mejoras

app.py

@@ -1,59 +1,45 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+from typing import List, Tuple, Dict
 
-"""
-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("AuriLab/gpt-bi-instruct-cesar")  # Cambiado el modelo
+client = InferenceClient("AuriLab/gpt-bi-instruct-cesar")
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
+def format_messages(history: List[Tuple[str, str]], system_message: str, user_message: str) -> List[Dict[str, str]]:
     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})
-
+    messages.extend([
+        {"role": "user" if i % 2 == 0 else "assistant", "content": msg}
+        for turn in history
+        for i, msg in enumerate(turn)
+        if msg
+    ])
+    messages.append({"role": "user", "content": user_message})
+    return messages
+
+def respond(message: str, history: List[Tuple[str, str]], system_message: str, max_tokens: int, temperature: float, top_p: float) -> str:
+    messages = format_messages(history, system_message, message)
     response = ""
-
-    for message in client.chat_completion(
+    
+    for msg in client.chat_completion(
         messages,
         max_tokens=max_tokens,
         stream=True,
         temperature=temperature,
         top_p=top_p,
+        repetition_penalty=1.2,  # Add repetition penalty
+        presence_penalty=0.5,    # Penalize presence of repeated tokens
+        frequency_penalty=0.5,   # Penalize frequency of repeated tokens
     ):
-        token = message.choices[0].delta.content
-
+        token = msg.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=[
         gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=1024, value=512, step=1, label="Max new tokens"),
+        gr.Slider(minimum=1, maximum=256, 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(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
+        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
     ],
 )