Upload app.py

app.py

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+import os
+import streamlit as st
+from langchain_community.graphs import Neo4jGraph
+from langchain_groq import ChatGroq
+from langchain.chains import GraphCypherQAChain
+from dotenv import load_dotenv
+
+# Load environment variables
+load_dotenv()
+NEO4J_URI = os.getenv("NEO4J_URI")
+NEO4J_USERNAME = os.getenv("NEO4J_USERNAME")
+NEO4J_PASSWORD = os.getenv("NEO4J_PASSWORD")
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+
+# Initialize Neo4j graph
+graph = Neo4jGraph(url=NEO4J_URI, username=NEO4J_USERNAME, password=NEO4J_PASSWORD)
+
+# Load movie dataset into Neo4j
+moview_query = """
+LOAD CSV WITH HEADERS FROM
+'https://raw.githubusercontent.com/tomasonjo/blog-datasets/main/movies/movies_small.csv' as row
+MERGE(m:Movie{id:row.movieId})
+SET m.released = date(row.released),
+    m.title = row.title,
+    m.imdbRating = toFloat(row.imdbRating)
+FOREACH (director in split(row.director, '|') | 
+    MERGE (p:Person {name:trim(director)})
+    MERGE (p)-[:DIRECTED]->(m))
+FOREACH (actor in split(row.actors, '|') | 
+    MERGE (p:Person {name:trim(actor)})
+    MERGE (p)-[:ACTED_IN]->(m))
+FOREACH (genre in split(row.genres, '|') | 
+    MERGE (g:Genre {name:trim(genre)})
+    MERGE (m)-[:IN_GENRE]->(g))
+"""
+graph.query(moview_query)
+graph.refresh_schema()
+
+# Initialize LLM
+llm = ChatGroq(groq_api_key=GROQ_API_KEY, model_name="Gemma2-9b-It")
+
+# Create QA Chain
+chain = GraphCypherQAChain.from_llm(graph=graph, llm=llm, verbose=True)
+
+# Streamlit UI
+st.title("Movie Director Finder")
+
+query = st.text_input("Enter your query:", "Who was the director of the movie Casino")
+if st.button("Find Director"):
+    response = chain.invoke({"query": query})
+    st.write(response)