Update app.py

app.py

@@ -42,8 +42,14 @@ def command_handler(user_input):
     return None
 
 # Function to get the response from OpenAI with professionalism and energy
-def get_groq_response(message, user_language):
+def get_groq_response(message, user_language, custom_data=None):
     try:
+        # If custom data is available, include it in the AI prompt
+        if custom_data:
+            prompt = f"Use the following information for analysis: {custom_data}. Then answer the user's query: {message}"
+        else:
+            prompt = message
+
         response = openai.ChatCompletion.create(
             model="llama-3.1-70b-versatile",
             messages=[
@@ -61,7 +67,7 @@ def get_groq_response(message, user_language):
                         f"Your primary goal is to assist users by providing accurate, personalized, and actionable insights related to private markets. Always maintain professionalism and conciseness. Ensure that responses are easy to interpret, and avoid jargon whenever possible.\n\n"
                     )
                 },
-                {"role": "user", "content": message}
+                {"role": "user", "content": prompt}
             ]
         )
         return response.choices[0].message["content"]
@@ -110,14 +116,13 @@ def market_analysis_agent(user_input, history=[]):
             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)
+            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)