Update hf_app.py

hf_app.py

@@ -1,4 +1,69 @@
 from dotenv import load_dotenv
+import gradio as gr
+from transformers import pipeline
+import os
 
 load_dotenv()
-hf_token = os.getenv('HF_TOKEN')
+# Load the Hugging Face model and tokenizer for text generation
+hf_token = os.getenv('HF_TOKEN')  # Hugging Face Token for authentication
+model_name = "meta-llama/Llama-3-70b-chat-hf"  # Hugging Face model
+chat_pipeline = pipeline("text-generation", model=model_name, use_auth_token=hf_token)
+
+# Function to handle the chatbot's response to user queries
+# You can only answer finance-related queries.
+# - Do not answer non-finance questions.
+def run_action(message, history):
+    system_prompt = """You are a financial assistant. 
+    - Answer in 50 words.
+    - Ensure responses adhere to the safety policy."""
+
+    messages = [{"role": "system", "content": system_prompt}]
+
+    # Convert history into the appropriate format
+    for entry in history:
+        if entry["role"] == "user":
+            messages.append({"role": "user", "content": entry["content"]})
+        elif entry["role"] == "assistant":
+            messages.append({"role": "assistant", "content": entry["content"]})
+
+    # Add the user's current action
+    messages.append({"role": "user", "content": message})
+
+    # Generate the model output using Hugging Face's pipeline
+    response = chat_pipeline(messages)
+
+    return response[0]['generated_text']
+
+# Main loop for the chatbot to handle user input
+def main_loop(message, history):
+    """
+    Main loop for the chatbot to handle user input.
+    """
+    # Validate the user's input for safety
+    if not is_safe(message):
+        return "Your input violates our safety policy. Please try again with a finance-related query."
+    
+    # Generate and validate the response
+    return run_action(message, history)
+
+# Gradio Chat Interface
+demo = gr.ChatInterface(
+    main_loop,
+    chatbot=gr.Chatbot(
+        height=450,
+        placeholder="Ask a finance-related question. Type 'exit' to quit.",
+        type="messages",  # Proper rendering of chat format
+    ),
+    textbox=gr.Textbox(
+        placeholder="What do you want to ask about finance?",
+        container=False,
+        scale=7,
+    ),
+    title="Finance Chatbot",
+    theme="Monochrome",
+    examples=["What is compound interest?", "How to save for retirement?", "What are tax-saving options?"],
+    cache_examples=False,
+)
+
+# Launch the Gradio app
+demo.launch(share=True, server_name="0.0.0.0")