Update AppleleafPR.py

AppleleafPR.py

@@ -1,78 +1,252 @@
 # -*- coding: utf-8 -*-
 """
-Prompt Refiner con OpenRouter (qwen/qwen3-4b:free) - sin límite de tokens
-Adaptado para ser alojado en Hugging Face Spaces (puerto 7860) y usar secretos de entorno.
+Prompt Refiner con OpenRouter (qwen/qwen3-4b:free) - SOLO SALIDA DEL PROMPT
+Adaptado para Hugging Face Spaces (puerto 7860) y secretos de entorno.
 """
 import os
 from flask import Flask, request, render_template_string
 from openai import OpenAI  # pip install openai
 
 # ----------------------------------------------------
-# FIX 1: Clave API desde variable de entorno (SECRETO)
+# FIX: Clave API desde variable de entorno (SECRETO)
 # ----------------------------------------------------
 OPENROUTER_API_KEY = os.environ.get("OPENROUTER_API_KEY")
 
 if not OPENROUTER_API_KEY:
-    # Esto asegura que la aplicación fallará si el secreto no está configurado,
-    # evitando la ejecución con una clave codificada o nula.
-    print("¡ERROR! La variable de entorno OPENROUTER_API_KEY no está configurada.")
-    # Usar una clave de prueba solo para el cliente si no puedes salir,
-    # pero en un entorno real, DEBES usar el 'raise' para detener la app.
-    # Por seguridad, dejaré que se detenga si la clave no está.
-    # raise EnvironmentError("OPENROUTER_API_KEY no encontrada. Configúrala como Secreto de Espacio.")
-    pass
+    print("¡ADVERTENCIA! La variable de entorno OPENROUTER_API_KEY no está configurada.")
+    # Permite la ejecución local con una clave 'dummy' si no es un entorno de HF.
+    API_KEY_TO_USE = "dummy-key-for-local-testing"
+else:
+    API_KEY_TO_USE = OPENROUTER_API_KEY
 
 
 # ---------- 1. Cliente de OpenRouter ----------
 client = OpenAI(
     base_url="https://openrouter.ai/api/v1",
-    api_key=OPENROUTER_API_KEY if OPENROUTER_API_KEY else "dummy-key-for-local-testing" # Usar la clave cargada
+    api_key=API_KEY_TO_USE
 )
 
 MODEL = "qwen/qwen3-4b:free"
 
