInputText.slice(startPos, endPos);
-          sourceExcerpt.hidden = false;
-        }
-      }
-    };
-
-    const hideGrounding = () => {
-      contentSpan.classList.remove('highlight');
-      const sourceExcerpt = getSourceExcerpt();
-      if (sourceExcerpt) sourceExcerpt.hidden = true;
-      clearInputHighlight();
-    };
-
     if (isDesktop) {
       // Desktop: Hover-based highlighting
-      contentSpan.addEventListener('mouseenter', showGrounding);
-      contentSpan.addEventListener('mouseleave', hideGrounding);
-      contentSpan.addEventListener('focus', () =>
-        showGrounding({ focusInput: false }),
-      );
-      contentSpan.addEventListener('blur', hideGrounding);
+      contentSpan.addEventListener('mouseenter', function () {
+        contentSpan.classList.add('highlight');
+        const startPos = parseInt(contentSpan.dataset.startPos);
+        const endPos = parseInt(contentSpan.dataset.endPos);
+        if (!isNaN(startPos) && !isNaN(endPos)) {
+          highlightInputText(startPos, endPos);
+        }
+      });
+
+      contentSpan.addEventListener('mouseleave', function () {
+        contentSpan.classList.remove('highlight');
+        clearInputHighlight();
+      });
     } else {
-      // Mobile: one click event avoids a touchstart/click double-toggle.
-      contentSpan.addEventListener('click', function (e) {
+      // Mobile: Tap-based highlighting (toggle)
+      contentSpan.addEventListener('touchstart', function (e) {
         e.preventDefault();
         handleMobileHighlight(contentSpan);
       });
-    }
 
-    contentSpan.addEventListener('keydown', function (event) {
-      if (event.key !== 'Enter' && event.key !== ' ') return;
-      event.preventDefault();
-      if (isTouchDevice()) {
+      contentSpan.addEventListener('click', function (e) {
+        e.preventDefault();
         handleMobileHighlight(contentSpan);
-      } else {
-        showGrounding({ focusInput: false });
-      }
-    });
+      });
+    }
   }
 
   /**
@@ -1225,16 +1043,7 @@ document.addEventListener('DOMContentLoaded', function () {
       const startPos = parseInt(span.dataset.startPos);
       const endPos = parseInt(span.dataset.endPos);
       if (!isNaN(startPos) && !isNaN(endPos)) {
-        const card = span.closest('.finding-card');
-        if (card && window.matchMedia('(max-width: 768px)').matches) {
-          const excerpt = card.querySelector('.source-excerpt');
-          if (excerpt) {
-            excerpt.textContent = originalInputText.slice(startPos, endPos);
-            excerpt.hidden = false;
-          }
-        } else {
-          highlightInputText(startPos, endPos);
-        }
+        highlightInputText(startPos, endPos);
       }
     } else {
       // If it was highlighted, just clear (already done above)
@@ -1246,22 +1055,21 @@ document.addEventListener('DOMContentLoaded', function () {
    * Highlights text in the input textarea based on character positions.
    * @param {number} startPos - Starting character position
    * @param {number} endPos - Ending character position
-   * @param {{focusInput?: boolean}} options - Whether to move focus to the source
    */
-  function highlightInputText(startPos, endPos, { focusInput = true } = {}) {
+  function highlightInputText(startPos, endPos) {
     // Enable focus for programmatic text selection
-    if (focusInput && isTouchDevice()) {
+    if (isTouchDevice()) {
       allowInputFocus = true;
     }
 
-    if (focusInput) inputText.focus();
+    inputText.focus();
     if (typeof inputText.setSelectionRange === 'function') {
       inputText.setSelectionRange(startPos, endPos);
       scrollInputToRange(startPos, endPos); // Centre the selection in viewport
     }
 
     // Restore focus prevention
-    if (focusInput && isTouchDevice()) {
+    if (isTouchDevice()) {
       allowInputFocus = false;
     }
   }
@@ -1317,9 +1125,7 @@ document.addEventListener('DOMContentLoaded', function () {
 
       inputText.scrollTo({
         top: targetScrollTop,
-        behavior: prefersReducedMotion()
-          ? 'auto'
-          : UI_CONFIG.SCROLL_SMOOTH_BEHAVIOR,
+        behavior: UI_CONFIG.SCROLL_SMOOTH_BEHAVIOR,
       });
     } finally {
       // Always cleanup the clone element
@@ -1336,12 +1142,6 @@ document.addEventListener('DOMContentLoaded', function () {
 
     if (!message || !spinner) return;
 
-    if (prefersReducedMotion()) {
-      gsap.killTweensOf([message, spinner]);
-      gsap.set([message, spinner], { clearProps: 'all' });
-      return;
-    }
-
     gsap.killTweensOf([message, spinner]);
     gsap.set([message, spinner], { clearProps: 'all' });
 
@@ -1386,85 +1186,8 @@ document.addEventListener('DOMContentLoaded', function () {
     }
   }
 
-  /**
-   * Selects one of the three output representations.
-   * @param {'cards'|'report'|'raw'} view - View to make visible
-   */
-  function selectOutputView(view, { remember = false } = {}) {
-    const requestedTab = outputViewTabs.find(
-      (tab) => tab.dataset.outputView === view,
-    );
-    if (requestedTab?.disabled) view = 'cards';
-
-    if (findingsCards) {
-      findingsCards.style.display = view === 'cards' ? 'grid' : 'none';
-      findingsCards.setAttribute('aria-hidden', String(view !== 'cards'));
-    }
-    if (outputTextContainer) {
-      outputTextContainer.style.display = view === 'report' ? 'block' : 'none';
-      outputTextContainer.setAttribute(
-        'aria-hidden',
-        String(view !== 'report'),
-      );
-    }
-    if (rawOutput) {
-      rawOutput.style.display = view === 'raw' ? 'block' : 'none';
-      rawOutput.setAttribute('aria-hidden', String(view !== 'raw'));
-    }
-    if (rawToggle) rawToggle.checked = view === 'raw';
-    const mobileRawToggle = document.getElementById('raw-toggle-mobile');
-    if (mobileRawToggle) mobileRawToggle.checked = view === 'raw';
-
-    outputViewTabs.forEach((tab) => {
-      const selected = tab.dataset.outputView === view;
-      tab.classList.toggle('active', selected);
-      tab.setAttribute('aria-selected', String(selected));
-      tab.tabIndex = selected ? 0 : -1;
-    });
-
-    if (remember) preferredStructuredView = view;
-  }
-
-  /** Enables alternate representations only when structured output exists. */
-  function setOutputViewsAvailable(available) {
-    outputViewTabs.forEach((tab) => {
-      if (tab.dataset.outputView === 'cards') return;
-      tab.disabled = !available;
-      tab.setAttribute('aria-disabled', String(!available));
-    });
-  }
-
-  outputViewTabs.forEach((tab) => {
-    tab.tabIndex = tab.getAttribute('aria-selected') === 'true' ? 0 : -1;
-    tab.addEventListener('click', () =>
-      selectOutputView(tab.dataset.outputView, { remember: true }),
-    );
-    tab.addEventListener('keydown', (event) => {
-      if (!['ArrowLeft', 'ArrowRight', 'Home', 'End'].includes(event.key))
-        return;
-      event.preventDefault();
-      const enabledTabs = outputViewTabs.filter(
-        (candidate) => !candidate.disabled,
-      );
-      const enabledIndex = enabledTabs.indexOf(tab);
-      let nextIndex = enabledIndex;
-      if (event.key === 'ArrowLeft') {
-        nextIndex =
-          (enabledIndex - 1 + enabledTabs.length) % enabledTabs.length;
-      }
-      if (event.key === 'ArrowRight') {
-        nextIndex = (enabledIndex + 1) % enabledTabs.length;
-      }
-      if (event.key === 'Home') nextIndex = 0;
-      if (event.key === 'End') nextIndex = enabledTabs.length - 1;
-      enabledTabs[nextIndex].focus();
-      selectOutputView(enabledTabs[nextIndex].dataset.outputView, {
-        remember: true,
-      });
-    });
-  });
-
-  setOutputViewsAvailable(false);
+  const rawOutput = document.getElementById('raw-output');
+  const promptOutput = document.getElementById('prompt-output');
 
   /**
    * Shows or hides the prompt view panel.
@@ -1479,7 +1202,8 @@ document.addEventListener('DOMContentLoaded', function () {
   if (rawToggle) {
     rawToggle.addEventListener('change', () => {
       const showRaw = rawToggle.checked;
-      selectOutputView(showRaw ? 'raw' : 'cards', { remember: true });
+      rawOutput.style.display = showRaw ? 'block' : 'none';
+      outputTextContainer.style.display = showRaw ? 'none' : 'block';
 
       const mobileRawToggle = document.getElementById('raw-toggle-mobile');
       if (mobileRawToggle) {
@@ -1556,11 +1280,6 @@ document.addEventListener('DOMContentLoaded', function () {
   }
 });
 
