import os
import gradio as gr
import gradio

from llama_index import GPTSimpleVectorIndex, SimpleDirectoryReader, ServiceContext,LLMPredictor
from langchain.chat_models import ChatOpenAI
from llama_index.llm_predictor.chatgpt import ChatGPTLLMPredictor
import huggingface_hub
from huggingface_hub import Repository
from datetime import datetime
import csv

DATASET_REPO_URL = "https://huggingface.co/datasets/diazcalvi/kionlinde"#"https://huggingface.co/datasets/julien-c/persistent-space-dataset"
DATA_FILENAME = "kion.json"
DATA_FILE = os.path.join("data", DATA_FILENAME)

HF_TOKEN = os.environ.get("HF_TOKEN")
print("is none?", HF_TOKEN is None)

print("hfh", huggingface_hub.__version__)



#os.system("git config --global user.name \"Carlos Diaz\"")
#os.system("git config --global user.email \"diazcalvi@gmail.com\"")


##repo = Repository(
#    local_dir="data", clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN
#)


index_name = "./data/kion.json"
documents_folder = "./documents"
#@st.experimental_memo
#@st.cache_resource
def initialize_index(index_name, documents_folder):
    #llm_predictor = ChatGPTLLMPredictor()
    llm_predictor = LLMPredictor(llm=ChatOpenAI(temperature=0, model_name="gpt-3.5-turbo")) #	text-davinci-003"))"gpt-3.5-turbo"
    
    service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor)
    if os.path.exists(index_name):
        index = GPTSimpleVectorIndex.load_from_disk(index_name)
    else:
        documents = SimpleDirectoryReader(documents_folder).load_data()
        index = GPTSimpleVectorIndex.from_documents(documents)
        index.save_to_disk(index_name)
        print(DATA_FILE)
        index.save_to_disk(DATA_FILE)

    return index

#@st.experimental_memo
#@st.cache_data(max_entries=200, persist=True)
def query_index(_index, query_text):
    response = _index.query(query_text)
    return str(response)

def generate_html() -> str:
    with open(DATA_FILE) as csvfile:
        reader = csv.DictReader(csvfile)
        rows = []
        for row in reader:
            rows.append(row)
        rows.reverse()
        if len(rows) == 0:
            return "no messages yet"
        else:
            html = "<div class='chatbot'>"
            for row in rows:
                html += "<div>"
                html += f"<span>{row['name']}</span>"
                html += f"<span class='message'>{row['message']}</span>"
                html += "</div>"
            html += "</div>"
            return html


def store_message(name: str, message: str):
    if name and message:
        print(DATA_FILE)
        print(DATA_FILENAME)
        print(DATASET_REPO_URL)
        with open(DATA_FILE, "a") as csvfile:
            writer = csv.DictWriter(csvfile, fieldnames=["name", "message", "time"])
            writer.writerow(
                {"name": name, "message": message, "time": str(datetime.now())}
            )
        commit_url = repo.push_to_hub()
        print(commit_url)

    return commit_url #generate_html()



def greet(text):
    response = query_index(index, "Act as a KION equipment expert and answer this with detail:" + text + ". (Include the context reference details, file name, page number, and date if available)")
    return response




index = None
api_key = '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'#st.text_input("Enter your OpenAI API key here:", type="password")
if api_key:
    os.environ['OPENAI_API_KEY'] = api_key
    index = initialize_index(index_name, documents_folder)    


if index is None:
    st.warning("Please enter your api key first.")



gradio_interface = gradio.Interface(
  fn=greet,
  inputs="text",
  outputs="text",
  examples=[
    ["What can I ask you? Give me 20 different examples."],
    ["What are some of the LPG Lift trucks, and what series and models? Make a list."],
    ["What dealers do we have in Michigan and how can I contact them?"],
    ["What can you tell me about Eike Wibrow? Expand on background"],
    ["What do you know about Bravo Montacargas and how to contact them? When were they added to the Dealer Network?"],
    ["Give me some details on the P60"],
    ["What is the Youth Apprentice Signing Day?"],
    ["Do we have a dealer in NC? List them"],
    ["Tell  me more about Tri-Lift NC"],
    ["What are some the optional equipment for the E18, E20? Series 346?"],
    ["Who are our contact/leads on HTX?"],
    ["KBG40 and KBG50. What is the overall length?"],
    ["What are the mission, vision and values of KION NA? List them"],
    ["When was the new linde MT18 added to the product line?"],
    ["Who is Jonathan Dawley?"]
  ],
  title="KION - Linde & Baoli AI",
  description="Enter a query about any KION/Linde & Baoli products, parts, news. The AI knows all the details, loads, sizes, manuals and procedures to support hundreds of parts and equipment. Also is aware of all the recent news. You can check out also our repository [here](https://www.kion-na.com/products/)",
  article="© Carlos Diaz Calvi 2023"
)
gradio_interface.launch()