Update app.py

app.py

@@ -1,23 +1,67 @@
-import openai
+# Somali Chatbot with Translation + English Chatbot using Gradio
+
 import gradio as gr
-import os
-
-openai.api_key = os.getenv("OPENAI_API_KEY")
-
-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})
-
-    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
-
-gr.ChatInterface(chat, title="Chatbot Af Soomaali").launch()
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline, AutoModelForCausalLM
+import torch
+
+# Load Translation Model: facebook/nllb-200-3.3B
+trans_model = "facebook/nllb-200-3.3B"
+trans_tokenizer = AutoTokenizer.from_pretrained(trans_model)
+trans_model_loaded = AutoModelForSeq2SeqLM.from_pretrained(trans_model)
+
+def translate(text, src_lang, tgt_lang):
+    translator = pipeline("translation",
+                          model=trans_model_loaded,
+                          tokenizer=trans_tokenizer,
+                          src_lang=src_lang,
+                          tgt_lang=tgt_lang,
+                          max_length=512)
+    return translator(text)[0]['translation_text']
+
+# Load Chatbot Model: meta-llama/Meta-Llama-3-8B-Instruct
+chatbot_model_name = "meta-llama/Meta-Llama-3-8B-Instruct"
+chatbot_tokenizer = AutoTokenizer.from_pretrained(chatbot_model_name)
+chatbot_model = AutoModelForCausalLM.from_pretrained(
+    chatbot_model_name, torch_dtype=torch.float16, device_map="auto")
+
+def ask_chatbot(prompt):
+    input_ids = chatbot_tokenizer.encode(prompt, return_tensors="pt").to(chatbot_model.device)
+    with torch.no_grad():
+        output = chatbot_model.generate(input_ids, max_new_tokens=256, do_sample=True, temperature=0.7)
+    return chatbot_tokenizer.decode(output[0], skip_special_tokens=True)
+
+# Full pipeline function
+def somali_chatbot_pipeline(somali_input):
+    # Step 1: Somali -> English
+    english_input = translate(somali_input, src_lang="som_Latn", tgt_lang="eng_Latn")
+
+    # Step 2: Ask English chatbot
+    chatbot_response = ask_chatbot(english_input)
+
+    # Step 3: English -> Somali
+    somali_output = translate(chatbot_response, src_lang="eng_Latn", tgt_lang="som_Latn")
+
+    return somali_output
+
+# Gradio Interface (with submit button)
+def build_interface():
+    with gr.Blocks() as demo:
+        gr.Markdown("""
+        # 🤖 Chatbot Soomaaliyeed 
+        Qor su'aal Af Soomaali ah. Nidaamku wuxuu si qarsoodi ah ugu rogaa luqadda Ingiriisiga, ka dib wuxuu weydiiyaa chatbot English ah, kadibna jawaabta wuxuu kuu soo celinayaa Af Soomaali.
+        """)
+
+        with gr.Row():
+            somali_input = gr.Textbox(label="Su’aashaada Af Soomaali", placeholder="Maxaa keena macaanka?", lines=3)
+        with gr.Row():
+            submit_btn = gr.Button("Dir Su’aasha")
+        with gr.Row():
+            somali_output = gr.Textbox(label="Jawaabta Chatbot-ka (Af Soomaali)", lines=5)
+
+        submit_btn.click(fn=somali_chatbot_pipeline, inputs=somali_input, outputs=somali_output)
+
+    return demo
+
+if __name__ == "__main__":
+    iface = build_interface()
+    iface.launch()