Update app.py

app.py

@@ -17,7 +17,7 @@ folder = snapshot_download(repo_id="umaiku/faiss_index", repo_type="dataset", lo
 embeddings = HuggingFaceEmbeddings(model_name="intfloat/multilingual-e5-small")
 
 vector_db = FAISS.load_local("faiss_index", embeddings, allow_dangerous_deserialization=True)
-retriever = vector_db.as_retriever(search_kwargs={"k": 1})
+retriever = vector_db.as_retriever(search_type="similarity_score_threshold", search_kwargs={"score_threshold": 0.75})
 
 def respond(
     message,
@@ -29,11 +29,14 @@ def respond(
 ):
     messages = [{"role": "system", "content": system_message}]
 
-    document = retriever.invoke(message)[0]
+    document = retriever.invoke(message)
 
-    print(document)
+    if document == []:
+        message = message + "\nNo cases were found about this subject"
+    else:
+        message = message + "\nUse the following jurisprudence case to answer " + document[0].page_content + "\n Give the following url " + document[0].metadata["case_url"]
     
-    message = message + "\nUse the following jurisprudence case to answer " + document.page_content + "\n Give the following url " + document.metadata["case_url"]
+    print(message)
     
     for val in history:
         if val[0]: