fix error

app.py

@@ -19,8 +19,8 @@ if "confluence_qa" not in st.session_state:
 
 @st.cache_resource
 def load_confluence(config):
-    # st.write("loading the confluence page")
-    confluence_qa = ConfluenceQA(config=config)
+    st.write("loading the confluence page")
+    confluence_qa = ConfluenceQA(config)
     confluence_qa.init_embeddings()
     confluence_qa.define_model()
     confluence_qa.store_in_vector_db()

confluence_qa.py

@@ -18,11 +18,16 @@ class ConfluenceQA:
         self.llm = HuggingFacePipeline(pipeline = pipe,model_kwargs={"temperature": 0, "max_length": 1024},)
 
     def store_in_vector_db(self) -> None:
-        config = self.config        
+        persist_directory = self.config.get("persist_directory",None)
+        confluence_url = self.config.get("confluence_url",None)
+        username = self.config.get("username",None)
+        api_key = self.config.get("api_key",None)
+        space_key = self.config.get("space_key",None)  
+        include_attachment = self.config.get("include_attachment", False)      
         loader = ConfluenceLoader(
-            url=config.confluence_url, username=config.username, api_key=config.api_key
+            url=confluence_url, username=username, api_key=api_key
         )
-        documents = loader.load(include_attachments=config.include_attachments, limit=50, space_key=config.space_key)
+        documents = loader.load(include_attachments=include_attachment, limit=50, space_key=space_key)
         text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=150)
         documents = text_splitter.split_documents(documents)
         # text_splitter = TokenTextSplitter(chunk_size=1000, chunk_overlap=10)  # This the encoding for text-embedding-ada-002
@@ -40,7 +45,7 @@ class ConfluenceQA:
         chain_type_kwargs = {"prompt": QA_CHAIN_PROMPT}
         self.qa = RetrievalQA.from_chain_type(llm=self.llm, chain_type="stuff", retriever=self.db.as_retriever(), chain_type_kwargs=chain_type_kwargs)
 
-    def __init__(self,config) -> None:
+    def __init__(self,config:dict = {}) -> None:
         self.db=None
         self.embeddings=None
         self.llm=None