Update app.py

app.py

@@ -1,48 +1,128 @@
-import openai
+import os
 import gradio as gr
+import openai
+from langdetect import detect
 
-# Import necessary datasets
-from company_profile import company_profile
-from financials import financials
-from workforce import workforce
-
-# Set up OpenAI API
-openai.api_key = "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"
+# Set up OpenAI API with your custom endpoint
+openai.api_key = os.getenv("API_KEY")
 openai.api_base = "https://api.groq.com/openai/v1"
 
-# Function to query the AI agent
-def query_ai(user_input):
-    context_data = f"""
-    Company Name: {company_profile['Razorpay']['overview']['description']}
-    Headquarters: {company_profile['Razorpay']['overview']['headquarters']}
-    
-    Latest Valuation: {financials['Razorpay']['latest_valuation']}
-    Total Funding: {financials['Razorpay']['total_funding']}
-    Employees: {workforce['Razorpay']['total_employees']}
-    """
-    
-    system_prompt = """
-    You are Satyam AI Agent, an expert in financial research and private market analysis.
-    Your responses should be brief, professional, and to the point, with a positive and energetic tone.
-    """
+# Import datasets from the Python files in your project
+from datasets.company_profile import company_profile
+from datasets.workforce import workforce
+from datasets.financials import financials
+from datasets.investors import investors
+from datasets.products_services import products_services
+from datasets.market_trends import market_trends
+from datasets.partnerships_collaborations import partnerships_collaborations
+from datasets.legal_compliance import legal_compliance
+from datasets.customer_insights import customer_insights
+from datasets.news_updates import news_updates
+from datasets.social_media import social_media
+from datasets.tech_stack import tech_stack
 
+# Command handler for specific queries
+def command_handler(user_input):
+    if user_input.lower().startswith("define "):
+        term = user_input[7:].strip()
+        definitions = {
+            "market analysis": (
+                "Market analysis is like peeking into the crystal ball of business! 🔮 It's where we gather "
+                "data about the market to forecast trends, track competition, and make smarter investment decisions!"
+            ),
+            "financials": (
+                "Financial analysis is like the heartbeat of a company 💓. It tells us if the company is healthy, "
+                "sustainable, and ready to grow! 💰"
+            ),
+            "investors": (
+                "Investors are like the superheroes of the business world 🦸‍♂️. They bring in the cash to fuel growth, "
+                "while hoping for big returns on their investment!"
+            )
+        }
+        return definitions.get(term.lower(), "Hmm, I don’t have a fun story for that term yet. Try another!")
+    return None
+
+# Function to get the response from OpenAI with humor and energy
+def get_groq_response(message, user_language):
     try:
         response = openai.ChatCompletion.create(
             model="llama-3.1-70b-versatile",
             messages=[
-                {"role": "system", "content": system_prompt},
-                {"role": "user", "content": f"{context_data}\n\n{user_input}"}
+                {
+                    "role": "system",
+                    "content": (
+                        f"You are a cheerful and energetic Private Market Analyst AI with a passion for explaining "
+                        f"complex market analysis with humor, analogies, and wit. Keep it fun, engaging, and informative! "
+                        f"Use your energy to keep the user excited and curious about market trends!"
+                    )
+                },
+                {"role": "user", "content": message}
             ]
         )
         return response.choices[0].message["content"]
     except Exception as e:
-        return f"Error: {str(e)}"
-
-# Gradio interface
-gr.Interface(
-    fn=query_ai,
-    inputs="text",
-    outputs="text",
-    title="Satyam Market Analysis",
-    description="Ask me about private companies like Razorpay, including financials, products, and more!"
-).launch()
+        return f"Oops, looks like something went wrong! Error: {str(e)}"
+
+# Function to handle the interaction and queries
+def market_analysis_agent(user_input, history=[]):
+    try:
+        # Detect the language of the user's input
+        detected_language = detect(user_input)
+        user_language = "Hindi" if detected_language == "hi" else "English"
+        
+        # Handle special commands like "Define [term]"
+        command_response = command_handler(user_input)
+        if command_response:
+            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 "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)
+
+        # Add some cool and fun responses for engagement
+        cool_replies = [
+            "You're on fire! 🔥",
+            "Boom! 💥 That’s a market insight right there!",
+            "You’ve got this! 🚀",
+            "Let's keep that momentum going! 💎",
+            "That’s the power of market knowledge! 💪",
+            "You’re crushing it! 🎯"
+        ]
+        response = f"{response} {cool_replies[hash(user_input) % len(cool_replies)]}"
+        
+        # Add to chat history
+        history.append((user_input, response))
+        return history, history
+
+    except Exception as e:
+        return [(user_input, f"Oops, something went wrong: {str(e)}")], history
+
+# Gradio Interface setup
+chat_interface = gr.Interface(
+    fn=market_analysis_agent,  # Function for handling user interaction
+    inputs=["text", "state"],  # Inputs: user message and chat history
+    outputs=["chatbot", "state"],  # Outputs: chatbot messages and updated history
+    live=False,  # Disable live responses; show after submit
+    title="Private Market AI Agent",  # Title of the app
+    description=(
+        "Welcome to your cheerful and energetic Private Market Analyst! 🎉\n\n"
+        "Ask me anything about company profiles, market trends, financials, investors, and more! 🌟"
+        "I’ll break it down with jokes, stories, and humor to make market analysis a blast! 🚀"
+    )
+)
+
+# Launch the Gradio interface
+if __name__ == "__main__":
+    chat_interface.launch()