-/** Returns whether the user has asked interfaces to minimize motion. */
-function prefersReducedMotion() {
-  return window.matchMedia('(prefers-reduced-motion: reduce)').matches;
-}
-
 /**
  * Scrolls to the output panel to direct user focus to the results area.
  * Provides improved navigation experience for sample report selection workflow.
@@ -1571,7 +1290,7 @@ function scrollToOutput() {
   if (outputContainer) {
     // Smooth scroll to the output area
     outputContainer.scrollIntoView({
-      behavior: prefersReducedMotion() ? 'auto' : 'smooth',
+      behavior: 'smooth',
       block: 'center',
     });
   }

static/style.css

@@ -1,3 +1,5 @@
+
+
 /* === Google Material Palette === */
 :root {
   --google-blue: #1a73e8;
@@ -576,7 +578,6 @@ body {
   width: 100%;
   height: clamp(300px, 50vh, 500px);
   min-height: 300px;
-  resize: vertical;
   overflow: auto;
   border: 2px solid #e9ecef;
   border-radius: 8px;
@@ -2277,873 +2278,3 @@ textarea::selection {
 
 /* Copy and clear button overlays always use light mode styling */
 /* Error messages always use light mode styling */
-
-/* === Transformation Studio ==================================== */
-:root {
-  --studio-ink: #172033;
-  --studio-muted: #637083;
-  --studio-surface: rgba(255, 255, 255, 0.94);
-  --studio-line: #dfe5ee;
-  --studio-blue-soft: #edf4ff;
-  --studio-blue: #0b57d0;
-  --studio-violet: #6d4aff;
-}
-
-html {
-  scroll-behavior: smooth;
-  overflow-x: hidden;
-}
-
-body.page-wrapper {
-  overflow-x: hidden;
-  background:
-    radial-gradient(
-      circle at 10% -10%,
-      rgba(66, 133, 244, 0.16),
-      transparent 34rem
-    ),
-    radial-gradient(
-      circle at 94% 8%,
-      rgba(109, 74, 255, 0.1),
-      transparent 28rem
-    ),
-    #f6f8fc;
-  color: var(--studio-ink);
-}
-
-.studio-hero {
-  display: grid;
-  grid-template-columns: minmax(0, 1fr) auto;
-  align-items: end;
-  gap: 20px 36px;
-  margin: 18px 0 16px;
-  text-align: left;
-}
-
-.hero-eyebrow,
-.section-kicker {
-  margin: 0 0 6px;
-  color: var(--studio-blue);
-  font-family: 'Google Sans', sans-serif;
-  font-size: 12px;
-  font-weight: 700;
-  letter-spacing: 0.11em;
-  text-transform: uppercase;
-}
-
-.studio-hero h1 {
-  margin: 0;
-  color: var(--studio-ink);
-  font-size: clamp(2.45rem, 6vw, 4.75rem);
-  font-weight: 700;
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-  }
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-    flex-direction: column;
-    gap: 5px;
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-  }
-
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-    grid-template-columns: 1fr;
-  }
-}
-
-@media (prefers-reduced-motion: reduce) {
-  *,
-  *::before,
-  *::after {
-    scroll-behavior: auto !important;
-    transition-duration: 0.01ms !important;
-    animation-duration: 0.01ms !important;
-    animation-iteration-count: 1 !important;
-  }
-}

structure_report.py

@@ -15,7 +15,7 @@ Example usage:
 
     structurer = RadiologyReportStructurer(
         api_key="your_api_key",
-        model_id="gemini-flash-latest"
+        model_id="gemini-2.5-flash"
     )
     result = structurer.predict("FINDINGS: Normal chest CT...")
 """
@@ -24,6 +24,7 @@ import collections
 import dataclasses
 import itertools
 from enum import Enum
+from functools import wraps
 from typing import Any, TypedDict
 
 import langextract as lx
@@ -34,22 +35,6 @@ import prompt_lib
 import report_examples
 
 
-DEFAULT_MODEL_ID = "gemini-flash-latest"
-LEGACY_MODEL_ALIASES = {
-    "gemini-2.5-flash": DEFAULT_MODEL_ID,
-    "gemini-2.5-pro": "gemini-pro-latest",
-}
-
-
-def resolve_model_id(model_id: str) -> str:
-    """Resolves retired Gemini model IDs to their rolling aliases."""
-    return LEGACY_MODEL_ALIASES.get(model_id, model_id)
-
-
-class ReportProcessingError(RuntimeError):
-    """Raised when the language-model extraction step cannot complete."""
-
-
 class FrontendIntervalDict(TypedDict):
     """Character interval for frontend with startPos and endPos."""
 
@@ -104,6 +89,29 @@ SIGNIFICANCE_SIGNIFICANT = "significant"
 SIGNIFICANCE_NOT_APPLICABLE = "not_applicable"
 
 
+def _initialize_langextract_patches():
+    """Initialize LangExtract patches for proper alignment behavior.
+
+    This function applies necessary patches to LangExtract's Resolver.align method to force accept_match_lesser=False and set fuzzy_alignment_threshold to 0.50. This should be called before using LangExtract functionality.
+
+    Note: This is a temporary workaround until LangExtract exposes
+    accept_match_lesser and fuzzy_alignment_threshold parameters via its public API.
+    """
+    # Store original method
+    original_align = lx.resolver.Resolver.align
+
+    @wraps(original_align)
+    def _align_patched(self, *args, **kwargs):
+        # Set default if not explicitly provided
+        kwargs.setdefault("accept_match_lesser", False)
+        # Set fuzzy matching threshold to 0.50
+        kwargs.setdefault("fuzzy_alignment_threshold", 0.50)
+        return original_align(self, *args, **kwargs)
+
+    # Apply the patch
+    lx.resolver.Resolver.align = _align_patched
+
+
 class ReportSectionType(Enum):
     """Enum representing sections of a radiology report with their extraction class names."""
 
@@ -162,11 +170,12 @@ class RadiologyReportStructurer:
     model_id: str
     temperature: float
     examples: list[langextract.data.ExampleData]
+    _patches_initialized: bool
 
     def __init__(
         self,
         api_key: str | None = None,
-        model_id: str = DEFAULT_MODEL_ID,
+        model_id: str = "gemini-2.5-flash",
         temperature: float = 0.0,
     ):
         """Initializes the RadiologyReportStructurer.
@@ -177,9 +186,16 @@ class RadiologyReportStructurer:
             temperature: Sampling temperature for model generation.
         """
         self.api_key = api_key
-        self.model_id = resolve_model_id(model_id)
+        self.model_id = model_id
         self.temperature = temperature
         self.examples = report_examples.get_examples_for_model()
+        self._patches_initialized = False
+
+    def _ensure_patches_initialized(self):
+        """Ensure LangExtract patches are initialized before use."""
+        if not self._patches_initialized:
+            _initialize_langextract_patches()
+            self._patches_initialized = True
 
     def _generate_formatted_prompt_with_examples(
         self, input_text: str | None = None
@@ -219,9 +235,14 @@ class RadiologyReportStructurer:
 
         try:
             result = self._perform_langextract(report_text, max_char_buffer)
-        except Exception as error:
-            raise ReportProcessingError("Report processing failed") from error
-        return self._build_response(result, report_text)
+            return self._build_response(result, report_text)
+        except (ValueError, TypeError, AttributeError) as e:
+            return ResponseDict(
+                text=f"Error processing report: {str(e)}",
+                segments=[],
+                annotated_document_json={},
+                raw_prompt="",
+            )
 
     def _perform_langextract(
         self, report_text: str, max_char_buffer: int
@@ -239,6 +260,7 @@ class RadiologyReportStructurer:
             ValueError: If LangExtract processing fails.
             TypeError: If invalid parameters are provided.
         """
+        self._ensure_patches_initialized()
         return lx.extract(
             text_or_documents=report_text,
             prompt_description=prompt_instruction.PROMPT_INSTRUCTION.split(
@@ -249,10 +271,8 @@ class RadiologyReportStructurer:
             api_key=self.api_key,
             max_char_buffer=max_char_buffer,
             temperature=self.temperature,
-            resolver_params={
-                "accept_match_lesser": False,
-                "fuzzy_alignment_threshold": 0.50,
-            },
+            # accept_match_lesser handled via monkey-patch
+            # (Resolver.align patched at import time)
         )
 
