Greetings,
New to this channel, and hope this is relevant. I am trying to use langchain-neo4j with a database that I converted into a graph - it was originally on mongo and I converted it to Neo4j.
I tried using langchain-neo4j with that database with ChatOpenAI and even for a small graph with about 100 records converted into a graph I am getting a huge context window that does not fit openAI. Here is the error message I am getting: "Request too large for gpt-3.5-turbo in organization *** on tokens per min (TPM): Limit 200000, Requested 364902.
I am using a tiny sample of the database of about 100 records while I have around 50K records and this already puts me over the token limit, so I wonder what is happening.
I am using code very similar to the example in langchain-neo4j :
from langchain_openai import ChatOpenAI
from langchain_neo4j import GraphCypherQAChain, Neo4jGraph
llm = ChatOpenAI(
temperature=0,
api_key="sk-...", # Replace with your OpenAI API key
)
graph = Neo4jGraph(url="bolt://localhost:7687", username="neo4j", password="password")
chain = GraphCypherQAChain.from_llm(llm=llm, graph=graph, allow_dangerous_requests=True)
chain.run("Who starred in Top Gun?")
When I try the entire database using graph = Neo4jGraph which all the records, it takes hours to load only this command.
Am I doing something wrong?
When created the graph - I created one node per record so in the small data base I have 100 main nodes connected to many to their dependencies - all of them are separated. So essentially I have 100 disconnected graphs in the database.
Hopefully someone can put me in the right direction or the right forum.