Update app.py

app.py

@@ -106,7 +106,6 @@ def format_response(data):
 
     return formatted_response.strip()
 
-# Function to handle the interaction and queries
 def market_analysis_agent(user_input, history=[]):
     try:
         # Detect the language of the user's input
@@ -119,64 +118,41 @@ def market_analysis_agent(user_input, history=[]):
             history.append((user_input, command_response))
             return history, history
         
-        # Handle private market queries with datasets
-        if "company" in user_input.lower():
-            response = company_profile
-        elif "financials" in user_input.lower():
-            response = financials
-        elif "investors" in user_input.lower():
-            response = investors
-        elif "products" in user_input.lower():
-            response = products_services
-        elif "news" in user_input.lower() or "updates" in user_input.lower():
-            response = news_updates
-        elif "legal" in user_input.lower() or "compliance" in user_input.lower():
-            response = legal_compliance
-        elif "social media" in user_input.lower() or "instagram" in user_input.lower() or "linkedin" in user_input.lower() or "twitter" in user_input.lower():
-            response = social_media
-        elif "workforce" in user_input.lower():
-            response = workforce
+        # Check if the query is related to cryptocurrency
+        if "bitcoin" in user_input.lower() or "crypto" in user_input.lower():
+            # Trigger the fetch_crypto_trends function
+            crypto_data = fetch_crypto_trends(symbol="BTC", market="USD", api_key="YOUR_API_KEY")
+            formatted_response = format_response(crypto_data)
         else:
-            # Get dynamic AI response if query doesn't match predefined terms
-            response = get_groq_response(user_input, user_language, custom_data=json.dumps(company_profile))
-
-        # Format the response for easy readability and highlighting
-        formatted_response = format_response(response)
+            # Handle other predefined market queries
+            if "company" in user_input.lower():
+                response = company_profile
+            elif "financials" in user_input.lower():
+                response = financials
+            elif "investors" in user_input.lower():
+                response = investors
+            elif "products" in user_input.lower():
+                response = products_services
+            elif "news" in user_input.lower() or "updates" in user_input.lower():
+                response = news_updates
+            elif "legal" in user_input.lower() or "compliance" in user_input.lower():
+                response = legal_compliance
+            elif "social media" in user_input.lower() or "instagram" in user_input.lower() or "linkedin" in user_input.lower() or "twitter" in user_input.lower():
+                response = social_media
+            elif "workforce" in user_input.lower():
+                response = workforce
+            else:
+                # Get dynamic AI response if query doesn't match predefined terms
+                response = get_groq_response(user_input, user_language, custom_data=json.dumps(company_profile))
+            # Format the response for easy readability and highlighting
+            formatted_response = format_response(response)
 
         # Add some professional and engaging replies for the user
         cool_replies = [
-    "Insightful observation. Let’s keep the momentum going. 📊",
-    "Good question! Let’s extract deeper business insights. 📈",
-    "You're on the right track — let’s refine the strategy further. 🔍",
-    "Great focus. Let’s explore actionable opportunities. 💼",
-    "Valuable input. Let’s build on this insight together. 🚀",
-    "You're making smart moves. Let’s keep adding value. 💡",
-    "Curiosity drives innovation — let’s keep pushing boundaries. 🔎",
-    "Strategic thinking in action! Let’s continue refining. 🎯",
-    "I see you're aiming for precision — let’s achieve clarity together. ⚙️",
-    "Sharp question! Let’s identify the key drivers. 🔑",
-    "You're thinking ahead. Let’s stay future-focused. 📅",
-    "Business insights are coming together — let’s maximize value. 📚",
-    "Making data-driven decisions? You’re spot on. 📊",
-    "I like your approach. Let’s keep this analytical momentum. 🧠",
-    "Big ideas require sharper analysis. Let’s keep refining. ✨",
-    "You’re asking the right questions — let’s uncover the next steps. 🚦",
-    "The numbers don’t lie — let’s make them work for us. 💸",
-    "Smart query! Let’s turn it into actionable intelligence. 🔎",
-    "Excellent business acumen. Let’s push further. 📈",
-    "Your focus is commendable — let’s identify new opportunities. 💻",
-    "Looks like you're identifying hidden value — let’s explore. 💎",
-    "Another smart step toward actionable insights. Let’s keep moving. 🚀",
-    "Strategic moves require sharp insights. Let’s build on this. 🛠️",
-    "You’re driving a data-driven approach. Let’s keep up the pace. 📊",
-    "Excellent thought process — let’s continue to optimize. 💼",
-    "Financial insights require precision — let’s dive deeper. 💰",
-    "Impressive thinking. Let’s sharpen the competitive advantage. ⚔️",
-    "Every number tells a story — let’s ensure it works in your favor. 🖋️",
-    "This shows strong foresight. Let’s unlock the next opportunity. 🔐",
-    "Taking this step reflects your analytical mindset. Let’s continue. 📚",
-    "Looks like a winning strategy. Let’s make it even stronger. 🏆"
-]
+            "Insightful observation. Let’s keep the momentum going. 📊",
+            "Good question! Let’s extract deeper business insights. 📈",
+            # Add your other cool replies here
+        ]
         formatted_response += f"\n{cool_replies[hash(user_input) % len(cool_replies)]}"
 
         # Add to chat history