Update app.py

app.py

@@ -1,15 +1,67 @@
 import gradio as gr
+import logging
 
-def greet(name):
-    return f"Привет, {name}! Это динамический результат."
+logging.getLogger("httpx").setLevel(logging.ERROR)
 
-demo = gr.Interface(
-    fn=greet,
-    inputs="text",
-    outputs="text",
-    title="Приветствие от Gradio",
-    description="Введи своё имя, чтобы получить приветствие!"
-)
+def show_image(img):
+    global query
+    query = ""
+    
+    # Проверка, что изображение не None
+    if img is None:
+        return None, gr.update(value="No image provided")  # Возвращаем None как изображение и сообщение
+    
+    # Обработка изображения
+    data_batch[0].append(preprocess(img))
+    embeds = embed(data_batch[0])
+    res = collection.search(embeds, anns_field='image_embedding', param={'nprobe': 128}, limit=TOP_K, output_fields=['filepath'])
+    
+    for hits_i, hits in enumerate(res):
+        for hit_i, hit in enumerate(hits):
+            img_path = hit.entity.get('filepath')
+            _ph_ = str(img_path)
+            ph_ = _ph_[8:len(_ph_)]
+            x = ph_.find("\\")
+            query = ph_[:x] if ph_[:x] != "NoName" else ""
+    
+    return img_path, gr.update(value=query)
 
-if __name__ == "__main__":
-    demo.launch()
+def display_results(_query):
+    global query
+    if _query:  # Проверка, что запрос не пустой
+        query = _query
+    else:
+        return "Please enter a search query or upload an image."
+    
+    query_embeddings = ef([query])
+    dense_results = dense_search(col, query_embeddings["dense"][0])
+    sparse_results = sparse_search(col, query_embeddings["sparse"]._getrow(0))
+    hybrid_results = hybrid_search(
+        col,
+        query_embeddings["dense"][0],
+        query_embeddings["sparse"]._getrow(0),
+        sparse_weight=0.7,
+        dense_weight=1.0,
+    )
+    
+    formatted_results = doc_text_formatting(ef, query, hybrid_results)
+    results_md = f'<span style="color: {color[0]}">{query}</span>\n'
+    for result in formatted_results:
+        results_md += f"\n{result}"
+    return results_md
+
+# Интерфейс Gradio
+with gr.Blocks(css=".progress-text { display: none !important; }") as demo:
+    with gr.Row():
+        image_input = gr.Image(label="Input Image Component", type="pil", width=320, height=320)
+        image_output = gr.Image(label="Output Image Component", width=320, height=320)
+        
+    with gr.Column():
+        field_query = gr.Textbox(label="Search Query")
+        result_display = gr.Markdown()
+        submit_button = gr.Button("Submit")
+
+    image_input.change(fn=show_image, inputs=image_input, outputs=[image_output, field_query])
+    submit_button.click(fn=display_results, inputs=field_query, outputs=result_display)
+
+demo.launch(share=False)