Update app.py

app.py

@@ -32,70 +32,43 @@ def evaluar_prompt(prompt):
         outputs = model.generate(inputs["input_ids"], max_length=150)  # Limit max_length for faster results
         analysis = tokenizer.decode(outputs[0], skip_special_tokens=True)
 
-        # Initialize feedback
-        feedback = f"Análisis del prompt '{prompt}':\n\n"
-
         # Initialize variables to store detailed advice
-        clarity_advice = ""
-        logic_advice = ""
-        relevance_advice = ""
-        evidence_advice = ""
+        claridad_consejo = ""
+        logica_consejo = ""
+        relevancia_consejo = ""
+        evidencia_consejo = ""
         
         # Evaluate clarity
         if len(prompt.split()) < 5:
-            feedback += "Clarity: The prompt is too brief and may not be clear. Consider adding more details to clarify your request.\n"
-            clarity_advice = "Your prompt is very short, which can lead to ambiguity. Try expanding it to provide more context or specifics."
-        else:
-            feedback += "Clarity: The prompt is clear and well-defined.\n"
-
+            claridad_consejo = "Tu prompt es muy corto, lo que puede generar ambigüedad. Intenta expandirlo para proporcionar más contexto o detalles específicos."
         # Evaluate logic
-        if any(word in prompt.lower() for word in ["best", "worst", "only"]):
-            feedback += (
-                "Logic: The prompt uses subjective terms like 'best' which could introduce bias. "
-                "Consider rephrasing to improve objectivity.\n"
-            )
-            logic_advice = f"Words like '{', '.join([w for w in ['best', 'worst', 'only'] if w in prompt.lower()])}' suggest a subjective perspective. Rephrase to focus on objective criteria."
-        else:
-            feedback += "Logic: The prompt is logical and avoids subjective terms.\n"
-
+        if any(word in prompt.lower() for word in ["mejor", "peor", "único"]):
+            logica_consejo = f"Palabras como '{', '.join([w for w in ['mejor', 'peor', 'único'] if w in prompt.lower()])}' sugieren una perspectiva subjetiva. Reformula el prompt para enfocarte en criterios objetivos."
         # Evaluate relevance
-        if "talk about" in prompt.lower() or "describe" in prompt.lower():
-            feedback += "Relevance: The prompt is relevant and aligned with the request for information.\n"
-        else:
-            feedback += "Relevance: The relevance of the prompt could be improved to better align with the goal. Ensure your prompt directly addresses the core question or objective.\n"
-            relevance_advice = "Your prompt might not directly address the core issue. Ensure that it is directly relevant to the information or action you seek."
-
+        if not any(word in prompt.lower() for word in ["hablar", "describe", "explica", "analiza"]):
+            relevancia_consejo = "Tu prompt podría no abordar directamente el problema central. Asegúrate de que esté directamente relacionado con la información o acción que buscas."
         # Evaluate evidence request
-        if any(word in prompt.lower() for word in ["evidence", "proof", "demonstrate"]):
-            feedback += "Evidence: The prompt requests evidence, which is positive for a well-founded analysis.\n"
-        else:
-            feedback += (
-                "Evidence: The prompt does not explicitly request evidence, which could limit the depth of analysis. "
-                "Consider asking for evidence to support the response.\n"
-            )
-            evidence_advice = "Asking for evidence strengthens your prompt by grounding it in verifiable facts. Consider explicitly requesting evidence or examples."
+        if not any(word in prompt.lower() for word in ["evidencia", "pruebas", "demuestra"]):
+            evidencia_consejo = "Solicitar evidencia fortalece tu prompt al basarlo en hechos verificables. Considera pedir explícitamente evidencia o ejemplos."
 
-        # Summary of the evaluation
-        final_score = 65  # Example score
-
-        feedback += f"\n**Final Score:** {final_score}\n"
-        feedback += "\n### Suggestions for Improvement:\n"
+        # Compile suggestions
+        sugerencias = "### Sugerencias para Mejorar:\n"
 
         # Provide specific advice based on the issues identified
-        if clarity_advice:
-            feedback += f"\n* **Clarity:** {clarity_advice}"
-        if logic_advice:
-            feedback += f"\n* **Logic:** {logic_advice}"
-        if relevance_advice:
-            feedback += f"\n* **Relevance:** {relevance_advice}"
-        if evidence_advice:
-            feedback += f"\n* **Evidence:** {evidence_advice}"
+        if claridad_consejo:
+            sugerencias += f"\n* **Claridad:** {claridad_consejo}"
+        if logica_consejo:
+            sugerencias += f"\n* **Lógica:** {logica_consejo}"
+        if relevancia_consejo:
+            sugerencias += f"\n* **Relevancia:** {relevancia_consejo}"
+        if evidencia_consejo:
+            sugerencias += f"\n* **Evidencia:** {evidencia_consejo}"
 
         # If no advice is necessary, indicate that the prompt is strong
-        if not any([clarity_advice, logic_advice, relevance_advice, evidence_advice]):
-            feedback += "\nYour prompt is well-constructed with no major areas for improvement."
+        if not any([claridad_consejo, logica_consejo, relevancia_consejo, evidencia_consejo]):
+            sugerencias += "\nTu prompt está bien construido y no presenta áreas importantes para mejorar."
 
