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import gradio as gr
from response_parser import *
def initialization(state_dict: Dict) -> None:
if not os.path.exists('cache'):
os.mkdir('cache')
if state_dict["bot_backend"] is None:
state_dict["bot_backend"] = BotBackend()
if 'OPENAI_API_KEY' in os.environ:
del os.environ['OPENAI_API_KEY']
def get_bot_backend(state_dict: Dict) -> BotBackend:
return state_dict["bot_backend"]
def switch_to_gpt4(state_dict: Dict, whether_switch: bool) -> None:
bot_backend = get_bot_backend(state_dict)
if whether_switch:
bot_backend.update_gpt_model_choice("GPT-4")
else:
bot_backend.update_gpt_model_choice("GPT-3.5")
def add_text(state_dict: Dict, history: List, text: str) -> Tuple[List, Dict]:
bot_backend = get_bot_backend(state_dict)
bot_backend.add_text_message(user_text=text)
history = history + [(text, None)]
return history, gr.update(value="", interactive=False)
def add_file(state_dict: Dict, history: List, files) -> List:
bot_backend = get_bot_backend(state_dict)
for file in files:
path = file.name
filename = os.path.basename(path)
bot_msg = [f'📁[{filename}]', None]
history.append(bot_msg)
bot_backend.add_file_message(path=path, bot_msg=bot_msg)
_, suffix = os.path.splitext(filename)
if suffix in {'.jpg', '.jpeg', '.png', '.bmp', '.webp'}:
copied_file_path = f'{bot_backend.jupyter_work_dir}/{filename}'
width, height = get_image_size(copied_file_path)
bot_msg[0] += \
f'\n<img src=\"file={copied_file_path}\" style=\'{"" if width < 800 else "width: 800px;"} max-width' \
f':none; max-height:none\'> '
return history
def undo_upload_file(state_dict: Dict, history: List) -> Tuple[List, Dict]:
bot_backend = get_bot_backend(state_dict)
bot_msg = bot_backend.revoke_file()
if bot_msg is None:
return history, gr.Button.update(interactive=False)
else:
assert history[-1] == bot_msg
del history[-1]
if bot_backend.revocable_files:
return history, gr.Button.update(interactive=True)
else:
return history, gr.Button.update(interactive=False)
def refresh_file_display(state_dict: Dict) -> List[str]:
bot_backend = get_bot_backend(state_dict)
work_dir = bot_backend.jupyter_work_dir
filenames = os.listdir(work_dir)
paths = []
for filename in filenames:
path = os.path.join(work_dir, filename)
if not os.path.isdir(path):
paths.append(path)
return paths
def refresh_token_count(state_dict: Dict):
bot_backend = get_bot_backend(state_dict)
model_choice = bot_backend.gpt_model_choice
sliced = bot_backend.sliced
token_count = bot_backend.context_window_tokens
token_limit = config['model_context_window'][config['model'][model_choice]['model_name']]
display_text = f"**Context token:** {token_count}/{token_limit}"
if sliced:
display_text += '\\\nToken limit exceeded, conversion has been sliced.'
return gr.Markdown.update(value=display_text)
def restart_ui(history: List) -> Tuple[List, Dict, Dict, Dict, Dict, Dict, Dict]:
history.clear()
return (
history,
gr.Textbox.update(value="", interactive=False),
gr.Button.update(interactive=False),
gr.Button.update(interactive=False),
gr.Button.update(interactive=False),
gr.Button.update(interactive=False),
gr.Button.update(visible=False)
)
def restart_bot_backend(state_dict: Dict) -> None:
bot_backend = get_bot_backend(state_dict)
bot_backend.restart()
def stop_generating(state_dict: Dict) -> None:
bot_backend = get_bot_backend(state_dict)
if bot_backend.code_executing:
bot_backend.send_interrupt_signal()
else:
bot_backend.update_stop_generating_state(stop_generating=True)
def bot(state_dict: Dict, history: List) -> List:
bot_backend = get_bot_backend(state_dict)
while bot_backend.finish_reason in ('new_input', 'function_call'):
if history[-1][1]:
history.append([None, ""])
else:
history[-1][1] = ""
try:
response = chat_completion(bot_backend=bot_backend)
for chunk in response:
if chunk['choices'] and chunk['choices'][0]['finish_reason'] == 'function_call':
if bot_backend.function_name in bot_backend.jupyter_kernel.available_functions:
yield history, gr.Button.update(value='⏹️ Interrupt execution'), gr.Button.update(visible=False)
else:
yield history, gr.Button.update(interactive=False), gr.Button.update(visible=False)
if bot_backend.stop_generating:
response.close()
if bot_backend.content:
bot_backend.add_gpt_response_content_message()
if bot_backend.display_code_block:
bot_backend.update_display_code_block(
display_code_block="\n⚫Stopped:\n```python\n{}\n```".format(bot_backend.code_str)
)
history = copy.deepcopy(bot_backend.bot_history)
history[-1][1] += bot_backend.display_code_block
bot_backend.add_function_call_response_message(function_response=None)
bot_backend.reset_gpt_response_log_values()
