app.py

import openai
import os

# Initialize the OpenAI client
from openai import OpenAI
# HF
API_KEY = os.getenv("OPENAI_API_KEY")
client = OpenAI(api_key=API_KEY)

import gradio as gr

def gpt41(users_input):
    response = client.responses.create(
        model="gpt-4.1-mini",
        input=f'''
        You name is AI Academy, the purpose of this chatbot is to support the user
        On their learning journey to create AI Agents. Diego have created a youtube video under 'AI Academy' youtube Channel,
        Explaining how to create AI Agents, for beginners that dont know how to code. The proocess shows them how to download
        an IDE then start to code. README:
        'Intro
        
        This repository is a basic guide on how to build AI Agents using pyhton and OpenAI Agents SDK
        
        Requirements
        
        OpenAI API Key (This has a cost attached to it, you will need a credit card, the good news is that is very cheap, model: GPT 4.1 mini. Input price: $0.40 / 1M tokens (like 'words') and $1.60 for 1M output) Get your key here -> https://www.google.com/url?sa=t&source=web&rct=j&opi=89978449&url=https://platform.openai.com/api-keys&ved=2ahUKEwi3m7vSg--NAxUzTTABHY5LJRcQFnoECCkQAQ&usg=AOvVaw1YhcGDWJXhiKSfmL59Pnfn
        Beginner friendly step by step
        
        -Download Cursor, VS Code or Windsurf to your computer (Google it) -Open your IDE (Cursor, Windsurf, VSCode) and then click on Open Folder (create a folder for this project) -Go to the top left and chose Terminal -> New Terminal
        
        In the Terminal: copy and paste this + enter:
        git clone https://github.com/diegocp01/openai_agents.git
        Make sure your folder name on the left is the same as the terminal. (if not, take a screenshoot and ask chatgpt. Is a quick cd command)
        
        -Create a new file inside of the openai-sdk-agent folder, called '.env' -Inside of the .env file copy this:
        
        # Copy and paste your openai api key below instead of the 'sk-12....'
        OPENAI_API_KEY=sk-12232432
        
        # The LLM to use find more llm names here
        #https://platform.openai.com/docs/models
        MODEL_CHOICE=gpt-4.1-nano
        -In the Terminal: Install the required dependencies: Create a virtual enviroment like this ->
        
        python -m venv .venv
        If your IDE asks you to create a python ENV click YES
        
        -Then in the terminal paste this (This activates the enviroment):
        
        source .venv/bin/activate
        -Now you will install the openai agents sdk and other frameworks needed -(The frameworks are listed in the requirements file)
        
        pip install -r requirements.txt
        Then paste this in the terminal (with your openai key from .env file)
        
        export OPENAI_API_KEY=sk-122
        Files
        
        v1_basic_agent.py - Basic Agent
        v2_structured_output.py - Agent with organized outputs
        v3_tool_calls.py - Agent with access to tools
        v4_handoffs.py - Orchestrator Agents with Specialized agents
        Running the Agents
        
        Basic Agent (v1)
        
        Run the basic agent example:
        
        python v1_basic_agent.py
        Structured Output Agent (v2)
        
        Run the Agent with organized outputs:
        
        python v2_structured_output.py
        Tool Calls Agent (v3)
        
        Run the tool calls travel agent example:
        
        python v3_tool_calls.py
        Now we will give our agent some TOOLS! (This is when it gets fun!) Recipe Agent
        
        Handoffs Agent (v4)
        
        Run the Orchestrator Agents with Specialized agents
        
        python v4_handoffs.py
        Run the interactive user interface app
        
        streamlit run app.py'
        Here is the code for the basic structure: 
        v1_basic_agent.py '
        
        # ==============================================================================
        # This Agent is only a regular talk to ChatGPT, you send a prompt and get a response
        # ==============================================================================
        
        
        # --- Imports ---
        from agents import Agent, Runner
        from dotenv import load_dotenv
        
        # --- Load environment variables ---
        load_dotenv()
        
        # --- Agent ---
        agent = Agent(
            name="Assistant", 
            instructions="You are a helpful assistant", # This is the system prompt that tells the AI how to behave, change it if you want
            model="gpt-4.1-nano" # Change the model here
        )
        
        # --- Main --
        # The main function runs the AI agent synchronously with a predefined prompt,
        # asking it to write a haiku about recursion, and then prints the generated response.
        def main():
            result = Runner.run_sync(agent, """
            Say: Hello my name is ChatGPT, this is a test. Now add something you will 
            like to tell the user. Your whole output is max 30 words.
            """) # This is the PROMPT
            print(result.final_output)
        
        # --- Run ---
        # This ensures that the main() function only runs when this script is executed directly,
        # not when it is imported as a module in another file.
        if __name__ == "__main__":
            main()'

        If the user asks for code for the other files you ask the user to provide it.
        The user's question: {users_input}
        ''',
        max_output_tokens=700
    )
    return(response.output_text)

# Gradio Interface
demo = gr.Interface(
    fn=gpt41,
    inputs="text",
    outputs="text",
    title="🧠 AI Academy Support Assistant",
    description="Welcome to your AI Agent learning! 🚀\n"
                "**Disclaimer**: This chatbot is stateless — it does NOT remember past messages. "
                "Ask one question at a time."
)

demo.launch()