pass prompt

app.py

@@ -35,9 +35,6 @@ class AutismResearchApp:
 
         query = col1.text_input("O que você precisa saber?")
         
-        # Adicionar opção para usar resposta padrão
-        use_default = st.checkbox("Usar resposta padrão (recomendado para melhor qualidade)", value=True)
-        
         if col2.button("Enviar"):
             if not query:
                 st.error("Por favor, digite uma pergunta.")
@@ -49,8 +46,8 @@ class AutismResearchApp:
                 status.write("📚 Analisando dados...")
                 status.write("✍️ Gerando resposta...")
                 
-                # Definir se deve usar resposta padrão
-                self.model_handler.force_default_response = use_default
+                # Sempre usar o modelo, nunca a resposta padrão
+                self.model_handler.force_default_response = False
                 
                 answer = self.model_handler.generate_answer(query)
                 

services/model_handler.py

@@ -456,33 +456,32 @@ class ModelHandler:
             logging.error(f"Error extracting content: {str(e)}")
             return ""
     
-    def _format_prompt(self, prompt_type, query):
+    def _format_prompt(self, prompt_type, content):
         """
-        Formata um prompt para o modelo com base no tipo de prompt e na consulta.
+        Formata o prompt de acordo com o tipo.
         
         Args:
             prompt_type: O tipo de prompt (translation, research, presentation)
-            query: A consulta do usuário ou o resultado de uma etapa anterior
+            content: O conteúdo a ser incluído no prompt
             
         Returns:
-            Um prompt formatado
+            O prompt formatado
         """
-        try:
-            if not query or not query.strip():
-                logging.warning(f"Empty query provided to _format_prompt for {prompt_type}")
-                return ""
-                
-            if prompt_type == "translation":
-                return f"""Task: Translate the following text to English
+        if not content or not content.strip():
+            logging.warning(f"Empty content provided to _format_prompt for {prompt_type}")
+            return "No input provided."
+            
+        if prompt_type == "translation":
+            return f"""Task: Translate the following text to English
 
 Instructions:
 Provide a direct English translation of the input text.
 
-Input: {query}
+Input: {content}
 
 Output:"""
-            elif prompt_type == "research":
-                return f"""Task: Research Assistant
+        elif prompt_type == "research":
+            return f"""Task: Research Assistant
 
 Instructions:
 You are a research assistant tasked with providing comprehensive information.
@@ -492,35 +491,36 @@ Please provide a detailed explanation about the topic, including:
 - Current scientific understanding
 - Important facts and statistics
 - Recent developments or research
+- Real-world implications and applications
 
-Aim to write at least 3-4 paragraphs with detailed information.
+Aim to write at least 4-5 paragraphs with detailed information.
+Be thorough and informative, covering all important aspects of the topic.
+Use clear and accessible language suitable for a general audience.
 
-Input: {query}
+Input: {content}
 
 Output:"""
-            elif prompt_type == "presentation":
-                return f"""Task: Presentation Assistant
+        elif prompt_type == "presentation":
+            return f"""Task: Presentation Assistant
 
 Instructions:
 You are presenting research findings to a general audience.
 Please format the information in a clear, engaging, and accessible way.
 Include:
-- A clear introduction to the topic
+- A clear introduction to the topic with a compelling title
 - Key points organized with headings or bullet points
 - Simple explanations of complex concepts
 - A brief conclusion or summary
 - Translate the entire response to Portuguese
 - Add appropriate emojis to make the presentation more engaging
+- Format the text using markdown for better readability
 
-Input: {query}
+Input: {content}
 
 Output:"""
-            else:
-                logging.warning(f"Unknown prompt type: {prompt_type}")
-                return ""
-        except Exception as e:
-            logging.error(f"Error formatting prompt: {str(e)}")
-            return ""
+        else:
+            logging.error(f"Unknown prompt type: {prompt_type}")
+            return f"Unknown prompt type: {prompt_type}"
     
     @staticmethod
     @st.cache_resource
@@ -673,7 +673,7 @@ Output:"""
                     research_length = len(research_content.strip()) if research_content and isinstance(research_content, str) else 0
                     logging.info(f"Research content length: {research_length} characters")
                     
-                    if not research_content or not research_content.strip() or research_length < 100:
+                    if not research_content or not research_content.strip() or research_length < 150:
                         logging.warning(f"Research result too short ({research_length} chars), trying with a more specific prompt")
                         # Tentar novamente com um prompt mais específico
                         enhanced_prompt = f"""Task: Detailed Research
@@ -681,7 +681,9 @@ Output:"""
 Instructions:
 Provide a comprehensive explanation about '{translation_content}'.
 Include definition, characteristics, causes, and current understanding.
-Write at least 3-4 paragraphs with detailed information.
+Write at least 4-5 paragraphs with detailed information.
+Be thorough and informative, covering all important aspects of the topic.
+Use clear and accessible language suitable for a general audience.
 
 Output:"""
                         logging.info(f"Enhanced research prompt: {enhanced_prompt}")
@@ -692,7 +694,7 @@ Output:"""
                         logging.info(f"Enhanced research content length: {research_length} characters")
                     
                     # Se ainda estiver vazio ou muito curto, usar uma resposta padrão
-                    if not research_content or not research_content.strip() or research_length < 100:
+                    if not research_content or not research_content.strip() or research_length < 150:
                         logging.warning(f"Research result still too short ({research_length} chars), using default response")
                         # Usar resposta padrão
                         logging.info("Using default research content")
@@ -718,7 +720,7 @@ Output:"""
                     presentation_length = len(presentation_content.strip()) if presentation_content and isinstance(presentation_content, str) else 0
                     logging.info(f"Presentation content length: {presentation_length} characters")
                     
-                    if not presentation_content or not presentation_content.strip() or presentation_length < 100:
+                    if not presentation_content or not presentation_content.strip() or presentation_length < 150:
                         logging.warning(f"Presentation result too short ({presentation_length} chars), using default presentation")
                         # Usar apresentação padrão
                         logging.info("Using default presentation content")

test_model.py

@@ -0,0 +1,46 @@
+import logging
+import sys
+from services.model_handler import ModelHandler
+
+# Configure logging
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+)
+
+def test_model(force_default=False):
+    """
+    Testa o ModelHandler com uma consulta de exemplo.
+    
+    Args:
+        force_default: Se deve forçar o uso da resposta padrão
+    """
+    logging.info("Initializing model handler...")
+    model_handler = ModelHandler()
+    
+    # Definir a consulta de teste
+    test_query = "O que é autismo?"
+    logging.info(f"Testing with query: {test_query}")
+    
+    # Definir se deve forçar a resposta padrão
+    model_handler.force_default_response = force_default
+    
+    # Gerar a resposta
+    answer = model_handler.generate_answer(test_query)
+    
+    # Imprimir a resposta
+    print("\n==================================================\n")
+    if force_default:
+        print("RESPOSTA PADRÃO FORÇADA:")
+    else:
+        print("RESPOSTA DO MODELO:")
+    print(answer)
+    print("\n==================================================\n")
+
+if __name__ == "__main__":
+    # Testar com a resposta do modelo
+    test_model(force_default=False)
+    
+    # Testar com a resposta padrão forçada
+    logging.info("Testing with forced default response...")
+    test_model(force_default=True)