| from __future__ import annotations |
|
|
| from functools import lru_cache |
| import json |
|
|
| import gradio as gr |
|
|
| from agent import Agent |
| from config import AppConfig, load_environment |
| from model import ModelRunner |
| from prompts import DEFAULT_SYSTEM_PROMPT |
| from tools import build_default_tool_registry |
|
|
|
|
| @lru_cache(maxsize=1) |
| def get_agent() -> Agent: |
| api_key = load_environment() |
| runner = ModelRunner.load( |
| model_name=AppConfig.model_name, |
| api_key=api_key, |
| base_url=AppConfig.base_url, |
| ) |
| tools = build_default_tool_registry() |
| return Agent(runner=runner, tools=tools, system_prompt=DEFAULT_SYSTEM_PROMPT) |
|
|
|
|
| def run_agent(task: str, max_steps: int, temperature: float) -> tuple[str, str]: |
| agent = get_agent() |
| result, trace = agent.run(task, max_steps=int(max_steps), temperature=temperature, verbose=False) |
| response = "" if result is None else str(result) |
| trace_text = json.dumps(trace, indent=2, ensure_ascii=False) |
| return response, trace_text |
|
|
|
|
| def build_demo() -> gr.Blocks: |
| custom_css = """ |
| @import url('https://fonts.googleapis.com/css2?family=Inter:opsz,wght@14..32,300;14..32,400;14..32,500;14..32,600;14..32,700&display=swap'); |
| |
| /* ========== BASE ========== */ |
| *, *::before, *::after { |
| font-family: 'Inter', -apple-system, BlinkMacSystemFont, 'Segoe UI', Helvetica, sans-serif !important; |
| box-sizing: border-box !important; |
| } |
| |
| /* ========== TITLE ========== */ |
| #app-title { |
| background: transparent !important; |
| border: none !important; |
| padding: 8px 0 !important; |
| } |
| |
| /* ========== DISCLAIMER BANNER ========== */ |
| #disclaimer-banner { |
| background-color: #3F3F46 !important; |
| border: 2px solid #FF2717 !important; |
| border-left: 6px solid #FEA12D !important; |
| border-radius: 8px !important; |
| padding: 16px 20px !important; |
| margin-bottom: 12px !important; |
| } |
| #disclaimer-banner p { |
| margin: 2px 0 !important; |
| color: #E4E4E7 !important; |
| } |
| """ |
|
|
| with gr.Blocks(theme=gr.themes.Base(), title="Financial Agent", css=custom_css) as demo: |
| |
| gr.Markdown( |
| """ |
| # Financial Agent |
| Uses **LLaMA 3.3 70B** via NVIDIA NIM (OpenAI-compatible API). |
| Ask for stock prices, company profiles, and more! The agent can use tools to fetch real-time data and provide accurate responses. |
| """, |
| elem_id="app-title", |
| ) |
|
|
| with gr.Row(): |
| with gr.Column(scale=1): |
| task_input = gr.Textbox( |
| label="User task", |
| value="", |
| lines=3, |
| placeholder="Ask for a stock price, e.g. Tesla, Apple, Nvidia...", |
| ) |
| with gr.Row(): |
| max_steps_slider = gr.Slider( |
| minimum=1, |
| maximum=20, |
| value=5, |
| step=1, |
| label="Max iterations", |
| ) |
| temperature_slider = gr.Slider( |
| minimum=0.0, |
| maximum=1.0, |
| value=0.3, |
| step=0.05, |
| label="Temperature", |
| ) |
| run_button = gr.Button("Run agent", variant="primary") |
|
|
| with gr.Column(scale=1): |
| response_output = gr.Textbox(label="Final response", lines=3) |
| trace_output = gr.Code(label="Tool trace", language="json", elem_id="trace_output") |
|
|
| run_button.click( |
| fn=run_agent, |
| inputs=[task_input, max_steps_slider, temperature_slider], |
| outputs=[response_output, trace_output], |
| ) |
|
|
| gr.Markdown( |
| """ |
| # Agent User Guide |
| |
| | If you want to... | Example prompt | |
| |------------------|----------------| |
| | Know the latest price of a stock | "What's the current price of Apple?" | |
| | Get company information | "Tell me about Tesla's business sector and industry" | |
| | Build a low-risk portfolio | "Create a minimum variance portfolio with Microsoft, Google, and Amazon" | |
| | Maximize return for the risk taken | "Give me the best risk-return portfolio using Apple, Nvidia, and Meta" | |
| | Reduce downside risk compared to the S&P500 | "Build a portfolio that minimizes losses relative to the S&P500 using these 5 stocks" | |
| | Find economic data from the US (FRED) | "What was the unemployment rate in December 2024?" | |
| | Check Mexican CETES rates | "What's the 28-day CETES rate today?" | |
| | Know monthly inflation in Mexico | "What was Mexico's monthly inflation last month?" | |
| | Know annual inflation in Mexico | "What's the current annual inflation rate in Mexico?" | |
| | Get the UDI value in Mexico | "What is the UDI value today?" | |
| | Check Mexican TIE interest rates | "Show me the 91-day TIE rate" | |
| | Know Mexico's central bank interest rate | "What is Mexico's target interest rate right now?" | |
| | Get cross-currency exchange rates | "What's the current exchange rate for EUR/USD?" | |
| | Analyze news sentiment for a stock | "What is the market sentiment around Tesla right now?" | |
| | Calculate the impact of inflation | "how much would inflation in mexico affect my 1000 pesos over 5 months?" | |
| | Make a fundamental analysis of a stock | "What is the fundamental analysis of Microsoft?" | |
| """ |
| ) |
|
|
| gr.Markdown( |
| """ |
| ⚠️ **EDUCATIONAL PURPOSES ONLY — NOT FINANCIAL ADVICE** |
| |
| This agent is a student project built for a Deep Learning course. It is **not** a licensed financial advisor, |
| broker, or investment service. All outputs — including stock prices, portfolio suggestions, economic indicators, |
| and any other financial data — are provided **strictly for educational and demonstration purposes**. |
| |
| **Do not use this tool to make real investment, trading, or financial decisions.** |
| The information may be inaccurate, delayed, or incomplete. Always consult a qualified financial professional |
| before making any investment decision. The authors assume no liability for any actions taken based on |
| the outputs of this agent. |
| """, |
| elem_id="disclaimer-banner", |
| ) |
|
|
| return demo |
|
|
|
|
| demo = build_demo() |
|
|
| if __name__ == "__main__": |
| demo.launch() |
|
|
