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"""Test."""
# pylint: disable=invalid-name, unused-import, broad-except,
import os
from copy import deepcopy
from textwrap import dedent
import gradio as gr
import httpx
from loguru import logger
from app import (embed_files, ingest, ns, ns_initial, process_files, respond,
upload_files)
from load_api_key import load_api_key, pk_base, sk_base
api_key = load_api_key()
if api_key is not None:
os.environ.setdefault("OPENAI_API_KEY", api_key)
if api_key.startswith("sk-"):
os.environ.setdefault("OPENAI_API_BASE", sk_base)
elif api_key.startswith("pk-"):
os.environ.setdefault("OPENAI_API_BASE", pk_base)
# resetip
try:
url = "https://api.pawan.krd/resetip"
headers = {"Authorization": f"{api_key}"}
httpx.post(url, headers=headers)
except Exception as exc_:
logger.error(exc_)
raise
openai_api_key = os.getenv("OPENAI_API_KEY")
openai_api_base = os.getenv("OPENAI_API_BASE")
logger.info(f"openai_api_key (env var/hf space SECRETS): {openai_api_key}")
logger.info(f"openai_api_base: {openai_api_base}")
with gr.Blocks(theme=gr.themes.Soft()) as demo:
with gr.Tab("Upload files"): # Tab1
with gr.Accordion("Info", open=False):
_ = """
### multilingual dokugpt/多语dokugpt
和你的文件对话： 可用中文向外语文件提问或用外语向中文文件提问
Talk to your docs (.pdf, .docx, .epub, .txt .md and
other text docs): You can ask questions in a language you prefer, independent of the document language.
It
takes quite a while to ingest docs (5-30 min. depending
on net, RAM, CPU etc.).
Send empty query (hit Enter) to check embedding status and files info ([filename, numb of chars])
Homepage: https://huggingface.co/spaces/mikeee/multilingual-dokugpt
"""
gr.Markdown(dedent(_))
# Upload files and generate vectorstore
with gr.Row():
file_output = gr.File()
# file_output = gr.Text()
# file_output = gr.DataFrame()
upload_button = gr.UploadButton(
"Click to upload",
# file_types=["*.pdf", "*.epub", "*.docx"],
file_count="multiple",
)
with gr.Row():
text2 = gr.Textbox("Process docs")
process_btn = gr.Button("Click to process")
with gr.Row():
text_embed = gr.Textbox("Generate embeddings")
embed_btn = gr.Button("Click to embed")
reset_btn = gr.Button("Reset everything", visible=False)
with gr.Tab("Query docs"): # Tab1
# interactive chat
chatbot = gr.Chatbot()
msg = gr.Textbox(label="Query")
clear = gr.Button("Clear")
# actions
def reset_all():
"""Reset ns."""
# global ns
globals().update(**{"ns": deepcopy(ns_initial)})
return f"reset done: ns={ns}"
# Tab1
upload_button.upload(upload_files, upload_button, file_output)
process_btn.click(process_files, [], text2)
embed_btn.click(embed_files, [], text_embed)
reset_btn.click(reset_all, [], text2)
# Tab2
msg.submit(respond, [msg, chatbot], [msg, chatbot])
clear.click(lambda: None, None, chatbot, queue=False)
if __name__ == "__main__":
demo.queue(concurrency_count=20).launch()
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