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Runtime error
Runtime error
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Β·
47edb75
1
Parent(s):
27514c1
fixed with UI improved
Browse files
app.py
CHANGED
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@@ -10,22 +10,18 @@ from PIL import Image
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# --------------------------
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# Qdrant Cloud Connection
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# --------------------------
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QDRANT_URL = "https://
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QDRANT_API_KEY = "
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COLLECTION_NAME = "lost_and_found"
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# CLIP model (text + image embeddings)
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MODEL_NAME = "sentence-transformers/clip-ViT-B-32"
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embedder = SentenceTransformer(MODEL_NAME)
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# CLIP
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VECTOR_SIZE = 512
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# Qdrant Client
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qclient = QdrantClient(
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url=QDRANT_URL,
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api_key=QDRANT_API_KEY
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)
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# Ensure collection exists
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qclient.recreate_collection(
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@@ -38,13 +34,11 @@ qclient.recreate_collection(
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# --------------------------
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def image_to_base64(img: Image.Image) -> str:
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"""Convert PIL image to base64 string"""
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buf = io.BytesIO()
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img.save(buf, format="PNG")
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return base64.b64encode(buf.getvalue()).decode("utf-8")
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def base64_to_image(b64_str: str) -> Image.Image:
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"""Convert base64 string back to PIL image"""
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img_bytes = base64.b64decode(b64_str)
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return Image.open(io.BytesIO(img_bytes))
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@@ -55,15 +49,12 @@ def embed_image(img: Image.Image):
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return embedder.encode(img).tolist()
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def add_item(image, description, finder_name, finder_phone):
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"""Add a found item to Qdrant database"""
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if image is None or description.strip() == "":
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return "
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# Encode image
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embedding = embed_image(image)
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img_b64 = image_to_base64(image)
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# Store metadata including image
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metadata = {
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"description": description,
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"finder_name": finder_name if finder_name.strip() else "NA",
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@@ -71,7 +62,6 @@ def add_item(image, description, finder_name, finder_phone):
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"image_b64": img_b64
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}
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# Insert into Qdrant
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qclient.upsert(
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collection_name=COLLECTION_NAME,
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points=[
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@@ -82,20 +72,17 @@ def add_item(image, description, finder_name, finder_phone):
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)
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]
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)
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return "
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def search_items(query_text, query_image):
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"""Search by text or image"""
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if not query_text and query_image is None:
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return "
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# Use text or image embedding
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if query_image:
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query_vector = embed_image(query_image)
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else:
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query_vector = embed_text(query_text)
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# Search Qdrant
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results = qclient.search(
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collection_name=COLLECTION_NAME,
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query_vector=query_vector,
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@@ -103,11 +90,10 @@ def search_items(query_text, query_image):
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)
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if not results:
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return "
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# Format results
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gallery = []
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output_text = "
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for r in results:
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desc = r.payload.get("description", "No description")
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name = r.payload.get("finder_name", "NA")
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@@ -124,50 +110,56 @@ def search_items(query_text, query_image):
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return output_text, gallery
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def clear_database():
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"""Clear all stored items in Qdrant"""
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qclient.delete_collection(COLLECTION_NAME)
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qclient.recreate_collection(
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collection_name=COLLECTION_NAME,
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vectors_config=VectorParams(size=VECTOR_SIZE, distance=Distance.COSINE),
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)
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return "
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# --------------------------
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# Gradio UI
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# --------------------------
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with gr.Blocks() as demo:
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gr.Markdown(
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with gr.Tab("
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with gr.Row():
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image_in = gr.Image(type="pil", label="Upload
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desc_in = gr.Textbox(label="Item Description")
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with gr.Row():
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finder_name = gr.Textbox(label="Finder's Name")
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finder_phone = gr.Textbox(label="Finder's Phone
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add_btn = gr.Button("Add Item")
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add_output = gr.Textbox(label="Status")
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with gr.Tab("
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with gr.Row():
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search_text = gr.Textbox(label="Search by Text")
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search_image = gr.Image(type="pil", label="Or Search by Image")
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search_btn = gr.Button("Search")
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search_output = gr.Markdown(label="Results")
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gallery = gr.Gallery(label="Matched Items", show_label=True, elem_id="gallery")
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with gr.Tab("
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clear_btn = gr.Button("Clear
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clear_output = gr.Textbox(label="Status")
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#
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add_btn.click(add_item, inputs=[image_in, desc_in, finder_name, finder_phone], outputs=add_output)
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search_btn.click(search_items, inputs=[search_text, search_image], outputs=[search_output, gallery])
