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import streamlit as st
from langchain_community.document_loaders import AsyncHtmlLoader
from langchain.schema import Document
import json
from typing import Iterable
# Placeholder for async fetch function (adjust based on actual async handling in your environment)
async def fetch_documents(urls):
loader = AsyncHtmlLoader(urls)
docs = await loader.load()
return docs
def save_docs_to_jsonl(array: Iterable[Document], file_path: str) -> None:
with open(file_path, 'w') as jsonl_file:
for doc in array:
jsonl_file.write(json.dumps(doc.to_dict()) + '\n') # Assuming Document objects have a to_dict method
def load_docs_from_jsonl(file_path) -> Iterable[Document]:
array = []
with open(file_path, 'r') as jsonl_file:
for line in jsonl_file:
data = json.loads(line)
obj = Document(**data)
array.append(obj)
return array
def fetch_clean_organize_page():
st.title("Fetch, Clean, and Organize Documents")
# Initialize 'selected_urls' at the start of your app if it doesn't exist
if 'selected_urls' not in st.session_state:
st.session_state['selected_urls'] = [] # Default to an empty list
urls = st.session_state['selected_urls']
if st.button("Fetch Documents"):
# Async fetching operation placeholder
# Adjust based on your async handling strategy
docs = fetch_documents(urls) # This needs proper async handling
st.session_state['docs'] = docs # Assuming docs are fetched and stored correctly
if 'docs' in st.session_state:
st.write(f"Fetched {len(st.session_state['docs'])} documents.")
if st.button("Save Documents as JSON"):
save_docs_to_jsonl(st.session_state['docs'], "documents.jsonl")
st.success("Documents saved as JSON.")
# Provide download link (streamlit >= 0.88.0)
with open("documents.jsonl", "rb") as file:
btn = st.download_button(
label="Download JSON",
data=file,
file_name="documents.jsonl",
mime="application/octet-stream")
# Assuming this function is called in your app
fetch_clean_organize_page()
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