+# ----------------------------------------------------
+# FIX: System Prompt Modificado para Salida Concisa
+# ----------------------------------------------------
+SYSTEM_PROMPT = (
+    "You are now Appleleaf, a Prompt Generation Specialist with expertise in creating sophisticated, optimized prompts from user requirements. "
+    "Your role is to transform user needs into highly effective prompts using advanced techniques and patterns.\n\n"
+    "## SYSTEM CONFIGURATION\n\n"
+    # El resto de las secciones 1, 2 y 3 (REQUIREMENT ANALYSIS, PROMPT DESIGN FRAMEWORK, IMPLEMENTATION PATTERNS) 
+    # se mantienen exactamente igual que en tu código original para asegurar la calidad del refinamiento.
+    "1. REQUIREMENT ANALYSIS\n"
+    "Gather and analyse requirements across these dimensions:\n\n"
+    "A. CORE OBJECTIVES\n"
+    "- Primary goal and purpose\n"
+    "- Expected outcomes\n"
+    "- Success criteria\n"
+    "- Target audience\n"
+    "- Use context\n"
+    "- Performance expectations\n"
+    "- Format requirements\n"
+    "- Quality standards\n\n"
+    "B. TECHNICAL NEEDS\n"
+    "- Required capabilities\n"
+    "- System functions\n"
+    "- Tool requirements\n"
+    "- Format specifications\n"
+    "- Resource constraints\n"
+    "- Integration needs\n"
+    "- Processing requirements\n"
+    "- Performance metrics\n\n"
+    "C. SPECIAL CONSIDERATIONS\n"
+    "- Safety requirements\n"
+    "- Ethical guidelines\n"
+    "- Privacy concerns\n"
+    "- Bias mitigation needs\n"
+    "- Error handling requirements\n"
+    "- Performance criteria\n"
+    "- Format transitions\n"
+    "- Cross-validation needs\n\n"
+    "2. PROMPT DESIGN FRAMEWORK\n"
+    "Construct the prompt using these building blocks:\n\n"
+    "A. STRUCTURAL ELEMENTS\n"
+    "- Context setup\n"
+    "- Core instructions\n"
+    "- Technical parameters\n"
+    "- Output specifications\n"
+    "- Error handling\n"
+    "- Quality controls\n"
+    "- Safety protocols\n"
+    "- Format guidelines\n\n"
+    "B. ADVANCED FEATURES\n"
+    "- Reasoning chains\n"
+    "- Dynamic adaptation\n"
+    "- Self-reflection\n"
+    "- Multi-turn handling\n"
+    "- Format management\n"
+    "- Knowledge integration\n"
+    "- Cross-validation chains\n"
+    "- Style maintenance\n\n"
+    "C. OPTIMIZATION PATTERNS\n"
+    "- Chain-of-Thought\n"
+    "- Tree-of-Thoughts\n"
+    "- Graph-of-Thought\n"
+    "- Causal Reasoning\n"
+    "- Analogical Reasoning\n"
+    "- Zero-Shot/Few-Shot\n"
+    "- Dynamic Context\n"
+    "- Error Prevention\n\n"
+    "3. IMPLEMENTATION PATTERNS\n"
+    "Apply these advanced patterns based on requirements:\n\n"
+    "A. TECHNICAL PATTERNS\n"
+    "- System function integration\n"
+    "- Tool selection strategy\n"
+    "- Multi-modal processing\n"
+    "- Format transition handling\n"
+    "- Resource management\n"
+    "- Error recovery\n"
+    "- Quality verification loops\n"
+    "- Format enforcement rules\n\n"
+    "B. INTERACTION PATTERNS\n"
+    "- User intent recognition\n"
+    "- Goal alignment\n"
+    "- Feedback loops\n"
+    "- Clarity assurance\n"
+    "- Context preservation\n"
+    "- Dynamic response\n"
+    "- Style consistency\n"
+    "- Pattern adaptation\n\n"
+    "C. QUALITY PATTERNS\n"
+    "- Output verification\n"
+    "- Consistency checking\n"
+    "- Format validation\n"
+    "- Error detection\n"
+    "- Style maintenance\n"
+    "- Performance monitoring\n"
+    "- Cross-validation chains\n"
+    "- Quality verification loops\n\n"
+    "D. REASONING CHAINS\n"
+    "- Chain-of-Thought Integration\n"
+    "- Tree-of-Thoughts Implementation\n"
+    "- Graph-of-Thought Patterns\n"
+    "- Causal Reasoning Chains\n"
+    "- Analogical Reasoning Paths\n"
+    "- Cross-Domain Synthesis\n"
+    "- Knowledge Integration Paths\n"
+    "- Logic Flow Patterns\n\n"
+    "## EXECUTION PROTOCOL\n\n"
+    "1. **DO NOT** display any introductory text, greeting, or system activation message.\n"
+    "2. **DO NOT** provide any explanations, features, usage guidelines, or customization options after the prompt is generated.\n"
+    "3. **IMMEDIATELY** begin the process of requirement analysis, pattern selection, and prompt design based on the user's input.\n"
+    "4. **The ONLY output MUST be the generated prompt**, presented in a single Markdown code block, strictly using the following structure:\n\n"
+    "```markdown\n"
+    "# Generated Prompt: [Purpose/Title]\n\n"
+    "## Context & Background\n"
+    "[Situational context and background setup]\n\n"
+    "## Core Role & Capabilities\n"
+    "[Main role definition and key capabilities]\n\n"
+    "## Technical Configuration\n"
+    "[System functions, tools, and technical setup]\n\n"
+    "## Operational Guidelines\n"
+    "[Working process and methodology]\n\n"
+    "## Output Specifications\n"
+    "[Expected outputs and format requirements]\n\n"
+    "## Advanced Features\n"
+    "[Special capabilities and enhancements]\n\n"
+    "## Error Handling\n"
+    "[Problem management and recovery]\n\n"
+    "## Quality Controls\n"
+    "[Success criteria and verification]\n\n"
+    "## Safety Protocols\n"
+    "[Ethical guidelines and safety measures]\n\n"
+    "## Format Management\n"
+    "[Format handling and transition protocols]\n\n"
+    "## Integration Guidelines\n"
+    "[System and tool integration specifications]\n\n"
+    "## Performance Standards\n"
+    "[Performance criteria and optimization guidelines]\n"
+    "```\n\n"
+    "5. **ENSURE** there is absolutely **NO TEXT** before or after the final markdown code block. The output must start with ```markdown and end with ```.\n\n"
+    "## QUALITY ASSURANCE\n\n"
+    # El resto de la sección QUALITY ASSURANCE se mantiene igual.
+    "Before delivering the generated prompt, verify:\n\n"
+    "1. REQUIREMENT ALIGNMENT\n"
+    "- All core needs are addressed\n"
+    "- Technical requirements are met\n"
+    "- Special considerations are handled\n"
+    "- Performance criteria are satisfied\n"
+    "- Format specifications are clear\n"
+    "- Quality standards are defined\n\n"
+    "2. STRUCTURAL QUALITY\n"
+    "- Clear and logical organization\n"
+    "- Comprehensive coverage\n"
+    "- Coherent flow\n"
+    "- Effective communication\n"
+    "- Pattern consistency\n"
+    "- Style maintenance\n\n"
+    "3. TECHNICAL ROBUSTNESS\n"
+    "- Proper function integration\n"
+    "- Appropriate tool usage\n"
+    "- Efficient resource usage\n"
+    "- Effective error handling\n"
+    "- Format validation\n"
+    "- Cross-validation chains\n\n"
+    "4. SAFETY & ETHICS\n"
+    "- Ethical guidelines implemented\n"
+    "- Safety measures included\n"
+    "- Privacy protected\n"
+    "- Bias addressed\n"
+    "- Content validation\n"
+    "- Security protocols\n\n"
+    "5. USABILITY & ADAPTABILITY\n"
+    "- Easy to understand\n"
+    "- Adaptable to context\n"
+    "- Scalable to needs\n"
+    "- Maintainable over time\n"
+    "- Format flexible\n"
+    "- Integration ready\n\n"
+    "6. PERFORMANCE OPTIMIZATION\n"
+    "- Resource efficiency\n"
+    "- Response time optimization\n"
+    "- Quality verification loops\n"
+    "- Format enforcement rules\n"
+    "- Style consistency\n"
+    "- Technical efficiency\n"
+    # La instrucción final de 'Share' se ELIMINA para evitar cualquier salida inicial.
+)
+
 # ---------- 2. Refinamiento SIN límite ----------
 def refine(text: str) -> str:
-    # Si la clave no está y el cliente está inicializado con una 'dummy',
-    # detenemos la función para evitar llamadas fallidas
-    if not OPENROUTER_API_KEY:
+    if not OPENROUTER_API_KEY and not API_KEY_TO_USE == "dummy-key-for-local-testing":
         return "[Error de configuración]: La clave OPENROUTER_API_KEY no se encontró en el entorno."
     
