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import copy
import json
import os
import gradio as gr
import openai
from dotenv import load_dotenv
from gradio_pdf import PDF
from create_assistant import INSTRUCTIONS, MODEL
from thread import create_assistant_then_thread, render_markdown
load_dotenv()
OUTPUT_PATH = "data"
IMAGES_PATH = "images"
def fix_image_paths_in_thread(thread, base_path):
for tweet in thread:
for media in tweet.get("media"):
media["path"] = os.path.join(
"file", OUTPUT_PATH, os.path.basename(base_path), media["path"]
)
return thread
def run_create_thread(
url_or_path, openai_api_key, assistant_instructions, assistant_model
):
if not openai_api_key:
raise gr.Error("No OpenAI API Key provided.")
client = openai.OpenAI(api_key=openai_api_key)
try:
saved_path = create_assistant_then_thread(
url_or_path,
OUTPUT_PATH,
client,
assistant_kwargs={
"instructions": assistant_instructions,
"model": assistant_model,
},
)
except Exception as e:
raise gr.Error(e)
with open(os.path.join(saved_path, "processed_thread.json"), "r") as f:
thread = json.load(f)
fixed_thread = fix_image_paths_in_thread(copy.deepcopy(thread), saved_path)
thread_md = render_markdown(fixed_thread)
return (
thread_md,
json.dumps(thread, indent=2),
)
with gr.Blocks() as demo:
banner = gr.Markdown(
"""<div style="display: flex; align-items: center; justify-content: center; margin-top: 20px;">
<img src="file/images/logo.png" alt="ThreadGPT Logo" style="height: 60px; margin-right: 12px; margin-top: -12px;">
<h1 style="font-size: 48px">ThreadGPT</h1>
</div>
<p align="center" style="font-size: 12px;">🚨 Please be aware that usage of GPT-4 with the assistant API can incur high costs. Make sure to monitor your usage and understand the pricing details provided by OpenAI before proceeding. 🚨
<br>
❗ There currently seems to be a bug with the Assistant API where a completed run returns no new messages from the assistant. If you encounter this, please click "Retry 🔁". ❗</p>"""
)
with gr.Accordion("Configuration"):
with gr.Row():
api_key = gr.Textbox(
value=os.getenv("OPENAI_API_KEY"),
placeholder="sk-**************",
label="OpenAI API Key",
type="password",
interactive=True,
)
with gr.Column():
assistant_instr = gr.Textbox(
value=INSTRUCTIONS,
placeholder="Enter system instructions",
label="System Instructions",
interactive=True,
)
assistant_model = gr.Textbox(
value=MODEL,
placeholder="Enter model",
label="Model",
interactive=True,
)
with gr.Row():
url_or_path_state = gr.State("")
txt = gr.Textbox(
scale=6,
show_label=False,
placeholder="https://arxiv.org/pdf/1706.03762.pdf",
container=False,
)
upload_btn = gr.UploadButton("Upload PDF 📄", file_types=[".pdf"])
retry_btn = gr.Button("Retry 🔄")
with gr.Row(visible=False) as output_row:
with gr.Column():
pdf = PDF(height=900)
with gr.Column():
with gr.Tab("Markdown"):
md_viewer = gr.Markdown()
with gr.Tab("JSON"):
json_viewer = gr.Textbox(lines=44)
txt.submit(
lambda url_or_path: ("", url_or_path, gr.Row(visible=True), "", ""),
[txt],
[txt, url_or_path_state, output_row, md_viewer, json_viewer],
).then(
lambda url_or_path: url_or_path,
[url_or_path_state],
[pdf],
).then(
run_create_thread,
[url_or_path_state, api_key, assistant_instr, assistant_model],
[md_viewer, json_viewer],
)
upload_btn.upload(
lambda path: (path, gr.Row(visible=True), "", ""),
[upload_btn],
[url_or_path_state, output_row, md_viewer, json_viewer],
).then(
lambda url_or_path: url_or_path,
[url_or_path_state],
[pdf],
).then(
run_create_thread,
[url_or_path_state, api_key, assistant_instr, assistant_model],
[md_viewer, json_viewer],
)
retry_btn.click(
lambda url_or_path: url_or_path,
[url_or_path_state],
[pdf],
).then(
run_create_thread,
[url_or_path_state, api_key, assistant_instr, assistant_model],
[md_viewer, json_viewer],
)
if __name__ == "__main__":
demo.launch(allowed_paths=[OUTPUT_PATH, IMAGES_PATH])
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