fixed+improved UI

app.py

@@ -1,138 +1,170 @@
-import os
 import gradio as gr
+import uuid
+import base64
+import io
 from qdrant_client import QdrantClient
-from qdrant_client.http import models
+from qdrant_client.models import PointStruct, VectorParams, Distance
 from sentence_transformers import SentenceTransformer
 from PIL import Image
-from dotenv import load_dotenv
 
-# Load environment variables from .env
-load_dotenv()
-
-# Get Qdrant Cloud credentials (must be in .env or deployment secrets)
-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")
+# --------------------------
+# Qdrant Cloud Connection
+# --------------------------
+QDRANT_URL = "https://ff4da494-27b1-413c-ba58-d5ea14932fe1.europe-west3-0.gcp.cloud.qdrant.io:6333"
+QDRANT_API_KEY = "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJhY2Nlc3MiOiJtIn0.jjeB1JgnUSlb1hOOKMdRpVvMrUER57-udT-X1AWXT1E"
 COLLECTION_NAME = "lost_and_found"
 
-# Check creds
-if not QDRANT_URL or not QDRANT_API_KEY:
-    raise RuntimeError(
-        "❌ Missing Qdrant Cloud credentials. Please set QDRANT_URL and QDRANT_API_KEY in your environment."
-    )
+# CLIP model (text + image embeddings)
+MODEL_NAME = "sentence-transformers/clip-ViT-B-32"
+embedder = SentenceTransformer(MODEL_NAME)
 
-# Initialize Qdrant client
-qclient = QdrantClient(url=QDRANT_URL, api_key=QDRANT_API_KEY)
+# CLIP ViT-B/32 always gives 512-dimensional embeddings
+VECTOR_SIZE = 512
 
-# Load sentence transformer model
-model = SentenceTransformer("clip-ViT-B-32")
+# Qdrant Client (Cloud)
+qclient = QdrantClient(
+    url=QDRANT_URL,
+    api_key=QDRANT_API_KEY
+)
 
-# 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),
-    )
+# 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")
+
+def base64_to_image(b64_str: str) -> Image.Image:
+    img_bytes = base64.b64decode(b64_str)
+    return Image.open(io.BytesIO(img_bytes))
+
+def embed_text(text: str):
+    return embedder.encode(text).tolist()
+
+def embed_image(img: Image.Image):
+    return embedder.encode(img).tolist()
+
+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."
 
-# 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."
+    embedding = embed_image(image)
+    img_b64 = image_to_base64(image)
 
-    # Encode description and image
-    vector_desc = model.encode(description).tolist()
-    vector_img = model.encode(Image.open(image)).tolist()
+    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
+    }
 
-    # Upload to Qdrant (store both text & image vectors)
     qclient.upsert(
         collection_name=COLLECTION_NAME,
         points=[
-            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},
-            ),
-        ],
+            PointStruct(
+                id=str(uuid.uuid4()),
+                vector=embedding,
+                payload=metadata
+            )
+        ]
     )
+    return "Item successfully added!"
 
-    return f"✅ Item added successfully: {description}"
-
-# Search function (text or image)
-def search_items(text_query, image_query):
-    search_results = []
-
-    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"))
-            )
+def search_items(query_text, query_image):
+    if not query_text and query_image is None:
+        return "Please enter text or upload an image to search.", []
+
+    if query_image:
+        query_vector = embed_image(query_image)
+    else:
+        query_vector = embed_text(query_text)
 
-    if not unique_results:
-        return [("not_found.png", "No match found")]
+    results = qclient.search(
+        collection_name=COLLECTION_NAME,
+        query_vector=query_vector,
+        limit=5
+    )
 
-    return unique_results
+    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 successfully."
 
+# --------------------------
 # Gradio UI
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
+# --------------------------
+
+with gr.Blocks() as demo:
     gr.Markdown(
         """
-        # 🔍 Lost & Found Database  
-        Upload found items or search using text/image.
+        # Lost & Found System  
+        A simple platform to add and search lost items.  
         """
     )
 
-    with gr.Tab("➕ Add Items"):
+    with gr.Tab("Add Item"):
+        gr.Markdown("### Add a Found Item")
         with gr.Row():
-            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"):
+            image_in = gr.Image(type="pil", label="Upload Image")
+            desc_in = gr.Textbox(label="Item Description")
+        with gr.Row():
+            finder_name = gr.Textbox(label="Finder's Name (optional)")
+            finder_phone = gr.Textbox(label="Finder's Phone Number (optional)")
+        add_btn = gr.Button("Submit Item", variant="primary")
+        add_output = gr.Textbox(label="Status", interactive=False)
+
+    with gr.Tab("Search"):
+        gr.Markdown("### Search Lost Items")
         with gr.Row():
-            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)
-
-# Launch app
+            search_text = gr.Textbox(label="Search by Text")
+            search_image = gr.Image(type="pil", label="Or Upload Image")
+        search_btn = gr.Button("Search", variant="primary")
+        search_output = gr.Markdown()
+        gallery = gr.Gallery(label="Matched Items", show_label=True, elem_id="gallery")
+
+    with gr.Tab("Admin"):
+        gr.Markdown("### Admin Controls")
+        clear_btn = gr.Button("Clear Database", variant="stop")
+        clear_output = gr.Textbox(label="Status", interactive=False)
+
+    # Button 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 App
+# --------------------------
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(server_name="0.0.0.0", server_port=7860)