Update app.py

app.py

@@ -1,40 +1,28 @@
 import gradio as gr
-from transformers import AutoTokenizer, AutoModelForCausalLM
-import sqlite3
+from bertopic import BERTopic
 
-model_name = "Richieburundi/Ariginalmodel"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name)
+model_name = "RichieBurundi/Ariginalmodel"
 
-def read_files_from_db():
-    conn = sqlite3.connect('Richieburundi/Amxxprogramer')
-    cursor = conn.cursor()
-    cursor.execute("SELECT * FROM files")
-    files = cursor.fetchall()
-    conn.close()
-    return files
+try:
+    model = BERTopic.load(model_name)
+except Exception as e:
+    print(f"Error loading model: {e}")
+    # Здесь можно добавить fallback логику или использовать другую модель
 
-def generate_code(input_text):
-    files = read_files_from_db()
-    
-    context = "Available files:\n"
-    for file in files:
-        context += f"- {file[1]}\n"
-    
-    prompt = f"{context}\nGenerate code based on the following input:\n{input_text}\n"
-    
-    inputs = tokenizer(prompt, return_tensors="pt")
-    outputs = model.generate(**inputs, max_length=500)
-    generated_code = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    
-    return generated_code
+def generate_text(input_text):
+    try:
+        topics, probs = model.transform([input_text])
+        generated_text = model.generate_topic_labels(topics[0], probs[0], top_n=1)[0]
+        return generated_text
+    except Exception as e:
+        return f"Error generating text: {e}"
 
 iface = gr.Interface(
-    fn=generate_code,
+    fn=generate_text,
     inputs="text",
     outputs="text",
-    title="Code Generation AI",
-    description="Enter your code or instructions, and the AI will generate code based on available files."
+    title="Ariginal Model Text Generation",
+    description="Enter your text, and the model will generate a response."
 )
 
 iface.launch()