-        return feedback, final_score
+        return sugerencias, 65  # Returning only the suggestions and an arbitrary score
 
     except Exception as e:
         return str(e), "Error"
@@ -103,96 +76,86 @@ def evaluar_prompt(prompt):
 def interfaz():
     with gr.Blocks(css="""
         body {
-            font-family: Arial, sans-serif;
-            background-color: #f4f4f4;
+            font-family: 'Helvetica Neue', Arial, sans-serif;
+            background-color: #f7f7f7;
             color: #333333;
             margin: 0;
             padding: 0;
         }
         .container {
-            max-width: 1200px;
+            max-width: 800px;
             margin: 0 auto;
-            padding: 20px;
+            padding: 40px;
             display: flex;
             flex-direction: column;
             align-items: center;
+            background-color: #ffffff;
+            border-radius: 8px;
+            box-shadow: 0 4px 12px rgba(0, 0, 0, 0.1);
         }
         .hero-section {
-            background-color: white;
             text-align: center;
-            padding: 50px 0;
-            width: 100%;
+            margin-bottom: 40px;
         }
         .hero-section h1 {
-            font-size: 48px;
+            font-size: 36px;
             font-weight: bold;
             color: #007BFF;
-            margin: 0;
+            margin-bottom: 10px;
         }
         .hero-section p {
-            font-size: 20px;
+            font-size: 18px;
             color: #666;
-            margin: 20px 0 0;
+            margin-top: 0;
         }
         .evaluation-section {
-            background-color: #333333;
-            color: white;
-            padding: 50px;
             width: 100%;
             display: flex;
-            justify-content: space-between;
-            align-items: center.
+            flex-direction: column;
+            gap: 20px;
         }
         .evaluation-section h2 {
-            font-size: 36px;
+            font-size: 28px;
             font-weight: bold;
-            margin-bottom: 20px.
-        }
-        .evaluation-section .left,
-        .evaluation-section .right {
-            width: 45%.
+            color: #333;
+            margin-bottom: 10px;
         }
-        .evaluation-section .left p,
-        .evaluation-section .right p {
+        .evaluation-section .gr-textbox,
+        .evaluation-section .gr-number {
+            width: 100%;
+            padding: 12px;
             font-size: 16px;
-            line-height: 1.6.
-        }
-        .evaluation-section .right {
-            text-align: left.
+            border: 1px solid #ddd;
+            border-radius: 4px;
+            box-sizing: border-box;
+            transition: border-color 0.2s;
         }
-        .evaluation-section .button-container {
-            margin-top: 20px.
+        .evaluation-section .gr-textbox:focus,
+        .evaluation-section .gr-number:focus {
+            border-color: #007BFF;
+            outline: none;
         }
-        .evaluation-section .button-container .gr-button {
+        .evaluation-section .gr-button {
             background-color: #007BFF;
             color: white;
-            padding: 15px 30px;
-            font-size: 18px;
+            padding: 12px 20px;
+            font-size: 16px;
+            font-weight: bold;
             border: none;
-            cursor: pointer.
-        }
-        .evaluation-section .button-container .gr-button:hover {
-            background-color: #0056b3.
+            border-radius: 4px;
+            cursor: pointer;
+            transition: background-color 0.2s;
+            text-align: center;
         }
-        .evaluation-section .gr-textbox,
-        .evaluation-section .gr-number {
-            width: 100%;
-            padding: 15px;
-            font-size: 16px;
-            margin-top: 10px;
-            box-sizing: border-box.
+        .evaluation-section .gr-button:hover {
+            background-color: #0056b3;
         }
     """) as demo:
         with gr.Row(elem_id="hero-section"):
-            gr.Markdown("<h1>Alfred</h1>", elem_classes="hero-section")
-            gr.Markdown("<p>Research & Development phase.</p>", elem_classes="hero-section")
+            gr.Markdown("<div class='container'><h1>Evaluación de Prompts</h1><p>Ingrese su prompt a continuación para recibir sugerencias de mejora basadas en principios de pensamiento crítico.</p></div>", elem_classes="hero-section")
         
         with gr.Row(elem_id="evaluation-section"):
             with gr.Column(elem_id="left"):
-                gr.Markdown("<h2>Análisis del Prompt</h2>", elem_classes="evaluation-section")
-                gr.Markdown("<p>Ingrese su prompt a continuación para recibir una evaluación detallada basada en principios de pensamiento crítico.</p>", elem_classes="evaluation-section")
-            
-            with gr.Column(elem_id="right"):
                 prompt_input = gr.Textbox(label="Escribe tu prompt aquí:", placeholder="Escribe tu prompt...", elem_classes="gr-textbox")
                 feedback_output = gr.Textbox(label="Retroalimentación:", interactive=False, elem_classes="gr-textbox")
                 calificacion_output = gr.Number(label="Calificación Final:", interactive=False, elem_classes="gr-number")