File size: 5,641 Bytes
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from front_end.js import js
from front_end.css import css
from LAMBDA import LAMBDA
from utils.utils import to_absolute_path
def launch_app():
Lambda = LAMBDA(config_path='config.yaml')
with gr.Blocks(theme=gr.themes.Soft(), css=css, js=js) as demo:
with gr.Tab("LAMBDA"):
gr.HTML("<H1>Welcome to LAMBDA! Easy Data Analysis!</H1>")
chatbot = gr.Chatbot(value=Lambda.conv.chat_history_display, height=600, label="LAMBDA", show_copy_button=True, type="tuples")
with gr.Group():
with gr.Row(equal_height=True):
upload_btn = gr.UploadButton(label="Upload Data", scale=1)
msg = gr.Textbox(show_label=False, placeholder="Sent message to LLM", scale=6, elem_id="chatbot_input")
submit = gr.Button("Submit", scale=1)
with gr.Row(equal_height=True):
board = gr.Button(value="Show/Update DataFrame", elem_id="df_btn", elem_classes="df_btn")
export_notebook = gr.Button(value="Notebook")
down_notebook = gr.DownloadButton("Download Notebook", visible=False)
generate_report = gr.Button(value="Generate Report")
down_report = gr.DownloadButton("Download Report", visible=False)
edit = gr.Button(value="Edit Code", elem_id="ed_btn", elem_classes="ed_btn")
save = gr.Button(value="Save Dialogue")
clear = gr.ClearButton(value="Clear All")
with gr.Group():
with gr.Row(visible=False, elem_id="ed", elem_classes="ed"):
code = gr.Code(label="Code", scale=6)
code_btn = gr.Button("Submit Code", scale=1)
code_btn.click(fn=Lambda.chat_streaming, inputs=[msg, chatbot, code], outputs=[msg, chatbot]).then(
Lambda.conv.stream_workflow, inputs=[chatbot, code], outputs=chatbot)
df = gr.Dataframe(visible=False, elem_id="df", elem_classes="df")
upload_btn.upload(fn=Lambda.add_file, inputs=upload_btn)
msg.submit(Lambda.chat_streaming, [msg, chatbot], [msg, chatbot], queue=False).then(
Lambda.conv.stream_workflow, chatbot, chatbot
)
submit.click(Lambda.chat_streaming, [msg, chatbot], [msg, chatbot], queue=False).then(
Lambda.conv.stream_workflow, chatbot, chatbot
)
board.click(Lambda.open_board, inputs=[], outputs=df)
edit.click(Lambda.rendering_code, inputs=None, outputs=code)
export_notebook.click(Lambda.export_code, inputs=None, outputs=[export_notebook, down_notebook])
down_notebook.click(Lambda.down_notebook, inputs=None, outputs=[export_notebook, down_notebook])
generate_report.click(Lambda.generate_report, inputs=[chatbot], outputs=[generate_report, down_report])
down_report.click(Lambda.down_report, inputs=None, outputs=[generate_report, down_report])
save.click(Lambda.save_dialogue, inputs=chatbot)
clear.click(fn=Lambda.clear_all, inputs=[msg, chatbot], outputs=[msg, chatbot])
# The Configuration Page
with gr.Tab("Configuration"):
gr.Markdown("# System Configuration for LAMBDA")
with gr.Row():
conv_model = gr.Textbox(value="gpt-5-mini", label="Conversation Model")
programmer_model = gr.Textbox(value="gpt-4.1-mini", label="Programmer Model")
inspector_model = gr.Textbox(value="gpt-4.1-mini", label="Inspector Model")
api_key = gr.Textbox(label="API Key", type="password", placeholder="Input Your API key")
with gr.Row():
base_url_conv_model = gr.Textbox(value='https://api.openai.com/v1', label="Base URL (Conv Model)")
base_url_programmer = gr.Textbox(value='https://api.openai.com/v1', label="Base URL (Programmer)")
base_url_inspector = gr.Textbox(value='https://api.openai.com/v1', label="Base URL (Inspector)")
with gr.Row():
max_attempts = gr.Number(value=5, label="Max Attempts", precision=0)
max_exe_time = gr.Number(value=18000, label="Max Execution Time (s)", precision=0)
with gr.Row():
load_chat = gr.Checkbox(value=False, label="Load from Cache")
chat_history_path = gr.Textbox(label="Chat History Path", visible=False, interactive=True)
save_btn = gr.Button("Save Configuration", variant="primary")
status_output = gr.Markdown("")
def toggle_chat_history_path(load_chat_checked):
return gr.Textbox(visible=load_chat_checked, interactive=True)
save_btn.click(
fn=Lambda.update_config,
inputs=[
conv_model, programmer_model, inspector_model, api_key,
base_url_conv_model, base_url_programmer, base_url_inspector,
max_attempts, max_exe_time,
load_chat, chat_history_path
],
outputs=[status_output, chatbot]
)
load_chat.change(
fn=toggle_chat_history_path,
inputs=load_chat,
outputs=chat_history_path
)
demo.launch(server_name="0.0.0.0", server_port=8000, allowed_paths=[to_absolute_path(Lambda.config["project_cache_path"])],
share=True, inbrowser=True)
if __name__ == '__main__':
launch_app()
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