| 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() |
|
|
| |
| 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()) |
|
|
| |
| 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() |
|
|