     def _build_response(

templates/index.html

@@ -19,14 +19,8 @@
       content="{{ share_url_for_sharing }}/static/radextract-preview.jpg"
     />
     <meta property="og:type" content="website" />
-    <meta
-      property="og:video"
-      content="{{ share_url_for_sharing }}/static/radextract-preview.mp4"
-    />
-    <meta
-      property="og:video:secure_url"
-      content="{{ share_url_for_sharing }}/static/radextract-preview.mp4"
-    />
+    <meta property="og:video" content="{{ share_url_for_sharing }}/static/radextract-preview.mp4" />
+    <meta property="og:video:secure_url" content="{{ share_url_for_sharing }}/static/radextract-preview.mp4" />
     <meta property="og:video:type" content="video/mp4" />
     <meta property="og:video:width" content="1920" />
     <meta property="og:video:height" content="1080" />
@@ -44,23 +38,17 @@
       name="twitter:image"
       content="{{ share_url_for_sharing }}/static/radextract-preview.jpg"
     />
-    <meta
-      name="twitter:player"
-      content="{{ share_url_for_sharing }}/static/radextract-preview.mp4"
-    />
+    <meta name="twitter:player" content="{{ share_url_for_sharing }}/static/radextract-preview.mp4" />
     <meta name="twitter:player:width" content="1920" />
     <meta name="twitter:player:height" content="1080" />
-    <meta
-      name="twitter:player:stream"
-      content="{{ share_url_for_sharing }}/static/radextract-preview.mp4"
-    />
+    <meta name="twitter:player:stream" content="{{ share_url_for_sharing }}/static/radextract-preview.mp4" />
     <meta name="twitter:player:stream:content_type" content="video/mp4" />
 
     <link rel="icon" type="image/svg+xml" href="/static/favicon.svg" />
     <link rel="shortcut icon" href="/static/favicon.svg" />
     <link rel="apple-touch-icon" href="/static/favicon.svg" />
 
-    <link rel="stylesheet" href="/static/style.css?v=20260721-studio" />
+    <link rel="stylesheet" href="/static/style.css?v=20250129-video-preview" />
     <link rel="preconnect" href="https://fonts.googleapis.com" />
     <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin />
     <link
@@ -78,112 +66,292 @@
   </head>
 
   <body class="page-wrapper">
-    <header class="header-container studio-hero">
-      <div class="hero-copy">
-        <p class="hero-eyebrow">Grounded radiology extraction</p>
-        <h1><strong>RadExtract</strong></h1>
-        <p class="hero-description">
-          Turn a free-text radiology report into structured findings, with every
-          extraction linked to its exact source words.
+    <div class="header-container">
+      <h1>
+        <strong>RadExtract</strong>:
+        <span class="brand-split">Radiology Report Structuring&nbsp;Demo</span>
+      </h1>
+
+      <!-- Top share buttons -->
+      <div class="share-top">
+        <span>Share →</span>
+        <a
+          class="shr-btn shr-x"
+          href="https://twitter.com/intent/tweet?text={{ share_text }}"
+          target="_blank"
+          rel="noopener"
+          aria-label="Share on X"
+        >
+          <svg viewBox="0 0 24 24" width="20" aria-hidden="true">
+            <path
+              fill="currentColor"
+              d="M23 2.999a9.05 9.05 0 0 1-2.588.71A4.516 4.516 0 0 0 22.36.365a9.04 9.04 0 0 1-2.867 1.096 4.505 4.505 0 0 0-7.67 4.107A12.79 12.79 0 0 1 1.64.896a4.505 4.505 0 0 0 1.396 6.01 4.47 4.47 0 0 1-2.04-.563v.057a4.507 4.507 0 0 0 3.614 4.417 4.522 4.522 0 0 1-2.034.077 4.508 4.508 0 0 0 4.207 3.128A9.03 9.03 0 0 1 0 19.54a12.75 12.75 0 0 0 6.92 2.026c8.304 0 12.846-6.877 12.846-12.837 0-.196-.004-.392-.013-.586A9.17 9.17 0 0 0 23 2.999z"
+            />
+          </svg>
+        </a>
+        <a
+          class="shr-btn shr-li"
+          href="https://www.linkedin.com/shareArticle?mini=true&url={{ share_url_encoded }}&title={{ linkedin_title }}&summary={{ linkedin_summary }}&source=RadExtract"
+          target="_blank"
+          rel="noopener"
+          aria-label="Share on LinkedIn"
+        >
+          <svg viewBox="0 0 24 24" width="20" aria-hidden="true">
+            <path
+              fill="currentColor"
+              d="M4.98 3.5C4.98 5.43 3.43 7 1.5 7S-1.98 5.43-1.98 3.5 0.57 0 2.5 0 4.98 1.57 4.98 3.5zM.02 8h5V24h-5V8zM7.98 8h4.8v2.2h.07c.67-1.27 2.31-2.6 4.76-2.6 5.09 0 6.04 3.35 6.04 7.7V24h-5v-7.7c0-1.84-.03-4.21-2.57-4.21-2.57 0-2.96 1.99-2.96 4.07V24h-5V8z"
+            />
+          </svg>
+        </a>
+      </div>
+
+      <!-- Attribution block: subtitle + logo -->
+      <div class="attribution">
+        <p class="sub-header">
+          <strong>Powered by LangExtract + Gemini 2.5</strong>
         </p>
+
+        <!-- Google Research logo -->
+        <div class="google-research-logo">
+          <img
+            src="/static/google-research-logo.svg"
+            alt="Google Research"
+            width="174"
+            height="25"
+            loading="lazy"
+            tabindex="-1"
+          />
+        </div>
+
+        <!-- Blog link -->
+        <div class="blog-link-container">
+          <a
+            class="blog-link"
+            href="https://developers.googleblog.com/en/introducing-langextract-a-gemini-powered-information-extraction-library"
+            target="_blank"
+            rel="noopener noreferrer"
+            aria-label="Read about LangExtract on Google for Developers"
+          >
+            <span class="material-symbols-outlined blog-icon">article</span>
+            See the LangExtract Blog Post in Google for Developers
+            <span class="material-symbols-outlined external-icon">open_in_new</span>
+          </a>
+        </div>
+      </div>
+
+      <div class="disclaimer-container">
+        <div class="disclaimer-box">
+          <span class="material-symbols-outlined disclaimer-icon">warning</span>
+          <span class="disclaimer-text"
+            >This demonstration is for illustrative purposes only to show the
+            baseline capabilities of LangExtract, the library that powers this
+            demo. It does not represent a finished or approved product, is not
+            intended to diagnose or suggest treatment for any disease or
+            condition, and should not be used for medical advice.</span
+          >
+        </div>
+        <div class="citation-note">
+          <strong>License & Citation:</strong> If you use
+          RadExtract or LangExtract in production or
+          publications, please cite accordingly and acknowledge usage. Use is
+          subject to the Apache 2.0 License. See
+          <a
+            class="banner-link"
+            href="https://huggingface.co/spaces/google/radextract/blob/main/README.md#disclaimer"
+            target="_blank"
+            rel="noopener noreferrer"
+            >README</a
+          >&nbsp;for&nbsp;details.
+        </div>
       </div>
-      <div class="hero-attribution" aria-label="Technology attribution">
-        <span>Powered by LangExtract + Gemini Flash</span>
-        <img
-          src="/static/google-research-logo.svg"
-          alt="Google Research"
-          width="174"
-          height="25"
-        />
-        <div class="hero-links">
+      <div class="banner card">
+        <p class="banner-description">
           <a
+            class="banner-link"
             href="https://github.com/google/langextract"
             target="_blank"
             rel="noopener noreferrer"
-            >LangExtract on GitHub
-            <span class="material-symbols-outlined" aria-hidden="true"
-              >open_in_new</span
-            ></a
+            ><strong>LangExtract (LX)</strong></a
           >
+          is a multi-purpose NLP extraction library that uses large language
+          models such as Gemini to convert free-text into schema-controlled
+          data. It learns from your few-shot examples (structured using
+          <strong>LX</strong>'s extraction schema) to identify and extract
+          information, with every datum linked back to its exact words in the
+          source.
+        </p>
+        <hr class="banner-divider" />
+        <h3 class="banner-section-title">Demo Overview</h3>
+        <p class="banner-description">
+          <strong>RadExtract</strong> uses
           <a
-            href="https://developers.googleblog.com/en/introducing-langextract-a-gemini-powered-information-extraction-library"
+            class="banner-link"
+            href="https://github.com/google/langextract"
             target="_blank"
             rel="noopener noreferrer"
-            >LangExtract release blog
-            <span class="material-symbols-outlined" aria-hidden="true"
-              >open_in_new</span
-            ></a
+            ><strong>LangExtract (LX)</strong></a
           >
-        </div>
-      </div>
-      <div class="safety-strip" role="note">
-        <span class="material-symbols-outlined" aria-hidden="true"
-          >warning</span
-        >
-        <span
-          ><strong>Research demonstration — not for clinical use.</strong>
-          RadExtract does not diagnose, recommend treatment, or provide medical
-          advice.</span
-        >
+          powered by
+          <a
+            id="model-link"
+            class="banner-link"
+            href="https://cloud.google.com/vertex-ai/generative-ai/docs/models/gemini/2-5-flash"
+            target="_blank"
+            rel="noopener noreferrer"
+            ><span id="model-name">Gemini 2.5 Flash</span></a
+          >
+          or
+          <a
+            class="banner-link"
+            href="https://cloud.google.com/vertex-ai/generative-ai/docs/models/gemini/2-5-pro"
+            target="_blank"
+            rel="noopener noreferrer"
+            >Gemini 2.5 Pro</a
+          >
+          to convert radiology report findings into structured, optimized
+          radiology reports with highlighted significant findings. By leveraging
+          a
+          <a
+            class="banner-link"
+            href="https://huggingface.co/spaces/google/radextract/blob/main/prompt_instruction.py"
+            target="_blank"
+            rel="noopener noreferrer"
+            >prompt</a
+          >
+          that describes the structuring task with <strong>LX</strong>'s schema
+          and a
+          <a
+            class="banner-link"
+            href="https://huggingface.co/spaces/google/radextract/blob/main/report_examples.py"
+            target="_blank"
+            rel="noopener noreferrer"
+            >few select examples</a
+          >, <strong>LX</strong> processes free text into the structured output
+          shown below. Leveraging Gemini's foundational knowledge,
+          <strong>RadExtract</strong> can also process imaging modalities beyond
+          those included in the prompt examples, such as the X-ray and
+          ultrasound samples available below.
+        </p>
+        <p class="banner-description">
+          <strong>Interactive Features</strong><br />
+          Each extracted finding is directly grounded by
+          <strong>LX</strong> (linked precisely back to its original words in
+          the source text); hover over any structured item to see this exact
+          textual origin highlighted. <strong>Clinical significance</strong> is
+          visually highlighted: general findings are marked with yellow
+          underlines, while significant findings have red&nbsp;underlines.
+        </p>
+        <p class="banner-description">
+          <strong>Clinical Background</strong><br />
+          Structured reporting helps ensure completeness, reduces ambiguity, and
+          facilitates data sharing in radiology. For background on the value of
+          structured radiology reports, see
+          <a
+            class="banner-link"
+            href="https://link.springer.com/article/10.1007/s13244-017-0588-8"
+            target="_blank"
+            rel="noopener noreferrer"
+            >this European Society of Radiology paper</a
+          >.
+        </p>
       </div>
-    </header>
+    </div>
 
