app.py

from langchain_core.messages import BaseMessage, HumanMessage
from langchain_openai import ChatOpenAI
from typing import Annotated
import operator
from typing import Sequence, TypedDict
import numpy as np
import pandas as pd
from dotenv import load_dotenv
import os
from typing import Annotated
import operator
from typing import Sequence, TypedDict
import matplotlib.pyplot as plt
from langchain.schema.output_parser import StrOutputParser
import app_crypto_rf_model as rf
import app_crypto_scrape as sa
import app_crypto_arima_model as arima
import streamlit as st
import requests
from requests import Request, Session
from requests.exceptions import ConnectionError, Timeout, TooManyRedirects
import json

st.set_page_config(page_title="LangChain Agent", layout="wide")
load_dotenv()

COINGECKO_API_KEY=os.environ["COINGECKO_API_KEY"]
OPENAI_API_KEY = os.environ["OPENAI_API_KEY"]

llm = ChatOpenAI(model="gpt-3.5-turbo")

#======================== AGENTS ==================================
# The agent state is the input to each node in the graph
class AgentState(TypedDict):
    # The annotation tells the graph that new messages will always
    # be added to the current states
    messages: Annotated[Sequence[BaseMessage], operator.add]
    # The 'next' field indicates where to route to next
    next: str
             
tool=data_analyst.data_analyst_tools()

from langchain_core.runnables import RunnableConfig
st.title("💬 Krypto")

#@st.cache_data

#@st.cache_resource
#def initialize_session_state():
if "chat_history" not in st.session_state:
    st.session_state["messages"] = [{"role":"system", "content":"""
How can I help you?
"""}]

#initialize_session_state()

# Streamlit UI elements
st.image('crypto_image.png')
#st.text("Start by entering the currency.")

sideb = st.sidebar

with st.sidebar:
    #st.subheader("This is the LangGraph workflow visualization of this application rendered in real-time.")
    #st.image(create_graph_image())
    
    title = st.text_input("Start by entering the currency name:")

check1 = sideb.button(f"analyze {title}")
results=[]

if check1:
    st.write(f"I am now producing analysis for {title}")
    
    model = ChatOpenAI(temperature=0.7, api_key=OPENAI_API_KEY)
    chain= model | StrOutputParser()
    result=chain.invoke(f"You are a cryptocurrency data analyst.\
                Provide correct cryptocurrency ticker from Coingecko website for cryptocurrency: {title}.\
                Expected output: ticker.\
                Provide it in the following format: >>cryptocurrencyticker>> \
                for example: >>BTC>>")
    

    # for s in graph_data.stream(inputs):
    #         for key, value in s.items():
    #             print(f"Finished running: {value}:")
    #             result = value["messages"][-1].content
    #             results.append(value["messages"][-1].content)

    print(result)
    print('ticker',str(result).split(">>")[0])
    if len(str(result).split(">>")[1])<10:
        cryptocurrencyticker=(str(result).split(">>")[1])
    else:
        cryptocurrencyticker=(str(result).split(">>")[0])
    cryptocurrency=title

    print(cryptocurrency,cryptocurrencyticker)
    print('here')

    # # 1. Scrape historical Price and Volume  currency data
    # from datetime import date
    # today = date.today()
    # Day_end = today.strftime("%d")
    # Month_end = today.strftime("%m")
    # Year_end = today.strftime("%Y")

    # from datetime import date
    # from datetime import timedelta

    # past=today-timedelta(days=200)
    # Day_start = past.strftime("%d")
    # Month_start = past.strftime("%m")
    # Year_start = past.strftime("%Y")

    # date_start=[Year_start,Month_start,Day_start]
    # date_end=[Year_end,Month_end,Day_end]

    # import datetime
    # import time

    # #DATE definitions

    # date_time = datetime.datetime(int(date_start[0]),int(date_start[1]),int(date_start[2]))
    # date_time_now = datetime.datetime(int(date_end[0]),int(date_end[1]),int(date_end[2]))
    # unix_past=time.mktime(date_time.timetuple()) #change the date format into unix for scraping
    # unix_now=time.mktime(date_time_now.timetuple())
    # past=datetime.datetime(int(date_start[0]),int(date_start[1]),int(date_start[2])).strftime('%Y-%m-%d')
    # now=datetime.datetime(int(date_end[0]),int(date_end[1]),int(date_end[2])).strftime('%Y-%m-%d')
    # datum_range=pd.date_range(start=past,end=now, freq='D')
    
    # #empty lists
    # unix_all=[]
    # coins_names=[]

    # #create date variable
    # for val in datum_range:
    #     unix_all=np.append(unix_all,time.mktime(val.timetuple()))
    # #from utils import slice
    # # Get API for CoinGecko
    # #cg = CoinGeckoAPI()

    # url = f"https://api.coingecko.com/api/v3/coins/{cryptocurrency.lower()}/market_chart/range?vs_currency=usd&from={unix_past}&to={unix_now}"

    # headers = {
    #     "accept": "application/json",
    #     "x-cg-demo-api-key": COINGECKO_API_KEY
    # }
    # response = ''
    # while response == '':
    #     try:
    #         response = requests.get(url, headers=headers, proxies={"http": "http://111.233.225.166:1234"})
    #         break
    #     except:
    #         print("Connection refused by the server..")
    #         print("Let me sleep for 5 seconds")
    #         print("ZZzzzz...")
    #         time.sleep(5)
    #         print("Was a nice sleep, now let me continue...")
    #         continue
    
    # data=response.json()

     #This example uses Python 2.7 and the python-request library.



    url = 'https://sandbox-api.coinmarketcap.com/v1/cryptocurrency/listings/latest'
    parameters = {
    'start':'1',
    'limit':'5000',
    'convert':'USD'
    }
    headers = {
    'Accepts': 'application/json',
    'X-CMC_PRO_API_KEY': 'b54bcf4d-1bca-4e8e-9a24-22ff2c3d462c',
    }

    session = Session()
    session.headers.update(headers)

    try:
        response = session.get(url, params=parameters)
        data = json.loads(response.text)
        print(data)
    except (ConnectionError, Timeout, TooManyRedirects) as e:
        print(e)

    #data=cg.get_coin_market_chart_range_by_id(id=cryptocurrency.lower(),vs_currency='usd',include_market_cap='true', include_24hr_vol='true', from_timestamp=unix_past,to_timestamp=unix_now)
    #df_ts_coins=su.scrape_historical_series([currency],date_start,date_end)
    #================== Scrape Current/Historical Price ====================
    st.write(data)