break
history, weather_exit = parse_response(
chunk=chunk,
history=history,
bot_backend=bot_backend
)
yield (
history,
gr.Button.update(
interactive=False if bot_backend.stop_generating else True,
value='⏹️ Stop generating'
),
gr.Button.update(visible=False)
)
if weather_exit:
exit(-1)
except openai.OpenAIError as openai_error:
bot_backend.reset_gpt_response_log_values(exclude=['finish_reason'])
yield history, gr.Button.update(interactive=False), gr.Button.update(visible=True)
raise openai_error
yield history, gr.Button.update(interactive=False, value='⏹️ Stop generating'), gr.Button.update(visible=False)
if __name__ == '__main__':
config = get_config()
with gr.Blocks(theme=gr.themes.Base()) as block:
"""
Reference: https://www.gradio.app/guides/creating-a-chatbot-fast
"""
# UI components
state = gr.State(value={"bot_backend": None})
with gr.Tab("Chat"):
chatbot = gr.Chatbot([], elem_id="chatbot", label="Local Code Interpreter", height=750)
with gr.Row():
with gr.Column(scale=0.85):
text_box = gr.Textbox(
show_label=False,
placeholder="Enter text and press enter, or upload a file",
container=False
)
with gr.Column(scale=0.15, min_width=0):
file_upload_button = gr.UploadButton("📁", file_count='multiple', file_types=['file'])
with gr.Row(equal_height=True):
with gr.Column(scale=0.08, min_width=0):
check_box = gr.Checkbox(label="Use GPT-4", interactive=config['model']['GPT-4']['available'])
with gr.Column(scale=0.314, min_width=0):
model_token_limit = config['model_context_window'][config['model']['GPT-3.5']['model_name']]
token_count_display_text = f"**Context token:** 0/{model_token_limit}"
token_monitor = gr.Markdown(value=token_count_display_text)
with gr.Column(scale=0.15, min_width=0):
retry_button = gr.Button(value='🔂OpenAI Error, click here to retry', visible=False)
with gr.Column(scale=0.15, min_width=0):
stop_generation_button = gr.Button(value='⏹️ Stop generating', interactive=False)
with gr.Column(scale=0.15, min_width=0):
restart_button = gr.Button(value='🔄 Restart')
with gr.Column(scale=0.15, min_width=0):
undo_file_button = gr.Button(value="↩️Undo upload file", interactive=False)
with gr.Tab("Files"):
file_output = gr.Files()
# Components function binding
txt_msg = text_box.submit(add_text, [state, chatbot, text_box], [chatbot, text_box], queue=False).then(
lambda: gr.Button.update(interactive=False), None, [undo_file_button], queue=False
).then(
bot, [state, chatbot], [chatbot, stop_generation_button, retry_button]
)
txt_msg.then(fn=refresh_file_display, inputs=[state], outputs=[file_output])
txt_msg.then(lambda: gr.update(interactive=True), None, [text_box], queue=False)
txt_msg.then(fn=refresh_token_count, inputs=[state], outputs=[token_monitor])
retry_button.click(lambda: gr.Button.update(visible=False), None, [retry_button], queue=False).then(
bot, [state, chatbot], [chatbot, stop_generation_button, retry_button]
).then(
fn=refresh_file_display, inputs=[state], outputs=[file_output]
).then(
lambda: gr.update(interactive=True), None, [text_box], queue=False
).then(
fn=refresh_token_count, inputs=[state], outputs=[token_monitor]
)
check_box.change(fn=switch_to_gpt4, inputs=[state, check_box]).then(
fn=refresh_token_count, inputs=[state], outputs=[token_monitor]
)
file_msg = file_upload_button.upload(
add_file, [state, chatbot, file_upload_button], [chatbot], queue=False
)
file_msg.then(lambda: gr.Button.update(interactive=True), None, [undo_file_button], queue=False)
file_msg.then(fn=refresh_file_display, inputs=[state], outputs=[file_output])
undo_file_button.click(
fn=undo_upload_file, inputs=[state, chatbot], outputs=[chatbot, undo_file_button]
).then(
fn=refresh_file_display, inputs=[state], outputs=[file_output]
)
stop_generation_button.click(fn=stop_generating, inputs=[state], queue=False).then(
fn=lambda: gr.Button.update(interactive=False), inputs=None, outputs=[stop_generation_button], queue=False
)
restart_button.click(
fn=restart_ui, inputs=[chatbot],
outputs=[
chatbot, text_box, restart_button, file_upload_button, undo_file_button, stop_generation_button,
retry_button
]
).then(
fn=restart_bot_backend, inputs=[state], queue=False
).then(
fn=refresh_file_display, inputs=[state], outputs=[file_output]
).then(
fn=lambda: (gr.Textbox.update(interactive=True), gr.Button.update(interactive=True),
gr.Button.update(interactive=True)),
inputs=None, outputs=[text_box, restart_button, file_upload_button], queue=False
).then(
fn=refresh_token_count,
inputs=[state], outputs=[token_monitor]
)
block.load(fn=initialization, inputs=[state])
block.queue()
block.launch(inbrowser=True)
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