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from typing import List | |
import streamlit as st | |
from langchain.docstore.document import Document | |
from knowledge_gpt.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() | |
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: | |
pass | |
#openai.ChatCompletion.create( | |
# engine="chatbot-streamlit",#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 | |