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from typing import List
import streamlit as st
from langchain.docstore.document import Document
from core.parsing import File
import openai
from streamlit.logger import get_logger
from typing import NoReturn
logger = get_logger(__name__)
def wrap_doc_in_html(docs: List[Document]) -> str:
"""Wraps each page in document separated by newlines in <p> tags"""
text = [doc.page_content for doc in docs]
if isinstance(text, list):
# Add horizontal rules between pages
text = "\n<hr/>\n".join(text)
return "".join([f"<p>{line}</p>" for line in text.split("\n")])
def is_query_valid(query: str) -> bool:
if not query:
st.error("Please enter a question!")
return False
return True
def is_file_valid(file: File) -> bool:
if (
len(file.docs) == 0
or "".join([doc.page_content for doc in file.docs]).strip() == ""
):
st.error("Cannot read document! Make sure the document has selectable text")
logger.error("Cannot read document")
return False
return True
def display_file_read_error(e: Exception, file_name: str) -> NoReturn:
st.error("Error reading file. Make sure the file is not corrupted or encrypted")
logger.error(f"{e.__class__.__name__}: {e}. Extension: {file_name.split('.')[-1]}")
st.stop()
@st.cache_data(show_spinner=False)
def is_open_ai_key_valid(openai_api_key, model: str) -> bool:
if model == "debug":
return True
if not openai_api_key:
st.error("Please enter your OpenAI API key in the sidebar!")
return False
try:
openai.ChatCompletion.create(
model=model,
messages=[{"role": "user", "content": "test"}],
api_key=openai_api_key,
)
except Exception as e:
st.error(f"{e.__class__.__name__}: {e}")
logger.error(f"{e.__class__.__name__}: {e}")
return False
return True
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