Update app.py

app.py

@@ -28,21 +28,17 @@ def command_handler(user_input):
         term = user_input[7:].strip()
         definitions = {
             "market analysis": (
-                "Market analysis is the process of evaluating a business's position in the market by assessing "
-                "competitors, trends, and customer behavior to make informed decisions for growth and investment. "
-                "Think of it as gathering the insights needed to craft a winning strategy. 📊"
+                "Market analysis evaluates a business's position by studying competitors, trends, and customer behavior. "
+                "It helps in crafting strategies for growth. 📊"
             ),
             "financials": (
-                "Financial analysis provides a snapshot of a company's fiscal health. It involves reviewing metrics like "
-                "profit margins, revenues, and expenditures to assess if the business is sustainable and scalable. 💵"
+                "Financial analysis examines profit margins, revenues, and expenses to determine fiscal health and sustainability. 💵"
             ),
             "investors": (
-                "Investors are the capital partners that fuel innovation and expansion. They provide financial resources "
-                "in exchange for equity or debt, aiming to generate a return on their investment. It's all about leveraging "
-                "their capital to scale. 🏦"
+                "Investors provide capital in exchange for equity or debt, enabling business growth and scaling. 🏦"
             )
         }
-        return definitions.get(term.lower(), "I don't have a definition for that term yet. Let’s dive into your query directly!")
+        return definitions.get(term.lower(), "Definition not available. Let’s dive into your query!")
     return None
 
 # Function to get the response from OpenAI with professionalism and energy
@@ -54,10 +50,9 @@ def get_groq_response(message, user_language):
                 {
                     "role": "system",
                     "content": (
-                        f"You are a professional, energetic Private Market Analyst AI. Your task is to explain market trends, "
-                        f"company insights, and investment strategies in a clear, engaging, and authoritative manner. "
-                        f"While providing top-tier market analysis, keep the tone polished, insightful, and relevant to business leaders. "
-                        f"Always maintain professionalism while making the content informative and engaging."
+                        f"You are a professional and concise Private Market Analyst AI. Your task is to explain market trends, "
+                        f"company insights, and investment strategies in a clear, impactful, and concise manner. "
+                        f"Keep the responses brief yet informative, focusing on the key points. Always maintain professionalism. "
                     )
                 },
                 {"role": "user", "content": message}
@@ -69,27 +64,15 @@ def get_groq_response(message, user_language):
 
 # Function to format the response data in a readable and copyable form
 def format_response(data):
-    # Check if the dataset is empty or not in a format that can be iterated
     if not data:
         return "No data available for this query."
 
-    # Ensure that the data is iterable (list, dict, etc.)
     if isinstance(data, dict):
-        formatted_response = "Here are the insights for your query:\n\n"
-        
+        formatted_response = "Insights:\n\n"
         for key, value in data.items():
-            formatted_response += f"**{key.capitalize()}**:\n"
-            if isinstance(value, list):  # Check if the value is a list
-                for idx, item in enumerate(value, start=1):
-                    formatted_response += f"{idx}. {item}\n"
-            else:
-                formatted_response += f"{value}\n"
-            formatted_response += "\n"
-
-    elif isinstance(data, list):  # If the data is a list
-        formatted_response = "Here are the insights for your query:\n\n"
-        for idx, item in enumerate(data, start=1):
-            formatted_response += f"{idx}. {item}\n"
+            formatted_response += f"**{key.capitalize()}**: {value}\n"
+    elif isinstance(data, list):
+        formatted_response = "Insights:\n\n" + "\n".join(f"{idx+1}. {item}" for idx, item in enumerate(data))
     else:
         formatted_response = str(data)
 
@@ -134,11 +117,10 @@ def market_analysis_agent(user_input, history=[]):
 
         # Add some professional and engaging replies for the user
         cool_replies = [
-            "That’s a great insight! Keep the questions coming. 🔍",
-            "Excellent direction! Let’s explore that further. 📈",
-            "Insightful! Let’s dive into the numbers. 📊",
-            "You've got the right focus. Let's sharpen those strategies. 🧠",
-            "You're on the right track. Let’s optimize that idea! 🔧"
+            "Insightful! Let's keep going! 🔍",
+            "Good question! More insights ahead. 📈",
+            "You're on the right track. Let’s keep this going. 🧠",
+            "Great focus! Let’s explore further. 💡"
         ]
         formatted_response += f"\n{cool_replies[hash(user_input) % len(cool_replies)]}"
 
@@ -159,8 +141,8 @@ chat_interface = gr.Interface(
     description=(
         "Welcome to your professional Private Market Analyst AI! 📊\n\n"
         "Ask me anything about market trends, company profiles, financial analysis, investors, and more! "
-        "I’ll provide you with actionable insights, backed by data and clear explanations, to help you make informed decisions. "
-        "Let’s break down the complexities of the market with precision and insight. 🔍"
+        "I’ll provide you with concise insights that are informative and to the point, helping you make well-informed decisions. "
+        "Let's break down market complexities with clarity. 🔍"
     )
 )