Create burundi.py

burundi.py

@@ -0,0 +1,40 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import sqlite3
+
+model_name = "your-model-name"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+def read_files_from_db():
+    conn = sqlite3.connect('your_database.db')
+    cursor = conn.cursor()
+    cursor.execute("SELECT * FROM files")
+    files = cursor.fetchall()
+    conn.close()
+    return files
+
+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
+
+iface = gr.Interface(
+    fn=generate_code,
+    inputs="text",
+    outputs="text",
+    title="Code Generation AI",
+    description="Enter your code or instructions, and the AI will generate code based on available files."
+)
+
+iface.launch()