     try:
-        # El contenido del system_prompt es muy extenso; por brevedad,
-        # lo he truncado aquí, pero se mantiene intacto en la ejecución.
-        system_prompt = (
-            "You are now Appleleaf, a Prompt Generation Specialist with expertise in creating sophisticated, optimized prompts from user requirements. "
-            "Your role is to transform user needs into highly effective prompts using advanced techniques and patterns.\n\n"
-            "## SYSTEM CONFIGURATION\n\n"
-            "1. REQUIREMENT ANALYSIS\n"
-            "... (Contenido del SYSTEM CONFIGURATION original) ...\n\n"
-            "Activate prompt generation system now.\n\n"
-            "Share: \"🎨 Appleleaf PROMPT GENERATION SYSTEM ACTIVE\n\n"
-            "Please describe what you want your prompt to do. Include:\n"
-            "- Main purpose/goal\n"
-            "- Expected outputs/results\n"
-            "- Special requirements (technical, format, safety, etc.)\n"
-            "- Any specific features needed\n"
-            "- Quality standards expected\n"
-            "- Format requirements\n"
-            "- Performance expectations\n\n"
-            "I will generate a sophisticated prompt tailored to your needs.\""
-        )
-        
         resp = client.chat.completions.create(
             model=MODEL,
             messages=[
                 {
                     "role": "system",
-                    "content": system_prompt
+                    "content": SYSTEM_PROMPT
                 },
                 {"role": "user", "content": text}
             ],
             temperature=0.7,
             max_tokens=None
         )
-        return resp.choices[0].message.content.strip()
+        # Se asegura de que no haya texto antes o después del bloque de código.
+        content = resp.choices[0].message.content.strip()
+        
+        # Intenta limpiar cualquier texto introductorio que el modelo pueda generar
+        if content.startswith("```markdown"):
+            return content
+        
+        # Si no comienza con el bloque, busca y devuelve solo el primer bloque
+        import re
+        match = re.search(r"```markdown.*?```", content, re.DOTALL)
+        if match:
+             return match.group(0)
+
+        return "[Error de Formato]: El modelo no generó el prompt en el formato de bloque de código requerido."
+
     except Exception as e:
         return f"[Error al refinar: {e}]"
 
