ArcheanVision/Crypto_Agent_Signals_predict
10
1import os2from dotenv import load_dotenv3import streamlit as st4import pandas as pd5import plotly.express as px6import cloudscraper7import warnings8import logging9# Charger les variables d'environnement (si vous utilisez un .env localement)10load_dotenv()11API_KEY = os.environ.get("API_KEY")12headers = {13 "Authorization": f"Bearer {API_KEY}",14 "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) " 15 "AppleWebKit/537.36 (KHTML, like Gecko) " 16 "Chrome/115.0.0.0 Safari/537.36"17}18 19url = "https://archeanvision.com/api/signals/available"20 21# Create a cloudscraper instance22scraper = cloudscraper.create_scraper() # This will handle Cloudflare challenges23response = scraper.get(url, headers=headers)24 25print(response.status_code)26print(response.text)27 28# Load environment variables from .env29load_dotenv()30 31# Suppress deprecation warnings about experimental query params functions32warnings.filterwarnings(33 "ignore", 34 message="Please replace `st.experimental_get_query_params` with `st.query_params`"35)36warnings.filterwarnings(37 "ignore", 38 message="Please replace `st.experimental_set_query_params` with `st.query_params`"39)40warnings.filterwarnings("ignore", category=DeprecationWarning)41 42# Adjust Streamlit loggers to show only errors43logging.getLogger("streamlit.deprecation").setLevel(logging.ERROR)44logging.getLogger("streamlit.runtime.scriptrunner").setLevel(logging.ERROR)45 46 47# ---------------------------- #48# AUTO-REFRESH #49# ---------------------------- #50st.set_page_config(51 page_title="Dashboard Auto-Refresh",52 layout="wide"53)54 55REFRESH_INTERVAL = 260 # seconds56st.markdown(f"<meta http-equiv='refresh' content='{REFRESH_INTERVAL}'>", unsafe_allow_html=True)57# ---------------------------- #58 59LOGO_IMAGE_URL = "https://archeanvision.com/assets/archeanvision.png"60st.sidebar.image(LOGO_IMAGE_URL, use_container_width=True, caption="ArcheanVision")61 62# Get the API key from environment variables (stored in .env or Hugging Face Secrets)63if not API_KEY:64 st.error("API_KEY is not set. Please add it to your environment (e.g. .env file or Hugging Face Secrets).")65 st.stop()66 67# --- Helper Functions Using cloudscraper ---68 69def get_active_markets_cloudscraper(api_key):70 """Retrieves the list of active markets using cloudscraper to bypass Cloudflare."""71 headers = {72 "Authorization": f"Bearer {api_key}",73 "User-Agent": ("Mozilla/5.0 (Windows NT 10.0; Win64; x64) "74 "AppleWebKit/537.36 (KHTML, like Gecko) "75 "Chrome/115.0.0.0 Safari/537.36")76 }77 url = "https://archeanvision.com/api/signals/available"78 scraper = cloudscraper.create_scraper()79 response = scraper.get(url, headers=headers)80 response.raise_for_status() # Raises an exception for HTTP errors81 return response.json() # Assuming the endpoint returns JSON82 83def get_market_data_cloudscraper(api_key, market):84 """Retrieves market data for the given market using cloudscraper."""85 headers = {86 "Authorization": f"Bearer {api_key}",87 "User-Agent": ("Mozilla/5.0 (Windows NT 10.0; Win64; x64) "88 "AppleWebKit/537.36 (KHTML, like Gecko) "89 "Chrome/115.0.0.0 Safari/537.36")90 }91 # Endpoint for market data (1,440 points ~ 24h); adjust as per API docs92 url = f"https://archeanvision.com/api/signals/{market}/data"93 scraper = cloudscraper.create_scraper()94 response = scraper.get(url, headers=headers)95 response.raise_for_status()96 return response.json()97 98def get_market_signals_cloudscraper(api_key, market):99 """Retrieves market signals for the given market using cloudscraper."""100 headers = {101 "Authorization": f"Bearer {api_key}",102 "User-Agent": ("Mozilla/5.0 (Windows NT 10.0; Win64; x64) "103 "AppleWebKit/537.36 (KHTML, like Gecko) "104 "Chrome/115.0.0.0 Safari/537.36")105 }106 url = f"https://archeanvision.com/api/signals/{market}/signals"107 scraper = cloudscraper.create_scraper()108 response = scraper.get(url, headers=headers)109 response.raise_for_status()110 return response.json()111 112# --- End Helper Functions ---113 114def get_selected_market(market_list):115 """116 Retourne le marché sélectionné à partir des paramètres d'URL ou, par défaut, le premier élément.117 Met à jour le paramètre de l'URL si l'utilisateur choisit un marché différent.118 """119 # Récupère les paramètres sous forme de dictionnaire-like120 params = st.query_params121 122 # Récupérer le paramètre "market" ou définir la valeur par défaut123 default_market = params.get("market", market_list[0])124 # Si "market" est une liste (clé répétée), on prend le dernier (ou le premier) élément125 if isinstance(default_market, list):126 default_market = default_market[0]127 128 # Trouver l'index correspondant129 default_index = market_list.index(default_market) if default_market in market_list else 0130 131 # Affiche un menu déroulant pour choisir le marché132 selected = st.selectbox("Select a market:", market_list, index=default_index)133 134 # Si l'utilisateur choisit un marché différent, on met à jour le paramètre dans l'URL135 if selected != default_market:136 st.query_params.market = selected # Mise à jour via la notation par attribut137 # Vous pouvez également faire : st.query_params["market"] = selected138 139 return selected140 141 142def main():143 st.title("Active AI Crypto Markets - ArcheanVision")144 145 st.markdown("""146 ### What is ArcheanVision?147 **ArcheanVision** is an autonomous multi-market trading agent. 