Update app.py

app.py

@@ -1,35 +1,42 @@
 import os
+import tempfile
 from dotenv import load_dotenv
+import streamlit as st
+from openai.embeddings_utils import OpenAIEmbeddings
+from openai.chat_models import ChatOpenAI
 from langchain.document_loaders import PyPDFLoader
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain.schema import Document
 from langchain.prompts import PromptTemplate
 from langchain.vectorstores import Neo4jVector
-from langchain.chat_models import ChatOpenAI
-from langchain.embeddings import OpenAIEmbeddings
 from langchain.graphs import Neo4jGraph
 from langchain_experimental.graph_transformers import LLMGraphTransformer
 from langchain.chains.graph_qa.cypher import GraphCypherQAChain
-import streamlit as st
-import tempfile
 from neo4j import GraphDatabase
 
 def main():
     st.set_page_config(
         layout="wide",
-        page_title="Graphy v1",
+        page_title="MayaJal",
         page_icon=":graph:"
     )
+
+    # Debug statement
+    st.write("Starting the app...")
+
     st.sidebar.image('logo.png', use_column_width=True) 
     with st.sidebar.expander("Expand Me"):
         st.markdown("""
     This application allows you to upload a PDF file, extract its content into a Neo4j graph database, and perform queries using natural language.
     It leverages LangChain and OpenAI's GPT models to generate Cypher queries that interact with the Neo4j database in real-time.
     """)
-    st.title("Graphy: Realtime GraphRAG App")
+    st.title("Mayajal: Realtime GraphRAG App")
 
     load_dotenv()
 
+    # Debug statement
+    st.write("Loaded environment variables.")
+
     # Set OpenAI API key
     if 'OPENAI_API_KEY' not in st.session_state:
         st.sidebar.subheader("OpenAI API Key")
@@ -42,7 +49,11 @@ def main():
             llm = ChatOpenAI(model_name="gpt-4o")  # Use model that supports function calling
             st.session_state['embeddings'] = embeddings
             st.session_state['llm'] = llm
+            # Debug statement
+            st.write("OpenAI API Key set and models initialized.")
     else:
+        # Debug statement
+        st.write("OpenAI API Key already set.")
         embeddings = st.session_state['embeddings']
         llm = st.session_state['llm']
 
@@ -83,6 +94,8 @@ def main():
 
     # Ensure that the Neo4j connection is established before proceeding
     if graph is not None:
+        # Debug statement
+        st.write("Neo4j connection established.")
         # File uploader
         uploaded_file = st.file_uploader("Please select a PDF file.", type="pdf")
 
@@ -92,6 +105,8 @@ def main():
                 with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as tmp_file:
                     tmp_file.write(uploaded_file.read())
                     tmp_file_path = tmp_file.name
+                    # Debug statement
+                    st.write("PDF file uploaded and saved to temporary file.")
 
                 # Load and split the PDF
                 loader = PyPDFLoader(tmp_file_path)
@@ -113,8 +128,8 @@ def main():
                 graph.query(cypher)
 
                 # Define allowed nodes and relationships
-                allowed_nodes = ["Patient", "Disease", "Medication", "Test", "Symptom", "Doctor"]
-                allowed_relationships = ["HAS_DISEASE", "TAKES_MEDICATION", "UNDERWENT_TEST", "HAS_SYMPTOM", "TREATED_BY"]
+                allowed_nodes = None
+                allowed_relationships = None
 
                 # Transform documents into graph documents
                 transformer = LLMGraphTransformer(
@@ -179,6 +194,8 @@ def main():
                 )
                 st.session_state['qa'] = qa
     else:
+        # Debug statement
+        st.write("Neo4j connection not established.")
         st.warning("Please connect to the Neo4j database before you can upload a PDF.")
 
     if 'qa' in st.session_state:
@@ -194,5 +211,3 @@ def main():
 
 if __name__ == "__main__":
     main()
-
-