Create an easy app for Openai Epython

Create an easy app for Openai Epython

Want to start with AI and Automation? Create an easy app for Openai Epython Is your clear and effective guide to introduce smart Chatbot using Python and Opelai's API. In just a few steps, newcomers can go by writing their first line of code to have an effective functional application by GPT-3.5 or GPT-4. This lesson will move to you by setting your environment, including reliance, and the writing code associated with Opelai to manage applications and procedures. You will build a fully functional chatbot using less than 50 lines of the Python code.

Healed Key

• Set your Python Nature and produce your Opelai API key
• Build an active Chatbot with a short and readable Python code
• Learn how to act with answers and treat the tokens well
• Add the best tasks to avoid excessive costs and hitting boundaries

What you need before starting

This Opelai API Python Tutorial Built for beginners. If you are new to APIs or Python, make sure you have the following:

• Installed Python (version 3.7 or more). Download it from the official Python website.
• Code editor as a vs code, pycharm, or any editor of a light text
• The basic use of the command line of command (end or command to command)
• The Openai Account With API Key

Step-by-step: Create Your Opelaai Your First Chaton Eppython

1. Set up the visual area

To keep your project depending on, create visual nature:

python -m venv openai_app
cd openai_app
source bin/activate  # On Windows: .Scriptsactivate

2 Enter the Required Required

Enter the Opelai Python client and Dotenv package:

pip install openai python-dotenv

This page dotenv The package helps you for the shop secrets, such as API buttons, safely in .env file.

3. Prepare your API key

Login to your Dashboard at Openai, create API key, and keep it in .env File to your project:

OPENAI_API_KEY="your_api_key_here"

Keep this file secure and never load it in a public place.

4. Write a little Python Chatbot text

Keep the following code as chatbot.py. This document permits to discuss AI model directly from your terminal:

import os
import openai
from dotenv import load_dotenv

load_dotenv()

openai.api_key = os.getenv("OPENAI_API_KEY")

def ask_openai(prompt, model="gpt-3.5-turbo"):
    try:
        response = openai.ChatCompletion.create(
            model=model,
            messages=[{"role": "user", "content": prompt}]
        )
        answer = response['choices'][0]['message']['content']
        return answer.strip()
    except Exception as e:
        return f"Error: {str(e)}"

while True:
    user_input = input("You: ")
    if user_input.lower() in ["exit", "quit"]:
        break
    reply = ask_openai(user_input)
    print("Bot:", reply)

5. Run your Chatbot

Start chatting with making script in your own advance:

python chatbot.py

Add questions or appear, and the bot will respond. To stop the system, type exit or quit.

To understand the response format at Openai

API Returns the Organized JSS item. Important parts include:

• choices[0].message.content: This contains a true model response
• usage: Displays Token Statistics of this application
• model: Indicates which model generated feedback

Understanding this structure helps increase the increase and manage the use of better Town. For a comprehensive AI application system, see how GPT-4 and Python works well.

Openi API Price, Measurement Restrictions, and Telephone Management

The cost of using Openai models depend on the amount of tokens. Here is the General Pricing:

• GPT-3.5-TURBO: ~ $ 0.0015 for 1k installation tokens, ~ $ 0.002 with 1k Output Tokens
• GPT-4: ~ $ 0.03 for each entry tokens 1K, ~ $ 0.06 with 1k Output Tokens

When you create an account, you can find free credits allow restricted use without charge. This is especially useful while reading or trying.

Smart Workices to control API costs

• Start brief automatically and see how many tokens use each call
• Set the monthly limit on your bill payment
• Update API logs always to identify any excessive use
• Use GPT-3.5-Turbo of the possible solutions on cost and only change in GPT-4 when required

Error to manage stiffness

Real Land Requests must be prepared for network disorders, time out, or errors. Here is a work version that promotes honesty by sending messages by a better error:

def ask_openai(prompt, model="gpt-3.5-turbo"):
    try:
        response = openai.ChatCompletion.create(
            model=model,
            messages=[{"role": "user", "content": prompt}],
            timeout=10
        )
        return response['choices'][0]['message']['content'].strip()
    except openai.error.RateLimitError:
        return "Rate limit exceeded. Try again later."
    except openai.error.AuthenticationError:
        return "Invalid API key. Check your .env file."
    except Exception as e:
        return f"An error occurred: {str(e)}"

GPT-3.5 vs GPT-4: Key Differences

The Source Code is open

Reach the perfect Chatbot project here: The convenient chatbot Opelai in GitTub.

With a visual guide through process, check out the YouTube Walkthrough video.