148 It operates simultaneously on multiple crypto assets, monitoring price movements149 in real time and delivering **data** as well as **signals** (BUY, SELL, etc.)150 to automate and optimize decision-making.151 - **AI Agent**: Continuously analyzes crypto markets. 152 - **Multi-Market**: Manages multiple assets at once. 153 - **Live Data**: Access to streaming data feeds (SSE). 154 - **Buy/Sell Signals**: Generated in real-time to seize market opportunities. 155 Below is a dashboard showcasing the active markets, their 24h data 156 (1,440 most recent data points), and their associated signals.157 ---158 **Join our Discord as a beta tester** to help improve the agent and the system. 159 - Official platform: [https://archeanvision.com](https://archeanvision.com) 160 - Discord link: [https://discord.gg/k9xHuM7Jr8](https://discord.gg/k9xHuM7Jr8)161 """)162 163 # Retrieve active markets using cloudscraper164 try:165 active_markets = get_active_markets_cloudscraper(API_KEY)166 except Exception as e:167 st.error(f"Error fetching active markets: {e}")168 return169 170 if not active_markets:171 st.error("No active markets found through the API.")172 return173 174 # Expecting active_markets to be a list of market names, e.g. ["BTC", "ETH", ...]175 market_list = []176 if isinstance(active_markets, list):177 for item in active_markets:178 # Depending on the response structure, adjust accordingly.179 if isinstance(item, dict) and "market" in item:180 market_list.append(item["market"])181 elif isinstance(item, str):182 market_list.append(item)183 else:184 st.warning(f"Item missing 'market' key: {item}")185 else:186 st.error("The structure of 'active_markets' is not a list as expected.")187 return188 189 if not market_list:190 st.error("The market list is empty or 'market' keys not found.")191 return192 193 selected_market = get_selected_market(market_list)194 if not selected_market:195 st.error("No market selected.")196 return197 198 st.subheader(f"Selected Market: {selected_market}")199 st.write(f"Fetching data for **{selected_market}** ...")200 201 # Retrieve market data using cloudscraper202 try:203 market_data = get_market_data_cloudscraper(API_KEY, selected_market)204 except Exception as e:205 st.error(f"Error fetching market data for {selected_market}: {e}")206 return207 208 if not market_data:209 st.error(f"No data found for market {selected_market}.")210 return211 212 df = pd.DataFrame(market_data)213 if "close_time" in df.columns:214 df['close_time'] = pd.to_datetime(df['close_time'], unit='ms', errors='coerce')215 else:216 st.error("The 'close_time' column is missing from the retrieved data.")217 return218 219 st.write("### Market Data Overview")220 st.dataframe(df.head())221 222 required_cols = {"close", "last_predict_15m", "last_predict_1h"}223 if not required_cols.issubset(df.columns):224 st.error(225 f"The required columns {required_cols} are not all present. "226 f"Available columns: {list(df.columns)}"227 )228 return229 230 fig = px.line(231 df,232 x='close_time',233 y=['close', 'last_predict_15m', 'last_predict_1h'],234 title=f"{selected_market} : Close Price & Predictions",235 labels={236 'close_time': 'Time',237 'value': 'Price',238 'variable': 'Metric'239 }240 )241 st.plotly_chart(fig, use_container_width=True)242 243 st.write(f"### Signals for {selected_market}")244 try:245 signals = get_market_signals_cloudscraper(API_KEY, selected_market)246 except Exception as e:247 st.error(f"Error fetching signals for {selected_market}: {e}")248 return249 250 if not signals:251 st.warning(f"No signals found for market {selected_market}.")252 else:253 df_signals = pd.DataFrame(signals)254 if 'date' in df_signals.columns:255 df_signals['date'] = pd.to_datetime(df_signals['date'], unit='s', errors='coerce')256 for col in df_signals.columns:257 if df_signals[col].apply(lambda x: isinstance(x, dict)).any():258 df_signals[col] = df_signals[col].apply(lambda x: str(x) if isinstance(x, dict) else x)259 if 'date' in df_signals.columns:260 df_signals = df_signals.sort_values('date', ascending=False)261 st.write("Total number of signals:", len(df_signals))262 st.write("Preview of the last 4 signals:")263 st.dataframe(df_signals.head(4))264 265if __name__ == "__main__":266 main()267 268