Update app.py

app.py

@@ -1,5 +1,8 @@
 # app.py
 
+import os
+from typing import List, Any
+
 import gradio as gr
 from PIL import Image
 
@@ -12,54 +15,64 @@ cbc = SmartCBC()   # loads YOLO + classifier once
 
 
 # -------------------------------------------------
-# Helper to normalize Gallery input
+# Helper: convert uploaded files to PIL Images
 # -------------------------------------------------
-def _normalize_gallery_images(images):
+def files_to_pil_list(files: List[Any]) -> List[Image.Image]:
     """
-    Gradio Gallery (type='pil') can return:
-      - list[PIL.Image]
-      - or list[(PIL.Image, metadata_dict)]
+    Gradio Files (file_count='multiple') returns a list of file objects or dicts.
+
+    Each item commonly looks like:
+      - {"name": "/tmp/....png", "orig_name": "...", ...}
+      - or a file-like object with .name
 
-    This function strips metadata if present and returns a flat list of images.
+    This helper normalizes them into a list of RGB PIL Images.
     """
-    if images is None:
-        return []
-
-    normalized = []
-    for item in images:
-        # Sometimes (media, metadata), sometimes media only
-        if isinstance(item, tuple):
-            media = item[0]
+    pil_list: List[Image.Image] = []
+
+    if files is None:
+        return pil_list
+
+    for f in files:
+        # Newer gradio often returns dicts with "name"
+        if isinstance(f, dict) and "name" in f:
+            path = f["name"]
+        # Older style: File object with .name
+        elif hasattr(f, "name"):
+            path = f.name
+        # Fallback: assume it's already a path-like
         else:
-            media = item
-        normalized.append(media)
-    return normalized
+            path = str(f)
+
+        if not os.path.isfile(path):
+            raise FileNotFoundError(f"Uploaded file not found on disk: {path}")
+
+        img = Image.open(path).convert("RGB")
+        pil_list.append(img)
+
+    return pil_list
 
 
 # -------------------------------------------------
 # Core Gradio wrapper
 # -------------------------------------------------
-def analyze_images(images, age, gender, output_mode):
+def analyze_images(files, age, gender, output_mode):
     """
     Wrapper for SmartCBC.analyze().
 
-    - Accepts one or multiple images from a Gradio Gallery.
-    - Delegates to SmartCBC.analyze(), which auto-routes to analyze_batch()
-      if a list of images is provided.
+    - Accepts one or multiple images from a Gradio Files input.
+    - If a single image -> sends a single PIL.Image
+      If multiple -> sends a list[Image.Image] (SmartCBC can route to analyze_batch).
     - Returns either a human-readable text report or full JSON.
     """
-    # No images
-    if images is None or len(images) == 0:
+    if files is None or len(files) == 0:
         return "Please upload at least one image.", None
 
-    # Normalize gallery output (strip metadata if any)
-    img_list = _normalize_gallery_images(images)
+    pil_images = files_to_pil_list(files)
 
-    # If single image, send just that; if multiple, send list → analyze_batch
-    if len(img_list) == 1:
-        image_input = img_list[0]
+    if len(pil_images) == 1:
+        image_input = pil_images[0]
     else:
-        image_input = img_list
+        image_input = pil_images
 
     # Run SmartCBC pipeline
     result = cbc.analyze(
@@ -70,15 +83,13 @@ def analyze_images(images, age, gender, output_mode):
 
     # Choose output mode
     if output_mode == "Text Report":
-        # result["report_text"] is produced by build_api_response()
         return result.get("report_text", "No report generated."), None
     else:
-        # Show full structured JSON
         return None, result
 
 
 # -------------------------------------------------
-# Gradio UI Layout
+# Gradio UI Layout (compatible with Gradio 4.0.0)
 # -------------------------------------------------
 with gr.Blocks(title="SmartCBC - Multimodal Blood Analysis") as demo:
 
@@ -96,13 +107,11 @@ with gr.Blocks(title="SmartCBC - Multimodal Blood Analysis") as demo:
     )
 
     with gr.Row():
-        img_in = gr.Gallery(
+        # Use Files for multi-image upload (works on Gradio 4.0.0)
+        img_in = gr.Files(
             label="Upload 1 or Multiple Blood Smear Images (FOVs)",
-            columns=3,
-            height="auto",
-            allow_preview=True,
-            type="pil",          # works with gradio==4.44.1
-            file_types=["image"] # ensure only images are selectable
+            file_count="multiple",
+            file_types=["image"],
         )
 
         with gr.Column():