Update app.py

app.py

@@ -1,57 +1,15 @@
-from smolagents import CodeAgent, HfApiModel, load_tool, tool
-import datetime
-import pytz
+import requests
+import numpy as np
 import yaml
-import random
+from smolagents import CodeAgent, HfApiModel, load_tool, tool
+from textblob import TextBlob
 from tools.final_answer import FinalAnswerTool
 from Gradio_UI import GradioUI
-import os
-
-
-@tool
-def time_traveling_fortune_teller(timezone: str) -> str:
-    """A fun tool that tells the current time in a given timezone and provides a random fortune.
-    Args:
-        timezone: A string representing a valid timezone (e.g., 'America/New_York').
-    """
-    try:
-        tz = pytz.timezone(timezone)
-        current_time = datetime.datetime.now(tz).strftime('%Y-%m-%d %H:%M:%S')
-        current_hour = datetime.datetime.now(tz).hour
-        
-        # Fun fortunes based on time of day
-        morning_fortunes = [
-            "☀️ Rise and shine! Today is a blank canvas, so go paint your masterpiece!",
-            "🌅 A surprise awaits you this morning… maybe it's coffee, maybe it's chaos. Who knows?",
-            "🍩 Today might be sweet! Maybe a donut is in your future? (Or at least a snack!)"
-        ]
-        
-        afternoon_fortunes = [
-            "🌞 Power through! Your afternoon holds the promise of success (or at least a good nap).",
-            "🍕 Lunchtime decisions determine your fate—choose wisely!",
-            "🚀 Something unexpected will happen soon. Could be good, could be hilarious!"
-        ]
-        
-        evening_fortunes = [
-            "🌙 The stars say… it's time to relax! Or binge-watch your favorite show.",
-            "🔥 A late-night snack might be calling your name. The universe approves.",
-            "🌌 Your dreams tonight will hold a secret message. If you remember them!"
-        ]
-        
-        # Choose fortune based on time of day
-        if 5 <= current_hour < 12:
-            fortune = random.choice(morning_fortunes)
-        elif 12 <= current_hour < 18:
-            fortune = random.choice(afternoon_fortunes)
-        else:
-            fortune = random.choice(evening_fortunes)
-        
-        return f"⏳ The local time in {timezone} is {current_time}.\n🔮 Your fortune: {fortune}"
-    
-    except Exception as e:
-        return f"⚠️ Oops! The time-traveling fortune teller got lost in another dimension. Error: {str(e)}"
 
+# ✅ Final Answer Tool
 final_answer = FinalAnswerTool()
+
+# ✅ AI Model
 model = HfApiModel(
     max_tokens=2096,
     temperature=0.5,
@@ -59,18 +17,166 @@ model = HfApiModel(
     custom_role_conversions=None,
 )
 
-# Import tool from Hub
+# ✅ Import Tool from Hub
 image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
 
+# ✅ Load Prompt Templates
 with open("prompts.yaml", 'r') as stream:
     prompt_templates = yaml.safe_load(stream)
 
