LLM + Agents + Langchain + MSF API + Neo4J KB + Streamlit - A hobby project with the learning of LLM Agents with a Knowledge graph.
- Neo4J Agent and query in LLM more examples Neo4j
- Requires a Marvel Strike Force Web account to authenticate
- A Neo4J Knowledge graph connection to store the data.
Requires python >= 3.11, Neo4J credentials, OpenAI API key and MSF account.
- Install libraries via
pip install -r requirements.txt - Then add the .env variable as in
.env.example - A client ID for your own app at MSF
- X-API-KEY available from the MSF Dev Portal
- Run
streamlit run app.py - Authenticate first time and paste the redirected URL on the small text input
- Once data loading completed, start querying!
A sample visualization of the current Knowledge graph with the fetched data
- RAG on descriptive data
- More guided usecases on streamlit
- Integrate other Cypher queries into tools
- Extended API search
- web crawl (optional) -> future feature
- Simulate gamev -> future feature