v11

app.py

@@ -1,50 +1,50 @@
+import os
+import uuid
 import gradio as gr
-from qdrant_client import QdrantClient
-from qdrant_client.http import models
-from sentence_transformers import SentenceTransformer
 from PIL import Image
-import uuid
-import os
+from qdrant_client import QdrantClient, models
+from transformers import CLIPProcessor, CLIPModel
 
-# ------------------------------
+# ==============================
 # Setup
-# ------------------------------
-COLLECTION = "lost_and_found"
+# ==============================
 UPLOAD_DIR = "uploaded_images"
 os.makedirs(UPLOAD_DIR, exist_ok=True)
 
-# Connect to Qdrant (local or remote)
-qclient = QdrantClient(path="qdrant_db")
+qclient = QdrantClient(":memory:")
+COLLECTION = "lost_and_found"
 
-# SentenceTransformer model
-model = SentenceTransformer("clip-ViT-B-32")
+# Create collection (with deprecation fix)
+if not qclient.collection_exists(COLLECTION):
+    qclient.create_collection(
+        COLLECTION,
+        vectors_config=models.VectorParams(size=512, distance=models.Distance.COSINE),
+    )
 
-# Recreate collection
-if qclient.collection_exists(COLLECTION):
-    qclient.delete_collection(COLLECTION)
+# Load CLIP
+clip_model = CLIPModel.from_pretrained("openai/clip-vit-base-patch32")
+clip_proc = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32")
 
-qclient.create_collection(
-    COLLECTION,
-    vectors_config=models.VectorParams(size=512, distance=models.Distance.COSINE),
-)
 
-# ------------------------------
-# Helper functions
-# ------------------------------
+# ==============================
+# Encode Function
+# ==============================
 def encode_data(text=None, image=None):
-    """Encode text or image into vector"""
-    if text and image:
-        text_vec = model.encode([text], convert_to_tensor=False)[0]
-        img_vec = model.encode([image], convert_to_tensor=False)[0]
-        return (text_vec + img_vec) / 2
-    elif text:
-        return model.encode([text], convert_to_tensor=False)[0]
-    elif image:
-        return model.encode([image], convert_to_tensor=False)[0]
-    else:
-        raise ValueError("No input provided")
-
-def add_item(mode, text, image, finder_name, finder_phone):
+    if text:
+        inputs = clip_proc(text=[text], return_tensors="pt", padding=True)
+        return clip_model.get_text_features(**inputs).detach().numpy()[0]
+
+    if image:
+        inputs = clip_proc(images=image, return_tensors="pt")
+        return clip_model.get_image_features(**inputs).detach().numpy()[0]
+
+    raise ValueError("Need either text or image for encoding")
+
+
+# ==============================
+# Add Item
+# ==============================
+def add_item(mode, text, image, uploader_name, uploader_phone):
     try:
         img_path = None
         if image:
@@ -63,8 +63,8 @@ def add_item(mode, text, image, finder_name, finder_phone):
                     payload={
                         "mode": mode,
                         "text": text or "",
-                        "finder_name": finder_name if mode == "found" else "",
-                        "finder_phone": finder_phone if mode == "found" else "",
+                        "uploader_name": uploader_name or "N/A",
+                        "uploader_phone": uploader_phone or "N/A",
                         "image_path": img_path,
                         "has_image": bool(image),
                     },
@@ -75,6 +75,10 @@ def add_item(mode, text, image, finder_name, finder_phone):
     except Exception as e:
         return f"❌ Error: {e}"
 
+
+# ==============================
+# Search Items
+# ==============================
 def search_items(text, image, max_results, min_score):
     try:
         vector = encode_data(text=text if text else None, image=image if image else None)
@@ -94,10 +98,10 @@ def search_items(text, image, max_results, min_score):
                 f"id:{r.id} | score:{r.score:.3f} | mode:{p.get('mode','')} | text:{p.get('text','')}"
             )
 
