Update app.py

app.py

@@ -222,20 +222,74 @@ def ejecutar_codigo_sandbox(codigo, nombre):
     return False, "❌ Lenguaje no soportado"
 
 
-def run_chat(message, history, user_context, max_tokens, temperature, top_p, token, file_content, file_name, memoria):
+def normalize_history(history):
+    """
+    Normaliza history a una lista de dicts limpios con claves 'user' y 'assistant'.
+    Soporta todos los formatos posibles de Gradio.
+    """
+    normalized = []
+    if not isinstance(history, list):
+        return normalized
+
+    for item in history:
+        user_msg = ""
+        assistant_msg = ""
+
+        if isinstance(item, dict):
+            # Formato moderno: {"user": ..., "assistant": ...}
+            if "user" in item or "assistant" in item:
+                user_msg = str(item.get("user", "") or "")
+                assistant_msg = str(item.get("assistant", "") or "")
+            # Formato alternativo: {"message": ..., "response": ...}
+            elif "message" in item or "response" in item:
+                user_msg = str(item.get("message", "") or "")
+                assistant_msg = str(item.get("response", "") or "")
+            # Formato API: {"role": ..., "content": ...} — improbable pero por si acaso
+            elif "role" in item and "content" in item:
+                role = item["role"]
+                content = str(item.get("content", "") or "")
+                if role == "user":
+                    user_msg = content
+                elif role == "assistant":
+                    assistant_msg = content
+        elif isinstance(item, (list, tuple)) and len(item) >= 2:
+            # Formato legacy: (user, assistant)
+            user_msg = str(item[0] or "")
+            assistant_msg = str(item[1] or "")
+
+        # Solo agregar si tiene contenido
+        if user_msg.strip() or assistant_msg.strip():
+            normalized.append({"user": user_msg, "assistant": assistant_msg})
+
+    return normalized
+
+
+def history_to_messages(normalized_history):
     """
-    Gradio Chatbot devuelve una lista de dicts:
-    [{"user": "saludo", "assistant": "hola"}, ...]
+    Convierte historial normalizado a formato messages para la API.
     """
+    messages = []
+    for item in normalized_history:
+        if item["user"].strip():
+            messages.append({"role": "user", "content": item["user"]})
+        if item["assistant"].strip():
+            messages.append({"role": "assistant", "content": item["assistant"]})
+    return messages
+
+
+def run_chat(message, history, user_context, max_tokens, temperature, top_p, token, file_content, file_name, memoria):
+    # --- Normalizar history al inicio ---
+    norm_history = normalize_history(history)
+
     # --- SEGURIDAD ---
     for bloqueo in BLOQUEOS_JAILBREAK:
         if bloqueo in message.lower():
-            chatbot_output = history + [{"user": message, "assistant": "Soy Aura, asistente especializado exclusivamente en programación."}]
+            chatbot_output = norm_history + [{"user": message, "assistant": "Soy Aura, asistente especializado exclusivamente en programación."}]
             yield chatbot_output, "", "", "⛔ Bloqueado por seguridad.", ""
             return
 
     if not HF_TOKEN:
-        chatbot_output = history + [{"user": message, "assistant": "⚠️ Falta HF_TOKEN. Configura tu API Key en Settings → Secrets."}]
+        chatbot_output = norm_history + [{"user": message, "assistant": "⚠️ Falta HF_TOKEN. Configura tu API Key en Settings → Secrets."}]
         yield chatbot_output, "", "", "Configura HF_TOKEN.", ""
         return
 
@@ -256,27 +310,9 @@ def run_chat(message, history, user_context, max_tokens, temperature, top_p, tok
     if memoria and memoria.strip():
         final_system += f"\n--- MEMORIA ---\n{memoria}\n"
 
-    # --- Convertir history del chatbot a formato API messages ---
+    # --- Construir messages para la API ---
     messages = [{"role": "system", "content": final_system}]
-
-    if not isinstance(history, list):
-        history = []
-
-    for item in history:
-        if isinstance(item, dict):
-            # Formato Gradio moderno: {"user": ..., "assistant": ...}
-            user_msg = item.get("user", "") or item.get("message", "")
-            assistant_msg = item.get("assistant", "") or item.get("response", "")
-            if user_msg:
-                messages.append({"role": "user", "content": user_msg})
-            if assistant_msg:
-                messages.append({"role": "assistant", "content": assistant_msg})
-        elif isinstance(item, (list, tuple)) and len(item) >= 2:
-            # Formato legacy: (user, assistant)
-            if item[0]:
-                messages.append({"role": "user", "content": item[0]})
-            if item[1]:
-                messages.append({"role": "assistant", "content": item[1]})
+    messages.extend(history_to_messages(norm_history))
 
     user_content = message + (contexto_archivo if contexto_archivo else "")
     messages.append({"role": "user", "content": user_content})
@@ -293,10 +329,10 @@ def run_chat(message, history, user_context, max_tokens, temperature, top_p, tok
         ):
             if chunk.choices and chunk.choices[0].delta.content:
                 resp_text += chunk.choices[0].delta.content
-                chatbot_so_far = history + [{"user": message, "assistant": resp_text}]
+                chatbot_so_far = norm_history + [{"user": message, "assistant": resp_text}]
                 yield chatbot_so_far, "", "", "Generando...", ""
     except Exception as e:
-        chatbot_output = history + [{"user": message, "assistant": f"Error IA: {e}"}]
+        chatbot_output = norm_history + [{"user": message, "assistant": f"Error IA: {e}"}]
         yield chatbot_output, "", "", str(e), ""
         return
 
@@ -316,7 +352,7 @@ def run_chat(message, history, user_context, max_tokens, temperature, top_p, tok
             if exito:
                 break
             intentos += 1
-            chatbot_so_far = history + [{"user": message, "assistant": f"{resp_text}\n\n🔄 *Auto-corrigiendo ({intentos}/{MAX_AUTOFIX})...*"}]
+            chatbot_so_far = norm_history + [{"user": message, "assistant": f"{resp_text}\n\n🔄 *Auto-corrigiendo ({intentos}/{MAX_AUTOFIX})...*"}]
             yield chatbot_so_far, "", "", ultima_ejecucion, ""
             try:
                 new_resp = ""
@@ -341,10 +377,8 @@ def run_chat(message, history, user_context, max_tokens, temperature, top_p, tok
                 break
 
     # --- Output final ---
-    chatbot_output = history + [{"user": message, "assistant": resp_text}]
+    chatbot_output = norm_history + [{"user": message, "assistant": resp_text}]
     yield chatbot_output, resp_text, resp_text, ultima_ejecucion, memoria
-
-
 # ============================================
 # INTERFAZ GRADIO
 # ============================================