Update app.py

app.py

@@ -27,13 +27,6 @@ vector_db = FAISS.load_local("faiss_index_8k", embeddings, allow_dangerous_deser
 
 df = pd.read_csv("faiss_index/bger_cedh_db 1954-2024.csv")
 
-system_prompt = """ You are an assistant in Swiss Jurisprudence law.
-Please answer the user in the same language that he used in his question using the following given context, not prior or other knowledge.
-If no relevant cases were retrieved or the issue has not been addressed within the context, just say "I can't find enough relevant information".
-Don't make up an answer or give irrelevant information not requested by the user and do not give any links that are not provided in the context.
-Otherwise, if relevant cases were found, start by summarizing these cases in the user's question's language and reference the sources, including the source, urls and dates.
-"""
-
 def respond(
     message,
     history: list[tuple[str, str]],
@@ -43,6 +36,10 @@ def respond(
     top_p,
     score,
 ):
+    messages = [{"role": "system", "content": system_message}]
+
+    print(system_message)
+    
     retriever = vector_db.as_retriever(search_type="similarity_score_threshold", search_kwargs={"score_threshold": score})
     documents = retriever.invoke(message)
 
@@ -59,27 +56,24 @@ def respond(
         context += "Case url: " + doc.metadata["case_url"] + spacer
         context += "Case text: " + doc.page_content + spacer
         #context += "Case text: " + case_text[:8000] + spacer
-
-    system_message += f"""
+    
+    
+    message = f"""
+A user is asking you the following question: {message}
+Please answer the user in the same language that he used in his question using the following given context not prior knowledge.
+Context:
 The following case extracts have been found in either Swiss Federal Court or European Court of Human Rights cases and could fit the question:
 {context}
-Instructions: Always answer the user using the language used in his question.
-"""
-
-    messages = [{"role": "system", "content": system_message}]
-
-    print(system_message)
-    print(message)
-   
-#    message = f"""
-#The user is asking you the following question: {message}
-#The following case extracts have been found in either Swiss Federal Court or European Court of Human Rights cases and could fit the question:
-#{context}
-#Task: Always answer the user using the language used in his question: {message}
-#    """
-    
-#    print(message)
+Task:
+If the retrieved context is not relevant cases or the issue has not been addressed within the context, just say "I can't find enough relevant information".
+Don't make up an answer or give irrelevant information not requested by the user.
+Otherwise, if relevant cases were found, start by summarizing these cases in the user's question's language and reference the sources, including the urls and dates.
+Instructions:
+Always answer the user using the language used in his question: {message}
+    """
     
+    print(message)
+
 #    for val in history:
 #        if val[0]:
 #            messages.append({"role": "user", "content": val[0]})
@@ -109,7 +103,7 @@ For information on how to customize the ChatInterface, peruse the gradio docs: h
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
-        gr.Textbox(value=system_prompt, label="System message"),
+        gr.Textbox(value="You are an assistant in Swiss Jurisprudence cases.", label="System message"),
         gr.Slider(minimum=1, maximum=24000, value=5000, step=1, label="Max new tokens"),
         gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
         gr.Slider(