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clear_btn.click(clear_database, outputs=clear_output)
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# --------------------------
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# Launch
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# --------------------------
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if __name__ == "__main__":
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demo.launch(server_name="0.0.0.0", server_port=7860)
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# --------------------------
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# Qdrant Cloud Connection
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# --------------------------
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QDRANT_URL = "https://YOUR-CLUSTER-URL.qdrant.io" # π Replace with your cluster URL
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QDRANT_API_KEY = "YOUR_API_KEY" # π Replace with your API key
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COLLECTION_NAME = "lost_and_found"
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# CLIP model (text + image embeddings)
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MODEL_NAME = "sentence-transformers/clip-ViT-B-32"
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embedder = SentenceTransformer(MODEL_NAME)
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VECTOR_SIZE = 512 # CLIP always outputs 512-dim vectors
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# Qdrant Client
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qclient = QdrantClient(url=QDRANT_URL, api_key=QDRANT_API_KEY)
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# Ensure collection exists
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qclient.recreate_collection(
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# --------------------------
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def image_to_base64(img: Image.Image) -> str:
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buf = io.BytesIO()
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img.save(buf, format="PNG")
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return base64.b64encode(buf.getvalue()).decode("utf-8")
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def base64_to_image(b64_str: str) -> Image.Image:
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img_bytes = base64.b64decode(b64_str)
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return Image.open(io.BytesIO(img_bytes))
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return embedder.encode(img).tolist()
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def add_item(image, description, finder_name, finder_phone):
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if image is None or description.strip() == "":
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return "Please provide both an image and a description."
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embedding = embed_image(image)
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img_b64 = image_to_base64(image)
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metadata = {
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"description": description,
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"finder_name": finder_name if finder_name.strip() else "NA",
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"image_b64": img_b64
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}
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qclient.upsert(
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collection_name=COLLECTION_NAME,
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points=[
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)
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]
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)
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return "Item successfully added."
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def search_items(query_text, query_image):
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if not query_text and query_image is None:
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return "Enter text or upload an image to search.", []
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if query_image:
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query_vector = embed_image(query_image)
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else:
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query_vector = embed_text(query_text)
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results = qclient.search(
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collection_name=COLLECTION_NAME,
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query_vector=query_vector,
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)
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if not results:
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return "No matches found.", []
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gallery = []
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output_text = "### Matches Found:\n\n"
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for r in results:
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desc = r.payload.get("description", "No description")
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name = r.payload.get("finder_name", "NA")
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return output_text, gallery
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def clear_database():
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qclient.delete_collection(COLLECTION_NAME)
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qclient.recreate_collection(
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collection_name=COLLECTION_NAME,
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vectors_config=VectorParams(size=VECTOR_SIZE, distance=Distance.COSINE),
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)
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return "Database cleared."
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# --------------------------
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# Gradio UI
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# --------------------------
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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gr.Markdown(
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"""
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# Lost & Found System
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Upload, search, and manage found items with text or image queries.
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"""
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)
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with gr.Tab("Add Item"):
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with gr.Row():
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image_in = gr.Image(type="pil", label="Upload Image", height=250)
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desc_in = gr.Textbox(label="Item Description", placeholder="e.g. Silver keychain with tag")
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with gr.Row():
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finder_name = gr.Textbox(label="Finder's Name", placeholder="John Doe")
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finder_phone = gr.Textbox(label="Finder's Phone", placeholder="+123456789")
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add_btn = gr.Button("Add Item", variant="primary")
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add_output = gr.Textbox(label="Status", interactive=False)
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with gr.Tab("Search"):
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with gr.Row():
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search_text = gr.Textbox(label="Search by Text", placeholder="Enter keywords...")
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search_image = gr.Image(type="pil", label="Or Search by Image", height=250)
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search_btn = gr.Button("Search", variant="primary")
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search_output = gr.Markdown(label="Results")
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gallery = gr.Gallery(label="Matched Items", show_label=True, elem_id="gallery").style(
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grid=[2], height="auto"
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)
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with gr.Tab("Admin"):
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clear_btn = gr.Button("Clear Database", variant="stop")
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clear_output = gr.Textbox(label="Status", interactive=False)
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# Actions
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add_btn.click(add_item, inputs=[image_in, desc_in, finder_name, finder_phone], outputs=add_output)
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search_btn.click(search_items, inputs=[search_text, search_image], outputs=[search_output, gallery])
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clear_btn.click(clear_database, outputs=clear_output)
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# --------------------------
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# Launch
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# --------------------------
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if __name__ == "__main__":
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demo.launch(server_name="0.0.0.0", server_port=7860)
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