import streamlit as st
import requests
import pandas as pd
import matplotlib.pyplot as plt
from datetime import datetime
from dotenv import load_dotenv
import os

# Load API token from .env
load_dotenv()
BEARER_TOKEN = os.getenv("TWITTER_BEARER_TOKEN")

# Streamlit setup
st.set_page_config(page_title="ZKGM Tracker", layout="wide")
st.title("ZKGM Tweet Tracker")
username = st.text_input("Enter Twitter Username (without @):", "elonmusk")

# Headers for Twitter API
headers = {"Authorization": f"Bearer {BEARER_TOKEN}"}

# Get Twitter User ID from username
def get_user_id(username):
    url = f"https://api.twitter.com/2/users/by/username/{username}"
    response = requests.get(url, headers=headers)
    if response.status_code == 200:
        return response.json()["data"]["id"]
    else:
        st.warning(f"Failed to fetch user ID. Status: {response.status_code}")
        st.code(response.text)
    return None

# Search user's tweets for "zkgm" (case-insensitive)
def get_zkgm_mentions(user_id, max_results=500):
    tweets = []
    pagination_token = None
    url = f"https://api.twitter.com/2/users/{user_id}/tweets"

    while len(tweets) < max_results:
        params = {
            "max_results": 100,
            "tweet.fields": "created_at",
        }
        if pagination_token:
            params["pagination_token"] = pagination_token

        response = requests.get(url, headers=headers, params=params)
        if response.status_code != 200:
            st.error(f"Twitter API error: {response.status_code}")
            st.code(response.text)
            break

        data = response.json()
        for tweet in data.get("data", []):
            if "zkgm" in tweet["text"].lower():
                tweets.append(tweet)

        pagination_token = data.get("meta", {}).get("next_token")
        if not pagination_token:
            break

    return tweets

# Main app logic
if st.button("Count Mentions and Show Chart"):
    with st.spinner("Fetching tweets..."):
        user_id = get_user_id(username)
        if not user_id:
            st.error("User not found or invalid username.")
        else:
            zkgm_tweets = get_zkgm_mentions(user_id)
            count = len(zkgm_tweets)
            st.success(f"✅ @{username} has mentioned 'ZKGM' {count} time(s).")

            if count > 0:
                df = pd.DataFrame(zkgm_tweets)
                df["created_at"] = pd.to_datetime(df["created_at"])
                df["month"] = df["created_at"].dt.to_period("M")

                counts_by_month = df.groupby("month").size()

                # Bar chart
                st.subheader("📈 Monthly Mentions")
                fig, ax = plt.subplots()
                counts_by_month.plot(kind="bar", ax=ax, color="#4e79a7")
                ax.set_ylabel("Mentions")
                ax.set_xlabel("Month")
                st.pyplot(fig)