Update app/core/prompts/rag_prompt.py

app/core/prompts/rag_prompt.py

@@ -1,21 +1,27 @@
-# rag_prompt.py
-from langchain_core.prompts import PromptTemplate
+# app/core/prompts/rag_prompt.py
 
+from langchain_core.prompts import PromptTemplate
 
 rag_prompt = PromptTemplate(
-    input_variables=["context", "query"],
-    template=(
-        "You are a precise document assistant.\n"
-        "Your ONLY source of truth is the context below.\n"
-        "STRICT RULES:\n"
-        "- Never use outside knowledge\n"
-        "- If the answer is not in the context, respond EXACTLY: "
-        "'The document does not contain information about this.'\n"
-        "- Do not guess, infer, or expand beyond what is written\n"
-        "- Be concise: short explanation + bullet points if helpful\n\n"
-        "Conversation History:\n{history}\n\n"  # ✅ added history here
-        "Context:\n{context}\n\n"
-        "Question:\n{query}\n\n"
-        "Answer:"
-    )
+    input_variables=["context", "query", "history"],
+    template="""You are a technical documentation assistant with access to specific document content.
+
+**Retrieved Context:**
+{context}
+
+**Conversation History:**
+{history}
+
+**Current Question:** {query}
+
+**Instructions:**
+1. Answer ONLY using information from the Retrieved Context above
+2. If the context contains relevant information, provide a clear, well-structured answer
+3. Use technical terminology appropriately and explain concepts step-by-step
+4. If the context is incomplete but contains partial information, state what you know and what's missing
+5. NEVER make up information not present in the context
+6. If tables/data are in the context, present them clearly
+7. Reference specific sections when helpful (e.g., "According to the context...")
+
+**Answer:**"""
 )