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Developer Gpt

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Turn ChatGPT into your personal full-stack developer with this prompt. πŸ‘Ά Beginner Friendly πŸ“ Provides Steps For Creating Project πŸ’¬ Provides Comments In The Code So You Understand How It Works πŸ“š Provides Explanations On How To Implement Code
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Updated: 1 year ago

Prompt Details

Chat - GPT-3.5 (gpt-3.5-turbo)
Token size
327 ($0.00070 / call)
Example input
I would like to create a chatbot for my website that uses the ChatGPT api to respond to my customers questions.
Example output
Great! To create a chatbot that uses the ChatGPT API, we'll need to use a programming language such as Python and a web framework like Flask or Django. Here are the high-level steps we'll need to follow: Download and install a code editor or IDE (Integrated Development Environment) like Visual Studio Code or PyCharm. Install Python on your computer. Create a new folder on your computer to hold your chatbot project. Open your code editor or IDE and create a new file called in the folder you just created. Install the Flask web framework by running pip install flask in your terminal or command prompt. Obtain the API key for the ChatGPT API and store it securely in a separate file. We'll use this key to authenticate our requests to the API. Create a Flask app instance in and define a route that will handle incoming requests to your chatbot. When a request comes in, extract the user's question from the request and use the ChatGPT API to generate a response. Send the response back to the user in the form of a JSON object. Here's the code: # Import necessary modules from flask import Flask, request, jsonify import openai_secret_manager import openai import os # Load OpenAI API key from environment variables secrets = openai_secret_manager.get_secret("openai") openai.api_key = secrets["api_key"] # Create Flask app instance app = Flask(__name__) # Define route for chatbot @app.route("/chatbot", methods=["POST"]) def chatbot(): # Extract user's message from request user_message = request.form["message"] # Use OpenAI's GPT-3 to generate a response to the user's message response = openai.Completion.create( engine="text-davinci-002", prompt=user_message, max_tokens=60, n=1, stop=None, temperature=0.5, ) # Extract the response text from the API's JSON response chatbot_response = response.choices[0].text.strip() # Create a JSON response object with the chatbot's response response_data = {"message": chatbot_response} # Send the response back to the user return jsonify(response_data) # Run the Flask app if __name__ == "__main__": This code sets up a simple Flask app with a single route at /chatbot. When a POST request is made to this route, the chatbot uses the ChatGPT API to generate a response to the user's message and sends it back in the form of a JSON object. Remember to always keep your API key secure, and don't share it with anyone else. Good luck with your chatbot project!
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