Update app.py

app.py

@@ -10,25 +10,22 @@ import re
 from langchain.docstore.document import Document
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain_community.retrievers import BM25Retriever
-# from smolagents import Tool, HfApiModel, CodeAgent
-from smolagents import CodeAgent, HfApiModel, DuckDuckGoSearchTool, ManagedAgent
-from smolagents.agents import ToolCallingAgent
-from smolagents import Tool, HfApiModel, TransformersModel, LiteLLMModel
-from typing import Optional
+from smolagents import CodeAgent, HfApiModel, DuckDuckGoSearchTool
 import gradio as gr
 import logging
 from nltk.corpus import words
 from sklearn.feature_extraction.text import TfidfVectorizer
 from sklearn.metrics.pairwise import cosine_similarity
 
+# Set up logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger("Daily Wellness AI Guru")
 
+# Securely input the GROQ API key
 if 'GROQ_API_KEY' not in os.environ or not os.environ['GROQ_API_KEY']:
     os.environ['GROQ_API_KEY'] = getpass.getpass('Enter GROQ_API_KEY: ')
 else:
     print("GROQ_API_KEY is already set.")
-# Set up logging
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger(__name__)
 
 # Load NLTK word list for valid word checks
 try:
@@ -153,7 +150,6 @@ class RetrieverTool(Tool):
     def forward(self, query: str) -> str:
         assert isinstance(query, str), "Search query must be a string."
         docs = self.retriever.invoke(query)
-        # Return only the content of the most relevant document
         if docs:
             return docs[0].page_content.strip()
         else:
@@ -161,54 +157,56 @@ class RetrieverTool(Tool):
 
 retriever_tool = RetrieverTool(docs_processed)
 
+# Define DuckDuckGoSearchTool
+duckduckgo_search_tool = DuckDuckGoSearchTool()
+
 # Define the improved custom prompt
 custom_prompt = """
-You are a friendly and knowledgeable AI assistant for a daily wellness company. Your goal is to provide clear, concise, and actionable answers to the user's health and wellness-related questions. Use a warm, approachable tone to make the user feel at ease.
+You are Daily Wellness AI Guru, a friendly and knowledgeable assistant here to simplify wellness. Your goal is to provide clear, concise, and actionable answers to the user's health and wellness-related questions. Mention how Daily Wellness AI offers tailored solutions for day-to-day wellness tasks. Use a warm and friendly tone to make the user feel at ease.
 
 When answering:
-1. Focus on brevity without sacrificing accuracy or helpfulness.
-2. Highlight key points in an easy-to-understand manner.
-3. Include examples, tips, or short step-by-step guides where relevant.
-4. Format lists or steps using markdown for better readability (e.g., numbered lists, bullet points).
-5. Ensure your response is self-contained, engaging, and ends with a polite closing remark.
-
-Answer each question in a similar concise, helpful, and friendly way.
+1. Address the user warmly with "Hello! This is Daily Wellness AI Guru."
+2. Highlight the key points in an easy-to-understand manner.
+3. Include practical examples, tips, or short guides where relevant.
+4. Format the response for clarity using markdown (e.g., numbered lists, bullet points).
+5. Reinforce how Daily Wellness AI helps simplify wellness through AI-powered solutions.
+6. End with an engaging and polite closing remark that invites further questions.
 """
 
 # Define the agent using smolagents
-model = LiteLLMModel("groq/llama3-8b-8192")  # Ensure the model is available
+model = HfApiModel("groq/llama3-8b-8192")  # Ensure the model is available
 agent = CodeAgent(
-    tools=[retriever_tool], model=model, max_iterations=4, verbose=True
+    tools=[retriever_tool, duckduckgo_search_tool], model=model, max_iterations=4, verbose=True
 )
 
 # Gradio interface for interacting with the RAG pipeline
 def gradio_interface(query):
     try:
+        # Validate input
         is_valid, message = is_valid_input(query)
         if not is_valid:
             return message
 
-        # Perform similarity search to verify the query's viability
+        # Perform similarity search
         similar, similar_question, similarity_score = similarity_search(query, corpus_questions, threshold=0.2)
-        if not similar:
-            return (
-                "I'm here to assist with health and wellness-related topics. "
-                "However, I couldn't find a closely related question in the dataset. "
-                "Please refine your query."
-            )
-        
-        # Directly query the agent if the question is valid
-        return agent.run(f"{custom_prompt}\n\nQuestion: {query}").strip()
+        if similar:
+            response = agent.run(f"{custom_prompt}\n\nQuestion: {query}")
+            return response.strip()
+        else:
+            response = duckduckgo_search_tool.invoke(query)
+            return f"{response.strip()}\n\nRemember, Daily Wellness AI is here to simplify wellness with AI-powered solutions. Feel free to ask more questions!"
     except Exception as e:
         logger.error(f"Error during query processing: {e}")
         return "**An error occurred while processing your request. Please try again later.**"
 
+
+# Create the Gradio interface
 interface = gr.Interface(
     fn=gradio_interface,
     inputs=gr.Textbox(label="Enter your question", placeholder="e.g., How does box breathing help reduce anxiety?"),
     outputs=gr.Markdown(label="Answer"),
-    title="AI Chatbot for Wellness",
-    description="Ask questions based on the AIChatbot.csv file. Focus on health and wellness topics.",
+    title="Daily Wellness AI Guru Chatbot",
+    description="Ask health and wellness questions. Get actionable, friendly advice from your wellness companion.",
     theme="compact"
 )