Update app.py

app.py

@@ -2,10 +2,10 @@ import gradio as gr
 from huggingface_hub import InferenceClient
 
 """
-For more information on `huggingface_hub` Inference API support, please check the docs:
-https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
+For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
 """
-client = InferenceClient("Mattimax/DATA-AI_Chat_3_0.5B")
+client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+
 
 def respond(
     message,
@@ -15,30 +15,30 @@ def respond(
     temperature,
     top_p,
 ):
-    # Prepara il prompt basato sulla cronologia
-    prompt = system_message + "\n"
-    for user_msg, bot_msg in history:
-        prompt += f"User: {user_msg}\n"
-        if bot_msg:
-            prompt += f"Assistant: {bot_msg}\n"
-    
-    prompt += f"User: {message}\nAssistant:"
-    
-    # Invia la richiesta al modello usando text_generation
-    response = client.text_generation(
-        prompt=prompt,
-        max_new_tokens=max_tokens,
+    messages = [{"role": "system", "content": system_message}]
+
+    for val in history:
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
+
+    messages.append({"role": "user", "content": message})
+
+    response = ""
+
+    for message in client.chat_completion(
+        messages,
+        max_tokens=max_tokens,
+        stream=True,
         temperature=temperature,
         top_p=top_p,
-        stream=True,
-    )
-    
-    # Costruisce la risposta a partire dal generato
-    generated_text = ""
-    for chunk in response:
-        token = chunk.token.text if hasattr(chunk.token, 'text') else chunk.token
-        generated_text += token
-        yield generated_text
+    ):
+        token = message.choices[0].delta.content
+
+        response += token
+        yield response
+
 
 """
 For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
@@ -46,10 +46,7 @@ For information on how to customize the ChatInterface, peruse the gradio docs: h
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
-        gr.Textbox(
-            value="You are DATA-AI, created by M.INC.. You are a helpful assistant. Respond in the user language. DO NOT REPEAT THINGS. DO NOT START TO LOOP THE MESSAGES.",
-            label="System message"
-        ),
+        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
         gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
         gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
         gr.Slider(
@@ -62,5 +59,6 @@ demo = gr.ChatInterface(
     ],
 )
 
+
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()