Update app.py

app.py

@@ -1,67 +1,15 @@
 import gradio as gr
-import logging
 
-logging.getLogger("httpx").setLevel(logging.ERROR)
+def greet(name):
+    return f"Привет, {name}! Это динамический результат."
 
-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)
+demo = gr.Interface(
+    fn=greet,
+    inputs="text",
+    outputs="text",
+    title="Приветствие от Gradio",
+    description="Введи своё имя, чтобы получить приветствие!"
+)
 
-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)
+if __name__ == "__main__":
+    demo.launch()