from fastapi import FastAPI, Request, HTTPException
from fastapi.responses import PlainTextResponse
from fastapi.middleware.cors import CORSMiddleware
from twilio.twiml.messaging_response import MessagingResponse
import os,openai
import google.generativeai as genai
from llama_index.llms import OpenAI
from llama_index import VectorStoreIndex, SimpleDirectoryReader
from llama_index.llms import OpenAI
from llama_index import StorageContext, load_index_from_storage

secret = os.environ["key"]

genai.configure(api_key=secret)
model = genai.GenerativeModel('gemini-1.5-flash')

import user_guide_sync

global index,query_engine
query_engine = index = None
#query_engine = (user_guide_sync.update_user_guide).as_query_engine()

app = FastAPI()

app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

@app.post("/update_user_guide_data")
async def update_user_guide_data():
    user_guide_sync.update_user_guide()
    return "guide updated"

@app.post("/whatsapp")
async def reply_whatsapp(request: Request):
    
    form_data = await request.form()
    num_media = int(form_data.get("NumMedia", 0))
    from_number = form_data.get("From")
    message_body = form_data.get("Body")
    user_query = message_body

    response = MessagingResponse()
    #msg.media(GOOD_BOY_URL)
    try:
        global query_engine,index
        storage_context = StorageContext.from_defaults(persist_dir="llama_index")
        index = load_index_from_storage(storage_context=storage_context)
        
        # Set the GPT model (e.g., GPT-4, GPT-3.5 Turbo)
        llm = OpenAI(model="gpt-4o-mini", api_key=os.environ["OPENAI_API_KEY"])  # Use "gpt-4" if desired

        query_engine = index.as_query_engine(llm=llm)
        print("loaded")
        
        gpt_response = query_engine.query(f"""        
              if you find the very correct answer from provided data then only give the realistic(like real human) answer with steps and add the more details link and always add propper line breaks(\n).
              if not find the answer from provided data then honestly say 'please contact our helpdesk' 
              
              user question : {user_query}""")
        
        default = """Dear\n\nIf you have a specific question or need assistance, please feel free to submit a ticket, and our support team will be happy to help you \n\nSubmit a Ticket: \n\tEmail: support@storemate.lk\nThank You """
    
        print(str(gpt_response).lower())
        if "please contact our helpdesk" in str(gpt_response).lower() or "please contact" in str(gpt_response).lower():
                print("help desk option")
    
                openai.api_key = os.environ["OPENAI_API_KEY"]
                prompt = f"""
                         system:
                         you are parallax technologies chatbot design for answer the user question like a real human.
                         contact details Email : support@storemate.lk Youtube : https://www.youtube.com/channel/UCFkX9Fa-Qe6Qi4V5f0RcfSA Facebook : https://www.facebook.com/storemateinventory web link : https://storemate.lk
                         
                         only give single answer and don't give answer for general answers(this is CRM system for only pos system clients)
                         note : don't give nay steps for solve the issues
                         user:{user_query}
                         """
                messages = [
                    {"role": "system", "content": "you are parallax technologies chatbot design for answer the user question like a real human"},
                    {"role": "user", "content": prompt}
                ]

                gen_response = model.generate_content(prompt)
            
                gpt_response = openai.chat.completions.create(
                
                model="gpt-4o-mini",
                
                messages=messages,
                
                temperature=0,
                
                )
                
                response.message(str(gpt_response.choices[0].message.content))
                #response.message(gen_response.text)
                #response.message(gen_response.text +"\n\n"+default)
                return PlainTextResponse(str(response), media_type="application/xml")

        response.message(str(gpt_response)) 
        #response.message("https://storemate.lk")
        return PlainTextResponse(str(response), media_type="application/xml")   
    except Exception as e:
        print(str(e))
        response.message("please ask again...!")
        return PlainTextResponse(str(response), media_type="application/xml")  
    

# Run the application (Make sure you have the necessary setup to run FastAPI)