https://github.com/tomasonjo/neogpt-recommender

Context-aware knowledge-graph based chatbot using GPT4 and Neo4j
https://github.com/tomasonjo/neogpt-recommender

chatbot chatgpt gpt4 neo4j streamlit

Last synced: 3 months ago
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Context-aware knowledge-graph based chatbot using GPT4 and Neo4j

• Host: GitHub
• URL: https://github.com/tomasonjo/neogpt-recommender
• Owner: tomasonjo
• License: mit
• Created: 2023-04-04T11:57:39.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2024-01-07T12:10:36.000Z (about 1 year ago)
• Last Synced: 2024-10-10T09:23:16.333Z (4 months ago)
• Topics: chatbot, chatgpt, gpt4, neo4j, streamlit
• Language: Python
• Homepage: https://medium.com/neo4j/context-aware-knowledge-graph-chatbot-with-gpt-4-and-neo4j-d3a99e8ae21e
• Size: 115 KB
• Stars: 147
• Watchers: 9
• Forks: 49
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# NeoGPT-Recommender

Idea behind this repository is to create a context-aware chatbot that can read from and update a Neo4j database.

The Cypher is generated using GPT-4 endpoint, while the answers are generated with gpt-3.5-turbo model based on the information from the database.

Learn more: https://medium.com/neo4j/context-aware-knowledge-graph-chatbot-with-gpt-4-and-neo4j-d3a99e8ae21e

## Neo4j database

The project uses the [Recommendation project](https://sandbox.neo4j.com/?usecase=recommendations) that is available as part of the Neo4j Sandbox.

If you want a local instance of Neo4j, you can restore a database dump that is available [here](https://github.com/neo4j-graph-examples/recommendations/tree/main/data).

## Environment variables

Make sure to populate the environment variables as shown in the `.env.example` file

## Start the project

Run the project using

```

docker-compose up

```

and then open the localhost:8501 address in your favourite browser

![Chatbot](./chatbot.png)

## Training examples for the english2cypher part

You can use the following example to get an idea what this chatbot is capable of

```

# I don't like comedy

MATCH (u:User {id: $userId}), (g:Genre {name:"Comedy"})

MERGE (u)-[:DISLIKE_GENRE]->(g)

RETURN distinct {answer: 'noted'} AS result

# I like comedy

MATCH (u:User {id: $userId}), (g:Genre {name:"Comedy"})

MERGE (u)-[:LIKE_GENRE]->(g)

RETURN distinct {answer: 'noted'} AS result

# I have already watched Top Gun

MATCH (u:User {id: $userId}), (m:Movie {title:"Top Gun"})

MERGE (u)-[:WATCHED]->(m)

RETURN distinct {answer: 'noted'} AS result

# I like Top Gun

MATCH (u:User {id: $userId}), (m:Movie {title:"Top Gun"})

MERGE (u)-[:LIKE_MOVIE]->(m)

RETURN distinct {answer: 'noted'} AS result

# What is a good comedy?

MATCH (u:User {id:$userId}), (m:Movie)-[:IN_GENRE]->(:Genre {name:"Comedy"})

WHERE NOT EXISTS {(u)-[:WATCHED]->(m)}

RETURN {movie: m.title} AS result

ORDER BY m.imdbRating DESC LIMIT 1

# Who played in Top Gun?

MATCH (m:Movie)<-[:ACTED_IN]-(a)

RETURN {actor: a.name} AS result

# What is the plot of the Copycat movie?

MATCH (m:Movie {title: "Copycat"})

RETURN {plot: m.plot} AS result

# Did Luis Guzmán appear in any other movies?

MATCH (p:Person {name:"Luis Guzmán"})-[:ACTED_IN]->(movie)

RETURN {movie: movie.title} AS result

# Do you know of any matrix movies?

MATCH (m:Movie)

WHERE toLower(m.title) CONTAINS toLower("matrix")

RETURN {movie:m.title} AS result

# Which movies do I like?

MATCH (u:User {id: $userId})-[:LIKE_MOVIE]->(m:Movie)

RETURN {movie:m.title} AS result

# Recommend a movie

MATCH (u:User {id: $userId})-[:LIKE_MOVIE]->(m:Movie)

MATCH (m)<-[r1:RATED]-()-[r2:RATED]->(otherMovie)

WHERE r1.rating > 3 AND r2.rating > 3 AND NOT EXISTS {(u)-[:WATCHED|LIKE_MOVIE|DISLIKE_MOVIE]->(otherMovie)}

WITH otherMovie, count(*) AS count

ORDER BY count DESC

LIMIT 1

RETURN {recommended_movie:otherMovie.title} AS result

```