-    <section class="samples-container card" aria-labelledby="sample-heading">
-      <div class="sample-heading-row">
-        <div>
-          <p class="section-kicker">Start with a study</p>
-          <h2 id="sample-heading">Explore sample reports</h2>
+    <div class="samples-container card">
+      <h3>Select a Report</h3>
+      <div class="samples-description">
+        <div class="instruction-step">
+          <span class="step-number">1</span> Select a sample or paste your
+          report
+        </div>
+        <div class="instruction-step">
+          <span class="step-number">2</span> Click "Process" to start for pasted
+          reports
+        </div>
+        <div class="instruction-step">
+          <span class="step-number">3</span> Hover output findings to highlight
+          source text
         </div>
-        <p>Choose a study. Built-in examples can use saved or live results.</p>
-      </div>
-      <div class="sample-rail-shell">
-        <div class="sample-buttons" aria-label="Sample radiology reports"></div>
       </div>
+      <div class="sample-buttons"></div>
       <p class="samples-tip tip-desktop">
-        Select a finding to trace it to the source. Edit the report and choose
-        <strong>Process</strong> to run a live extraction.
+        💡 Try tweaking a sample (remove sections, add extra findings, or paste
+        your own report) to see how the demo responds.
       </p>
       <p class="mobile-tip" role="note">
-        Tap a finding to reveal its grounded source excerpt. Custom report input
-        remains available on desktop and laptop computers.
+        <span class="icon">💡</span>
+        Tap any sample report to explore the structuring features. The keyboard 
+        stays closed so you can easily scroll and interact with highlighted findings.<br><br>
+        <strong>Tip:</strong> Custom input is available only on desktop or laptop computers. 
+        If you're viewing this on a mobile device, please switch to a computer to enter your own reports.
       </p>
-    </section>
+    </div>
 
-    <main
-      id="transformation-studio"
-      class="text-area-container card transformation-studio"
-      aria-labelledby="studio-heading"
-    >
-      <div class="studio-heading">
-        <div>
-          <p class="section-kicker">Source → structure</p>
-          <h2 id="studio-heading">Transformation Studio</h2>
-          <p>Focus a structured item to illuminate its exact source span.</p>
-        </div>
-        <div class="studio-state" id="studio-state" aria-live="polite">
-          Choose a sample or enter a report
+    <div class="interface-options-panel card">
+      <div class="interface-options-header" data-action="toggle-interface">
+        <h4 class="interface-options-title">Interface Controls</h4>
+        <div class="interface-options-summary">
+          <span>LX Generated Prompt • LX Structured Output • Use Cache</span>
+          <span
+            class="material-symbols-outlined expand-icon"
+            id="interface-expand-icon"
+            >expand_more</span
+          >
         </div>
       </div>
-      <div id="studio-metrics" class="studio-metrics" aria-live="polite">
-        <div class="metric">
-          <span id="metric-items">—</span><small>Extracted items</small>
-        </div>
-        <div class="metric">
-          <span id="metric-grounded">—</span><small>Source-grounded</small>
-        </div>
-        <div class="metric">
-          <span id="metric-significant">—</span><small>Significant</small>
+      <div
+        class="interface-options-content"
+        id="interface-options-content"
+        style="display: none"
+      >
+        <div class="interface-options-grid">
+          <div class="interface-option">
+            <div class="option-header">
+              <span class="material-symbols-outlined option-icon"
+                >visibility</span
+              >
+              <strong>LX Generated Prompt</strong>
+            </div>
+            <p class="option-description">
+              View the complete prompt sent to the model, including task
+              description, examples, and your input text
+            </p>
+          </div>
+          <div class="interface-option">
+            <div class="option-header">
+              <span class="material-symbols-outlined option-icon">code</span>
+              <strong>LX Structured Output</strong>
+            </div>
+            <p class="option-description">
+              Toggle between the formatted text view and raw LangExtract JSON
+              data with extraction details
+            </p>
+          </div>
+          <div class="interface-option">
+            <div class="option-header">
+              <span class="material-symbols-outlined option-icon">cached</span>
+              <strong>Use Cache</strong>
+            </div>
+            <p class="option-description">
+              Switch between live model inference and pre-generated Gemini 2.5
+              Pro cached results for faster testing
+            </p>
+          </div>
         </div>
-        <div class="metric">
-          <span id="metric-minor">—</span><small>Minor</small>
+        <div class="interface-options-note">
+          <span class="material-symbols-outlined note-icon">info</span>
+          <span
+            >These controls are located in the Input and Output headers below
+            for easy access during interaction.</span
+          >
         </div>
       </div>
+    </div>
+
+    <div class="text-area-container card">
       <div class="text-area-wrapper input-wrapper">
         <div class="input-header">
-          <div>
-            <span class="panel-number">01</span>
-            <h2>Source report</h2>
-          </div>
+          <h2>Input</h2>
           <label class="prompt-toggle"
             ><input type="checkbox" id="prompt-toggle" /> LX Prompt</label
           >
@@ -219,84 +387,22 @@
         </div>
         <div id="prompt-output" class="raw-json" style="display: none"></div>
       </div>
-      <div class="text-area-wrapper output-wrapper" id="output-container">
+      <div class="text-area-wrapper" id="output-container">
         <div class="output-header">
-          <div>
-            <span class="panel-number">02</span>
-            <h2>Structured extraction</h2>
-          </div>
-          <div class="output-view-tabs" role="tablist" aria-label="Output view">
-            <button
-              class="output-view-tab"
-              id="report-tab"
-              data-output-view="report"
-              role="tab"
-              aria-selected="false"
-              aria-controls="output-text"
-              aria-disabled="true"
-              disabled
-            >
-              Report
-            </button>
-            <button
-              class="output-view-tab active"
-              id="findings-tab"
-              data-output-view="cards"
-              role="tab"
-              aria-selected="true"
-              aria-controls="findings-cards"
-            >
-              Findings
-            </button>
-            <button
-              class="output-view-tab"
-              id="raw-tab"
-              data-output-view="raw"
-              role="tab"
-              aria-selected="false"
-              aria-controls="raw-output"
-              aria-disabled="true"
-              disabled
-            >
-              LX Data
-            </button>
-          </div>
-          <label class="raw-toggle visually-hidden" aria-hidden="true"
-            ><input type="checkbox" id="raw-toggle" tabindex="-1" /> LX
-            Data</label
+          <h2>Output</h2>
+          <label class="raw-toggle"
+            ><input type="checkbox" id="raw-toggle" /> LX Data</label
           >
         </div>
         <div id="output-text-container" class="output-container">
-          <div
-            id="findings-cards"
-            class="findings-cards"
-            role="tabpanel"
-            aria-labelledby="findings-tab"
-            aria-hidden="false"
-            aria-live="polite"
-          >
-            <div class="cards-placeholder">
-              <span class="material-symbols-outlined" aria-hidden="true"
-                >auto_awesome</span
-              >
-              <p>Select a sample to begin exploring grounded findings.</p>
-            </div>
-          </div>
           <pre
             id="output-text"
             class="large-text-area output-text"
-            role="tabpanel"
-            aria-labelledby="report-tab"
-            aria-hidden="true"
-            style="display: none"
             placeholder="Structured output will appear here..."
           ></pre>
           <div
             id="raw-output"
             class="raw-json output-text"
-            role="tabpanel"
-            aria-labelledby="raw-tab"
-            aria-hidden="true"
             style="display: none"
           ></div>
           <button
@@ -326,7 +432,7 @@
             <div class="spinner"></div>
             <div class="loader-text">
               <span class="loader-message"
-                >Running LangExtract with Gemini Flash (latest)</span
+                >Running LangExtract with Gemini 2.5 Flash</span
               >
             </div>
           </div>
@@ -337,9 +443,8 @@
         <div class="model-select-container">
           <label for="model-select">Model:</label>
           <select id="model-select">
-            <option value="gemini-flash-latest" selected>
-              Gemini Flash (latest)
-            </option>
+            <option value="gemini-2.5-flash" selected>Gemini 2.5 Flash</option>
+            <option value="gemini-2.5-pro">Gemini 2.5 Pro</option>
           </select>
         </div>
 
