Update app.py

app.py

@@ -1,63 +1,112 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+import os
+import re
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
+# Initialize the client with the Zephyr 7B model
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
+# Shared context for both agents
+SHARED_CONTEXT = """You are part of a multi-agent system designed to provide respectful, empathetic, and accurate support for Zerodha, a leading Indian financial services company. Your role is crucial in ensuring all interactions uphold the highest standards of customer service while maintaining Zerodha's excellent reputation.
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
+Key points about Zerodha:
+1. India's largest discount broker, known for innovative technology and low-cost trading.
+2. Flat fee structure: ₹20 per executed order for intraday and F&O trades, zero brokerage for delivery equity investments.
+3. Main trading platform: Kite (web and mobile).
+4. Coin platform for commission-free direct mutual fund investments.
+5. Extensive educational resources through Varsity.
+6. Additional tools: Sentinel (price alerts) and ChartIQ (advanced charting).
+7. Console for account management and administrative tasks.
 
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
+Always prioritize user safety, ethical investing practices, and transparent communication. Never provide information that could mislead users or bring disrepute to Zerodha."""
 
-    messages.append({"role": "user", "content": message})
+# Communication Expert context
+COMMUNICATION_EXPERT_CONTEXT = SHARED_CONTEXT + """
+As the Communication Expert, your primary role is to interpret user queries with the utmost respect and empathy. You should:
+1. Rephrase the user's query to ensure it's understood in the most positive and constructive light.
+2. Identify and highlight any emotional subtext or concerns in the query.
+3. Frame the query in a way that invites a supportive and informative response.
+4. Ensure that any potential complaints or frustrations are acknowledged respectfully.
 
-    response = ""
+Your output should be a rephrased version of the user's query that maintains its original intent while setting the stage for an empathetic and respectful response."""
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
+# Response Expert context
+RESPONSE_EXPERT_CONTEXT = SHARED_CONTEXT + """
+As the Response Expert, your role is to provide accurate, helpful, and emotionally intelligent responses to user queries. You should:
+1. Address the user's question or concern directly and comprehensively.
+2. Maintain a tone of respect and empathy throughout your response.
+3. Provide clear, factual information about Zerodha's services and policies.
+4. When discussing financial matters, include appropriate disclaimers and encourage users to seek professional advice for complex decisions.
+5. For complaints or concerns, acknowledge them respectfully and provide constructive guidance or escalation paths.
+6. Always uphold Zerodha's reputation for transparency and user-centric service.
 
-        response += token
-        yield response
+Your output should be a complete, informative response that addresses the user's query while demonstrating empathy and respect."""
 
+def format_prompt(context, message):
+    return f"""<s>[INST] <<SYS>>
+{context}
+<</SYS>>
+
+{message} [/INST]
 """
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
+
+def communication_expert(query):
+    prompt = format_prompt(COMMUNICATION_EXPERT_CONTEXT, f"Please rephrase the following user query with empathy and respect: '{query}'")
+    response = client.text_generation(prompt, max_new_tokens=200, temperature=0.7)
+    return response
+
+def response_expert(rephrased_query):
+    prompt = format_prompt(RESPONSE_EXPERT_CONTEXT, f"Please provide a respectful and empathetic response to the following query: '{rephrased_query}'")
+    response = client.text_generation(prompt, max_new_tokens=500, temperature=0.7)
+    return response
+
+def post_process_response(response):
+    # Remove any potentially disrespectful language
+    response = re.sub(r'\b(stupid|dumb|idiotic|foolish)\b', 'mistaken', response, flags=re.IGNORECASE)
+    
+    # Ensure the response ends respectfully
+    if not re.search(r'(Thank you|Is there anything else|Hope this helps|Let me know if you need more information)\s*$', response, re.IGNORECASE):
+        response += "\n\nIs there anything else I can help you with regarding Zerodha's services?"
+    
+    # Add a disclaimer for financial advice
+    if re.search(r'\b(invest|trade|buy|sell|market)\b', response, re.IGNORECASE):
+        response += "\n\nPlease note that this information is for educational purposes only and should not be considered as financial advice. Always do your own research and consider consulting with a qualified financial advisor before making investment decisions."
+    
+    return response
+
+def zerodha_support(message, history):
+    # Step 1: Communication Expert rephrases the query
+    rephrased_query = communication_expert(message)
+    print(f"Rephrased query: {rephrased_query}")  # Debug print
+    
+    # Step 2: Response Expert generates a response
+    initial_response = response_expert(rephrased_query)
+    print(f"Initial response: {initial_response}")  # Debug print
+    
+    # Step 3: Post-process the response
+    final_response = post_process_response(initial_response)
+    print(f"Final response: {final_response}")  # Debug print
+    
+    return final_response
+
 demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
+    zerodha_support,
+    chatbot=gr.Chatbot(height=600),
+    textbox=gr.Textbox(placeholder="Ask your question about Zerodha here...", container=False, scale=7),
+    title="Zerodha Support Assistant",
+    description="Ask questions about Zerodha's services, trading, account management, and more. Our multi-agent system ensures respectful and empathetic responses.",
+    theme="soft",
+    examples=[
+        "How do I open a Zerodha account?",
+        "I'm frustrated with the recent changes to the Kite platform. Can you help?",
+        "What are the risks involved in F&O trading?",
+        "I think there's an error in my account statement. What should I do?",
+        "Can you explain Zerodha's policy on intraday trading margins?",
+        "I'm new to investing. What resources does Zerodha offer for beginners?",
+        "How does Zerodha ensure the security of my investments and personal data?"
     ],
 )
 
-
 if __name__ == "__main__":
-    demo.launch()
+    public_url = demo.launch(share=True, server_name="0.0.0.0", server_port=7860)
+    print(f"\n\nSHAREABLE LINK: {public_url}\n\n")