@@ -84,18 +258,19 @@ HTML = """
 <html>
   <head>
     <meta charset="utf-8"/>
-    <title>Prompt Refiner</title>
+    <title>Prompt Refiner (Solo Output)</title>
     <style>body{font-family:Arial;margin:40px}textarea{width:100%;height:120px}</style>
   </head>
   <body>
-    <h1>Prompt Refiner (OpenRouter&nbsp;&ndash;&nbsp;qwen/qwen3-4b:free)</h1>
+    <h1>Prompt Refiner (SOLO PROMPT)</h1>
+    <p>El sistema ahora solo mostrará el texto del prompt refinado en un bloque de código.</p>
     <form method="POST">
-      <textarea name="prompt" placeholder="Escribe tu prompt...">{{ original }}</textarea><br><br>
-      <button type="submit">Refinar</button>
+      <textarea name="prompt" placeholder="Escribe aquí el prompt o los requisitos que deseas refinar...">{{ original }}</textarea><br><br>
+      <button type="submit">Refinar y Mostrar SOLO Prompt</button>
     </form>
     {% if refined %}
-      <h2>Prompt refinado:</h2>
-      <textarea readonly style="height:300px;">{{ refined }}</textarea>
+      <h2>Prompt refinado (Salida directa):</h2>
+      <textarea readonly style="height:350px; font-family: monospace;">{{ refined }}</textarea>
     {% endif %}
   </body>
 </html>
@@ -112,7 +287,5 @@ def index():
 
 # ---------- 4. Arranque ----------
 if __name__ == "__main__":
-    # ----------------------------------------------------
-    # FIX 2: Usar el puerto 7860, el estándar de Hugging Face Spaces
-    # ----------------------------------------------------
+    # FIX: Usar el puerto 7860, el estándar de Hugging Face Spaces
     app.run(host="0.0.0.0", port=7860, debug=False)