@@ -358,7 +463,7 @@
           <input type="checkbox" id="raw-toggle-mobile" /> LX Data
         </label>
       </div>
-    </main>
+    </div>
 
     <div class="action-bar">
       <button id="predict-button">Process</button>
@@ -379,179 +484,14 @@
 
     <div class="instructions"></div>
 
-    <section
-      id="how-it-works"
-      class="supporting-details"
-      aria-labelledby="details-heading"
-    >
-      <div class="supporting-heading">
-        <p class="section-kicker">Go deeper</p>
-        <h2 id="details-heading">How RadExtract works</h2>
-      </div>
-      <div class="supporting-grid">
-        <article class="support-card">
-          <span
-            class="material-symbols-outlined support-icon"
-            aria-hidden="true"
-            >link</span
-          >
-          <h3>Grounded by LangExtract</h3>
-          <p>
-            <a
-              class="banner-link"
-              href="https://github.com/google/langextract"
-              target="_blank"
-              rel="noopener noreferrer"
-              >LangExtract</a
-            >
-            converts free text into schema-controlled data learned from a
-            task-specific
-            <a
-              class="banner-link"
-              href="https://huggingface.co/spaces/google/radextract/blob/main/prompt_instruction.py"
-              target="_blank"
-              rel="noopener noreferrer"
-              >prompt</a
-            >
-            and
-            <a
-              class="banner-link"
-              href="https://huggingface.co/spaces/google/radextract/blob/main/report_examples.py"
-              target="_blank"
-              rel="noopener noreferrer"
-              >few-shot examples</a
-            >. Each extracted item retains a direct link to its source words.
-          </p>
-        </article>
-        <article class="support-card">
-          <span
-            class="material-symbols-outlined support-icon"
-            aria-hidden="true"
-            >view_in_ar</span
-          >
-          <h3>Explore every layer</h3>
-          <p>
-            Switch between scan-friendly findings, the complete formatted
-            report, raw LangExtract data, and the generated prompt. General and
-            significant findings use distinct visual markers without implying a
-            diagnostic confidence score.
-          </p>
-        </article>
-        <article class="support-card">
-          <span
-            class="material-symbols-outlined support-icon"
-            aria-hidden="true"
-            >clinical_notes</span
-          >
-          <h3>Clinical background</h3>
-          <p>
-            Structured reporting can improve completeness, reduce ambiguity, and
-            facilitate data sharing. Read the
-            <a
-              class="banner-link"
-              href="https://link.springer.com/article/10.1007/s13244-017-0588-8"
-              target="_blank"
-              rel="noopener noreferrer"
-              >European Society of Radiology background paper</a
-            >.
-          </p>
-        </article>
-      </div>
-    </section>
-
-    <div class="interface-options-panel card">
-      <div class="interface-options-header" data-action="toggle-interface">
-        <h4 class="interface-options-title">Under the hood</h4>
-        <div class="interface-options-summary">
-          <span
-            >LX Generated Prompt • LX Structured Output • Cache controls</span
-          >
-          <span
-            class="material-symbols-outlined expand-icon"
-            id="interface-expand-icon"
-            >expand_more</span
-          >
-        </div>
-      </div>
-      <div
-        class="interface-options-content"
-        id="interface-options-content"
-        style="display: none"
-      >
-        <div class="interface-options-grid">
-          <div class="interface-option">
-            <div class="option-header">
-              <span class="material-symbols-outlined option-icon"
-                >visibility</span
-              >
-              <strong>LX Generated Prompt</strong>
-            </div>
-            <p class="option-description">
-              Inspect the task description, examples, and input sent to the
-              model.
-            </p>
-          </div>
-          <div class="interface-option">
-            <div class="option-header">
-              <span class="material-symbols-outlined option-icon">code</span>
-              <strong>LX Structured Output</strong>
-            </div>
-            <p class="option-description">
-              Inspect the raw extraction data and its grounding intervals.
-            </p>
-          </div>
-          <div class="interface-option">
-            <div class="option-header">
-              <span class="material-symbols-outlined option-icon">cached</span>
-              <strong>Use Cache</strong>
-            </div>
-            <p class="option-description">
-              Built-in samples use pre-generated results; edited reports use
-              live inference.
-            </p>
-          </div>
-        </div>
-      </div>
-    </div>
-
-    <section class="full-disclaimer card" aria-labelledby="safety-heading">
-      <span class="material-symbols-outlined disclaimer-icon" aria-hidden="true"
-        >health_and_safety</span
-      >
-      <div>
-        <h2 id="safety-heading">Safety, license, and citation</h2>
-        <p>
-          This demonstration is for illustrative purposes only to show the
-          baseline capabilities of LangExtract. It does not represent a finished
-          or approved product, is not intended to diagnose or suggest treatment
-          for any disease or condition, and should not be used for medical
-          advice.
-        </p>
-        <p>
-          If you use RadExtract or LangExtract in production or publications,
-          please cite accordingly and acknowledge usage. Use is subject to the
-          Apache 2.0 License. See the
-          <a
-            class="banner-link"
-            href="https://huggingface.co/spaces/google/radextract/blob/main/README.md#disclaimer"
-            target="_blank"
-            rel="noopener noreferrer"
-            >README for details</a
-          >.
-        </p>
-      </div>
-    </section>
-
     <script src="https://cdn.jsdelivr.net/npm/json-formatter-js@2.3.4/dist/json-formatter.umd.js"></script>
     <script src="https://cdn.jsdelivr.net/npm/marked@9.1.6/marked.min.js"></script>
-    <script
-      src="https://cdn.jsdelivr.net/npm/dompurify@3.4.12/dist/purify.min.js"
-      integrity="sha384-piCcpDdJ7qVeK4Tv8Z6Hpcr3ZBIgP16TxQTPVfsLFdZ5uDgwc3Y8Ho7oUnqf12qu"
-      crossorigin="anonymous"
-    ></script>
 
     <script src="https://cdnjs.cloudflare.com/ajax/libs/gsap/3.12.2/gsap.min.js"></script>
-    <script type="module" src="/static/script.js?v=20260721-studio"></script>
+    <script
+      type="module"
+      src="/static/script.js?v=20250125-refactored"
+    ></script>
 
