File size: 2,338 Bytes
c380b8d
 
 
 
 
addfeb0
c380b8d
f708ede
c380b8d
f708ede
c380b8d
f708ede
 
 
 
c380b8d
 
 
f708ede
c380b8d
addfeb0
c380b8d
 
f708ede
 
c380b8d
f708ede
 
 
 
 
 
 
 
 
c380b8d
 
 
f708ede
 
 
c380b8d
f708ede
 
 
c380b8d
 
 
addfeb0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
from openai import OpenAI
import gradio as gr
import os

# Set your OpenAI API key
client = OpenAI(api_key="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")

greetings = ["hello", "hi", "hey", "greetings", "good morning", "good afternoon", "good evening"]

def chatbot(input, conversation_history=[]):
    if input:
        # Check if the input starts with a common greeting, case-insensitive
        if any(input.lower().startswith(greet) for greet in greetings):
            conversation_history = []  # Reset the conversation history if a greeting is detected
        
        # Append the user's input to the conversation history
        conversation_history.append(f"User: {input}")
        
        # Define the structured interview messages
        messages = [
    {"role": "system", "content": "Your role is to answer the questions from the users friendly. If they ask weird questions or input things you do not understand, just say: 'Sorry, this question is beyond my understanding. Please try another one!"},
]
        
        # Extend the conversation history with the user's messages
        messages.extend([{"role": "user", "content": message} for message in conversation_history])
        
        try:
            # Generate a response using OpenAI's GPT model
            chat = client.chat.completions.create(model="gpt-3.5-turbo", messages=messages)
            reply = chat.choices[0].message.content
        except Exception as e:
            # Handle errors gracefully
            reply = "Sorry, I encountered an error. Please try again."
            print(f"Error: {e}")  # Logging the error to the console

        # Append the chatbot's response to the conversation history
        conversation_history.append(f"Chatbot: {reply}")
        
        return reply, conversation_history  # Return the updated conversation history to maintain state

    return "", conversation_history  # If no input, return empty string and current conversation history

# Gradio interface
inputs = [gr.components.Textbox(lines=7, label="Chat with AI"), gr.components.State()]
outputs = [gr.components.Textbox(label="Reply"), gr.components.State()]

gr.Interface(fn=chatbot, inputs=inputs, outputs=outputs, title="AI Chatbot",
             description="Ask anything you want",
             theme="Default").launch(share=True)