SYSTEM_PROMPT = ("You are an AI, named Solar Helper, an expert representative of Orange Cell Solar, who provides guidance on solar installations, highlighting the benefits of our recommended products such as Axitec and REC solar panels, and SMA, Enphase, Generac, Sol-Ark, Solax, and Tesla inverters."
                 "You are to politely decline to discuss any other topic, reminding them of your purpose. You are not to write code in any language, or answer unrelated question as you are a Solar-only chatbot. Anything related to solar power, or the installation process, or the products or the companies, is okay."
                 "Orange Cell Solar's approach focuses on determining the best system for a customer based on their energy needs, brand preferences, and budget. We are a small boutique company with extremely experienced installers and electricians who are fully licensed, and who know everything possible about solar and electrical, to make sure the system is safe, works well for years, and meets their specific needs. Anyone looking for a solar installer won't be able to beat the quality of the components, and the top-notch work, and the price of our systems."
                 "Encourage interested customers to contact us for a custom proposal based on their specific house and monthly utility usage. Our site survey with a drone and proprietary imagery ensures a seamless process after contract signing."
                 "Since you don't know their house or their consumption, and don't want to get into that, if customers are interested in learning more, this bot should encourage them to contact us at info@orangecellsolar.com or call us at 586-239-0010 so we can introduce ourselves, get their recent utility usage, look at their property and come up with a custom proposal. Our website is https://www.orangecellsolar.com/."
                 "Don't give out this contact info more than once, unless specifically asked for it.")

TITLE = "Solar Helper"
EXAMPLE_INPUT = "Why choose Orange Cell Solar?"
import gradio as gr
import os
import requests

zephyr_7b_beta = "https://api-inference.huggingface.co/models/HuggingFaceH4/zephyr-7b-beta/"

HF_TOKEN = os.getenv("HF_TOKEN")
HEADERS = {"Authorization": f"Bearer {HF_TOKEN}"}

def build_input_prompt(message, chatbot, system_prompt):
    """
    Constructs the input prompt string from the chatbot interactions and the current message.
    """
    input_prompt = "<|system|>\n" + system_prompt + "</s>\n<|user|>\n"
    for interaction in chatbot:
        input_prompt = input_prompt + str(interaction[0]) + "</s>\n<|assistant|>\n" + str(interaction[1]) + "\n</s>\n<|user|>\n"

    input_prompt = input_prompt + str(message) + "</s>\n<|assistant|>"
    return input_prompt


def post_request_beta(payload):
    """
    Sends a POST request to the predefined Zephyr-7b-Beta URL and returns the JSON response.
    """
    response = requests.post(zephyr_7b_beta, headers=HEADERS, json=payload)
    response.raise_for_status()  # Will raise an HTTPError if the HTTP request returned an unsuccessful status code
    return response.json()


def predict_beta(message, chatbot=[], system_prompt=""):
    input_prompt = build_input_prompt(message, chatbot, system_prompt)
    data = {
        "inputs": input_prompt
    }

    try:
        response_data = post_request_beta(data)
        json_obj = response_data[0]
        
        if 'generated_text' in json_obj and len(json_obj['generated_text']) > 0:
            bot_message = json_obj['generated_text']
            return bot_message
        elif 'error' in json_obj:
            raise gr.Error(json_obj['error'] + ' Please refresh and try again with smaller input prompt')
        else:
            warning_msg = f"Unexpected response: {json_obj}"
            raise gr.Error(warning_msg)
    except requests.HTTPError as e:
        error_msg = f"Request failed with status code {e.response.status_code}"
        raise gr.Error(error_msg)
    except json.JSONDecodeError as e:
        error_msg = f"Failed to decode response as JSON: {str(e)}"
        raise gr.Error(error_msg)

def test_preview_chatbot(message, history):
    response = predict_beta(message, history, SYSTEM_PROMPT)
    text_start = response.rfind("<|assistant|>", ) + len("<|assistant|>")
    response = response[text_start:]
    return response


welcome_preview_message = f"""
Welcome to **{TITLE}**! Say something like: 

"{EXAMPLE_INPUT}"
"""

chatbot_preview = gr.Chatbot(layout="panel", value=[(None, welcome_preview_message)])
textbox_preview = gr.Textbox(scale=7, container=False, value=EXAMPLE_INPUT)

demo = gr.ChatInterface(test_preview_chatbot, chatbot=chatbot_preview, textbox=textbox_preview)

demo.launch(share=True)