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437e8bc d8b2213 437e8bc d8b2213 437e8bc d8b2213 437e8bc d8b2213 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 | import os
import gradio as gr
from dotenv import load_dotenv
from agents.openai_agent import query_openai
from data_loaders.load_datasets import load_all_datasets
from tools.math_tools import run_math_analysis
load_dotenv()
# Callback functions
def openai_response(prompt):
return query_openai(prompt)
def run_tool(topic):
return run_math_analysis(topic)
def load_datasets_button():
datasets = load_all_datasets()
return "✅ Datasets loaded successfully:\n" + "\n".join(datasets.keys())
# Gradio UI
with gr.Blocks() as demo:
gr.Markdown("## 🤖 AI Business Agent (Math + Models + Data)")
with gr.Tab("1. Ask OpenAI"):
q = gr.Textbox(label="Your question to GPT-4")
a = gr.Textbox(label="Response", lines=10)
q_btn = gr.Button("Ask")
q_btn.click(openai_response, inputs=q, outputs=a)
with gr.Tab("2. Run Math Tool"):
tool = gr.Dropdown(
["linear_algebra", "probability", "optimization", "game_theory", "time_series", "markov"],
label="Choose Math Topic"
)
tool_btn = gr.Button("Run")
tool_out = gr.Textbox(label="Output", lines=10)
tool_btn.click(run_tool, inputs=tool, outputs=tool_out)
with gr.Tab("3. Load Datasets"):
load_btn = gr.Button("Load All Datasets")
load_out = gr.Textbox(label="Loaded Datasets")
load_btn.click(load_datasets_button, outputs=load_out)
demo.launch()
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