gpt_mavplot / llm_plot.py
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import gradio as gr
import os
from llm.gptPlotCreator import PlotCreator
plot_creator = PlotCreator()
def add_text(history, text):
history = history + [(text, None)]
return history, ""
def add_file(history, file):
history = history + [((file.name,), None)]
return history
def format_history(history):
return "\n".join([f"Human: {entry[0]}\nAI: {entry[1]}" for entry in history ])
def bot(history):
# Get the last input from the user
user_input = history[-1][0] if history and history[-1][0] else None
print(user_input)
# Check if it is a string
if isinstance(user_input, str):
# Generate the plot
print(history)
history_str = format_history(history)
response = plot_creator.create_plot(user_input, history_str)
print(response)
history[-1][1] = response[0]
history = history + [(None, f"Here is the code used to generate the plot:")]
history = history + [(None, f"{response[1]}")]
else:
file_path = user_input[0]
plot_creator.set_logfile_name(file_path)
# get only base name
filename, extension = os.path.splitext(os.path.basename(file_path))
history[-1][0] = f"user uploaded file: {filename}{extension}"
history[-1][1] = "I will be using the file you uploaded to generate the plot. Please describe the plot you would like to generate."
return history
with gr.Blocks() as demo:
gr.Markdown("# GPT MAVPlot\n\nThis web-based tool allows users to upload mavlink tlogs in which the chat bot will use to generate plots from. It does this by creating a python script using pymavlink and matplotlib. The output includes the plot and the code used to generate it. ")
chatbot = gr.Chatbot([], elem_id="chatbot").style(height=750)
with gr.Row():
with gr.Column(scale=0.85):
txt = gr.Textbox(
show_label=False,
placeholder="Enter text and press enter, or upload an image",
).style(container=False)
with gr.Column(scale=0.15, min_width=0):
btn = gr.UploadButton("πŸ“", file_types=["image", "video", "audio"])
txt.submit(add_text, [chatbot, txt], [chatbot, txt]).then(
bot, chatbot, chatbot
)
btn.upload(add_file, [chatbot, btn], [chatbot]).then(
bot, chatbot, chatbot
)
if __name__ == "__main__":
demo.launch()