app.py

import streamlit as st
import os
import os.path

from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, load_index_from_storage, ServiceContext, StorageContext
from llama_index.readers.file import PDFReader
from llama_index.llms.openai import OpenAI
from dotenv import load_dotenv



from llama_index.core.tools import QueryEngineTool, ToolMetadata
from llama_index.agent.openai import OpenAIAgent


load_dotenv()
storage_path = "./vectorstore"
documents_path = "./documents"

llm = OpenAI(model="gpt-3.5-turbo")
service_context = ServiceContext.from_defaults(llm=llm)

@st.cache_resource(show_spinner=False)
def initialize(): 
    if not os.path.exists(storage_path):
        documents = SimpleDirectoryReader(documents_path).load_data()
        index = VectorStoreIndex.from_documents(documents)
        index.storage_context.persist(persist_dir=storage_path)
    else:
        storage_context = StorageContext.from_defaults(persist_dir=storage_path)
        index = load_index_from_storage(storage_context)
    return index
index = initialize()

fitness_engine = index.as_query_engine(similarity_top_k=3,similarity_cutoff=0.5)

tools = [
   
    QueryEngineTool(
        query_engine=fitness_engine,
        metadata=ToolMetadata(
            name="fitnessdata",
            description="this gives information about diets , workoutplan and mental health",
        ),
    )]
agent = OpenAIAgent.from_tools(tools, verbose=True)

# # Retrieve input (e.g., from user input)
# input_text = "what are your views on processed food?"

# # Query the index
# results = agent.query(input_text)

# # Process results (e.g., select the most relevant result)
# if results:
#     response = results
# else:
#     response = "Sorry, I couldn't find a relevant response."

# # Display response
# print("Response:", response)
st.title("Fitness App")
input_text = st.text_input("Enter your question here:")
if st.button("Ask"):
    if input_text:
        # Query the index   
        results = agent.query(input_text)
        
        # Process results
        if results:
            response = results.response
        else:
            response = "Sorry, I couldn't find a relevant response."
            
        # Display response
        st.write("Response:", response)