-            # Always show finder info
-            finder_name = p.get("finder_name", "N/A") or "N/A"
-            finder_phone = p.get("finder_phone", "N/A") or "N/A"
-            desc += f" | finder:{finder_name} ({finder_phone})"
+            # Always show uploader details
+            uploader_name = p.get("uploader_name", "N/A") or "N/A"
+            uploader_phone = p.get("uploader_phone", "N/A") or "N/A"
+            desc += f" | uploader:{uploader_name} ({uploader_phone})"
 
             texts.append(desc)
             if p.get("has_image") and "image_path" in p:
@@ -106,63 +110,61 @@ def search_items(text, image, max_results, min_score):
     except Exception as e:
         return f"❌ Error: {e}", []
 
-def delete_all():
-    try:
-        qclient.delete_collection(COLLECTION)
-        qclient.create_collection(
-            COLLECTION,
-            vectors_config=models.VectorParams(size=512, distance=models.Distance.COSINE),
-        )
-        return "🗑️ All items deleted!"
-    except Exception as e:
-        return f"❌ Error: {e}"
 
-# ------------------------------
+# ==============================
+# Delete All
+# ==============================
+def clear_all():
+    qclient.recreate_collection(
+        COLLECTION, vectors_config=models.VectorParams(size=512, distance=models.Distance.COSINE)
+    )
+    return "🗑️ All items cleared."
+
+
+# ==============================
 # Gradio UI
-# ------------------------------
+# ==============================
 with gr.Blocks() as demo:
-    gr.Markdown("## 🔑 Lost & Found System")
+    gr.Markdown("# 🔑 Lost & Found Image/Text Search")
 
-    with gr.Tab("Add Item"):
-        mode = gr.Radio(["lost", "found"], label="Mode", value="lost")
-        text_in = gr.Textbox(label="Description")
+    with gr.Tab("➕ Add Item"):
+        mode = gr.Radio(["lost", "found"], label="Mode", value="found")
+        text_in = gr.Textbox(label="Description (optional)")
         img_in = gr.Image(type="pil", label="Upload Image")
-
-        finder_name = gr.Textbox(label="Finder Name (only if found)")
-        finder_phone = gr.Textbox(label="Finder Phone (only if found)")
-
+        uploader_name = gr.Textbox(label="Your Name")
+        uploader_phone = gr.Textbox(label="Your Phone")
         add_btn = gr.Button("Add to Database")
         add_out = gr.Textbox(label="Status")
 
         add_btn.click(
             add_item,
-            inputs=[mode, text_in, img_in, finder_name, finder_phone],
+            inputs=[mode, text_in, img_in, uploader_name, uploader_phone],
             outputs=add_out,
         )
 
-    with gr.Tab("Search"):
-        text_s = gr.Textbox(label="Search by text (optional)")
-        img_s = gr.Image(type="pil", label="Search by image (optional)")
-        max_r = gr.Slider(1, 10, value=5, step=1, label="Max results")
-        min_s = gr.Slider(0.5, 1.0, value=0.8, step=0.01, label="Min similarity threshold")
-
+    with gr.Tab("🔍 Search"):
+        search_text = gr.Textbox(label="Search by text (optional)")
+        search_img = gr.Image(type="pil", label="Search by image (optional)")
+        max_results = gr.Slider(1, 10, value=5, step=1, label="Max results")
+        min_score = gr.Slider(0.5, 1.0, value=0.8, step=0.01, label="Min similarity threshold")
         search_btn = gr.Button("Search")
-        search_out_text = gr.Textbox(label="Search results (text)")
-        search_gallery = gr.Gallery(label="Search Results", columns=2, height="auto")
+        search_out = gr.Textbox(label="Search results (text)")
+        search_gallery = gr.Gallery(label="Search Results")
 
         search_btn.click(
             search_items,
-            inputs=[text_s, img_s, max_r, min_s],
-            outputs=[search_out_text, search_gallery],
+            inputs=[search_text, search_img, max_results, min_score],
+            outputs=[search_out, search_gallery],
         )
 
-    with gr.Tab("Admin"):
-        del_btn = gr.Button("Delete All Items")
-        del_out = gr.Textbox(label="Status")
-        del_btn.click(delete_all, outputs=del_out)
+    with gr.Tab("🗑️ Admin"):
+        clear_btn = gr.Button("Clear All Items")
+        clear_out = gr.Textbox(label="Status")
+        clear_btn.click(clear_all, outputs=clear_out)
+
 
-# ------------------------------
+# ==============================
 # Launch
-# ------------------------------
+# ==============================
 if __name__ == "__main__":
     demo.launch()