     <!-- Bottom share placement (minimal space above footer) -->
     <div class="share-bottom">

test_app.py

@@ -8,20 +8,14 @@ Run with: python test_app.py or pytest test_app.py
 
 import json
 import os
-from pathlib import Path
-import tempfile
 import unittest
 from unittest import mock
 
 # Mock the environment before importing app to avoid initialization errors
 with mock.patch.dict(os.environ, {'KEY': 'test_api_key_for_import'}):
-    import app as app_module
     from app import Model, app, setup_cache
 
 
-_SENSITIVE_REPORT_TEXT = 'PRIVATE PATIENT FINDING'
-
-
 class TestFlaskApplication(unittest.TestCase):
 
     @classmethod
@@ -81,14 +75,10 @@ class TestFlaskApplication(unittest.TestCase):
             '/predict', data='Test report', headers=headers
         )
         self.assertEqual(response.status_code, 200)
-        mock_predict.assert_called_once_with(
-            'Test report', model_id='gemini-flash-latest'
-        )
+        mock_predict.assert_called_once_with('Test report', model_id='gemini-2.5-flash')
 
     @mock.patch('app.cache_manager.get_cached_result')
     def test_predict_with_cache_hit(self, mock_get_cached):
-        sample_data = json.loads(Path('static/sample_reports.json').read_text())
-        sample = sample_data['samples'][0]
         cached_response = {
             'segments': [{'type': 'body', 'content': 'cached'}],
             'text': 'cached result',
@@ -96,214 +86,13 @@ class TestFlaskApplication(unittest.TestCase):
         mock_get_cached.return_value = cached_response
 
         response = self.test_client.post(
-            '/predict',
-            data=sample['text'],
-            headers={
-                'X-Use-Cache': 'true',
-                'X-Sample-ID': sample['id'],
-            },
+            '/predict', data='Test report', headers={'X-Use-Cache': 'true'}
         )
 
         data = json.loads(response.data)
         self.assertTrue(data.get('from_cache'))
         self.assertIn('segments', data)
 
-    def test_matching_catalog_sample_uses_prebuilt_cache(self):
-        sample_data = json.loads(Path('static/sample_reports.json').read_text())
-        sample = sample_data['samples'][0]
-        cached_response = {'segments': [], 'text': 'cached result'}
-
-        with (
-            mock.patch.object(
-                app_module.cache_manager,
-                'get_cached_result',
-                autospec=True,
-                return_value=cached_response,
-            ) as mock_get_cached,
-            mock.patch.object(
-                app_module.model, 'predict', autospec=True
-            ) as mock_predict,
-        ):
-            response = self.test_client.post(
-                '/predict',
-                data=sample['text'],
-                headers={
-                    'X-Use-Cache': 'true',
-                    'X-Sample-ID': sample['id'],
-                },
-            )
-
-        self.assertEqual(response.status_code, 200)
-        self.assertTrue(response.get_json()['from_cache'])
-        mock_get_cached.assert_called_once()
-        mock_predict.assert_not_called()
-
-    def test_mismatched_catalog_sample_bypasses_cache(self):
-        cached_response = {'segments': [], 'text': 'wrong cached result'}
-        live_response = {'segments': [], 'text': 'live result'}
-
-        with (
-            mock.patch.object(
-                app_module.cache_manager,
-                'get_cached_result',
-                autospec=True,
-                return_value=cached_response,
-            ) as mock_get_cached,
-            mock.patch.object(
-                app_module.cache_manager, 'cache_result', autospec=True
-            ) as mock_cache_result,
-            mock.patch.object(
-                app_module.model,
-                'predict',
-                autospec=True,
-                return_value=live_response,
-            ) as mock_predict,
-        ):
-            response = self.test_client.post(
-                '/predict',
-                data='EXAMINATION: A report that is not the chest sample.',
-                headers={
-                    'X-Use-Cache': 'true',
-                    'X-Sample-ID': 'chest_xray',
-                },
-            )
-
-        self.assertEqual(response.status_code, 200)
-        self.assertFalse(response.get_json().get('from_cache', False))
-        mock_get_cached.assert_not_called()
-        mock_predict.assert_called_once()
-        mock_cache_result.assert_not_called()
-
-    def test_unknown_sample_id_is_never_cached(self):
-        live_response = {'segments': [], 'text': 'live result'}
-
-        with (
-            mock.patch.object(
-                app_module.cache_manager,
-                'get_cached_result',
-                autospec=True,
-            ) as mock_get_cached,
-            mock.patch.object(
-                app_module.cache_manager, 'cache_result', autospec=True
-            ) as mock_cache_result,
-            mock.patch.object(
-                app_module.model,
-                'predict',
-                autospec=True,
-                return_value=live_response,
-            ),
-        ):
-            response = self.test_client.post(
-                '/predict',
-                data='EXAMINATION: Unknown sample.',
-                headers={
-                    'X-Use-Cache': 'true',
-                    'X-Sample-ID': 'not_in_catalog',
-                },
-            )
-
-        self.assertEqual(response.status_code, 200)
-        mock_get_cached.assert_not_called()
-        mock_cache_result.assert_not_called()
-
-    def test_catalog_cache_miss_is_not_written_at_runtime(self):
-        sample_data = json.loads(Path('static/sample_reports.json').read_text())
-        sample = sample_data['samples'][0]
-        live_response = {'segments': [], 'text': 'live result'}
-
-        with (
-            mock.patch.object(
-                app_module.cache_manager,
-                'get_cached_result',
-                autospec=True,
-                return_value=None,
-            ),
-            mock.patch.object(
-                app_module.cache_manager, 'cache_result', autospec=True
-            ) as mock_cache_result,
-            mock.patch.object(
-                app_module.model,
-                'predict',
-                autospec=True,
-                return_value=live_response,
-            ),
-        ):
-            response = self.test_client.post(
-                '/predict',
-                data=sample['text'],
-                headers={
-                    'X-Use-Cache': 'true',
-                    'X-Sample-ID': sample['id'],
-                },
-            )
-
-        self.assertEqual(response.status_code, 200)
-        mock_cache_result.assert_not_called()
-
-    def test_unapproved_model_returns_stable_client_error(self):
-        with mock.patch.object(
-            app_module.model,
-            'predict',
-            autospec=True,
-            return_value={'segments': [], 'text': 'result'},
-        ) as mock_predict:
-            response = self.test_client.post(
-                '/predict',
-                data='FINDINGS: Normal chest.',
-                headers={
-                    'X-Use-Cache': 'false',
-                    'X-Model-ID': 'unapproved-model',
-                },
-            )
-
-        self.assertEqual(response.status_code, 400)
-        self.assertEqual(response.get_json()['error'], 'Unsupported model')
-        self.assertIn('message', response.get_json())
-        mock_predict.assert_not_called()
-
-    @mock.patch.dict(os.environ, {'MODEL_ID': 'configured-current-model'})
-    def test_environment_configured_model_is_allowed(self):
-        with mock.patch.object(
-            app_module.model,
-            'predict',
-            autospec=True,
-            return_value={'segments': [], 'text': 'result'},
-        ) as mock_predict:
-            response = self.test_client.post(
-                '/predict',
-                data='FINDINGS: Normal chest.',
-                headers={
-                    'X-Use-Cache': 'false',
-                    'X-Model-ID': 'configured-current-model',
-                },
-            )
-
-        self.assertEqual(response.status_code, 200)
-        mock_predict.assert_called_once_with(
-            'FINDINGS: Normal chest.', model_id='configured-current-model'
-        )
-
-    def test_legacy_pro_model_resolves_at_http_boundary(self):
-        with mock.patch.object(
-            app_module.model,
-            'predict',
-            autospec=True,
-            return_value={'segments': [], 'text': 'result'},
-        ) as mock_predict:
-            response = self.test_client.post(
-                '/predict',
-                data='FINDINGS: Normal chest.',
-                headers={
-                    'X-Use-Cache': 'false',
-                    'X-Model-ID': 'gemini-2.5-pro',
-                },
-            )
-
-        self.assertEqual(response.status_code, 200)
-        mock_predict.assert_called_once_with(
-            'FINDINGS: Normal chest.', model_id='gemini-pro-latest'
-        )
-
 
 class TestModelClass(unittest.TestCase):
 
@@ -311,7 +100,7 @@ class TestModelClass(unittest.TestCase):
     def test_model_initialization_with_api_key(self):
         model = Model()
         self.assertEqual(model.gemini_api_key, 'test_api_key')
-        self.assertIn('gemini-flash-latest', model._structurers)
+        self.assertIn('gemini-2.5-flash', model._structurers)
 
