organized import statements

app.py

@@ -3,31 +3,27 @@ import boto3
 from botocore import UNSIGNED
 from botocore.client import Config
 
-from langchain.document_loaders import WebBaseLoader
 
 from huggingface_hub import AsyncInferenceClient
 
 from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
 
-
 from langchain.text_splitter import RecursiveCharacterTextSplitter
-text_splitter = RecursiveCharacterTextSplitter(chunk_size=350, chunk_overlap=10)
-
 from langchain.llms import HuggingFaceHub
-model_id = HuggingFaceHub(repo_id="HuggingFaceH4/zephyr-7b-beta", model_kwargs={"temperature":0.1, "max_new_tokens":300})
-
 from langchain.embeddings import HuggingFaceHubEmbeddings
-embeddings = HuggingFaceHubEmbeddings()
-
 from langchain.vectorstores import Chroma
-
 from langchain.chains import RetrievalQA
-
 from langchain.prompts import ChatPromptTemplate
+from langchain.document_loaders import WebBaseLoader
+
+text_splitter = RecursiveCharacterTextSplitter(chunk_size=350, chunk_overlap=10)
+
+
+model_id = HuggingFaceHub(repo_id="HuggingFaceH4/zephyr-7b-beta", model_kwargs={"temperature":0.1, "max_new_tokens":300})
+
+
+embeddings = HuggingFaceHubEmbeddings()
 
-#web_links = ["https://www.databricks.com/","https://help.databricks.com","https://docs.databricks.com","https://kb.databricks.com/","http://docs.databricks.com/getting-started/index.html","http://docs.databricks.com/introduction/index.html","http://docs.databricks.com/getting-started/tutorials/index.html","http://docs.databricks.com/machine-learning/index.html","http://docs.databricks.com/sql/index.html"]
-#loader = WebBaseLoader(web_links)
-#documents = loader.load()
 
 s3 = boto3.client('s3', config=Config(signature_version=UNSIGNED))
 s3.download_file('rad-rag-demos', 'vectorstores/chroma.sqlite3', './chroma_db/chroma.sqlite3')