Update app.py

app.py

@@ -1,29 +1,23 @@
-import os
+import openai
 import gradio as gr
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-import torch
-
-# Read Hugging Face Token from environment
-hf_token = os.environ.get("HUGGINGFACE_TOKEN")
+import os
 
-# Load Somali model (private)
-tokenizer = AutoTokenizer.from_pretrained("cmlang/somali-flan-t5", use_auth_token=hf_token)
-model = AutoModelForSeq2SeqLM.from_pretrained("cmlang/somali-flan-t5", use_auth_token=hf_token)
+openai.api_key = os.getenv("OPENAI_API_KEY")
 
-# Chatbot function
-def chatbot_somali(msg):
-    inputs = tokenizer(msg, return_tensors="pt")
-    outputs = model.generate(**inputs, max_length=150)
-    reply = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    return reply
+def chat(user_input, history=[]):
+    messages = [{"role": "system", "content": "Ka jawaab su’aalaha af Soomaali"}]
+    for q, a in history:
+        messages.append({"role": "user", "content": q})
+        messages.append({"role": "assistant", "content": a})
+    messages.append({"role": "user", "content": user_input})
 
-# Gradio Interface
-iface = gr.Interface(
-    fn=chatbot_somali,
-    inputs=gr.Textbox(lines=2, placeholder="Weydii wax af Soomaali ah..."),
-    outputs="text",
-    title="Chatbot Af Soomaali",
-    description="Weydii wax kasta oo af Soomaali ah — chatbot-kan wuu fahmi doonaa!"
-)
+    response = openai.ChatCompletion.create(
+        model="gpt-4o",
+        messages=messages,
+        temperature=0.7
+    )
+    reply = response.choices[0].message.content
+    history.append((user_input, reply))
+    return history, history
 
-iface.launch()
+gr.ChatInterface(chat, title="Chatbot Af Soomaali").launch()