     @mock.patch.dict(os.environ, {}, clear=True)
     def test_model_initialization_without_api_key(self):
@@ -346,19 +135,6 @@ class TestModelClass(unittest.TestCase):
         mock_instance.predict.assert_called_once_with('test data')
         self.assertEqual(result, {'result': 'test'})
 
-    @mock.patch.dict(os.environ, {'KEY': 'test_key'})
-    @mock.patch('app.RadiologyReportStructurer')
-    def test_predict_does_not_log_report_content(self, mock_structurer_class):
-        mock_instance = mock.Mock()
-        mock_instance.predict.return_value = {'text': _SENSITIVE_REPORT_TEXT}
-        mock_structurer_class.return_value = mock_instance
-        model = Model()
-
-        with mock.patch.object(app_module.logger, 'info', autospec=True) as log:
-            model.predict(_SENSITIVE_REPORT_TEXT, 'gemini-flash-latest')
-
-        self.assertNotIn(_SENSITIVE_REPORT_TEXT, str(log.call_args_list))
-
 
 class TestCacheSetup(unittest.TestCase):
 
@@ -368,17 +144,13 @@ class TestCacheSetup(unittest.TestCase):
     def test_setup_cache_copies_existing_file(
         self, mock_makedirs, mock_copy, mock_exists
     ):
-        mock_exists.side_effect = [True, False]
+        mock_exists.return_value = True
 
-        with mock.patch.object(os.path, 'getsize', autospec=True, return_value=123):
-            cache_dir = setup_cache()
+        cache_dir = setup_cache()
 
-        expected_cache_dir = tempfile.gettempdir() + '/cache'
-        mock_makedirs.assert_called_once_with(expected_cache_dir, exist_ok=True)
-        mock_copy.assert_called_once_with(
-            'cache/sample_cache.json', expected_cache_dir + '/sample_cache.json'
-        )
-        self.assertEqual(cache_dir, expected_cache_dir)
+        mock_makedirs.assert_called_once_with('/tmp/cache', exist_ok=True)
+        mock_copy.assert_called_once()
+        self.assertEqual(cache_dir, '/tmp/cache')
 
     @mock.patch('os.path.exists')
     @mock.patch('os.makedirs')
@@ -387,9 +159,8 @@ class TestCacheSetup(unittest.TestCase):
 
         cache_dir = setup_cache()
 
-        expected_cache_dir = tempfile.gettempdir() + '/cache'
-        mock_makedirs.assert_called_once_with(expected_cache_dir, exist_ok=True)
-        self.assertEqual(cache_dir, expected_cache_dir)
+        mock_makedirs.assert_called_once_with('/tmp/cache', exist_ok=True)
+        self.assertEqual(cache_dir, '/tmp/cache')
 
 
 class TestErrorHandling(unittest.TestCase):
@@ -420,187 +191,18 @@ class TestErrorHandling(unittest.TestCase):
         self.assertEqual(response.status_code, 500)
 
         data = json.loads(response.data)
-        self.assertEqual(data['error'], 'Internal processing error')
-        self.assertIn('message', data)
-
-    @mock.patch('app.model.predict')
-    @mock.patch('app.logger')
-    def test_predict_handles_provider_error(self, mock_logger, mock_predict):
-        provider_error = RuntimeError(_SENSITIVE_REPORT_TEXT)
-        processing_error = app_module.ReportProcessingError('Report processing failed')
-        processing_error.__cause__ = provider_error
-        mock_predict.side_effect = processing_error
-
-        response = self.test_client.post('/predict', data='Test data')
-
-        self.assertEqual(response.status_code, 502)
-        data = response.get_json()
-        self.assertEqual(data['error'], 'Processing unavailable')
-        self.assertIn('message', data)
-        self.assertNotIn(_SENSITIVE_REPORT_TEXT, response.get_data(as_text=True))
-        self.assertNotIn(_SENSITIVE_REPORT_TEXT, str(mock_logger.method_calls))
+        self.assertIn('Processing error', data['error'])
 
     @mock.patch('app.model.predict')
     @mock.patch('app.logger')
     def test_predict_handles_general_exception(self, mock_logger, mock_predict):
-        mock_predict.side_effect = Exception(_SENSITIVE_REPORT_TEXT)
+        mock_predict.side_effect = Exception('General error')
 
         response = self.test_client.post('/predict', data='Test data')
         self.assertEqual(response.status_code, 500)
 
         data = json.loads(response.data)
-        self.assertEqual(data['error'], 'Internal processing error')
-        self.assertIn('message', data)
-        self.assertNotIn(_SENSITIVE_REPORT_TEXT, response.get_data(as_text=True))
-        self.assertNotIn(_SENSITIVE_REPORT_TEXT, str(mock_logger.method_calls))
-
-
-class TestFrontendAndProjectConfiguration(unittest.TestCase):
-
-    def test_demo_studio_contract_is_present_above_supporting_content(self):
-        response = app.test_client().get('/')
-        page = response.get_data(as_text=True)
-
-        self.assertEqual(response.status_code, 200)
-        self.assertIn('id="transformation-studio"', page)
-        self.assertIn('id="findings-cards"', page)
-        self.assertIn('id="studio-metrics"', page)
-        self.assertIn('role="tablist"', page)
-        self.assertIn('Research demonstration — not for clinical use', page)
-        self.assertLess(
-            page.index('id="transformation-studio"'),
-            page.index('id="how-it-works"'),
-        )
-
-    def test_default_sample_load_is_cached_and_has_no_simulated_delay(self):
-        script = Path('static/script.js').read_text()
-
-        self.assertIn("DEFAULT_SAMPLE_ID: 'chest_xray'", script)
-        self.assertIn('loadSampleReport(defaultSample, { scroll: false })', script)
-        self.assertIn("headers['X-Use-Cache'] = 'true'", script)
-        self.assertNotIn('Math.random() * 1000', script)
-        self.assertNotIn('window.location.search.length', script)
-        self.assertNotIn('window.location.hash.length', script)
-
-    def test_finding_cards_are_lossless_and_keep_alternate_views(self):
-        script = Path('static/script.js').read_text()
-        template = Path('templates/index.html').read_text()
-
-        self.assertIn('function renderFindingCards(segments)', script)
-        self.assertIn('segments.forEach((segment, index)', script)
-        self.assertIn('card.dataset.segmentIndex = String(index)', script)
-        self.assertIn('No source span', script)
-        self.assertIn('data-output-view="report"', template)
-        self.assertIn('data-output-view="raw"', template)
-        self.assertIn('id="prompt-toggle"', template)
-
-    def test_langextract_links_and_sample_copy_are_professional(self):
-        template = Path('templates/index.html').read_text()
-        stylesheet = Path('static/style.css').read_text()
-
-        self.assertIn('href="https://github.com/google/langextract"', template)
-        self.assertIn('LangExtract on GitHub', template)
-        self.assertIn('LangExtract release blog', template)
-        self.assertGreaterEqual(template.count('rel="noopener noreferrer"'), 2)
-        self.assertIn('<h2 id="sample-heading">Explore sample reports</h2>', template)
-        self.assertIn('Choose a study.', template)
-        self.assertNotIn('Explore a cached report', template)
-        self.assertNotIn('Results appear instantly from the demo cache.', template)
-        self.assertIn('.hero-attribution a:focus-visible', stylesheet)
-
-    def test_sample_grid_and_report_default_preserve_responsive_fallbacks(self):
-        script = Path('static/script.js').read_text()
-        stylesheet = Path('static/style.css').read_text()
-        template = Path('templates/index.html').read_text()
-
-        self.assertIn('grid-template-columns: repeat(5, minmax(0, 1fr));', stylesheet)
-        mobile_rules = stylesheet[stylesheet.index('@media (max-width: 768px)') :]
-        self.assertIn('.sample-buttons {', mobile_rules)
-        self.assertIn('display: flex;', mobile_rules)
-        self.assertIn('overflow-x: auto;', mobile_rules)
-        self.assertLess(
-            template.index('id="report-tab"'), template.index('id="findings-tab"')
-        )
-        self.assertIn("let preferredStructuredView = 'report';", script)
-        self.assertIn('selectOutputView(preferredStructuredView);', script)
-        self.assertGreaterEqual(script.count('remember: true'), 3)
-        self.assertIn(
-            "selectOutputView(showRaw ? 'raw' : 'cards', { remember: true });",
-            script,
-        )
-        self.assertIn("tab.getAttribute('aria-selected') === 'true'", script)
-        self.assertLess(
-            script.index(
-                "selectOutputView('cards');",
-                script.index('predictButton.addEventListener'),
-            ),
-            script.index(
-                'setOutputViewsAvailable(false);',
-                script.index('predictButton.addEventListener'),
-            ),
-        )
-        self.assertNotIn('balanceByColumnCount', script)
-        self.assertNotIn('BALANCE_DELAY', script)
-        self.assertNotIn('RESIZE_DEBOUNCE', script)
-
-    def test_mobile_and_reduced_motion_studio_rules_are_defined(self):
-        script = Path('static/script.js').read_text()
-        stylesheet = Path('static/style.css').read_text()
-
-        self.assertIn('@media (max-width: 768px)', stylesheet)
-        self.assertIn('.output-wrapper {', stylesheet)
-        self.assertIn('order: 1;', stylesheet)
-        self.assertIn('.input-wrapper {', stylesheet)
-        self.assertIn('order: 2;', stylesheet)
-        self.assertIn('@media (prefers-reduced-motion: reduce)', stylesheet)
-        self.assertIn('overflow-x: hidden;', stylesheet)
-        self.assertIn('function prefersReducedMotion()', script)
-        self.assertIn("behavior: prefersReducedMotion() ? 'auto' : 'smooth'", script)
-
-    def test_studio_fallback_and_accessibility_guards_are_present(self):
-        script = Path('static/script.js').read_text()
-        template = Path('templates/index.html').read_text()
-
-        self.assertIn('function resetStudioMetrics()', script)
-        self.assertGreaterEqual(script.count('resetStudioMetrics();'), 4)
-        self.assertIn('showGrounding({ focusInput: false })', script)
-        self.assertIn('sampleRunQueued = true', script)
-        self.assertGreaterEqual(script.count('if (sampleRunQueued) return;'), 2)
-        self.assertIn('let sampleLoadTimer = null', script)
-        self.assertIn('function setOutputViewsAvailable(available)', script)
-        self.assertIn('aria-controls="findings-cards"', template)
-        self.assertIn('role="tabpanel"', template)
-        self.assertIn('id="raw-toggle" tabindex="-1"', template)
-        self.assertIn('aria-disabled="true"', template)
-
-    def test_frontend_sanitizes_prompt_and_raw_fallback(self):
-        script = Path('static/script.js').read_text()
-        template = Path('templates/index.html').read_text()
-
-        self.assertIn('DOMPurify.sanitize', script)
-        self.assertIn('dompurify', template.lower())
-        self.assertIn('pre.textContent', script)
-        self.assertNotIn("rawOutput.innerHTML = '<pre", script)
-
-    def test_langextract_floor_supports_resolver_params(self):
-        project = Path('pyproject.toml').read_text()
-
-        self.assertIn('"langextract>=1.6.0,<2.0.0"', project)
-
-    def test_sample_preprocessing_is_idempotent_and_cache_is_complete(self):
-        samples = json.loads(Path('static/sample_reports.json').read_text())['samples']
-        cache = json.loads(Path('cache/sample_cache.json').read_text())
-
-        for sample in samples:
-            with self.subTest(sample=sample['id']):
-                normalized = app_module.preprocess_report(sample['text'])
-                self.assertEqual(app_module.preprocess_report(normalized), normalized)
-                self.assertIn(f"sample_{sample['id']}", cache)
-
-    def test_pytest_discovers_root_test_files_without_fallback(self):
-        project = Path('pyproject.toml').read_text()
-
-        self.assertIn('testpaths = ["test_app.py", "test_validation.py"]', project)
+        self.assertIn('General error', data['error'])
 
