app.py

# imports
import os
from dotenv import load_dotenv
from openai import OpenAI
import gradio as gr
from transformers import pipeline

# Load environment variables in a file called .env
# Print the key prefixes to help with any debugging

# load_dotenv(override=True)
# openai_api_key = os.getenv('OPENAI_API_KEY')

api_key = os.getenv("OPENAI_API_KEY")
client = OpenAI(api_key=api_key)

if api_key:
    print(f"OpenAI API Key exists and begins {api_key[:8]}")
else:
    print("OpenAI API Key not set")

# Initialize

openai = OpenAI()
MODEL = 'gpt-4.1-mini'


# System message

system_message = "You are a helpful assistant in a insurance company called 'Generali'. You should try to explain different types of insurance to a customer and help them decide what to buy. \
There are different types of insurance, for example: 'Rechtschutzversicherung', 'Reiseversicherung', 'Berufsunfähigkeitsversicherung', 'Risikolebensversicherung', 'Private Rentenversicherung', 'Krankenzusatzversicherung', 'Unfallversicherung', 'Private Krankenversicherung', 'Kfz-Versicherung', 'Privathaftpflichtversicherung', 'Hausratversicherung', 'Wohngebäudeversicherung' \
You should explain the customer what the different types of insurance are and what they are for. \
You should also explain the customer what the benefits of the different types of insurance are. \
You should also explain the customer what the costs of the different types of insurance are. \
For example, if the customer says in German 'Ich würde gerne eine Versicherung abschließen.' \
you could reply something in German language like, 'Perfekt - wir haben verschiedene Versicherungsarten für Sie.'\
Ask customer about their needs in regard to their situation if they are unsure what type of insurance to get.\
If the customer asks in German, then answer in German. If the customer asks in Czech, then answer in Czech."

# Define chat function
def chat(message, history):
    history = [{"role":h["role"], "content":h["content"]} for h in history]
    messages = [{"role": "system", "content": system_message}] + history + [{"role": "user", "content": message}]
    stream = openai.chat.completions.create(model=MODEL, messages=messages, stream=True)
    response = ""
    for chunk in stream:
        response += chunk.choices[0].delta.content or ''
        yield response

# Define audio function
# Load the text-to-speech pipeline for German
pipe = pipeline("text-to-speech", model="Xenova/mms-tts-deu")

# Generate speech from text
output_audio = pipe(response)

# Define custom red and white/pink theme
custom_theme = gr.Theme.from_hub("Bruhn/CrimsonNight")
#gr.themes.Default(
#    primary_hue=gr.themes.colors.red,
#    secondary_hue=gr.themes.colors.pink,
#    neutral_hue=gr.themes.colors.gray,


gr.ChatInterface(fn=chat).launch(share=True,theme=custom_theme)
gr.Audio(fn=output_audio,type="bytes").launch(share=True,label="Generierte Sprachausgabe")