Create app.py

app.py

@@ -0,0 +1,93 @@
+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import requests
+import json
+import os
+
+# --- API Key ---
+CMC_API_KEY = os.environ.get("CMC_API_KEY")  # Store your API key as a Hugging Face Secret
+
+if not CMC_API_KEY:
+    st.warning("Please add your CoinMarketCap API key as a Secret in Hugging Face Spaces.")
+else:
+    headers = {
+        'X-CMC_PRO_API_KEY': CMC_API_KEY,
+        'Accepts': 'application/json'
+    }
+
+    # --- Data Fetching ---
+    @st.cache_data(ttl=60)  # Cache data for 60 seconds
+    def get_crypto_price(symbol):
+        url = f'https://pro-api.coinmarketcap.com/v1/cryptocurrency/quotes/latest?symbol={symbol}'
+        try:
+            response = requests.get(url, headers=headers)
+            response.raise_for_status()
+            data = json.loads(response.text)
+            if data['status']['error_code'] == 0:
+                price = data['data'][symbol]['quote']['USD']['price']
+                return price
+            else:
+                return f"Error fetching data: {data['status']['error_message']}"
+        except requests.exceptions.RequestException as e:
+            return f"Error connecting to CoinMarketCap API: {e}"
+
+    # --- AI Model Integration ---
+    @st.cache_resource
+    def load_sentiment_model():
+        tokenizer = AutoTokenizer.from_pretrained("ElKulako/cryptobert")
+        model = AutoModelForSequenceClassification.from_pretrained("ElKulako/cryptobert")
+        return tokenizer, model
+
+    @st.cache_data
+    def analyze_sentiment(text, tokenizer, model):
+        try:
+            inputs = tokenizer(text, return_tensors="pt")
+            outputs = model(**inputs)
+            logits = outputs.logits
+            predicted_class_id = logits.argmax().item()
+            return model.config.id2label[predicted_class_id]
+        except Exception as e:
+            return f"Error analyzing sentiment: {e}"
+
+    tokenizer, sentiment_model = load_sentiment_model()
+
+    # --- Main Chatbot Logic ---
+    def process_user_message(user_input):
+        user_input_lower = user_input.lower()
+
+        if "current price of" in user_input_lower:
+            symbol = user_input_lower.split("current price of")[1].strip().upper()
+            price = get_crypto_price(symbol)
+            if isinstance(price, str) and "Error" in price:
+                return price
+            else:
+                sentiment_summary = analyze_sentiment(f"Recent news about {symbol}", tokenizer, sentiment_model)
+                return f"The current price of {symbol} is ${price:.2f}. Market sentiment is currently {sentiment_summary}."
+        elif "should i buy" in user_input_lower:
+            return "I am currently unable to provide buy/sell recommendations without technical analysis capabilities in this deployment."
+        elif "rsi say about" in user_input_lower:
+            return "I am currently unable to analyze RSI without the necessary libraries in this deployment."
+        else:
+            return "I'm still learning! I can currently tell you the price of a cryptocurrency and analyze the sentiment of related news."
+
+    # --- Streamlit UI ---
+    st.title("Crypto Trading Assistant")
+    st.markdown("Ask me about cryptocurrency prices and market sentiment.")
+
+    user_query = st.text_input("Your question:", "")
+
+    if CMC_API_KEY:
+        if user_query:
+            with st.spinner("Thinking..."):
+                bot_response = process_user_message(user_query)
+                st.write(f"**Bot:** {bot_response}")
+
+                # Simple price chart example if the user asked for the price
+                if "price of" in user_query.lower():
+                    symbol = user_query.lower().split("price of")[1].strip().upper()
+                    price_data = get_crypto_price(symbol)
+                    if not isinstance(price_data, str):
+                        st.subheader(f"Current Price of {symbol}: ${price_data:.2f}")
+                        st.line_chart([price_data]) # Simple single point chart
+    else:
+        st.error("CoinMarketCap API key is missing. Please add it as a Secret.")