Update app.py

app.py

@@ -1,48 +1,28 @@
 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
-"""
-client = InferenceClient("davnas/Italian_Cousine_1.2")
+client = InferenceClient("davnas/Italian_Cousine_2.1")
+
+def respond(message, history, system_message, max_tokens, temperature, top_p):
+    # Crea un prompt concatenando i messaggi precedenti e l'input attuale
+    prompt = system_message + "\n"
+    for user_msg, assistant_msg in history:
+        if user_msg:
+            prompt += f"User: {user_msg}\n"
+        if assistant_msg:
+            prompt += f"Assistant: {assistant_msg}\n"
+    prompt += f"User: {message}\nAssistant:"
+
+    # Usa text_generation invece di chat_completion
+    response_data = client.text_generation(prompt, max_new_tokens=max_tokens, temperature=temperature, top_p=top_p)
+    # response_data è una lista di completamenti, generalmente prendi il primo
+    if response_data and len(response_data) > 0 and "generated_text" in response_data[0]:
+        # Estrai solo il testo generato dopo 'Assistant:' per pulizia
+        response_text = response_data[0]["generated_text"].split("Assistant:", 1)[-1].strip()
+        return response_text
+    else:
+        return "Mi dispiace, non sono riuscito a generare una risposta."
 
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    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,
-    ):
-        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
-"""
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
@@ -59,6 +39,5 @@ demo = gr.ChatInterface(
     ],
 )
 
-
 if __name__ == "__main__":
     demo.launch()