Update app.py

app.py

@@ -84,28 +84,28 @@ def create_retriever_from_chroma(vectorstore_path="docs/chroma/", search_type='m
         vectorstore = Chroma.from_documents(
             documents=split_docs, embedding=embeddings, persist_directory=vectorstore_path
         )
+    
+    
+    retriever=vectorstore.as_retriever(search_type='mmr', search_kwargs={"k": 7})
 
-    metadata_field_info = [
-    AttributeInfo(
-        name="source",
-        description="The document  chunk is from, should be one of documents in data folder`, or `docs/cs229_lectures/MachineLearning-Lecture03.pdf`",
-        type="string",
-    ),
-    AttributeInfo(
-        name="page",
-        description="The page from the document",
-        type="integer",
-    ),
-]
-    document_content_description = "Respublic of Lithuania law documents"
-    retriever = SelfQueryRetriever.from_llm(
-    llm,
-    vectorstore,
-    document_content_description,
-    metadata_field_info,
-    verbose=True
+    contextualize_q_system_prompt = """If the question is not clear, given a chat history and the latest user question
+    which maybe reference context, formulate a standalone question,
+    which can be understood without the chat history. Do NOT answer the question,
+    just reformulate it if needed and otherwise return it as is."""
+    
+   )
+
+    contextualize_q_prompt = ChatPromptTemplate.from_messages(
+    [
+        ("system", contextualize_q_system_prompt),
+        MessagesPlaceholder("chat_history"),
+        ("human", "{input}"),
+    ]
 )
-    return retriever
+
+    ha_retriever = create_history_aware_retriever(llm, retriever, contextualize_q_prompt)
+
+    return ha_retriever