fixed + improved UI

app.py

@@ -1,165 +1,138 @@
+import os
 import gradio as gr
-import uuid
-import base64
-import io
 from qdrant_client import QdrantClient
-from qdrant_client.models import PointStruct, VectorParams, Distance
+from qdrant_client.http import models
 from sentence_transformers import SentenceTransformer
 from PIL import Image
+from dotenv import load_dotenv
 
-# --------------------------
-# Qdrant Cloud Connection
-# --------------------------
-QDRANT_URL = "https://ff4da494-27b1-413c-ba58-d5ea14932fe1.europe-west3-0.gcp.cloud.qdrant.io:6333"  # 🔑 Replace with your cluster URL
-QDRANT_API_KEY = "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJhY2Nlc3MiOiJtIn0.jjeB1JgnUSlb1hOOKMdRpVvMrUER57-udT-X1AWXT1E"                   
-COLLECTION_NAME = "lost_and_found"
-
-# CLIP model (text + image embeddings)
-MODEL_NAME = "sentence-transformers/clip-ViT-B-32"
-embedder = SentenceTransformer(MODEL_NAME)
-
-VECTOR_SIZE = 512  # CLIP always outputs 512-dim vectors
-
-# Qdrant Client
-qclient = QdrantClient(url=QDRANT_URL, api_key=QDRANT_API_KEY)
-
-# Ensure collection exists
-qclient.recreate_collection(
-    collection_name=COLLECTION_NAME,
-    vectors_config=VectorParams(size=VECTOR_SIZE, distance=Distance.COSINE),
-)
-
-# --------------------------
-# Helper Functions
-# --------------------------
-
-def image_to_base64(img: Image.Image) -> str:
-    buf = io.BytesIO()
-    img.save(buf, format="PNG")
-    return base64.b64encode(buf.getvalue()).decode("utf-8")
+# Load environment variables (.env file for local development)
+load_dotenv()
 
-def base64_to_image(b64_str: str) -> Image.Image:
-    img_bytes = base64.b64decode(b64_str)
-    return Image.open(io.BytesIO(img_bytes))
+# Get Qdrant Cloud credentials (set these in your .env or hosting platform)
+QDRANT_URL = os.getenv("https://ff4da494-27b1-413c-ba58-d5ea14932fe1.europe-west3-0.gcp.cloud.qdrant.io:6333")
+QDRANT_API_KEY = os.getenv("eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJhY2Nlc3MiOiJtIn0.jjeB1JgnUSlb1hOOKMdRpVvMrUER57-udT-X1AWXT1E")
+COLLECTION_NAME = "lost_and_found"
 
-def embed_text(text: str):
-    return embedder.encode(text).tolist()
+# Load sentence transformer model
+model = SentenceTransformer("clip-ViT-B-32")
 
-def embed_image(img: Image.Image):
-    return embedder.encode(img).tolist()
+# Initialize Qdrant client (Cloud if creds exist, else local)
+if QDRANT_URL and QDRANT_API_KEY:
+    qclient = QdrantClient(
+        url=QDRANT_URL,
+        api_key=QDRANT_API_KEY,
+    )
+else:
+    qclient = QdrantClient("localhost", port=6333)
 
-def add_item(image, description, finder_name, finder_phone):
-    if image is None or description.strip() == "":
-        return "Please provide both an image and a description."
+# Create collection if it doesn’t exist
+if not qclient.collection_exists(COLLECTION_NAME):
+    qclient.create_collection(
+        collection_name=COLLECTION_NAME,
+        vectors_config=models.VectorParams(size=512, distance=models.Distance.COSINE),
+    )
 
-    embedding = embed_image(image)
-    img_b64 = image_to_base64(image)
+# Add item function
+def add_item(image, description):
+    if image is None or not description.strip():
+        return "❌ Please provide both an image and a description."
 
-    metadata = {
-        "description": description,
-        "finder_name": finder_name if finder_name.strip() else "NA",
-        "finder_phone": finder_phone if finder_phone.strip() else "NA",
-        "image_b64": img_b64
-    }
+    # Encode description and image
+    vector_desc = model.encode(description).tolist()
+    vector_img = model.encode(Image.open(image)).tolist()
 
+    # Upload to Qdrant (store both)
     qclient.upsert(
         collection_name=COLLECTION_NAME,
         points=[
-            PointStruct(
-                id=str(uuid.uuid4()),
-                vector=embedding,
-                payload=metadata
-            )
-        ]
+            models.PointStruct(
+                id=None,
+                vector=vector_desc,
+                payload={"description": description, "image": image.name},
+            ),
+            models.PointStruct(
+                id=None,
+                vector=vector_img,
+                payload={"description": description, "image": image.name},
+            ),
+        ],
     )
-    return "Item successfully added."
 
