Use simple prompt format

app.py

@@ -74,35 +74,29 @@ class ResearchParrot:
         
         context = "\n\n".join([doc.page_content for doc in docs])
         
-        messages = [
-            {
-                "role": "system",
-                "content": """You are a research assistant for security researchers. Your job is to answer questions based on the research papers provided in the context.
-
-Guidelines:
-1. Base your answers primarily on the CONTEXT provided below.
-2. Be technical, detailed, and thorough in your explanations.
-3. If mathematical formulas or equations appear in the context, include them using LaTeX format ($...$ for inline, $$...$$ for blocks).
-4. Highlight attack techniques, payloads, algorithms, and code snippets from the context.
-5. If the context contains relevant information, use it to give a comprehensive answer.
-6. Only say you don't have information if the context truly has nothing related to the question."""
-            },
-            {
-                "role": "user", 
-                "content": f"""Here is context from research papers:
+        prompt = f"""You are a research assistant. Answer the question ONLY based on the provided context. 
+
+IMPORTANT RULES:
+- Only use information from the context below and Make a Step by Step approach.
+- If the context doesn't contain enough information to answer, say "I don't have enough information in the documents to answer this question."
+- Always make it more technical in depth as much as you can because your readers are security researchers not normal people.
+- Always highlight the attack technique, payload, math formula properly if available.
 
+Context:
 {context}
 
 Question: {question}
 
-Please provide a detailed, technical answer based on the context above. Include any relevant formulas in LaTeX format."""
-            }
+Answer:"""
+        
+        messages = [
+            {"role": "user", "content": prompt}
         ]
         
         response = self.client.chat_completion(
             messages=messages,
             model=self.model_id,
-            max_tokens=1024,
+            max_tokens=2048,
             temperature=0.3,
         )
         return response.choices[0].message.content