application file

app.py

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+from utils import chatbot
+import gradio as gr
+import logging
+import traceback
+
+try:
+    gr.ChatInterface(fn=chatbot,
+                     chatbot=gr.Chatbot(height=600),
+                     textbox=gr.Textbox(placeholder="Ask me a question related to jewellery.", container=False, scale=7),
+                     title="Jewelli Chatbot",
+    ).launch()
+
+except Exception as e:
+    logging.error(f"Error occurred: {e}\n{traceback.format_exc()}") 

available_slots.json

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+{
+    "monday": "9am - 5pm",
+    "tuesday": "9am - 5pm",
+    "wednesday": "9am - 5pm",
+    "thursday": "9am - 5pm",
+    "friday": "9am - 5pm",
+    "saturday": "9am - 5pm",
+    "sunday": "9am - 5pm"
+}

requirements.txt

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+gradio==3.46.1
+python-dotenv==1.0.0
+openai==0.28.1

utils.py

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+import openai
+import os
+from dotenv import load_dotenv
+from datetime import datetime
+import logging
+import traceback
+import json
+
+with open('available_slots.json', 'r') as file:
+    available_slots = str(json.load(file))
+
+now = datetime.now()
+date_strng = now.strftime("%d-%m-%Y_%H-%M-%S")
+
+if not os.path.exists('logs'):
+    os.makedirs('logs')
+
+    
+logging.basicConfig(filename='logs/{}.log'.format(date_strng), level=logging.INFO, format='%(asctime)s %(levelname)s %(name)s %(threadName)s : %(message)s')
+logging.info('Starting the application')
+
+load_dotenv()
+
+openai.api_key = os.getenv("OPENAI_API_KEY")
+
+context = f"""\
+You will act as a booking agent, who will book appointments for customers for home repair. \
+The customer needs to provide a day and time slot for the appointment. If the conversation \
+strays from booking system, tactfully steer it back. Keep your responses succinct and engaging. \
+When you determine the customer's preferences. The time slots available from the company are \
+provided under the "Available Slots" section. The customer can choose from these slots. \
+
+Available Slots:
+{available_slots}
+
+When you think the customer has provided a day and time slot, you can end the conversation by \
+returning your final response in the JSON format below.
+
+JSON Format:
+{{
+    "day": "customer's preferred day goes here",
+    "time": "customer's preferred time goes here
+}}
+"""
+messages = []
+messages.append({"role": "system", "content": context})
+
+def json_format(response):
+    dict_start = response.find('{')
+    dict_end = response.rfind('}') + 1 
+    json_string = response[dict_start:dict_end]
+    products_dict = json.loads(json_string)
+    return products_dict["productCategory"]
+
+def chatbot(user_message, history):
+    messages.append({"role": "user", "content": user_message})
+    logging.info("Getting response from gpt-3.5-turbo")
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo-16k",
+        messages=messages,
+        temperature=0,
+    )
+    messages.append({"role": "assistant", "content": response.choices[0].message.content})
+    
+    # try:
+    #     product_category = json_format(response.choices[0].message.content)
+    #     # image_url = get_product_details(product_category)
+    #     # if image_url:
+    #     #     return (image_url, product_category)
+    # except:
+    #     pass
+
+    logging.info("Messages list: {}".format(messages))
+    return response.choices[0].message.content