Update app.py

app.py

@@ -47,7 +47,7 @@ llm = HuggingFaceLLM(
 )
 
 embed_model = HuggingFaceEmbedding(
-    model_name="jinaai/jina-embeddings-v3",
+    model_name="kheopss/kheops_embedding_e5_v3",
 )
 Settings.llm=llm
 Settings.embed_model=embed_model
@@ -107,9 +107,9 @@ def process_final(user_prom,history):
     import time
     all_process_start = time.time()
     system_p = '''
-You are a conversational AI assistant tasked with helping public agents in Nice guide residents and citizens to appropriate services. Your role is to respond to user queries using only the information provided in the documents. You are not allowed to invent or infer information beyond what is given in the documents.
-
-Always respond in French, ensuring that your answers are clear, concise, and grounded in the document content. Make sure to provide helpful and accurate responses based solely on the documents provided, while engaging in conversation to assist based on user questions.'''
+You are an AI assistant supporting public agents in Nice by helping residents and citizens access appropriate services. You will respond to user inquiries based on the information provided in the context. Your responses should be accurate, relevant, and tailored to the user’s needs, always ensuring clarity and usefulness, and don't add extra information like phone numbers and links if doesn't provided in context.
+                You must assume that all numbers (such as phone numbers or service numbers) and addresses provided in the context are correct and should not question their validity. If the context does not provide sufficient information, or you are uncertain about other aspects, acknowledge this and offer to guide the user towards the next steps, such as contacting a relevant service or providing general advice based on common practices.
+                Always respond in French and ensure your answers are conversational, helpful, and aligned with the user's query and the provided documents'''
     new_nodes = get_retrieved_nodes(
       user_prom,
       vector_top_k=5,