Update app.py

app.py

@@ -1,45 +1,59 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+from pydantic import BaseModel
 from typing import List, Dict
 
 # Inisialisasi client model
 client = InferenceClient("meta-llama/Meta-Llama-3-8B-Instruct")
 
+# Model untuk data input API
+class ChatMessage(BaseModel):
+    role: str
+    content: str
+
 def chat_llama(chat_history: List[Dict[str, str]]):
-    print("Calling chat_llama with history:", chat_history)
+    # Mengirim chat_history ke model dan mendapatkan respons
     chat_completion = client.chat_completion(
         messages=chat_history,
         max_tokens=500
     )
+    # Menambahkan respons model ke chat_history
     chat_history.append({"role": "assistant", "content": chat_completion.choices[0].message.content})
-    print("Updated history:", chat_history)
+
     return chat_history
 
 def chat_mem(message, chat_history):
-    print("Received message:", message)
-    print("Current chat history:", chat_history)
-    
+    # Membuat chat_history_role untuk pengolahan model
     chat_history_role = [{"role": "system", "content": "You are a helpful assistant."}]
+    
+    # Menambahkan pesan dari chat_history ke chat_history_role
     if chat_history:
         for user_message, assistant_response in chat_history:
             chat_history_role.append({"role": "user", "content": user_message})
             chat_history_role.append({"role": "assistant", "content": assistant_response})
     
+    # Menambahkan pesan pengguna terbaru
     chat_history_role.append({"role": "user", "content": message})
+    
+    # Mendapatkan respons dari model
     chat_completion = client.chat_completion(
         messages=chat_history_role,
         max_tokens=500
     )
+    
+    # Menambahkan respons model ke chat_history_role
     chat_history_role.append({"role": "assistant", "content": chat_completion.choices[0].message.content})
-    print("Updated chat history role:", chat_history_role)
     
+    # Format ulang chat_history
     modified = [entry["content"] for entry in chat_history_role]
     chat_history = [(modified[i*2], modified[i*2+1]) for i in range(len(modified)//2)]
-    return "", chat_history
+
+    return "", chat_history  # Kembalikan pesan kosong dan chat_history yang diperbarui
 
 def api_chat(chat_history: List[Dict[str, str]]):
-    print("Received API request with history:", chat_history)
+    # Memanggil chat_llama untuk mendapatkan respons
     updated_history = chat_llama(chat_history)
+    # Mengambil respons terakhir sebagai output
     return updated_history[-1] if updated_history else {}
 
 # Mengatur antarmuka Gradio
@@ -47,6 +61,7 @@ with gr.Blocks() as demo:
     gr.Markdown("## Chat Demo")
     with gr.Row():
         with gr.Column():
+            # Bagian Antarmuka Pengguna
             chatbot = gr.Chatbot()
             msg = gr.Textbox(placeholder="Type your message here...", interactive=True)
             with gr.Row():
@@ -59,7 +74,7 @@ with gr.Blocks() as demo:
     gr.Markdown("### Send a POST request to `/api/chat` with the following JSON body:")
     gr.Markdown("```json\n[ { \"role\": \"user\", \"content\": \"Hello, how are you?\" }, { \"role\": \"assistant\", \"content\": \"I'm fine, thank you! How can I assist you today?\" }, { \"role\": \"user\", \"content\": \"Can you tell me a joke?\" } ]\n```")
     gr.Markdown("### API Response:")
-    gr.Interface(fn=api_chat, inputs="json", outputs="json").launch(share=True)
+    gr.Interface(fn=api_chat, inputs="json", outputs="json").launch()
 
 if __name__ == "__main__":
-    demo.launch(port=7861)
+    demo.launch()