Update app.py

app.py

@@ -2,20 +2,47 @@ import os
 import streamlit as st
 from openai import OpenAI
 from tavily import TavilyClient
-from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, ServiceContext, StorageContext, load_index_from_storage
+
+# llama-index imports - removed ServiceContext usage
+from llama_index.core import (
+    VectorStoreIndex,
+    SimpleDirectoryReader,
+    StorageContext,
+    load_index_from_storage,
+)
 from llama_index.llms.openai import OpenAI as LlamaOpenAI
 from llama_index.embeddings.openai import OpenAIEmbedding
 from llama_index.core.prompts import PromptTemplate
 import time
 
-# ---------- PAGE CONFIG ----------
-st.set_page_config(
-    page_title="TrustLogic Assistant",
-    page_icon="🤖",
-    layout="centered",
-    initial_sidebar_state="collapsed",
-)
+# ---------- LOAD KNOWLEDGE BASE (fixed) ----------
+@st.cache_resource
+def load_index():
+    """
+    Loads an existing index from ./storage if present.
+    If not present, builds a new VectorStoreIndex from the provided markdown file,
+    using explicit llm and embed_model parameters (no ServiceContext).
+    """
+    persist_dir = "./storage"
+
+    if os.path.exists(persist_dir):
+        # Load existing storage context and index (no service_context required)
+        storage_context = StorageContext.from_defaults(persist_dir=persist_dir)
+        return load_index_from_storage(storage_context)
 
+    # Else build index from docs
+    docs = SimpleDirectoryReader(input_files=["time_to_rethink_trust_book (3).md"]).load_data()
+
+    # Create embedding & LLM objects explicitly
+    embed_model = OpenAIEmbedding(model="text-embedding-3-small")
+    llm = LlamaOpenAI(model="gpt-4-turbo")
+
+    # Pass llm and embed_model explicitly to avoid global ServiceContext usage
+    index = VectorStoreIndex.from_documents(docs, llm=llm, embed_model=embed_model)
+
+    # persist storage
+    index.storage_context.persist(persist_dir=persist_dir)
+    return index
 
 # ---------- ENHANCED STYLING ----------
 st.markdown(
@@ -726,21 +753,6 @@ Answer:"""
 FOOTER_MESSAGE = "\n\n---\n*For detailed analysis and information, visit [trustlogic.center](https://trustlogic.center) for comprehensive copy generation and brand analysis.*"
 
 # ---------- LOAD KNOWLEDGE BASE ----------
-@st.cache_resource
-def load_index():
-    if os.path.exists("./storage"):
-        storage_context = StorageContext.from_defaults(persist_dir="./storage")
-        return load_index_from_storage(storage_context)
-    
-    docs = SimpleDirectoryReader(input_files=["time_to_rethink_trust_book (3).md"]).load_data()
-    embed_model = OpenAIEmbedding(model="text-embedding-3-small")
-    service_context = ServiceContext.from_defaults(
-        llm=LlamaOpenAI(model="gpt-4-turbo"),
-        embed_model=embed_model
-    )
-    index = VectorStoreIndex.from_documents(docs, service_context=service_context)
-    index.storage_context.persist(persist_dir="./storage")
-    return index
 
 # ---------- INITIALIZE SERVICES ----------
 index = load_index()