-def search_items(query_text, query_image):
-    if not query_text and query_image is None:
-        return "Enter text or upload an image to search.", []
+    return f"✅ Item added successfully: {description}"
 
-    if query_image:
-        query_vector = embed_image(query_image)
-    else:
-        query_vector = embed_text(query_text)
+# Search function (text or image)
+def search_items(text_query, image_query):
+    search_results = []
 
-    results = qclient.search(
-        collection_name=COLLECTION_NAME,
-        query_vector=query_vector,
-        limit=5
-    )
+    if text_query and text_query.strip():
+        vector = model.encode(text_query).tolist()
+        hits = qclient.search(
+            collection_name=COLLECTION_NAME,
+            query_vector=vector,
+            limit=5,
+        )
+        search_results.extend(hits)
+
+    if image_query is not None:
+        vector = model.encode(Image.open(image_query)).tolist()
+        hits = qclient.search(
+            collection_name=COLLECTION_NAME,
+            query_vector=vector,
+            limit=5,
+        )
+        search_results.extend(hits)
+
+    # Remove duplicates by description
+    seen = set()
+    unique_results = []
+    for hit in search_results:
+        desc = hit.payload.get("description")
+        if desc not in seen:
+            seen.add(desc)
+            unique_results.append(
+                (hit.payload.get("image"), hit.payload.get("description"))
+            )
 
-    if not results:
-        return "No matches found.", []
-
-    gallery = []
-    output_text = "### Matches Found:\n\n"
-    for r in results:
-        desc = r.payload.get("description", "No description")
-        name = r.payload.get("finder_name", "NA")
-        phone = r.payload.get("finder_phone", "NA")
-        output_text += f"- **{desc}** (Finder: {name}, Phone: {phone})\n"
-
-        if "image_b64" in r.payload:
-            try:
-                img = base64_to_image(r.payload["image_b64"])
-                gallery.append(img)
-            except Exception:
-                pass
-
-    return output_text, gallery
-
-def clear_database():
-    qclient.delete_collection(COLLECTION_NAME)
-    qclient.recreate_collection(
-        collection_name=COLLECTION_NAME,
-        vectors_config=VectorParams(size=VECTOR_SIZE, distance=Distance.COSINE),
-    )
-    return "Database cleared."
+    if not unique_results:
+        return [("not_found.png", "No match found")]
 
-# --------------------------
-# Gradio UI
-# --------------------------
+    return unique_results
 
+# Gradio UI
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
     gr.Markdown(
         """
-        # Lost & Found System
-        Upload, search, and manage found items with text or image queries.
+        # 🔍 Lost & Found Database  
+        Upload found items or search using text/image.
         """
     )
 
-    with gr.Tab("Add Item"):
-        with gr.Row():
-            image_in = gr.Image(type="pil", label="Upload Image", height=250)
-            desc_in = gr.Textbox(label="Item Description", placeholder="e.g. Silver keychain with tag")
+    with gr.Tab("➕ Add Items"):
         with gr.Row():
-            finder_name = gr.Textbox(label="Finder's Name", placeholder="John Doe")
-            finder_phone = gr.Textbox(label="Finder's Phone", placeholder="+123456789")
-        add_btn = gr.Button("Add Item", variant="primary")
-        add_output = gr.Textbox(label="Status", interactive=False)
-
-    with gr.Tab("Search"):
+            with gr.Column():
+                add_img = gr.Image(type="filepath", label="Upload Image")
+                add_desc = gr.Textbox(label="Description", placeholder="e.g. Silver key with round head")
+                add_btn = gr.Button("Add Item")
+                add_output = gr.Textbox(label="Status", interactive=False)
+        add_btn.click(fn=add_item, inputs=[add_img, add_desc], outputs=add_output)
+
+    with gr.Tab("🔎 Search"):
         with gr.Row():
-            search_text = gr.Textbox(label="Search by Text", placeholder="Enter keywords...")
-            search_image = gr.Image(type="pil", label="Or Search by Image", height=250)
-        search_btn = gr.Button("Search", variant="primary")
-        search_output = gr.Markdown(label="Results")
-        gallery = gr.Gallery(label="Matched Items", show_label=True, elem_id="gallery").style(
-            grid=[2], height="auto"
+            with gr.Column():
+                search_text = gr.Textbox(label="Search by Text", placeholder="e.g. key, wallet, phone")
+                search_img = gr.Image(type="filepath", label="Or Search by Image")
+                search_btn = gr.Button("Search")
+        gallery = gr.Gallery(
+            label="Matched Items",
+            show_label=True,
+            elem_id="gallery",
+            columns=[3],
+            rows=[2],
+            height="auto"
         )
+        search_btn.click(fn=search_items, inputs=[search_text, search_img], outputs=gallery)
 
-    with gr.Tab("Admin"):
-        clear_btn = gr.Button("Clear Database", variant="stop")
-        clear_output = gr.Textbox(label="Status", interactive=False)
-
-    # Actions
-    add_btn.click(add_item, inputs=[image_in, desc_in, finder_name, finder_phone], outputs=add_output)
-    search_btn.click(search_items, inputs=[search_text, search_image], outputs=[search_output, gallery])
-    clear_btn.click(clear_database, outputs=clear_output)
-
-# --------------------------
-# Launch
-# --------------------------
+# Launch app
 if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7860)
+    demo.launch()