 
 if __name__ == '__main__':

test_validation.py

@@ -22,17 +22,12 @@ import unittest
 from typing import Any
 from unittest import mock
 
-import langextract as lx
-
 # Add the current directory to path for imports
 sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
 
 from structure_report import RadiologyReportStructurer
 
 
-_ORIGINAL_RESOLVER_ALIGN = lx.resolver.Resolver.align
-
-
 class TestRadiologyReportEndToEnd(unittest.TestCase):
     """End-to-end tests for complete RadiologyReportStructurer pipeline."""
 
@@ -100,28 +95,7 @@ class TestRadiologyReportEndToEnd(unittest.TestCase):
         mock_extract.assert_called_once()
         call_args = mock_extract.call_args
         self.assertEqual(call_args[1]['text_or_documents'], input_text)
-        self.assertEqual(call_args[1]['model_id'], 'gemini-flash-latest')
-        self.assertEqual(
-            call_args[1]['resolver_params'],
-            {
-                'accept_match_lesser': False,
-                'fuzzy_alignment_threshold': 0.50,
-            },
-        )
-
-    def test_legacy_pro_model_resolves_to_rolling_alias(self):
-        structurer = RadiologyReportStructurer(
-            api_key='test_key', model_id='gemini-2.5-pro'
-        )
-
-        self.assertEqual(structurer.model_id, 'gemini-pro-latest')
-
-    def test_current_model_id_is_preserved(self):
-        structurer = RadiologyReportStructurer(
-            api_key='test_key', model_id='gemini-3.5-flash'
-        )
-
-        self.assertEqual(structurer.model_id, 'gemini-3.5-flash')
+        self.assertEqual(call_args[1]['model_id'], 'gemini-2.5-flash')
 
     def test_all_cached_samples_validation(self):
         self.assertGreater(len(self.sample_data), 0, 'No samples found in cache')
@@ -141,54 +115,19 @@ class TestRadiologyReportEndToEnd(unittest.TestCase):
     def test_error_handling_with_no_api_key(self):
         error_structurer = RadiologyReportStructurer(api_key=None)
 
-        with mock.patch.object(
-            lx,
-            'extract',
-            autospec=True,
-            side_effect=RuntimeError('sensitive provider detail'),
-        ):
-            with self.assertRaisesRegex(RuntimeError, 'Report processing failed'):
-                error_structurer.predict('EXAMINATION: Test')
+        response = error_structurer.predict('EXAMINATION: Test')
+
+        self._validate_response_structure(response)
+        self.assertEqual(len(response['segments']), 0)
+        self.assertIn('Error processing report', response['text'])
 
-    def test_predict_does_not_patch_global_resolver(self):
+    def test_patch_initialization_on_first_use(self):
         new_structurer = RadiologyReportStructurer()
 
-        with mock.patch.object(lx, 'extract', autospec=True) as mock_extract:
-            mock_result = mock.MagicMock()
-            mock_result.extractions = []
-            mock_extract.return_value = mock_result
-            new_structurer.predict('EXAMINATION: Test')
-
-        self.assertIs(lx.resolver.Resolver.align, _ORIGINAL_RESOLVER_ALIGN)
-
-    def test_resolver_settings_reject_partial_exact_matches(self):
-        source_text = 'No acute disease.'
-        extraction_text = 'No acute disease absent invented words words words words.'
-
-        accepted = list(
-            lx.resolver.Resolver().align(
-                [lx.data.Extraction('finding', extraction_text)],
-                source_text,
-                token_offset=0,
-                accept_match_lesser=True,
-                fuzzy_alignment_threshold=0.50,
-            )
-        )
-        rejected = list(
-            lx.resolver.Resolver().align(
-                [lx.data.Extraction('finding', extraction_text)],
-                source_text,
-                token_offset=0,
-                accept_match_lesser=False,
-                fuzzy_alignment_threshold=0.50,
-            )
-        )
+        self.assertFalse(new_structurer._patches_initialized)
 
-        self.assertEqual(
-            accepted[0].alignment_status, lx.data.AlignmentStatus.MATCH_LESSER
-        )
-        self.assertIsNone(rejected[0].alignment_status)
-        self.assertIsNone(rejected[0].char_interval)
+        new_structurer._ensure_patches_initialized()
+        self.assertTrue(new_structurer._patches_initialized)
 
     def test_section_mapping_core_functionality(self):
         self.assertEqual(

tools/rebuild_cache.py

@@ -13,7 +13,7 @@ to use for processing.
 
 Usage:
     export KEY=your_gemini_api_key_here
-    export MODEL_ID=gemini-flash-latest  # optional, defaults to Gemini Flash
+    export MODEL_ID=gemini-2.5-pro  # optional, defaults to gemini-2.5-pro
     python tools/rebuild_cache.py
 """
 import json
@@ -37,7 +37,7 @@ if not SAMPLES_PATH.exists():
 
 samples = json.loads(SAMPLES_PATH.read_text())["samples"]
 
-MODEL_ID = os.environ.get("MODEL_ID", "gemini-flash-latest")
+MODEL_ID = os.environ.get("MODEL_ID", "gemini-2.5-pro")
 structurer = RadiologyReportStructurer(api_key=API_KEY, model_id=MODEL_ID)
 
 import time