diff --git a/backend/rag_3/prompts.py b/backend/rag_3/prompts.py
index f0f3ae9..6e63b2e 100644
--- a/backend/rag_3/prompts.py
+++ b/backend/rag_3/prompts.py
@@ -18,10 +18,31 @@
 for retrieval. These summaries will be embedded and used to retrieve the raw image. \
 Give a concise summary of the image that is well optimized for retrieval."""
 
-RAG_PROMPT = """You will be given a mixed of text, tables, and images usually of \
-charts or graphs. Use this information to provide an answer to the user question.
-User-provided question:
-{question}
-Text and / or tables:
+RAG_PROMPT = """\
+As a chatbot assistant, your mission is to respond to user inquiries in a precise and \
+concise manner based on the documents provided as input. It is essential to respond in \
+the same language in which the question was asked. Responses must be written in a \
+professional style and must demonstrate great attention to detail. Do not invent \
+information. You must sift through various sources of information, disregarding any \
+data that is not relevant to the query's context. Your response should integrate \
+knowledge from the valid sources you have identified. Additionally, the question might \
+include hypothetical or counterfactual statements. You need to recognize these and \
+adjust your response to provide accurate, relevant information without being misled by \
+the counterfactuals. Respond to the question only taking into account the following \
+context. If no context is provided, do not answer. You may provide an answer if the \
+user explicitely asked for a general answer. You may ask the user to rephrase their \
+question, or their permission to answer without specific context from your own \
+knowledge.
+Please provide a list of the sources used at the end of your response with the \
+following template :
+```
+Sources :
+- **document title**, page x
+- **document title**, page x
+```
+
+Question: {question}
+
+Context:
 {text}
 """