+
+### 🔹 1. Fetch Latest BTC News ###
+@tool
+def fetch_btc_news():
+    """
+    Fetches the latest Bitcoin news from CryptoPanic API.
+    """
+    url = "https://cryptopanic.com/api/v1/posts/?auth_token=ccbeafb47d266a78086f76c3f547546f6b747e88&currencies=BTC"
+    
+    try:
+        response = requests.get(url)
+        response.raise_for_status()
+        data = response.json()
+        
+        articles = [{"title": post["title"], "url": post["url"]} for post in data["results"][:5]]
+        return articles
+    
+    except requests.exceptions.RequestException as e:
+        return {"error": str(e)}
+
+
+### 🔹 2. Analyze News Sentiment ###
+@tool
+def analyze_btc_news(articles):
+    """
+    Analyzes sentiment of Bitcoin news articles using TextBlob.
+    """
+    sentiments = []
+    keywords = []
+
+    for article in articles:
+        analysis = TextBlob(article["title"])
+        sentiments.append(analysis.sentiment.polarity)
+        keywords.extend(article["title"].split()[:5])  
+
+    avg_sentiment = np.mean(sentiments) if sentiments else 0
+    sentiment_label = "Positive 😊" if avg_sentiment > 0 else "Negative 😡" if avg_sentiment < 0 else "Neutral 😐"
+
+    return {"sentiment_score": avg_sentiment, "sentiment_label": sentiment_label, "keywords": list(set(keywords))}
+
+
+### 🔹 3. Get BTC Market Insights (5m, 1H, 1D, 7D, 1M, 1Y) ###
+@tool
+def btc_market_insights():
+    """
+    Fetch BTC price, historical trends, moving averages, and Fear & Greed Index.
+    """
+    try:
+        # ✅ Fetch BTC price & 24h change
+        price_url = "https://api.coingecko.com/api/v3/simple/price"
+        price_params = {"ids": "bitcoin", "vs_currencies": "usd", "include_24hr_change": "true"}
+        price_data = requests.get(price_url, params=price_params).json()
+        btc_price = price_data["bitcoin"]["usd"]
+        btc_change = price_data["bitcoin"]["usd_24h_change"]
+
+        # ✅ Fetch historical price data (1 year)
+        hist_url = "https://api.coingecko.com/api/v3/coins/bitcoin/market_chart"
+        hist_params = {"vs_currency": "usd", "days": "365", "interval": "minute"}
+        hist_data = requests.get(hist_url, params=hist_params).json()
+        prices = [entry[1] for entry in hist_data["prices"]]
+
+        # ✅ Compute moving averages
+        ma_5m = np.mean(prices[-1:])    # 5-minute
+        ma_1h = np.mean(prices[-12:])   # 1-hour
+        ma_1d = np.mean(prices[-24:])   # 1-day
+        ma_7d = np.mean(prices[-168:])  # 7-day
+        ma_1m = np.mean(prices[-720:])  # 1-month
+        ma_1y = np.mean(prices[-8760:]) # 1-year
+
+        # ✅ Fetch Fear & Greed Index
+        fgi_url = "https://api.alternative.me/fng/"
+        fgi_data = requests.get(fgi_url).json()
+        fear_greed = fgi_data["data"][0]["value"]
+        fgi_text = fgi_data["data"][0]["value_classification"]
+
+        return {
+            "price": btc_price,
+            "24h_change": btc_change,
+            "ma_5m": ma_5m,
+            "ma_1h": ma_1h,
+            "ma_1d": ma_1d,
+            "ma_7d": ma_7d,
+            "ma_1m": ma_1m,
+            "ma_1y": ma_1y,
+            "fear_greed": fear_greed,
+            "fgi_text": fgi_text
+        }
+
+    except requests.exceptions.RequestException as e:
+        return {"error": str(e)}
+
+
+### 🔹 4. Make Buy/Sell/HODL Decision ###
+@tool
+def btc_decision(news_analysis, market_insights):
+    """
+    Aggregates news sentiment & market insights to suggest Buy, Sell, or HODL.
+    Evaluates ultra short-term (5m-1H), short-term (1D), weekly (7D), monthly (1M), and yearly (1Y) trends.
+    """
+    sentiment_score = news_analysis["sentiment_score"]
+    fgi = int(market_insights["fear_greed"])
+    btc_price = market_insights["price"]
+
+    # ✅ Moving Averages
+    ma_5m = market_insights["ma_5m"]
+    ma_1h = market_insights["ma_1h"]
+    ma_1d = market_insights["ma_1d"]
+    ma_7d = market_insights["ma_7d"]
+    ma_1m = market_insights["ma_1m"]
+    ma_1y = market_insights["ma_1y"]
+
+    decision = {
+        "5m-1H": "HODL 🤔", 
+        "1D": "HODL 🤔", 
+        "7D": "HODL 🤔", 
+        "1M": "HODL 🤔", 
+        "1Y": "HODL 🤔"
+    }
+
+    # ✅ Ultra Short-Term Decision (5m - 1H)
+    if btc_price > ma_5m and btc_price > ma_1h and fgi < 40 and sentiment_score > 0:
+        decision["5m-1H"] = "BUY 🚀 (Short pump)"
+    elif btc_price < ma_5m and btc_price < ma_1h and fgi > 60 and sentiment_score < 0:
+        decision["5m-1H"] = "SELL 📉 (Short dump)"
+
+    # ✅ Short-Term Decision (1 Day)
+    if btc_price > ma_1d and fgi < 40 and sentiment_score > 0:
+        decision["1D"] = "BUY 📈 (Daily uptrend)"
+    elif btc_price < ma_1d and fgi > 60 and sentiment_score < 0:
+        decision["1D"] = "SELL 📉 (Daily downtrend)"
+
+    # ✅ Weekly, Monthly, Yearly decisions...
+    if btc_price > ma_7d and fgi < 40 and sentiment_score > 0:
+        decision["7D"] = "BUY 📈 (Weekly bullish)"
+    elif btc_price < ma_7d and fgi > 60 and sentiment_score < 0:
+        decision["7D"] = "SELL 📉 (Weekly bearish)"
+
+    if btc_price > ma_1m and fgi < 40 and sentiment_score > 0:
+        decision["1M"] = "BUY 📈 (Mid-term bullish)"
+    elif btc_price < ma_1m and fgi > 60 and sentiment_score < 0:
+        decision["1M"] = "SELL 📉 (Mid-term bearish)"
+
+    return decision
+
+
+# ✅ Agent Setup
 agent = CodeAgent(
     model=model,
-    tools=[final_answer, time_traveling_fortune_teller],  
+    tools=[final_answer, fetch_btc_news, analyze_btc_news, btc_market_insights, btc_decision],  
     max_steps=6,
     verbosity_level=1,
     prompt_templates=prompt_templates
 )
 
+# ✅ Launch UI
 GradioUI(agent).launch()