Deploying Pythonic RAG

app.py

@@ -1,3 +1,6 @@
+# flake8: noqa
+# pyright: ignore-all
+
 import os
 from typing import List
 from chainlit.types import AskFileResponse
@@ -25,6 +28,7 @@ Question:
 """
 user_role_prompt = UserRolePrompt(user_prompt_template)
 
+
 class RetrievalAugmentedQAPipeline:
     def __init__(self, llm: ChatOpenAI(), vector_db_retriever: VectorDatabase) -> None:
         self.llm = llm
@@ -39,21 +43,28 @@ class RetrievalAugmentedQAPipeline:
 
         formatted_system_prompt = system_role_prompt.create_message()
 
-        formatted_user_prompt = user_role_prompt.create_message(question=user_query, context=context_prompt)
+        formatted_user_prompt = user_role_prompt.create_message(
+            question=user_query, context=context_prompt
+        )
 
         async def generate_response():
-            async for chunk in self.llm.astream([formatted_system_prompt, formatted_user_prompt]):
+            async for chunk in self.llm.astream(
+                [formatted_system_prompt, formatted_user_prompt]
+            ):
                 yield chunk
 
         return {"response": generate_response(), "context": context_list}
 
+
 text_splitter = CharacterTextSplitter()
 
 
 def process_text_file(file: AskFileResponse):
     import tempfile
 
-    with tempfile.NamedTemporaryFile(mode="w", delete=False, suffix=".txt") as temp_file:
+    with tempfile.NamedTemporaryFile(
+        mode="w", delete=False, suffix=".txt"
+    ) as temp_file:
         temp_file_path = temp_file.name
 
     with open(temp_file_path, "wb") as f:
@@ -93,15 +104,14 @@ async def on_chat_start():
     # Create a dict vector store
     vector_db = VectorDatabase()
     vector_db = await vector_db.abuild_from_list(texts)
-    
+
     chat_openai = ChatOpenAI()
 
     # Create a chain
     retrieval_augmented_qa_pipeline = RetrievalAugmentedQAPipeline(
-        vector_db_retriever=vector_db,
-        llm=chat_openai
+        vector_db_retriever=vector_db, llm=chat_openai
     )
-    
+
     # Let the user know that the system is ready
     msg.content = f"Processing `{file.name}` done. You can now ask questions!"
     await msg.update()
@@ -119,4 +129,4 @@ async def main(message):
     async for stream_resp in result["response"]:
         await msg.stream_token(stream_resp)
 
-    await msg.send()
+    await msg.send()