AI agent using an LLM (openai) model - Python agent

A customer wants to check the status of their food delivery order.

### pip install openai
import openai
class AI_Agent:
def __init__(self, model):
self.model = model

def collect_input(self, user_input):
print(f"Customer: {user_input}")
return user_input

def send_query_to_model(self, user_input):
query = f"The customer wants to know: {user_input}"
response = self.model.process_query(query)
return response

def execute_action(self, model_response):
print(f"AI Response: {model_response}")

class OpenAI_Model:
def __init__(self, api_key):
openai.api_key = api_key

def process_query(self, query):
try:

# Using OpenAI's GPT model to process the query
response = openai.ChatCompletion.create(
model="gpt-3.5-turbo", # Use the specific model you want
messages=[{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": query}]
)
return response['choices'][0]['message']['content']
except Exception as e:
return f"Error: {e}"

# Replace 'your_openai_api_key' with your actual OpenAI API key
api_key = "your_openai_api_key"
openai_model = OpenAI_Model(api_key)
ai_agent = AI_Agent(openai_model)

# Simulate customer interaction
user_input = "Where's my order?"
input_collected = ai_agent.collect_input(user_input)
response = ai_agent.send_query_to_model(input_collected)
ai_agent.execute_action(response)

Explanation:
OpenAI's GPT Model: The OpenAI_Model class now interacts with OpenAI's API to process queries.

Agent Query: The agent formulates the user's query and sends it to the GPT model via OpenAI's API.

API Key: Replace "your_openai_api_key" with your actual API key to run the code.